Author: jayendrapatil

AWS Certified SysOps Administrator – Associate (SOA-C02) Exam Learning Path

AWS SysOps Administor - Associate SOA-C02 Certification
~ Last updated on : ~ jayendrapatil

AWS Certified SysOps Administrator – Associate (SOA-C02) Exam Learning Path

  • I recently recertified for the AWS Certified SysOps Administrator – Associate (SOA-C02) exam.
  • SOA-C02 is the updated version of the SOA-C01 AWS exam with hands-on labs included, which is the first with AWS.

NOTE: As of March 28, 2023, the AWS Certified SysOps Administrator – Associate exam will not include exam labs until further notice. This removal of exam labs is temporary while we evaluate the exam labs and make improvements to provide an optimal candidate experience.

AWS Certified SysOps Administrator – Associate (SOA-C02) Exam Content

  • AWS SysOps Administrator – Associate SOA-C02 is intended for system administrators in a cloud operations role.
  • SOA-C02 validates a candidate’s ability to deploy, manage, and operate workloads on AWS which includes
    • Deploy, manage, and operate workloads on AWS
    • Support and maintain AWS workloads according to the AWS Well-Architected Framework
    • Perform operations by using the AWS Management Console and the AWS CLI
    • Implement security controls to meet compliance requirements
    • Monitor, log, and troubleshoot systems
    • Apply networking concepts (for example, DNS, TCP/IP, firewalls)
    • Implement architectural requirements (for example, high availability, performance, capacity)
    • Perform business continuity and disaster recovery procedures
    • Identify, classify, and remediate incidents

Refer AWS Certified SysOps – Associate (SOA-C02) Exam Guide

SOA-C02 Exam Domains

AWS Certified SysOps Administrator – Associate (SOA-C02) Exam Summary

  • SOA-C02 is the first AWS exam that included 2 sections
    • Objective questions
    • Hands-on labs
  • With Labs
    • SOA-C02 Exam consists of around 50 objective-type questions and 3 Hands-on labs to be answered in 190 minutes.
    • Labs are performed in a separate instance. Copy-paste works, so make sure you copy the exact names on resource creation.
    • Labs are pretty easy if you have worked on AWS.
    • Plan to leave 20 minutes to complete each exam lab.
    • NOTE: Once you complete a section and click next you cannot go back to the section. The same is for the labs. Once a lab is completed, you cannot return back to the lab.
    • Practice the Sample Lab provided when you book the exam, which would give you a feel of how the hands-on exam would actually be.
  • Without Labs
    • SOA-C02 exam consists of 65 questions in 130 minutes, and the time is more than sufficient if you are well-prepared.
  • SOA-C02 exam includes two types of questions, multiple-choice and multiple-response.
  • SOA-C02 has a scaled score between 100 and 1,000. The scaled score needed to pass the exam is 720.
  • Associate exams currently cost $ 150 + tax.
  • You can get an additional 30 minutes if English is your second language by requesting Exam Accommodations. It might not be needed for Associate exams but is helpful for Professional and Specialty ones.
  • AWS exams can be taken either remotely or online, I prefer to take them online as it provides a lot of flexibility. Just make sure you have a proper place to take the exam with no disturbance and nothing around you.
  • Also, if you are taking the AWS Online exam for the first time try to join at least 30 minutes before the actual time as I have had issues with both PSI and Pearson with long wait times.

AWS Certified SysOps Administrator – Associate (SOA-C02) Exam Resources

AWS Certified SysOps Administrator – Associate (SOA-C02) Exam Topics

SOA-C02 mainly focuses on SysOps and DevOps tools in AWS and the ability to deploy, manage, operate, and automate workloads on AWS.

Management & Governance Tools

  • CloudFormation
    • provides an easy way to create and manage a collection of related AWS resources, provision and update them in an orderly and predictable fashion.
    • CloudFormation Concepts cover
      • Templates act as a blueprint for provisioning of AWS resources
      • Stacks are collection of resources as a single unit, that can be created, updated, and deleted by creating, updating, and deleting stacks.
      • Change Sets present a summary or preview of the proposed changes that CloudFormation will make when a stack is updated.
      • Nested stacks are stacks created as part of other stacks.
    • CloudFormation template anatomy consists of resources, parameters, outputs, and mappings.
    • CloudFormation supports multiple features
      • Drift detection enables you to detect whether a stack’s actual configuration differs, or has drifted, from its expected configuration.
      • Termination protection helps prevent a stack from being accidentally deleted.
      • Stack policy can prevent stack resources from being unintentionally updated or deleted during a stack update.
      • StackSets help create, update, or delete stacks across multiple accounts and Regions with a single operation.
      • Helper scripts with creation policies can help wait for the completion of events before provisioning or marking resources complete.
      • DependsOn attribute can specify the resource creation order and control the creation of a specific resource follows another.
      • Update policy supports rolling and replacing updates with AutoScaling.
      • Deletion policies to help retain or backup resources during stack deletion.
      • Custom resources can be configured for uses cases not supported for e.g. retrieve AMI IDs or interact with external services
    • Understand CloudFormation Best Practices esp. Nested Stacks and logical grouping
  • Elastic Beanstalk helps to quickly deploy and manage applications in the AWS Cloud without having to worry about the infrastructure that runs those applications. 
  • OpsWorks is a configuration management service that helps to configure and operate applications in a cloud enterprise by using Chef.
  • Understand CloudFormation vs Elastic Beanstalk vs OpsWorks
  • AWS Organizations
    • Difference between Service Control Policies and IAM Policies
    • SCP provides the maximum permission that a user can have, however, the user still needs to be explicitly given IAM policy.
    • Consolidated billing enables consolidating payments from multiple AWS accounts and includes combined usage and volume discounts including sharing of Reserved Instances across accounts.
  • Systems Manager is the operations hub and provides various services like parameter store, patch manager
    • Parameter Store provides secure, scalable, centralized, hierarchical storage for configuration data and secret management. Does not support secrets rotation. Use Secrets Manager instead
    • Session Manager provides secure and auditable instance management without the need to open inbound ports, maintain bastion hosts, or manage SSH keys.
    • Patch Manager helps automate the process of patching managed instances with both security-related and other types of updates.
  • CloudWatch
    • collects monitoring and operational data in the form of logs, metrics, and events, and visualizes it.
      • EC2 metrics can track (disk, network, CPU, status checks) but do not capture metrics like memory, disk swap, disk storage, etc.
      • CloudWatch unified agent can be used to gather custom metrics like memory, disk swap, disk storage, etc.
      • CloudWatch Alarm actions can be configured to perform actions based on various metrics for e.g. CPU below 5%
      • CloudWatch alarm can monitor StatusCheckFailed_System status on an EC2 instance and automatically recover the instance if it becomes impaired due to an underlying hardware failure or a problem that requires AWS involvement to repair.
      • Know ELB monitoring
        • Load Balancer metrics SurgeQueueLength and SpilloverCount
        • HealthyHostCount, UnHealthyHostCount determines the number of healthy and unhealthy instances registered with the load balancer.
        • Reasons for 4XX and 5XX errors
    • CloudWatch logs can be used to monitor, store, and access log files from EC2 instances, CloudTrail, Route 53, and other sources. You can create metric filters over the logs.
    • CloudWatch Subscription Filters can be used to send logs to Kinesis Data Streams, Lambda, or Kinesis Data Firehose.
    • EventBridge (CloudWatch Events) is a serverless event bus service that makes it easy to connect applications with data from a variety of sources.
    • EventBridge or CloudWatch events can be used as a trigger for periodically scheduled events.
    • CloudWatch unified agent helps collect metrics and logs from EC2 instances and on-premises servers and push them to CloudWatch.
  • CloudTrail for audit and governance
    • With Organizations, the trail can be configured to log CloudTrail from all accounts to a central account.
    • CloudTrail log file integrity validation can be used to check whether a log file was modified, deleted, or unchanged after being delivered.
  • AWS Config is a fully managed service that provides AWS resource inventory, configuration history, and configuration change notifications to enable security, compliance, and governance.
    • supports managed as well as custom rules that can be evaluated on periodic basis or as the event occurs for compliance and trigger automatic remediation
    • Conformance pack is a collection of AWS Config rules and remediation actions that can be easily deployed as a single entity in an account and a Region or across an organization in AWS Organizations.
  • Control Tower
    • to setup, govern, and secure a multi-account environment
    • strongly recommended guardrails cover EBS encryption
  • Service Catalog
    • allows organizations to create and manage catalogues of IT services that are approved for use on AWS with minimal permissions.
  • Trusted Advisor provides recommendations that help follow AWS best practices covering security, performance, cost, fault tolerance & service limits.
  • AWS Health Dashboard is the single place to learn about the availability and operations of AWS services.
  • Cost allocation tags can be used to differentiate resource costs and analyzed using Cost Explorer or on a Cost Allocation report.
  • Understand how to setup Billing Alerts using CloudWatch

Networking & Content Delivery

  • VPC – Virtual Private Cloud is a virtual network in AWS
    • Understand Public Subnet (has access to the Internet) vs Private Subnet (no access to the Internet)
    • Route table defines rules, termed as routes, which determine where network traffic from the subnet would be routed
    • Internet Gateway enables access to the internet
    • Bastion host – allow access to instances in the private subnet without directly exposing them to the internet.
    • NAT helps route traffic from private subnets to the internet
    • NAT instance vs NAT Gateway
    • Virtual Private Gateway – Connectivity between on-premises and VPC
    • Egress-Only Internet Gateway – relevant to IPv6 only to allow egress traffic from private subnet to internet, without allowing ingress traffic
    • VPC Flow Logs enables you to capture information about the IP traffic going to and from network interfaces in the VPC and can help in monitoring the traffic or troubleshooting any connectivity issues
    • Security Groups vs NACLs esp. Security Groups are stateful and NACLs are stateless.
    • VPC Peering provides a connection between two VPCs that enables routing of traffic between them using private IP addresses.
    • VPC Endpoints enables the creation of a private connection between VPC to supported AWS services and VPC endpoint services powered by PrivateLink using its private IP address
    • Ability to debug networking issues like EC2 not accessible, EC2 not reachable, or not able to communicate with others or Internet.
  • Route 53 provides a scalable DNS system
    • supports ALIAS record type helps map zone apex records to ELB, CloudFront, and S3 endpoints.
    • Understand Routing Policies and their use cases
      • Failover routing policy helps to configure active-passive failover.
      • Geolocation routing policy helps route traffic based on the location of the users.
      • Geoproximity routing policy helps route traffic based on the location of the resources and, optionally, shift traffic from resources in one location to resources in another.
      • Latency routing policy use with resources in multiple AWS Regions and you want to route traffic to the Region that provides the best latency with less round-trip time.
      • Weighted routing policy helps route traffic to multiple resources in specified proportions.
    • Focus on Weighted, Latency routing policies
  • Understand ELB, ALB, and NLB and what features they provide like
    • Understand keys differences ELB vs ALB vs NLB
    • ALB provides content and path routing
    • NLB provides the ability to give static IPs to the load balancer esp. if there is a requirement to whitelist IPs.
    • LB access logs provide the source IP address
    • supports Sticky sessions to enable the load balancer to bind a user’s session to a specific target.
  • Understand CloudFront and use cases
    • CloudFront can be used with S3 to expose static data and website
  • Know VPN and Direct Connect to provide AWS to on-premises connectivity. Not covered in detail.

Compute

  • Understand EC2 in depth
    • Understand EC2 instance types and use cases.
    • Understand EC2 purchase options esp. spot instances and improved reserved instances options.
    • Understand EC2 Metadata & Userdata.
    • Understand EC2 Security. 
      • Use IAM Role work with EC2 instances to access services
      • IAM Role can now be attached to stopped and runnings instances
    • AMIs provide the information required to launch an instance, which is a virtual server in the cloud.
      • AMIs are regional and can be shared publicly or with other accounts
      • Only AMIs with unencrypted volumes or encrypted with a CMK (customer-managed keys) can be shared.
      • The best practice is to use prebaked or golden images to reduce startup time for the applications. Leverage EC2 Image Builder.
    • Troubleshooting EC2 issues
      • RequestLimitExceeded
      • InstanceLimitExceeded – Concurrent running instance limit, default is 20, has been reached in a region. Request increase in limits.
      • InsufficientInstanceCapacity – AWS does not currently have enough available capacity to service the request. Change AZ or Instance Type.
    • Monitoring EC2 instances
      • System status checks failure – Stop and Start
      • Instance status checks failure – Reboot
    • EC2 supports Instance Recovery where the recovered instance is identical to the original instance, including the instance ID, private IP addresses, Elastic IP addresses, and all instance metadata.
    • EC2 Image Builder can be used to pre-baked images with software to speed up booting and launching time.
  • Understand Placement groups
    • Cluster Placement Group provide low latency, High-Performance Computing by the logical grouping of instances within a Single AZ
    • Spread Placement Groups is a group of instances that are each placed on distinct underlying hardware i.e. each instance on a distinct rack across AZ
    • Partition Placement Groups is a group of instances spread across partitions i.e. group of instances spread across racks across AZs
  • Understand Auto Scaling
    • Auto Scaling can be configured with multiple AZs for high availability to launch instances across multiple AZs
    • Auto Scaling attempts to distribute instances evenly between the AZs that are enabled for the Auto Scaling group
    • Auto Scaling supports
      • Dynamic scaling, which allows you to scale automatically in response to the changing demand
      • Schedule scaling, which allows you to scale the application in response to predictable load changes
      • Manual scaling can be performed by changing the desired capacity or adding and removing instances
    • Auto Scaling life cycle hooks can be used to perform activities before instance termination.
  • Understand Lambda and its use cases
    • Lambda functions can be hosted in VPC with internet access controlled by a NAT instance.
    • RDS Proxy acts as an intermediary between the application and an RDS database. RDS Proxy establishes and manages the necessary connection pools to the database so that the application creates fewer database connections.

Storage

  • S3 provides an object storage service
    • Understand storage classes with lifecycle policies
    • S3 data protection provides encryption at rest and encryption in transit
      • S3 default encryption can be used to encrypt the data with S3 bucket policies to prevent or reject unencrypted object uploads.
    • Multi-part handling for fault-tolerant and performant large file uploads
    • static website hosting, CORS
    • S3 Versioning can help recover from accidental deletes and overwrites.
    • Pre-Signed URLs for both upload and download
    • S3 Transfer Acceleration enables fast, easy, and secure transfers of files over long distances between the client and an S3 bucket using globally distributed edge locations in CloudFront.
  • Understand Glacier as archival storage. Glacier does not provide immediate access to the data even with expediated retrievals.
  • Understand EBS storage option
  • Storage Gateway allows storage of data in the AWS cloud for scalable and cost-effective storage while maintaining data security.
    •  Gateway-cached volumes stores data is stored in S3 and retains a copy of recently read data locally for low latency access to the frequently accessed data
    • Gateway-stored volumes maintain the entire data set locally to provide low latency access
  • EFS is a cost-optimized, serverless, scalable, and fully managed file storage for use with AWS Cloud and on-premises resources.
    • supports data at rest encryption only during the creation. After creation, the file system cannot be encrypted and must be copied over to a new encrypted disk.
    • supports General purpose and Max I/O performance mode.
    • If hitting PercentIOLimit issue move to Max I/O performance mode.
  • FSx makes it easy and cost-effective to launch, run, and scale feature-rich, high-performance file systems in the cloud
  • FSx for Windows supports SMB protocol and a Multi-AZ file system to provide high availability across multiple AZs.
  • AWS Backup can be used to automate backup for EC2 instances and EFS file systems
  • Data Lifecycle Manager to automate the creation, retention, and deletion of EBS snapshots and EBS-backed AMIs.
  • AWS DataSync automates moving data between on-premises storage and S3 or Elastic File System (EFS).

Databases

  • RDS provides cost-efficient, resizable capacity for an industry-standard relational database and manages common database administration tasks.
    • Understand RDS Multi-AZ vs Read Replicas and use cases
    • Multi-AZ deployment provides high availability, durability, and failover support
    • Read replicas enable increased scalability and database availability in the case of an AZ failure.
    • Automated backups and database change logs enable point-in-time recovery of the database during the backup retention period, up to the last five minutes of database usage.
  • Aurora is a fully managed, MySQL- and PostgreSQL-compatible, relational database engine
    • Backtracking “rewinds” the DB cluster to the specified time and performs in-place restore and does not create a new instance.
    • Automated Backups that help restore the DB as a new instance
  • Know ElastiCache use cases, mainly for caching performance
    • Understand ElastiCache Redis vs Memcached
    • Redis provides Multi-AZ support helps provide high availability across AZs and Online resharding to dynamically scale.
    • ElastiCache can be used as a caching layer for RDS.
  • Know DynamoDB. Not covered in detail

Security

  • IAM provides Identity and Access Management services.
  • S3 Encryption supports data at rest and in transit encryption
    • Understand S3 with SSE, SSE-C, SSE-KMS
    • S3 default encryption can help encrypt objects, however, it does not encrypt existing objects before the setting was enabled. You can use S3 Inventory to list the objects and S3 Batch to encrypt them.
  • Understand KMS for key management and envelope encryption
    • KMS with imported customer key material does not support rotation and has to be done manually.
  • AWS WAF – Web Application Firewall helps protect the applications against common web exploits like XSS or SQL Injection and bots that may affect availability, compromise security, or consume excessive resources
  • AWS GuardDuty is a threat detection service that continuously monitors the AWS accounts and workloads for malicious activity and delivers detailed security findings for visibility and remediation.
  • AWS Secrets Manager can help securely expose credentials as well as rotate them.
    • Secrets Manager integrates with Lambda and supports credentials rotation
  • AWS Shield is a managed Distributed Denial of Service (DDoS) protection service that safeguards applications running on AWS
  • Amazon Inspector
    • is an automated security assessment service that helps improve the security and compliance of applications deployed on AWS.
    • automatically assesses applications for exposure, vulnerabilities, and deviations from best practices.
  • AWS Certificate Manager (ACM) handles the complexity of creating, storing, and renewing public and private SSL/TLS X.509 certificates and keys that protect the AWS websites and applications.
  • Know AWS Artifact as on-demand access to compliance reports

Analytics

  • Amazon Athena can be used to query S3 data without duplicating the data and using SQL queries
  • OpenSearch (Elasticsearch) service is a distributed search and analytics engine built on Apache Lucene.
    • Opensearch production setup would be 3 AZs, 3 dedicated master nodes, 6 nodes with two replicas in each AZ.

Integration Tools

  • Understand SQS as a message queuing service and SNS as pub/sub notification service
    • Focus on SQS as a decoupling service
    • Understand SQS FIFO, make sure you know the differences between standard and FIFO
  • Understand CloudWatch integration with SNS for notification

Practice Labs

  • Create IAM users, IAM roles with specific limited policies.
  • Create a private S3 bucket
    • enable versioning
    • enable default encryption
    • enable lifecycle policies to transition and expire the objects
    • enable same region replication
  • Create a public S3 bucket with static website hosting
  • Set up a VPC with public and private subnets with Routes, SGs, NACLs.
  • Set up a VPC with public and private subnets and enable communication from private subnets to the Internet using NAT gateway
  • Create EC2 instance, create a Snapshot and restore it as a new instance.
  • Set up Security Groups for ALB and Target Groups, and create ALB, Launch Template, Auto Scaling Group, and target groups with sample applications. Test the flow.
  • Create Multi-AZ RDS instance and instance force failover.
  • Set up SNS topic. Use Cloud Watch Metrics to create a CloudWatch alarm on specific thresholds and send notifications to the SNS topic
  • Set up SNS topic. Use Cloud Watch Logs to create a CloudWatch alarm on log patterns and send notifications to the SNS topic.
  • Update a CloudFormation template and re-run the stack and check the impact.
  • Use AWS Data Lifecycle Manager to define snapshot lifecycle.
  • Use AWS Backup to define EFS backup with hourly and daily backup rules.

AWS Certified SysOps Administrator – Associate (SOA-C02) Exam Day

  • Make sure you are relaxed and get some good night’s sleep. The exam is not tough if you are well-prepared.
  • If you are taking the AWS Online exam
    • Try to join at least 30 minutes before the actual time as I have had issues with both PSI and Pearson with long wait times.
    • The online verification process does take some time and usually, there are glitches.
    • Remember, you would not be allowed to take the take if you are late by more than 30 minutes.
    • Make sure you have your desk clear, no hand-watches, or external monitors, keep your phones away, and nobody can enter the room.

Finally, All the Best 🙂

 

AWS Certified DevOps Engineer – Professional (DOP-C02) Exam Learning Path

AWS DevOps - Professional DOP-C02 Certificate
~ Last updated on : ~ jayendrapatil ~ 1 Comment

AWS Certified DevOps Engineer – Professional (DOP-C02) Exam Learning Path

  • AWS Certified DevOps Engineer – Professional (DOP-C02) exam is the upgraded pattern of the DevOps Engineer – Professional (DOP-C01) exam which was released in March 2023.
  • I recently attempted the latest pattern and DOP-C02 is quite similar to DOP-C01 with the inclusion of new services and features.

AWS Certified DevOps Engineer – Professional (DOP-C02) Exam Content

  • AWS Certified DevOps Engineer – Professional (DOP-C02) exam is intended for individuals who perform a DevOps engineer role and focuses on provisioning, operating, and managing distributed systems and services on AWS.
  • DOP-C02 basically validates
    • Implement and manage continuous delivery systems and methodologies on AWS
    • Implement and automate security controls, governance processes, and compliance validation
    • Define and deploy monitoring, metrics, and logging systems on AWS
    • Implement systems that are highly available, scalable, and self-healing on the AWS platform
    • Design, manage, and maintain tools to automate operational processes

Refer to AWS Certified DevOps Engineer – Professional Exam Guide

AWS DevOps - Professional DOP-C02 Exam Domains

AWS Certified DevOps Engineer – Professional (DOP-C02) Exam Resources

AWS Certified DevOps Engineer – Professional (DOP-C02) Exam Summary

  • Professional exams are tough, lengthy, and tiresome. Most of the questions and answers options have a lot of prose and a lot of reading that needs to be done, so be sure you are prepared and manage your time well.
  • Each solution involves multiple AWS services.
  • DOP-C02 exam has 75 questions to be solved in 170 minutes. Only 65 affect your score, while 10 unscored questions are for evaluation for future use.
  • DOP-C02 exam includes two types of questions, multiple-choice and multiple-response.
  • DOP-C02 has a scaled score between 100 and 1,000. The scaled score needed to pass the exam is 750.
  • Each question mainly touches multiple AWS services.
  • Professional exams currently cost $ 300 + tax.
  • You can get an additional 30 minutes if English is your second language by requesting Exam Accommodations. It might not be needed for Associate exams but is helpful for Professional and Specialty ones.
  • As always, mark the questions for review and move on and come back to them after you are done with all.
  • As always, having a rough architecture or mental picture of the setup helps focus on the areas that you need to improve. Trust me, you will be able to eliminate 2 answers for sure and then need to focus on only the other two. Read the other 2 answers to check the difference area and that would help you reach the right answer or at least have a 50% chance of getting it right.
  • AWS exams can be taken either remotely or online, I prefer to take them online as it provides a lot of flexibility. Just make sure you have a proper place to take the exam with no disturbance and nothing around you.
  • Also, if you are taking the AWS Online exam for the first time try to join at least 30 minutes before the actual time as I have had issues with both PSI and Pearson with long wait times.

AWS Certified DevOps Engineer – Professional (DOP-C02) Exam Topics

  • AWS Certified DevOps Engineer – Professional exam covers a lot of concepts and services related to Automation, Deployments, Disaster Recovery, HA, Monitoring, Logging, and Troubleshooting. It also covers security and compliance related topics.

Management & Governance tools

  • CloudFormation
    • provides an easy way to create and manage a collection of related AWS resources, provision and update them in an orderly and predictable fashion.
    • Make sure you have gone through and executed a CloudFormation template to provision AWS resources.
    • CloudFormation Concepts cover
      • Templates act as a blueprint for provisioning of AWS resources
      • Stacks are collection of resources as a single unit, that can be created, updated, and deleted by creating, updating, and deleting stacks.
      • Change Sets present a summary or preview of the proposed changes that CloudFormation will make when a stack is updated.
      • Nested stacks are stacks created as part of other stacks.
    • CloudFormation template anatomy consists of resources, parameters, outputs, and mappings.
    • CloudFormation supports multiple features
      • Drift detection enables you to detect whether a stack’s actual configuration differs, or has drifted, from its expected configuration.
      • Termination protection helps prevent a stack from being accidentally deleted.
      • Stack policy can prevent stack resources from being unintentionally updated or deleted during a stack update.
      • StackSets help create, update, or delete stacks across multiple accounts and Regions with a single operation.
      • Helper scripts with creation policies can help wait for the completion of events before provisioning or marking resources complete.
      • Update policy supports rolling and replacing updates with AutoScaling.
      • Deletion policies to help retain or backup resources during stack deletion.
      • Custom resources can be configured for uses cases not supported for e.g. retrieve AMI IDs or interact with external services
    • Understand CloudFormation Best Practices esp. Nested Stacks and logical grouping
  • Elastic Beanstalk
    • helps to quickly deploy and manage applications in the AWS Cloud without having to worry about the infrastructure that runs those applications. 
    • Understand Elastic Beanstalk overall – Applications, Versions, and Environments
    • Deployment strategies with their advantages and disadvantages
  • OpsWorks
    • is a configuration management service that helps to configure and operate applications in a cloud enterprise by using Chef.
    • Understand OpsWorks overall – stacks, layers, recipes
    • Understand OpsWorks Lifecycle events esp. the Configure event and how it can be used.
    • Understand OpsWorks Deployment Strategies
    • Know OpsWorks auto-healing and how to be notified for it.
  • Understand CloudFormation vs Elastic Beanstalk vs OpsWorks
  • AWS Organizations
  • Systems Manager
    • AWS Systems Manager and its various services like parameter store, patch manager
    • Parameter Store provides secure, scalable, centralized, hierarchical storage for configuration data and secret management. Does not support secrets rotation. Use Secrets Manager instead
    • Session Manager provides secure and auditable instance management without the need to open inbound ports, maintain bastion hosts, or manage SSH keys.
    • Patch Manager helps automate the process of patching managed instances with both security-related and other types of updates.
  • CloudWatch
    • supports monitoring, logging, and alerting.
    • CloudWatch logs can be used to monitor, store, and access log files from EC2 instances, CloudTrail, Route 53, and other sources. You can create metric filters over the logs.
    • CloudWatch Subscription Filters can be used to send logs to Kinesis Data Streams, Lambda, or Kinesis Data Firehose.
    • EventBridge (CloudWatch Events) is a serverless event bus service that makes it easy to connect applications with data from a variety of sources.
    • EventBridge or CloudWatch events can be used as a trigger for periodically scheduled events.
    • CloudWatch unified agent helps collect metrics and logs from EC2 instances and on-premises servers and push them to CloudWatch.
    • CloudWatch Synthetics helps create canaries, configurable scripts that run on a schedule, to monitor your endpoints and APIs
  • CloudTrail
    • for audit and governance
    • With Organizations, the trail can be configured to log CloudTrail from all accounts to a central account.
  • Config is a fully managed service that provides AWS resource inventory, configuration history, and configuration change notifications to enable security, compliance, and governance.
    • supports managed as well as custom rules that can be evaluated on periodic basis or as the event occurs for compliance and trigger automatic remediation
    • Conformance pack is a collection of AWS Config rules and remediation actions that can be easily deployed as a single entity in an account and a Region or across an organization in AWS Organizations.
  • Control Tower
    • to setup, govern, and secure a multi-account environment
    • strongly recommended guardrails cover EBS encryption
  • Service Catalog
    • allows organizations to create and manage catalogues of IT services that are approved for use on AWS with minimal permissions.
  • Trusted Advisor
    • helps with cost optimization and service limits in addition to security, performance, and fault tolerance.
  • AWS Health Dashboard is the single place to learn about the availability and operations of AWS services.

Developer Tools

  • Know AWS Developer tools
  • CodeCommit is a secure, scalable, fully-managed source control service that helps to host secure and highly scalable private Git repositories.
    • can help handle deployments of code to different environments using same repository and different branches.
  • CodeBuild is a fully managed build service that compiles source code, runs tests, and produces software packages that are ready to deploy.
  • CodeDeploy helps automate code deployments to any instance, including EC2 instances and instances running on-premises, Lambda, and ECS.
  • CodePipeline is a fully managed continuous delivery service that helps automate the release pipelines for fast and reliable application and infrastructure updates.
    • CodePipeline pipeline structure (Hint : run builds parallelly using runorder)
    • Understand how to configure notifications on events and failures
    • CodePipeline supports Manual Approval
  • CodeArtifact is a fully managed artifact repository service that makes it easy for organizations of any size to securely store, publish, and share software packages used in their software development process.
  • CodeGuru provides intelligent recommendations to improve code quality and identify an application’s most expensive lines of code. Reviewer helps improve code quality and Profiler helps optimize performance for applications
  • EC2 Image Builder helps to automate the creation, management, and deployment of customized, secure, and up-to-date server images that are pre-installed and pre-configured with software and settings to meet specific IT standards.

Disaster Recovery

  • Disaster recovery is mainly covered as a part of Re-silent cloud solutions.
  • Disaster Recovery whitepaper, although outdated, make sure you understand the differences and implementation for each type esp. pilot light, warm standby w.r.t RTO, and RPO.
  • Compute
    • Make components available in an alternate region,
    • Backup and Restore using either snapshots or AMIs that can be restored.
    • Use minimal low-scale capacity running which can be scaled once the failover happens
    • Use fully running compute in active-active confirmation with health checks.
    • CloudFormation to create, and scale infra as needed
  • Storage
    • S3 and EFS support cross-region replication
    • DynamoDB supports Global tables for multi-master, active-active inter-region storage needs.
    • Aurora Global Database provides cross-region read replicas and failover capabilities.
    • RDS supports cross-region read replicas which can be promoted to master in case of a disaster. This can be done using Route 53, CloudWatch, and lambda functions.
  • Network
    • Route 53 failover routing with health checks to failover across regions.
    • CloudFront Origin Groups support primary and secondary endpoints with failover.

Networking & Content Delivery

  • Networking is covered very lightly.
  • VPC – Virtual Private Cloud
    • Security Groups, NACLs
      • NACLs are stateless and need to open ephemeral ports for response traffic.
    • VPC Gateway Endpoints to provide access to S3 and DynamoDB
    • VPC Interface Endpoints or PrivateLink provide access to a variety of services like SQS, Kinesis, or Private APIs exposed through NLB.
    • VPC Peering to enable communication between VPCs within the same or different regions.
    • VPC Peering does not support overlapping CIDRs while PrivateLink does as only the endpoint is exposed.
    • VPC Flow Logs to track network traffic and can be published to CloudWatch Logs, S3, or Kinesis Data Firehose.
    • NAT Gateway provides managed NAT service that provides better availability, higher bandwidth, and requires less administrative effort.
  • Route 53
    • Routing Policies
      • focus on Weighted, Latency, and failover routing policies
      • failover routing provides active-passive configuration for disaster recovery while the others are active-active configurations.
  • CloudFront
    • fully managed, fast CDN service that speeds up the distribution of static, dynamic web or streaming content to end-users.
  • Load Balancer – ELB, ALB and NLB
    • ELB with Auto Scaling to provide scalable and highly available applications
    • Understand ALB vs NLB and their use cases.
    • Access logs needs to be enabled and logs only to S3.
  • Direct Connect & VPN
    • provide on-premises to AWS connectivity
    • Understand Direct Connect vs VPN
    • VPN can provide a cost-effective, quick failover for Direct Connect.
    • VPN over Direct Connect provides a secure dedicated connection and requires a public virtual interface.

Security, Identity & Compliance

  • AWS Identity and Access Management
  • AWS WAF
    • protects from common attack techniques like SQL injection and XSS, Conditions based include IP addresses, HTTP headers, HTTP body, and URI strings.
    • integrates with CloudFront, ALB, and API Gateway.
  • AWS KMS – Key Management Service
    • managed encryption service that allows the creation and control of encryption keys to enable data encryption.
  • Secrets Manager
    • helps protect secrets needed to access applications, services, and IT resources.
  • AWS GuardDuty
    • is a threat detection service that continuously monitors the AWS accounts and workloads for malicious activity and delivers detailed security findings for visibility and remediation.
  • AWS Security Hub is a cloud security posture management service that performs security best practice checks, aggregates alerts and enables automated remediation.
  • Firewall Manager helps centrally configure and manage firewall rules across the accounts and applications in AWS Organizations which includes a variety of protections, including WAF, Shield Advanced, VPC security groups, Network Firewall, and Route 53 Resolver DNS Firewall.

Storage

Database

Compute

  • EC2
  • Auto Scaling provides the ability to ensure a correct number of EC2 instances are always running to handle the load of the application
    • Auto Scaling Lifecycle events enable performing custom actions by pausing instances as an ASG launches or terminates them.
    • Blue/green deployments with Auto Scaling – With new launch configurations, new auto-scaling groups, or CloudFormation update policies.
  • Lambda
    • offers Serverless computing 
    • helps define reserved concurrency limits to reduce the impact
    • Lambda Alias now supports canary deployments
    • Reserved Concurrency guarantees the maximum number of concurrent instances for the function
    • Provisioned Concurrency
      • provides greater control over the performance of serverless applications and helps keep functions initialized and hyper-ready to respond in double-digit milliseconds.
      • supports Application Auto Scaling.
  • Step Functions helps developers use AWS services to build distributed applications, automate processes, orchestrate microservices, and create data and machine learning (ML) pipelines.
  • ECS – Elastic Container Service
    • container management service that supports Docker containers
    • supports two launch types
      • EC2 and
      • Fargate which provides the serverless capability
  • ECR provides a fully managed, secure, scalable, reliable container image registry service. It supports lifecycle policies for images.

Integration Tools

  • SQS in terms of loose coupling and scaling.
    • Difference between SQS Standard and FIFO esp. with throughput and order
    • SQS supports dead letter queues and redrive policy which specifies the source queue, the dead-letter queue, and the conditions under which SQS moves messages from the former to the latter if the consumer of the source queue fails to process a message a specified number of times.
  • CloudWatch integration with SNS and Lambda for notifications.

Analytics

Whitepapers

AWS Certified DevOps Engineer – Professional (DOP-C02) Exam Day

  • Make sure you are relaxed and get some good night’s sleep. The exam is not tough if you are well-prepared.
  • If you are taking the AWS Online exam
    • Try to join at least 30 minutes before the actual time as I have had issues with both PSI and Pearson with long wait times.
    • The online verification process does take some time and usually, there are glitches.
    • Remember, you would not be allowed to take the take if you are late by more than 30 minutes.
    • Make sure you have your desk clear, no hand-watches, or external monitors, keep your phones away, and nobody can enter the room.

Finally, All the Best 🙂

  •  

Kubernetes Resources

~ Last updated on : ~ jayendrapatil

Kubernetes Resources

Kubernetes Resources

Namespaces

  • Namespaces provide a mechanism for isolating groups of resources within a single cluster.
  • Namespace-based scoping is applicable only for namespaced objects (e.g. Deployments, Services, etc) and not for cluster-wide objects (e.g. StorageClass, Nodes, PersistentVolumes, etc).
  • Names of resources need to be unique within a namespace, but not across namespaces.
  • Kubernetes starts with four initial namespaces:
    • default – default namespace for objects with no other namespace.
    • kube-system – namespace for objects created by the Kubernetes system.
    • kube-public – namespace is created automatically and is readable by all users (including those not authenticated).
    • kube-node-lease – namespace holds Lease objects associated with each node. Node leases allow the kubelet to send heartbeats so that the control plane can detect node failure.
  • Resource Quotas can be defined for each namespace to limit the resources consumed.
  • Resources within the namespaces can refer to each other with their service names.
  • Resources across namespace can be reached using the full DNS <<service_name>>.<<namespace_name>>.svc.cluster.local

Practice Namespace Exercises

Pods

  • A Kubernetes pod is a group of containers and is the smallest unit that Kubernetes administers.
  • Pods have a single IP address applied to every container within the pod.
  • Pods are always co-located and co-scheduled and run in a shared context.
  • Containers in a pod share the same resources such as memory and storage.
  • Shared context allows the individual Linux containers inside a pod to be treated collectively as a single application as if all the containerized processes were running together on the same host in more traditional workloads.

Practice Pod Exercises

ReplicaSet

  • ReplicaSet ensures to maintain a stable set of replica Pods running at any given time. It helps guarantee the availability of a specified number of identical Pods.
  • ReplicaSet includes the pod definition template, a selector to match the pods, and a number of replicas.
  • ReplicaSet then fulfills its purpose by creating and deleting Pods as needed to reach the desired replica number using the Pod template.
  • It is recommended to use Deployments instead of directly using ReplicaSets, as they help manage ReplicaSets and provide declarative updates to Pods.

Practice ReplicaSet Exercises

Deployment

  • Deployment provides declarative updates for Pods and ReplicaSets.
  • Deployments describe the number of desired identical pod replicas to run and the preferred update strategy used when updating the deployment.
  • A Deployment runs multiple replicas of your application and automatically replaces any instances that fail or become unresponsive.
  • Deployments represent a set of multiple, identical Pods with no unique identities.
  • Deployments are well-suited for stateless applications that use ReadOnlyMany or ReadWriteMany volumes mounted on multiple replicas but are not well-suited for workloads that use ReadWriteOnce volumes. Use StatefulSets instead.

Deploy Container Resources

Practice Deployment Exercises

Services

  • Service is an abstraction over the pods, and essentially, the only interface the various application consumers interact with.
  • The lifetime of an individual pod cannot be relied upon; everything from their IP addresses to their very existence is prone to change.
  • Kubernetes doesn’t treat its pods as unique, long-running instances; if a pod encounters an issue and dies, it’s Kubernetes’ job to replace it so that the application doesn’t experience any downtime.
  • As pods are replaced, their internal names and IPs might change.
  • A service exposes a single machine name or IP address mapped to pods whose underlying names and numbers are unreliable.
  • A service ensures that, to the outside network, everything appears to be unchanged.

Practice Services Exercises

Ingress

Ingress

  • Ingress exposes HTTP and HTTPS routes from outside the cluster to services within the cluster.
  • Traffic routing is controlled by rules defined on the Ingress resource.
  • An Ingress may be configured to give Services externally-reachable URLs, load balance traffic, terminate SSL/TLS and offer name-based virtual hosting
  • An Ingress controller is responsible for fulfilling the Ingress, usually with a load balancer, though it may also configure your edge router or additional frontends to help handle the traffic.
  • An Ingress with no rules sends all traffic to a single default backend.

Practice Ingress Exercises

DaemonSet

  • A DaemonSet ensures that all (or some) Nodes run a copy of a Pod.
  • DaemonSet ensures pods are added to the newly created nodes and garbage collected as nodes are removed.
  • Some typical uses of a DaemonSet are:
    • running a cluster storage daemon on every node
    • running a logs collection daemon on every node
    • running a node monitoring daemon on every node

Refer DaemonSet Exercises

StatefulSet

StatefulSet Architecture

  • StatefulSet is ideal for stateful applications using ReadWriteOnce volumes.
  • StatefulSets are designed to deploy stateful applications and clustered applications that save data to persistent storage, such as persistent disks.
  • StatefulSets represent a set of Pods with unique, persistent identities and stable hostnames that Kubernetes maintains regardless of where they are scheduled.
  • State information and other resilient data for any given StatefulSet Pod are maintained in persistent disk storage associated with the StatefulSet.
  • StatefulSets use an ordinal index for the identity and ordering of their Pods. By default, StatefulSet Pods are deployed in sequential order and are terminated in reverse ordinal order.
  • StatefulSets are suitable for deploying Kafka, MySQL, Redis, ZooKeeper, and other applications needing unique, persistent identities and stable hostnames.

ConfigMaps

  • ConfigMap helps to store non-confidential data in key-value pairs.
  • Pods can consume ConfigMaps as environment variables, command-line arguments, or as configuration files in a volume.
  • ConfigMap helps decouple environment-specific configuration from the container images so that the applications are easily portable.
  • ConfigMap does not provide secrecy or encryption. If the data you want to store are confidential, use a Secret rather than a ConfigMap, or use additional (third party) tools to keep your data private.
  • A ConfigMap is not designed to hold large chunks of data and cannot exceed 1 MiB.
  • ConfigMap can be configured on a container inside a Pod as
    • Inside a container command and args
    • Environment variables for a container
    • Add a file in read-only volume, for the application to read
    • Write code to run inside the Pod that uses the Kubernetes API to read a ConfigMap
  • ConfigMap can be configured to be immutable as it helps
    • protect from accidental (or unwanted) updates that could cause applications outages
    • improve performance of the cluster by significantly reducing the load on kube-apiserver , by closing watches for ConfigMaps marked as immutable.
  • Once a ConfigMap is marked as immutable, it is not possible to revert this change nor to mutate the contents of the data or the binaryData field. The ConfigMap needs to be deleted and recreated.

Practice ConfigMaps Exercises

Secrets

  • Secret provides a container for sensitive data such as a password without putting the information in a Pod specification or in a container image.
  • Secrets are similar to ConfigMaps but are specifically intended to hold confidential data.
  • Secrets are not really encrypted but only base64 encoded.
  • Secrets are, by default, stored unencrypted in the API server’s underlying data store (etcd). Anyone with API access can retrieve or modify a Secret, and so can anyone with access to etcd. Additionally, anyone who is authorized to create a Pod in a namespace can use that access to read any Secret in that namespace; this includes indirect access such as the ability to create a Deployment.
  • To safeguard secrets, take at least the following steps:
    • Enable Encryption at Rest for Secrets.
    • Enable or configure RBAC rules that restrict reading data in Secrets.

Practice Secrets Exercises

Jobs & Cron Jobs

  • Job creates one or more Pods and will continue to retry execution of the Pods until a specified number of them successfully terminate.
  • As pods successfully complete, the Job tracks the successful completions.
  • When a specified number of successful completions is reached, the task (ie, Job) is complete.
  • Deleting a Job will clean up the Pods it created. Suspending a Job will delete its active Pods until the Job is resumed again.
  • A job can run multiple Pods in parallel using Parallelism field.
  • A CronJob creates Jobs on a repeating schedule.

Practice Jobs Exercises

Volumes

Kubernetes Volumes

  • Container on-disk files are ephemeral and lost if the container crashes.
  • Kubernetes supports Persistent volumes that exist beyond the lifetime of a pod. When a pod ceases to exist, Kubernetes destroys ephemeral volumes; however, Kubernetes does not destroy persistent volumes.
  • Persistent Volumes is supported using API resources
    • PersistentVolume (PV)
      • is a piece of storage in the cluster that has been provisioned by an administrator or dynamically provisioned using Storage Classes.
      • is a cluster-level resource and not bound to a namespace
      • are volume plugins like Volumes, but have a lifecycle independent of any individual pod that uses the PV.
    • PersistentVolumeClaim (PVC)
      • is a request for storage by a user.
      • is similar to a Pod.
      • Pods consume node resources and PVCs consume PV resources.
      • Pods can request specific levels of resources (CPU and Memory).
      • Claims can request specific size and access modes (e.g., they can be mounted ReadWriteOnce, ReadOnlyMany, or ReadWriteMany, see AccessModes).
  • Persistent Volumes can be provisioned
    • Statically – where the cluster administrator creates the PVs which is available for use by cluster users
    • Dynamically using StorageClasses where the cluster may try to dynamically provision a volume especially for the PVC.

Practice Volumes Exercises

Labels & Annotations

  • Labels and Annotations attach metadata to objects in Kubernetes.
  • Labels
    • are key/value pairs that can be attached to Kubernetes objects such as Pods and ReplicaSets.
    • can be arbitrary and are useful for attaching identifying information to Kubernetes objects.
    • provide the foundation for grouping objects and can be used to organize and to select subsets of objects.
    • are used in conjunction with selectors to identify groups of related resources.
  • Annotations
    • provide a storage mechanism that resembles labels
    • are key/value pairs designed to hold non-identifying information that can be leveraged by tools and libraries.

Practice Labels & Annotations Exercises

Nodes

  • A Kubernetes node manages and runs pods; it’s the machine (whether virtualized or physical) that performs the given work.
  • Just as pods collect individual containers that operate together, a node collects entire pods that function together.
  • When you’re operating at scale, you want to be able to hand work over to a node whose pods are free to take it.

Practice Nodes Exercises

AWS S3 Storage Classes

S3 Storage Classes Performance
~ Last updated on : ~ jayendrapatil ~ 19 Comments

AWS S3 Storage Classes

  • AWS S3 offers a range of S3 Storage Classes to match the use case scenario and performance access requirements.
  • S3 storage classes are designed to sustain the concurrent loss of data in one or two facilities.
  • S3 storage classes allow lifecycle management for automatic transition of objects for cost savings.
  • All S3 storage classes provide the same durability, first-byte latency, and support SSL encryption of data in transit, and data encryption at rest.
  • S3 also regularly verifies the integrity of the data using checksums and provides the auto-healing capability.

S3 Storage Classes Comparison

S3 Storage Classes Performance

S3 Standard

  • STANDARD is the default storage class, if none specified during upload
  • Low latency and high throughput performance
  • Designed for 99.999999999% i.e. 11 9’s Durability of objects across AZs
  • Designed for 99.99% availability over a given year
  • Resilient against events that impact an entire Availability Zone and is designed to sustain the loss of data in a two facilities
  • Ideal for performance-sensitive use cases and frequently accessed data
  • S3 Standard is appropriate for a wide variety of use cases, including cloud applications, dynamic websites, content distribution, mobile and gaming applications, and big data analytics.

S3 Intelligent Tiering (S3 Intelligent-Tiering)

  • S3 Intelligent Tiering storage class is designed to optimize storage costs by automatically moving data to the most cost-effective storage access tier, without performance impact or operational overhead.
  • Delivers automatic cost savings by moving data on a granular object-level between two access tiers
    • one tier that is optimized for frequent access and
    • another lower-cost tier that is optimized for infrequently accessed data.
  • a frequent access tier and a lower-cost infrequent access tier, when access patterns change.
  • Ideal to optimize storage costs automatically for long-lived data when access patterns are unknown or unpredictable.
  • For a small monthly monitoring and automation fee per object, S3 monitors access patterns of the objects and moves objects that have not been accessed for 30 consecutive days to the infrequent access tier.
  • There are no separate retrieval fees when using the Intelligent Tiering storage class. If an object in the infrequent access tier is accessed, it is automatically moved back to the frequent access tier.
  • No additional fees apply when objects are moved between access tiers
  • Suitable for objects greater than 128 KB (smaller objects are charged for 128 KB only) kept for at least 30 days (charged for a minimum of 30 days)
  • Same low latency and high throughput performance of S3 Standard
  • Designed for 99.999999999% i.e. 11 9’s Durability of objects across AZs
  • Designed for 99.9% availability over a given year

S3 Standard-Infrequent Access (S3 Standard-IA)

  • S3 Standard-Infrequent Access storage class is optimized for long-lived and less frequently accessed data. for e.g. for  backups and older data where access is limited, but the use case still demands high performance
  • Ideal for use for the primary or only copy of data that can’t be recreated.
  • Data stored redundantly across multiple geographically separated AZs and are resilient to the loss of an Availability Zone.
  • offers greater availability and resiliency than the ONEZONE_IA class.
  • Objects are available for real-time access.
  • Suitable for larger objects greater than 128 KB (smaller objects are charged for 128 KB only) kept for at least 30 days (charged for minimum 30 days)
  • Same low latency and high throughput performance of Standard
  • Designed for 99.999999999% i.e. 11 9’s Durability of objects across AZs
  • Designed for 99.9% availability over a given year
  • S3 charges a retrieval fee for these objects, so they are most suitable for infrequently accessed data.

S3 One Zone-Infrequent Access (S3 One Zone-IA)

  • S3 One Zone-Infrequent Access storage classes are designed for long-lived and infrequently accessed data, but available for millisecond access (similar to the STANDARD and STANDARD_IA storage class).
  • Ideal when the data can be recreated if the AZ fails, and for object replicas when setting cross-region replication (CRR).
  • Objects are available for real-time access.
  • Suitable for objects greater than 128 KB (smaller objects are charged for 128 KB only) kept for at least 30 days (charged for a minimum of 30 days)
  • Stores the object data in only one AZ, which makes it less expensive than Standard-Infrequent Access
  • Data is not resilient to the physical loss of the AZ resulting from disasters, such as earthquakes and floods.
  • One Zone-Infrequent Access storage class is as durable as Standard-Infrequent Access, but it is less available and less resilient.
  • Designed for 99.999999999% i.e. 11 9’s Durability of objects in a single AZ
  • Designed for 99.5% availability over a given year
  • S3 charges a retrieval fee for these objects, so they are most suitable for infrequently accessed data.

Reduced Redundancy Storage – RRS

  • NOTE – AWS recommends not to use this storage class. The STANDARD storage class is more cost-effective now.
  • Reduced Redundancy Storage (RRS) storage class is designed for non-critical, reproducible data stored at lower levels of redundancy than the STANDARD storage class, which reduces storage costs
  • Designed for durability of 99.99% of objects
  • Designed for 99.99% availability over a given year
  • Lower level of redundancy results in less durability and availability
  • RRS stores object on multiple devices across multiple facilities, providing 400 times the durability of a typical disk drive,
  • RRS does not replicate objects as many times as S3 standard storage and is designed to sustain the loss of data in a single facility.
  • If an RRS object is lost, S3 returns a 405 error on requests made to that object
  • S3 can send an event notification, configured on the bucket, to alert a user or start a workflow when it detects that an RRS object is lost which can be used to replace the lost object

S3 Glacier Instant Retrieval

  • Use for archiving data that is rarely accessed and requires milliseconds retrieval.
  • Storage class has a minimum storage duration period of 90 days
  • Designed for 99.999999999% i.e. 11 9’s Durability of objects across AZs
  • Designed for 99.99% availability

S3 Glacier Flexible Retrieval – S3 Glacier

  • S3 GLACIER storage class is suitable for low-cost data archiving where data access is infrequent and retrieval time of minutes to hours is acceptable.
  • Storage class has a minimum storage duration period of 90 days
  • Provides configurable retrieval times, from minutes to hours
    • Expedited retrieval: 1-5 mins
    • Standard retrieval: 3-5 hours
    • Bulk retrieval: 5-12 hours
  • GLACIER storage class uses the very low-cost Glacier storage service, but the objects in this storage class are still managed through S3
  • For accessing GLACIER objects,
    • the object must be restored which can take anywhere between minutes to hours
    • objects are only available for the time period (the number of days) specified during the restoration request
    • object’s storage class remains GLACIER
    • charges are levied for both the archive (GLACIER rate) and the copy restored temporarily
  • Vault Lock feature enforces compliance via a lockable policy.
  • Offers the same durability and resiliency as the STANDARD storage class
  • Designed for 99.999999999% i.e. 11 9’s Durability of objects across AZs
  • Designed for 99.99% availability

S3 Glacier Deep Archive

  • Glacier Deep Archive storage class provides the lowest-cost data archiving where data access is infrequent and retrieval time of hours is acceptable.
  • Has a minimum storage duration period of 180 days and can be accessed at a default retrieval time of 12 hours.
  • Supports long-term retention and digital preservation for data that may be accessed once or twice a year
  • Designed for 99.999999999% i.e. 11 9’s Durability of objects across AZs
  • Designed for 99.9% availability over a given year
  • DEEP_ARCHIVE retrieval costs can be reduced by using bulk retrieval, which returns data within 48 hours.
  • Ideal alternative to magnetic tape libraries

S3 Analytics – S3 Storage Classes Analysis

  • S3 Analytics – Storage Class Analysis helps analyze storage access patterns to decide when to transition the right data to the right storage class.
  • S3 Analytics feature observes data access patterns to help determine when to transition less frequently accessed STANDARD storage to the STANDARD_IA (IA, for infrequent access) storage class.
  • Storage Class Analysis can be configured to analyze all the objects in a bucket or filters to group objects.

AWS Certification Exam Practice Questions

  • Questions are collected from Internet and the answers are marked as per my knowledge and understanding (which might differ with yours).
  • AWS services are updated everyday and both the answers and questions might be outdated soon, so research accordingly.
  • AWS exam questions are not updated to keep up the pace with AWS updates, so even if the underlying feature has changed the question might not be updated
  • Open to further feedback, discussion and correction.
  1. What does RRS stand for when talking about S3?
    1. Redundancy Removal System
    2. Relational Rights Storage
    3. Regional Rights Standard
    4. Reduced Redundancy Storage
  2. What is the durability of S3 RRS?
    1. 99.99%
    2. 99.95%
    3. 99.995%
    4. 99.999999999%
  3. What is the Reduced Redundancy option in Amazon S3?
    1. Less redundancy for a lower cost
    2. It doesn’t exist in Amazon S3, but in Amazon EBS.
    3. It allows you to destroy any copy of your files outside a specific jurisdiction.
    4. It doesn’t exist at all
  4. An application is generating a log file every 5 minutes. The log file is not critical but may be required only for verification in case of some major issue. The file should be accessible over the internet whenever required. Which of the below mentioned options is a best possible storage solution for it?
    1. AWS S3
    2. AWS Glacier
    3. AWS RDS
    4. AWS S3 RRS (Reduced Redundancy Storage (RRS) is an Amazon S3 storage option that enables customers to store noncritical, reproducible data at lower levels of redundancy than Amazon S3’s standard storage. RRS is designed to sustain the loss of data in a single facility.)
  5. A user has moved an object to Glacier using the life cycle rules. The user requests to restore the archive after 6 months. When the restore request is completed the user accesses that archive. Which of the below mentioned statements is not true in this condition?
    1. The archive will be available as an object for the duration specified by the user during the restoration request
    2. The restored object’s storage class will be RRS (After the object is restored the storage class still remains GLACIER. Read more)
    3. The user can modify the restoration period only by issuing a new restore request with the updated period
    4. The user needs to pay storage for both RRS (restored) and Glacier (Archive) Rates
  6. Your department creates regular analytics reports from your company’s log files. All log data is collected in Amazon S3 and processed by daily Amazon Elastic Map Reduce (EMR) jobs that generate daily PDF reports and aggregated tables in CSV format for an Amazon Redshift data warehouse. Your CFO requests that you optimize the cost structure for this system. Which of the following alternatives will lower costs without compromising average performance of the system or data integrity for the raw data? [PROFESSIONAL]
    1. Use reduced redundancy storage (RRS) for PDF and CSV data in Amazon S3. Add Spot instances to Amazon EMR jobs. Use Reserved Instances for Amazon Redshift. (Spot instances impacts performance)
    2. Use reduced redundancy storage (RRS) for all data in S3. Use a combination of Spot instances and Reserved Instances for Amazon EMR jobs. Use Reserved instances for Amazon Redshift (Combination of the Spot and reserved with guarantee performance and help reduce cost. Also, RRS would reduce cost and guarantee data integrity, which is different from data durability )
    3. Use reduced redundancy storage (RRS) for all data in Amazon S3. Add Spot Instances to Amazon EMR jobs. Use Reserved Instances for Amazon Redshift (Spot instances impacts performance)
    4. Use reduced redundancy storage (RRS) for PDF and CSV data in S3. Add Spot Instances to EMR jobs. Use Spot Instances for Amazon Redshift. (Spot instances impacts performance)
  7. Which of the below mentioned options can be a good use case for storing content in AWS RRS?
    1. Storing mission critical data Files
    2. Storing infrequently used log files
    3. Storing a video file which is not reproducible
    4. Storing image thumbnails
  8. A newspaper organization has an on-premises application which allows the public to search its back catalogue and retrieve individual newspaper pages via a website written in Java. They have scanned the old newspapers into JPEGs (approx. 17TB) and used Optical Character Recognition (OCR) to populate a commercial search product. The hosting platform and software is now end of life and the organization wants to migrate its archive to AWS and produce a cost efficient architecture and still be designed for availability and durability. Which is the most appropriate? [PROFESSIONAL]
    1. Use S3 with reduced redundancy to store and serve the scanned files, install the commercial search application on EC2 Instances and configure with auto-scaling and an Elastic Load Balancer. (RRS impacts durability and commercial search would add to cost)
    2. Model the environment using CloudFormation. Use an EC2 instance running Apache webserver and an open source search application, stripe multiple standard EBS volumes together to store the JPEGs and search index. (Using EBS is not cost effective for storing files)
    3. Use S3 with standard redundancy to store and serve the scanned files, use CloudSearch for query processing, and use Elastic Beanstalk to host the website across multiple availability zones. (Standard S3 and Elastic Beanstalk provides availability and durability, Standard S3 and CloudSearch provides cost effective storage and search)
    4. Use a single-AZ RDS MySQL instance to store the search index and the JPEG images use an EC2 instance to serve the website and translate user queries into SQL. (RDS is not ideal and cost effective to store files, Single AZ impacts availability)
    5. Use a CloudFront download distribution to serve the JPEGs to the end users and Install the current commercial search product, along with a Java Container for the website on EC2 instances and use Route53 with DNS round-robin. (CloudFront needs a source and using commercial search product is not cost effective)
  9. A research scientist is planning for the one-time launch of an Elastic MapReduce cluster and is encouraged by her manager to minimize the costs. The cluster is designed to ingest 200TB of genomics data with a total of 100 Amazon EC2 instances and is expected to run for around four hours. The resulting data set must be stored temporarily until archived into an Amazon RDS Oracle instance. Which option will help save the most money while meeting requirements? [PROFESSIONAL]
    1. Store ingest and output files in Amazon S3. Deploy on-demand for the master and core nodes and spot for the task nodes.
    2. Optimize by deploying a combination of on-demand, RI and spot-pricing models for the master, core and task nodes. Store ingest and output files in Amazon S3 with a lifecycle policy that archives them to Amazon Glacier. (Master and Core must be RI or On Demand. Cannot be Spot)
    3. Store the ingest files in Amazon S3 RRS and store the output files in S3. Deploy Reserved Instances for the master and core nodes and on-demand for the task nodes. (Need better durability for ingest file. Spot instances can be used for task nodes for cost saving.)
    4. Deploy on-demand master, core and task nodes and store ingest and output files in Amazon S3 RRS (Input must be in S3 standard)

AWS Compute Optimizer

~ Last updated on : ~ jayendrapatil

AWS Compute Optimizer

  • AWS Compute Optimizer helps analyze the configuration and utilization metrics of the AWS resources.
  • reports whether the resources are optimal, and generates optimization recommendations to reduce the cost and improve the performance of the workloads.
  • delivers intuitive and easily actionable resource recommendations to help quickly identify optimal AWS resources for the workloads without requiring specialized expertise or investing substantial time and money.
  • provides a global, cross-account view of all resources
  • analyzes the specifications and the utilization metrics of the resources from CloudWatch for the last 14 days.
  • provides graphs showing recent utilization metric history data, as well as projected utilization for recommendations, which can be used to evaluate which recommendation provides the best price-performance trade-off.
  • Analysis and visualization of the usage patterns can help decide when to move or resize the running resources, and still meet your performance and capacity requirements.
  • generates recommendations for the following resources:

AWS Certification Exam Practice Questions

  • Questions are collected from Internet and the answers are marked as per my knowledge and understanding (which might differ with yours).
  • AWS services are updated everyday and both the answers and questions might be outdated soon, so research accordingly.
  • AWS exam questions are not updated to keep up the pace with AWS updates, so even if the underlying feature has changed the question might not be updated
  • Open to further feedback, discussion and correction.
  1. A company must assess the business’s EC2 instances and Elastic Block Store (EBS) volumes to determine how effectively the business is using resources. The company has not detected a pattern in how these EC2 instances are used by the apps that access the databases. Which option best fits these criteria in terms of cost-effectiveness?
    1. Use AWS Systems Manager OpsCenter.
    2. Use Amazon CloudWatch for detailed monitoring.
    3. Use AWS Compute Optimizer.
    4. Sign up for the AWS Enterprise Support plan. Turn on AWS Trusted Advisor.

References

AWS_Compute_Optimizer

AWS Auto Scaling Launch Template vs Launch Configuration

Auto Scaling Launch Template vs Launch Configuration
~ jayendrapatil

Auto Scaling Launch Template vs Launch Configuration

Auto Scaling Launch Template vs Launch Configuration

Launch Configuration

  • Launch configuration is an instance configuration template that an Auto Scaling Group uses to launch EC2 instances.
  • Launch configuration is similar to EC2 configuration and involves the selection of the Amazon Machine Image (AMI), block devices, key pair, instance type, security groups, user data, EC2 instance monitoring, instance profile, kernel, ramdisk, the instance tenancy, whether the instance has a public IP address, and is EBS-optimized.
  • Launch configuration can be associated with multiple ASGs
  • Launch configuration can’t be modified after creation and needs to be created new if any modification is required.
  • Basic or detailed monitoring for the instances in the ASG can be enabled when a launch configuration is created.
  • By default, basic monitoring is enabled when you create the launch configuration using the AWS Management Console, and detailed monitoring is enabled when you create the launch configuration using the AWS CLI or an API
  • AWS recommends using Launch Template instead.

Launch Template

  • A Launch Template is similar to a launch configuration, with additional features, and is recommended by AWS.
  • Launch Template allows multiple versions of a template to be defined.
  • With versioning, a subset of the full set of parameters can be created and then reused to create other templates or template versions for e.g, a default template that defines common configuration parameters can be created and allow the other parameters to be specified as part of another version of the same template.
  • Launch Template allows the selection of both Spot and On-Demand Instances or multiple instance types.
  • Launch templates support EC2 Dedicated Hosts. Dedicated Hosts are physical servers with EC2 instance capacity that are dedicated to your use.
  • Launch templates provide the following features
    • Support for multiple instance types and purchase options in a single ASG.
    • Launching Spot Instances with the capacity-optimized allocation strategy.
    • Support for launching instances into existing Capacity Reservations through an ASG.
    • Support for unlimited mode for burstable performance instances.
    • Support for Dedicated Hosts.
    • Combining CPU architectures such as Intel, AMD, and ARM (Graviton2)
    • Improved governance through IAM controls and versioning.
    • Automating instance deployment with Instance Refresh.

AWS Certification Exam Practice Questions

  • Questions are collected from Internet and the answers are marked as per my knowledge and understanding (which might differ with yours).
  • AWS services are updated everyday and both the answers and questions might be outdated soon, so research accordingly.
  • AWS exam questions are not updated to keep up the pace with AWS updates, so even if the underlying feature has changed the question might not be updated
  • Open to further feedback, discussion and correction.
  1. A company is launching a new workload. The workload will run on Amazon EC2 instances in an Amazon EC2 Auto Scaling group. The company needs to maintain different versions of the EC2 configurations. The company also needs the Auto Scaling group to automatically scale to maintain CPU utilization of 60%. How can a SysOps administrator meet these requirements?
    1. Configure the Auto Scaling group to use a launch configuration with a target tracking scaling policy.
    2. Configure the Auto Scaling group to use a launch configuration with a simple scaling policy.
    3. Configure the Auto Scaling group to use a launch template with a target tracking scaling policy.
    4. Configure the Auto Scaling group to use a launch template with a simple scaling policy.

References

AWS_Launch_Template

Breaking into Data Analytics: Tips and Strategies for Aspiring Data Analysts

~ Last updated on : ~ jayendrapatil

Breaking into Data Analytics: Tips and Strategies for Aspiring Data Analysts

Data analytics is analyzing and interpreting data to draw meaningful insights and conclusions. In today’s data-driven world, data analytics has become crucial for businesses to make informed decisions and gain a competitive edge. It uses statistical and computational techniques to analyze large datasets, identify patterns, and make predictions.

Data analytics is essential because it enables organizations to identify trends, make accurate forecasts, and gain insights into customer behavior. Businesses can make data-driven decisions, improve efficiency, and increase profitability by leveraging data analytics.

Anyone interested in working with data can benefit from data analytics. Whether you’re a recent graduate, a mid-career professional, or an executive, data analytics skills can help you progress your career and achieve your goals.

What is Data Analytics and Why is it Important?

Data analytics is the approach of analyzing and interpreting data to extract meaningful insights and information. It involves using various techniques and tools to examine large datasets, identify patterns, and draw conclusions. It has become increasingly important in today’s business landscape, enabling organizations to make informed decisions based on data-driven insights.

Data analytics is crucial for businesses because it helps them to identify trends, make accurate forecasts, and gain insights into customer behavior. With the help of data analytics, organizations can improve their operations, optimize their resources, and increase profitability. It can also help businesses identify improvement areas, streamline their processes, and stay ahead of the competition.

Data analytics is a growing field with a high demand for skilled professionals. There are various career opportunities in data analytics, including data analyst, business analyst, data scientist, data engineer, and more. These roles require a mix of technical and soft skills, such as data analysis, programming, communication, problem-solving, and critical thinking.

Essential Skills and Knowledge for Aspiring Data Analysts

To become a successful data analyst, there are a variety of technical and non-technical skills that you need to possess. Technical skills include knowledge of programming languages, databases, data visualization tools, and statistical analysis. Non-technical skills include communication, problem-solving, and critical thinking.

It’s also important to have domain knowledge in the industry you’re working in. For example, it’s important to understand healthcare terminology and regulations if you’re analyzing data for a healthcare organization. This will enable you to ask the right questions and draw meaningful insights from the data.

Many resources are available for acquiring the necessary skills and knowledge for data analytics. Online courses, boot camps, and degree programs are all viable options. Additionally, many free resources are available, such as YouTube tutorials and open-source software.

Tips and Strategies for Breaking into Data Analytics

Breaking into the field of data analytics can be challenging, but with the proper strategies and mindset, you can achieve your goals. Here are some tips and techniques to help you break into data analytics:

1. Identify your career goals and paths

Before starting your journey in data analytics, you must identify your career goals and the path you want to take. Do you want to become a data analyst, data scientist, or data engineer? Understanding your goals will help you focus your efforts and choose the right resources and tools.

2. Build a strong foundation in statistics and programming

You must have a reliable statistics and programming foundation to succeed in data analytics. Familiarize yourself with programming languages like Python and R, and learn statistical analysis techniques like regression analysis and hypothesis testing.

3. Gain experience through internships and projects

Internships and projects are excellent ways to gain practical experience in data analytics. Seek internships in data-driven organizations and participate in data analytics projects on platforms like Kaggle.

4. Network and build professional relationships

Networking is essential in any field, and data analytics is no exception. Attend industry events, join online communities, and connect with other professionals in the field. Building relationships with others can lead to job opportunities and valuable insights.

5. Create a strong portfolio and resume

Your portfolio and resume should showcase your skills, knowledge, and experience in data analytics. Include projects you’ve worked on, data visualizations you’ve created, and any relevant coursework or certifications.

By following these tips and strategies, you can position yourself for success in the field of data analytics. You can break into this exciting and growing field with determination, hard work, and a willingness to learn.

Data Science and Data Analytics Courses for Aspiring Data Analysts

Taking data science and data analytics courses can be an excellent way to gain the necessary skills and knowledge to break into the field of data analytics. Here are some pivotal points to consider when exploring data science and data analytics courses:

Overview of data science and data analytics courses

Data science and data analytics courses provide training in statistical analysis, data visualization, programming, and other relevant topics. They can be taken online or in person and vary in length and depth.

Benefits of taking data science and data analytics courses

Data science and data analytics courses can provide a comprehensive education in the field, help you gain practical skills, and provide networking opportunities. They can also help demonstrate your dedication and expertise to potential employers.

Types of courses available for aspiring data analysts

Various types of data science and data analytics courses are available, including certificate programs, boot camps, online courses, and degree programs. Each has its own strengths and weaknesses and can be tailored to fit different skill levels. Two highly recommended programs are Great Learning’s Data Science Courses and Data Analytics Courses, which provide in-depth knowledge of concepts and hands-on experience in solving real-world problems.

Comparison of different courses available

Consider factors like cost, length, content, and instructor experience when choosing a course. Research reviews and ratings from previous students to get an idea of the quality of the course.

Recommended courses for different skill levels

For beginners, introductory courses in Python and statistics can be helpful. For intermediate learners, courses on machine learning, data visualization, and databases can be useful. Advanced learners may benefit from big data, data engineering, and data science research courses.

Wrapping Up

Data analytics is a rapidly evolving field and an incredibly rewarding career choice for those with the right skills and experience. With the right tips and strategies, aspiring data analysts can break into the field and position themselves for tremendous success. By understanding the essential skills and industry language, carefully planning their entry into the field, and leveraging contacts in the field, ambitious analysts can take the first steps in achieving their career goals and begin to make an impact within the data analytics industry.

AWS Certified Developer – Associate DVA-C02 Exam Learning Path

AWS Certified Developer - Associate Certification
~ Last updated on : ~ jayendrapatil

AWS Certified Developer – Associate DVA-C02 Exam Learning Path

  • AWS Certified Developer – Associate DVA-C02 exam is the latest AWS exam released on 27th February 2023 and has replaced the previous AWS Developer – Associate DVA-C01 certification exam.
  • I passed the AWS Developer – Associate DVA-C02 exam with a score of 835/1000.

AWS Certified Developer – Associate DVA-C02 Exam Content

  • DVA-C02 validates a candidate’s ability to demonstrate proficiency in developing, testing, deploying, and debugging AWS cloud-based applications.
  • DVA-C02 also validates a candidate’s ability to complete the following tasks:
    • Develop and optimize applications on AWS
    • Package and deploy by using continuous integration and continuous delivery (CI/CD) workflows
    • Secure application code and data
    • Identify and resolve application issues

Refer AWS Certified Developer – Associate Exam Blue Print

AWS Certified Developer - Associate Domains

AWS Certified Developer – Associate DVA-C02 Summary

  • DVA-C02 exam consists of 65 questions in 130 minutes, and the time is more than sufficient if you are well-prepared.
  • DVA-C02 exam includes two types of questions, multiple-choice and multiple-response.
  • DVA-C02 has a scaled score between 100 and 1,000. The scaled score needed to pass the exam is 720.
  • Associate exams currently cost $ 150 + tax.
  • You can get an additional 30 minutes if English is your second language by requesting Exam Accommodations. It might not be needed for Associate exams but is helpful for Professional and Specialty ones.
  • AWS exams can be taken either remotely or online, I prefer to take them online as it provides a lot of flexibility. Just make sure you have a proper place to take the exam with no disturbance and nothing around you.
  • Also, if you are taking the AWS Online exam for the first time try to join at least 30 minutes before the actual time as I have had issues with both PSI and Pearson with long wait times.

AWS Certified Developer – Associate DVA-C02 Exam Resources

AWS Certified Developer – Associate DVA-C02 Exam Topics

  • AWS DVA-C02 exam concepts cover solutions that fall within AWS Well-Architected framework to cover scalable, highly available, cost-effective, performant, and resilient pillars.
  • AWS Certified Developer – Associate DVA-C02 exam covers a lot of the latest AWS services like Amplify, X-Ray while focusing majorly on other services like Lambda, DynamoDB, Elastic Beanstalk, S3, EC2
  • AWS Certified Developer – Associate DVA-C02 exam is similar to DVA-C01 with more focus on the hands-on development and deployment concepts rather than just the architectural concepts.
  • If you had been preparing for the DVA-C01, DVA-C02 is pretty much similar except for the addition of some new services covering Amplify, X-Ray, etc.

Compute

  • Elastic Cloud Compute – EC2
  • Auto Scaling and ELB
    • Auto Scaling provides the ability to ensure a correct number of EC2 instances are always running to handle the load of the application
    • Elastic Load Balancer allows the incoming traffic to be distributed automatically across multiple healthy EC2 instances
  • Autoscaling & ELB
    • work together to provide High Availability and Scalability.
    • Span both ELB and Auto Scaling across Multi-AZs to provide High Availability
    • Do not span across regions. Use Route 53 or Global Accelerator to route traffic across regions.
  • Lambda and serverless architecture, its features, and use cases.
    • Lambda integrated with API Gateway to provide a serverless, highly scalable, cost-effective architecture.
    • Lambda execution role needs the required permissions to integrate with other AWS services.
    • Environment variables to keep functions configurable.
    • Lambda Layers provide a convenient way to package libraries and other dependencies that you can use with your Lambda functions.
    • Function versions can be used to manage the deployment of the functions.
    • Function Alias supports creating aliases, which are mutable, for each function version.
    • provides /tmp ephemeral scratch storage.
    • Integrates with X-Ray for distributed tracing.
    • Use RDS proxy for connection pooling.
  • Elastic Container Service – ECS with its ability to deploy containers and microservices architecture.
    • ECS role for tasks can be provided through taskRoleArn
    • ALB provides dynamic port mapping to allow multiple same tasks on the same node.
  • Elastic Kubernetes Service – EKS
    • managed Kubernetes service to run Kubernetes in the AWS cloud and on-premises data centers
    • ideal for migration of an existing workload on Kubernetes
  • Elastic Beanstalk
    • at a high level, what it provides, and its ability to get an application running quickly.
    • Deployment types with their advantages and disadvantages

Databases

Storage

  • Simple Storage Service – S3
    • S3 storage classes with lifecycle policies
      • Understand the difference between SA Standard vs SA IA vs SA IA One Zone in terms of cost and durability
    • S3 Data Protection
      • S3 Client-side encryption encrypts data before storing it in S3
      • S3 encryption in transit can be enforced with S3 bucket policies using secureTransport attributes.
      • S3 encryption at rest can be enforced with S3 bucket policies using x-amz-server-side-encryption attribute.
    • S3 features including
      • S3 provides cost-effective static website hosting. However, it does not support HTTPS endpoint. Can be integrated with CloudFront for HTTPS, caching, performance, and low-latency access.
      • S3 versioning provides protection against accidental overwrites and deletions. Used with MFA Delete feature.
      • S3 Pre-Signed URLs for both upload and download provide access without needing AWS credentials.
      • S3 CORS allows cross-domain calls
      • S3 Transfer Acceleration enables fast, easy, and secure transfers of files over long distances between your client and an S3 bucket.
      • S3 Event Notifications to trigger events on various S3 events like objects added or deleted. Supports SQS, SNS, and Lambda functions.
      • Integrates with Amazon Macie to detect PII data
      • Replication that supports the same and cross-region replication required versioning to be enabled.
      • Integrates with Athena to analyze data in S3 using standard SQL.
  • Instance Store
    •  is physically attached  to the EC2 instance and provides the lowest latency and highest IOPS
  • Elastic Block Storage – EBS
    • EBS volume types and their use cases in terms of IOPS and throughput. SSD for IOPS and HDD for throughput
  • Elastic File System – EFS
    • simple, fully managed, scalable, serverless, and cost-optimized file storage for use with AWS Cloud and on-premises resources.
    • provides shared volume across multiple EC2 instances, while EBS can be attached to a single instance within the same AZ or EBS Multi-Attach can be attached to multiple instances within the same AZ
    • can be mounted with Lambda functions
    • supports the NFS protocol, and is compatible with Linux-based AMIs
    • supports cross-region replication and storage classes for cost management.
  • Difference between EBS vs S3 vs EFS
  • Difference between EBS vs Instance Store
  • Would recommend referring Storage Options whitepaper, although a bit dated 90% still holds right

Security & Identity

  • Identity Access Management – IAM
    • IAM role
      • provides permissions that are not associated with a particular user, group, or service and are intended to be assumable by anyone who needs it.
      • can be used for EC2 application access and Cross-account access
    • IAM Best Practices
  • Cognito
    • provides authentication, authorization, and user management for the web and mobile apps.
    • User pools are user directories that provide sign-up and sign-in options for the app users.
    • Identity pools enable you to grant the users access to other AWS services.
  • Key Management Services – KMS encryption service
    • for key management and envelope encryption
    • provides encryption at rest and does not handle encryption in transit.
  • Amazon Certificate Manager – ACM
    • helps easily provision, manage, and deploy public and private SSL/TLS certificates for use with AWS services and internally connected resources.
  • AWS Secrets Manager
    • helps protect secrets needed to access applications, services, and IT resources.
    • supports automatic rotations of secrets
  • Secrets Manager vs Systems Manager Parameter Store for secrets management
    • Secrets Manager supports automatic credentials rotation and is integrated with Lambda and other services like RDS, and DynamoDB.
    • Systems Manager Parameter Store provides free standard parameters and is cost-effective as compared to Secrets Manager.

Front-end Web and Mobile

  • API Gateway
    • is a fully managed service that makes it easy for developers to publish, maintain, monitor, and secure APIs at any scale.
    • Powerful, flexible authentication mechanisms, such as AWS IAM policies, Lambda authorizer functions, and Amazon Cognito user pools.
    • supports Canary release deployments for safely rolling out changes.
    • define usage plans to meter, restrict third-party developer access, configure throttling, and quota limits on a per API key basis
    • integrates with AWS X-Ray for understanding and triaging performance latencies.
    • API Gateway CORS allows cross-domain calls
  • Amplify
    • is a complete solution that lets frontend web and mobile developers easily build, ship, and host full-stack applications on AWS, with the flexibility to leverage the breadth of AWS services as use cases evolve.

Management Tools

  • CloudWatch
    • monitoring to provide operational transparency
    • is extendable with custom metrics
    • does not capture memory metrics, by default, and can be done using the CloudWatch agent.
  • EventBridge
    • is a serverless event bus service that makes it easy to connect applications with data from a variety of sources.
    • enables building loosely coupled and distributed event-driven architectures.
  • CloudTrail
    • helps enable governance, compliance, and operational and risk auditing of the AWS account.
    • helps to get a history of AWS API calls and related events for the AWS account.
  • CloudFormation
    • easy way to create and manage a collection of related AWS resources, and provision and update them in an orderly and predictable fashion.
    • Supports Serverless Application Model – SAM for the deployment of serverless applications including Lambda.
    • CloudFormation StackSets extends the functionality of stacks by enabling you to create, update, or delete stacks across multiple accounts and Regions with a single operation.

Integration Tools

  • Simple Queue Service
    • as message queuing service and SNS as pub/sub notification service
    • as a decoupling service and provide resiliency
    • SQS features like visibility, and long poll vs short poll
    • provide scaling for the Auto Scaling group based on the SQS size.
    • SQS Standard vs SQS FIFO difference
      • FIFO provides exactly-once delivery but with low throughput
  • Simple Notification Service – SNS
    • is a web service that coordinates and manages the delivery or sending of messages to subscribing endpoints or clients
    • Fanout pattern can be used to push messages to multiple subscribers.
  • Understand SQS as a message queuing service and SNS as a pub/sub notification service.
  • Know AWS Developer tools
    • CodeCommit is a secure, scalable, fully-managed source control service that helps to host secure and highly scalable private Git repositories.
    • CodeBuild is a fully managed build service that compiles source code, runs tests, and produces software packages that are ready to deploy.
    • CodeDeploy helps automate code deployments to any instance, including EC2 instances and instances running on-premises.
    • CodePipeline is a fully managed continuous delivery service that helps automate the release pipelines for fast and reliable application and infrastructure updates.
    • CodeArtifact is a fully managed artifact repository service that makes it easy for organizations of any size to securely store, publish, and share software packages used in their software development process.
  • X-Ray
    • helps developers analyze and debug production, distributed applications for e.g. built using a microservices lambda architecture

Analytics

  • Redshift as a business intelligence tool
  • Kinesis
    • for real-time data capture and analytics.
    • Integrates with Lambda functions to perform transformations
  • AWS Glue
    • fully-managed, ETL service that automates the time-consuming steps of data preparation for analytics

Networking

  • Does not cover much networking or designing networks, but be sure you understand VPC, Subnets, Routes, Security Groups, etc.

AWS Cloud Computing Whitepapers

On the Exam Day

  • Make sure you are relaxed and get some good night’s sleep. The exam is not tough if you are well-prepared.
  • If you are taking the AWS Online exam
    • Try to join at least 30 minutes before the actual time as I have had issues with both PSI and Pearson with long wait times.
    • The online verification process does take some time and usually, there are glitches.
    • Remember, you would not be allowed to take the take if you are late by more than 30 minutes.
    • Make sure you have your desk clear, no hand-watches, or external monitors, keep your phones away, and nobody can enter the room.

Finally, All the Best 🙂

AWS Auto Scaling Policies

~ Last updated on : ~ jayendrapatil

AWS Auto Scaling Policies

Maintain a Steady Count of Instances

  • Auto Scaling ensures a steady minimum (or desired if specified) count of Instances will always be running.
  • If an instance is found unhealthy, Auto Scaling will terminate the Instance and launch a new one.
  • ASG determines the health state of each instance by periodically checking the results of EC2 instance status checks.
  • ASG can be associated with an Elastic load balancer enabled to use the Elastic Load Balancing health check, Auto Scaling determines the health status of the instances by checking the results of both EC2 instance status and Elastic Load Balancing instance health.
  • Auto Scaling marks an instance unhealthy and launches a replacement if
    • the instance is in a state other than running,
    • the system status is impaired, or
    • Elastic Load Balancing reports the instance state as OutOfService.
  • After an instance has been marked unhealthy as a result of an EC2 or ELB health check, it is almost immediately scheduled for replacement. It never automatically recovers its health.
  • For an unhealthy instance, the instance’s health check can be changed back to healthy manually but you will encounter an error if the instance is already terminating.
  • Because the interval between marking an instance unhealthy and its actual termination is so small, attempting to set an instance’s health status back to healthy is probably useful only for a suspended group.
  • When the instance is terminated, any associated Elastic IP addresses are disassociated and are not automatically associated with the new instance.
  • Elastic IP addresses must be associated with the new instance manually.
  • Similarly, when the instance is terminated, its attached EBS volumes are detached and must be attached to the new instance manually.

Manual Scaling

  • Manual scaling can be performed by
    • Changing the desired capacity limit of the ASG
    • Attaching/Detaching instances to the ASG
  • Attaching/Detaching an EC2 instance can be done only if
    • Instance is in the running state.
    • AMI used to launch the instance must still exist.
    • Instance is not a member of another ASG.
    • Instance is in the same Availability Zone as the ASG.
    • If the ASG is associated with a load balancer, the instance and the load balancer must both be in the same VPC.
  • Auto Scaling increases the desired capacity of the group by the number of instances being attached. But if the number of instances being attached plus the desired capacity exceeds the maximum size, the request fails.
  • When Detaching instances, an option to decrement the desired capacity for the ASG by the number of instances being detached is provided. If chosen not to decrement the capacity, Auto Scaling launches new instances to replace the ones that you detached.
  • If an instance is detached from an ASG that is also registered with a load balancer, the instance is deregistered from the load balancer. If connection draining is enabled for the load balancer, Auto Scaling waits for the in-flight requests to complete.

Scheduled Scaling

  • Scaling based on a schedule allows you to scale the application in response to predictable load changes for e.g. last day of the month, the last day of a financial year.
  • Scheduled scaling requires the configuration of Scheduled actions, which tells Auto Scaling to perform a scaling action at a certain time in the future, with the start time at which the scaling action should take effect, and the new minimum, maximum, and desired size of group should have.
  • Auto Scaling guarantees the order of execution for scheduled actions within the same group, but not for scheduled actions across groups.
  • Multiple Scheduled Actions can be specified but should have unique time values and they cannot have overlapping times scheduled which will lead to their rejection.
  • Cooldown periods are not supported.

Dynamic Scaling

  • Allows automatic scaling in response to the changing demand for e.g. scale-out in case CPU utilization of the instance goes above 70% and scale in when the CPU utilization goes below 30%
  • ASG uses a combination of alarms & policies to determine when the conditions for scaling are met.
    • An alarm is an object that watches over a single metric over a specified time period. When the value of the metric breaches the defined threshold, for the number of specified time periods the alarm performs one or more actions (such as sending messages to Auto Scaling).
    • A policy is a set of instructions that tells Auto Scaling how to respond to alarm messages.
  • Dynamic scaling process works as below
    1. CloudWatch monitors the specified metrics for all the instances in the Auto Scaling Group.
    2. Changes are reflected in the metrics as the demand grows or shrinks
    3. When the change in the metrics breaches the threshold of the CloudWatch alarm, the CloudWatch alarm performs an action. Depending on the breach, the action is a message sent to either the scale-in policy or the scale-out policy
    4. After the Auto Scaling policy receives the message, Auto Scaling performs the scaling activity for the ASG.
    5. This process continues until you delete either the scaling policies or the ASG.
  • When a scaling policy is executed, if the capacity calculation produces a number outside of the minimum and maximum size range of the group, EC2 Auto Scaling ensures that the new capacity never goes outside of the minimum and maximum size limits.
  • When the desired capacity reaches the maximum size limit, scaling out stops. If demand drops and capacity decreases, Auto Scaling can scale out again.

Dynamic Scaling Policy Types

Target tracking scaling

  • Increase or decrease the current capacity of the group based on a target value for a specific metric.

Auto Scaling Target Tracking Scaling

Step scaling

  • Increase or decrease the current capacity of the group based on a set of scaling adjustments, known as step adjustments, that vary based on the size of the alarm breach.

Simple scaling

  • Increase or decrease the current capacity of the group based on a single scaling adjustment.

Multiple Policies

  • ASG can have more than one scaling policy attached at any given time.
  • Each ASG would have at least two policies: one to scale the architecture out and another to scale the architecture in.
  • If an ASG has multiple policies, there is always a chance that both policies can instruct the Auto Scaling to Scale Out or Scale In at the same time.
  • When these situations occur, Auto Scaling chooses the policy that has the greatest impact i.e. provides the largest capacity for both scale out and scale in on the ASG for e.g. if two policies are triggered at the same time and Policy 1 instructs to scale out the instance by 1 while Policy 2 instructs to scale out the instances by 2, Auto Scaling will use the Policy 2 and scale out the instances by 2 as it has a greater impact.

Predictive Scaling

  • Predictive scaling can be used to increase the number of EC2 instances in the ASG in advance of daily and weekly patterns in traffic flows.
  • Predictive scaling is well suited for situations where you have:
    • Cyclical traffic, such as high use of resources during regular business hours and low use of resources during evenings and weekends
    • Recurring on-and-off workload patterns, such as batch processing, testing, or periodic data analysis
    • Applications that take a long time to initialize, causing a noticeable latency impact on application performance during scale-out events
  • Predictive scaling provides proactive scaling that can help scale faster by launching capacity in advance of forecasted load, compared to using only dynamic scaling, which is reactive in nature.
  • Predictive scaling uses machine learning to predict capacity requirements based on historical data from CloudWatch. The machine learning algorithm consumes the available historical data and calculates the capacity that best fits the historical load pattern, and then continuously learns based on new data to make future forecasts more accurate.
  • Predictive scaling supports forecast only mode so that you can evaluate the forecast before you allow predictive scaling to actively scale capacity
  • When you are ready to start scaling with predictive scaling, switch the policy from forecast only mode to forecast and scale mode.

AWS Certification Exam Practice Questions

  • Questions are collected from Internet and the answers are marked as per my knowledge and understanding (which might differ with yours).
  • AWS services are updated everyday and both the answers and questions might be outdated soon, so research accordingly.
  • AWS exam questions are not updated to keep up the pace with AWS updates, so even if the underlying feature has changed the question might not be updated
  • Open to further feedback, discussion and correction.
  1. A user has created a web application with Auto Scaling. The user is regularly monitoring the application and he observed that the traffic is highest on Thursday and Friday between 8 AM to 6 PM. What is the best solution to handle scaling in this case?
    1. Add a new instance manually by 8 AM Thursday and terminate the same by 6 PM Friday
    2. Schedule Auto Scaling to scale up by 8 AM Thursday and scale down after 6 PM on Friday
    3. Schedule a policy which may scale up every day at 8 AM and scales down by 6 PM
    4. Configure a batch process to add a instance by 8 AM and remove it by Friday 6 PM
  2. A customer has a website which shows all the deals available across the market. The site experiences a load of 5 large EC2 instances generally. However, a week before Thanksgiving vacation they encounter a load of almost 20 large instances. The load during that period varies over the day based on the office timings. Which of the below mentioned solutions is cost effective as well as help the website achieve better performance?
    1. Keep only 10 instances running and manually launch 10 instances every day during office hours.
    2. Setup to run 10 instances during the pre-vacation period and only scale up during the office time by launching 10 more instances using the AutoScaling schedule.
    3. During the pre-vacation period setup a scenario where the organization has 15 instances running and 5 instances to scale up and down using Auto Scaling based on the network I/O policy.
    4. During the pre-vacation period setup 20 instances to run continuously.
  3. A user has setup Auto Scaling with ELB on the EC2 instances. The user wants to configure that whenever the CPU utilization is below 10%, Auto Scaling should remove one instance. How can the user configure this?
    1. The user can get an email using SNS when the CPU utilization is less than 10%. The user can use the desired capacity of Auto Scaling to remove the instance
    2. Use CloudWatch to monitor the data and Auto Scaling to remove the instances using scheduled actions
    3. Configure CloudWatch to send a notification to Auto Scaling Launch configuration when the CPU utilization is less than 10% and configure the Auto Scaling policy to remove the instance
    4. Configure CloudWatch to send a notification to the Auto Scaling group when the CPU Utilization is less than 10% and configure the Auto Scaling policy to remove the instance

References

Auto_Scaling_Options

Kubernetes Architecture

~ Last updated on : ~ jayendrapatil

Kubernetes Architecture

  • A Kubernetes cluster consists of at least one main (control) plane, and one or more worker machines, called nodes.
  • Both the control planes and node instances can be physical devices, virtual machines, or instances in the cloud.
  • In managed Kubernetes environments like AWS EKS, GCP GKE, Azure AKS the control plane is managed by the cloud provider.

Kubernetes Architecture

Control Plane

  • The control plane is also known as a master node or head node.
  • The control plane manages the worker nodes and the Pods in the cluster.
  • In production environments, the control plane usually runs across multiple computers and a cluster usually runs multiple nodes, providing fault-tolerance and high availability.
  • It is not recommended to run user workloads on master mode.
  • The Control plane’s components make global decisions about the cluster, as well as detect and respond to cluster events.
  • The control plane receives input from a CLI or UI via an API.

API Server (kube-apiserver)

  • API server exposes a REST interface to the Kubernetes cluster. It is the front end for the Kubernetes control plane.
  • All operations against pods, services, and so forth, are executed programmatically by communicating with the endpoints provided by it.
  • It tracks the state of all cluster components and manages the interaction between them.
  • It is designed to scale horizontally.
  • It consumes YAML/JSON manifest files.
  • It validates and processes the requests made via API.

etcd (key-value store)

  • Etcd is a consistent, distributed, and highly-available key-value store.
  • is stateful, persistent storage that stores all of Kubernetes cluster data (cluster state and config).
  • is the source of truth for the cluster.
  • can be part of the control plane, or, it can be configured externally.
  • ETCD benefits include
    • Fully replicated: Every node in an etcd cluster has access to the full data store.
    • Highly available: etcd is designed to have no single point of failure and gracefully tolerate hardware failures and network partitions.
    • Reliably consistent: Every data ‘read’ returns the latest data ‘write’ across all clusters.
    • Fast: etcd has been benchmarked at 10,000 writes per second.
    • Secure: etcd supports automatic Transport Layer Security (TLS) and optional secure socket layer (SSL) client certificate authentication.
    • Simple: Any application, from simple web apps to highly complex container orchestration engines such as Kubernetes, can read or write data to etcd using standard HTTP/JSON tools.

Scheduler (kube-scheduler)

  • The scheduler is responsible for assigning work to the various nodes. It keeps watch over the resource capacity and ensures that a worker node’s performance is within an appropriate threshold.
  • It schedules pods to worker nodes.
  • It watches api-server for newly created Pods with no assigned node, and selects a healthy node for them to run on.
  • If there are no suitable nodes, the pods are put in a pending state until such a healthy node appears.
  • It watches API Server for new work tasks.
  • Factors taken into account for scheduling decisions include:
    • Individual and collective resource requirements.
    • Hardware/software/policy constraints.
    • Affinity and anti-affinity specifications.
    • Data locality.
    • Inter-workload interference.
    • Deadlines and taints.

Controller Manager (kube-controller-manager)

  • Controller manager is responsible for making sure that the shared state of the cluster is operating as expected.
  • It watches the desired state of the objects it manages and watches their current state through the API server.
  • It takes corrective steps to make sure that the current state is the same as the desired state.
  • It is a controller of controllers.
  • It runs controller processes. Logically, each controller is a separate process, but to reduce complexity, they are all compiled into a single binary and run in a single process.
  • Some types of controllers are:
    • Node controller: Responsible for noticing and responding when nodes go down.
    • Job controller: Watches for Job objects that represent one-off tasks, then creates Pods to run those tasks to completion.
    • Endpoints controller: Populates the Endpoints object (that is, joins Services & Pods).
    • Service Account & Token controllers: Create default accounts and API access tokens for new namespaces.

Cloud Controller Manager

  • The cloud controller manager integrates with the underlying cloud technologies in your cluster when the cluster is running in a cloud environment.
  • The cloud-controller-manager only runs controllers that are specific to your cloud provider.
  • Cloud controller lets you link your cluster into cloud provider’s API, and separates out the components that interact with that cloud platform from components that only interact with your cluster.
  • The following controllers can have cloud provider dependencies:
    • Node controller: For checking the cloud provider to determine if a node has been deleted in the cloud after it stops responding.
    • Route controller: For setting up routes in the underlying cloud infrastructure.
    • Service controller: For creating, updating, and deleting cloud provider load balancers.

Data Plane Worker Node(s)

  • The data plane is known as the worker node or compute node.
  • A virtual or physical machine that contains the services necessary to run containerized applications.
  • A Kubernetes cluster needs at least one worker node, but normally has many.
  • The worker node(s) host the Pods that are the components of the application workload.
  • Pods are scheduled and orchestrated to run on nodes.
  • Cluster can be scaled up and down by adding and removing nodes.
  • Node components run on every node, maintaining running pods and providing the Kubernetes runtime environment.

kubelet

  • A Kubelet tracks the state of a pod to ensure that all the containers are running and healthy
  • provides a heartbeat message every few seconds to the control plane.
  • runs as an agent on each node in the cluster.
  • acts as a conduit between the API server and the node.
  • instantiates and executes Pods.
  • watches API Server for work tasks.
  • gets instructions from master and reports back to Masters.

kube-proxy

  • Kube proxy is a networking component that routes traffic coming into a node from the service to the correct containers.
  • is a network proxy that runs on each node in a cluster.
  • manages IP translation and routing.
  • maintains network rules on nodes. These network rules allow network communication to Pods from inside or outside of cluster.
  • ensures each Pod gets a unique IP address.
  • makes possible that all containers in a pod share a single IP.
  • facilitates Kubernetes networking services and load-balancing across all pods in a service.
  • It deals with individual host sub-netting and ensures that the services are available to external parties.

Container runtime

  • Container runtime is responsible for running containers (in Pods).
  • Kubernetes supports any implementation of the Kubernetes Container Runtime Interface CRI specifications
  • To run the containers, each worker node has a container runtime engine.
  • It pulls images from a container image registry and starts and stops containers.
  • Kubernetes supports several container runtimes: