AWS SageMaker Built-in Algorithms Summary

SageMaker Built-in Algorithms

BlazingText algorithm

    • provides highly optimized implementations of the Word2vec and text classification algorithms.
    • Word2vec algorithm
      • useful for many downstream natural language processing (NLP) tasks, such as sentiment analysis, named entity recognition, machine translation, etc.
      • maps words to high-quality distributed vectors, whose representation is called word embeddings
      • word embeddings capture the semantic relationships between words.
    • Text classification
      • is an important task for applications performing web searches, information retrieval, ranking, and document classification
    • provides the Skip-gram and continuous bag-of-words (CBOW) training architectures

DeepAR forecasting algorithm

    • is a supervised learning algorithm for forecasting scalar (one-dimensional) time series using recurrent neural networks (RNN).
    • use the trained model to generate forecasts for new time series that are similar to the ones it has been trained on.

Factorization machine

    • is a general-purpose supervised learning algorithm used for both classification and regression tasks.
    • extension of a linear model designed to capture interactions between features within high dimensional sparse datasets economically

Image classification algorithm

    • a supervised learning algorithm that supports multi-label classification
    • takes an image as input and outputs one or more labels
    • uses a convolutional neural network (ResNet) that can be trained from scratch or trained using transfer learning when a large number of training images are not available.
    • recommended input format is Apache MXNet RecordIO. Also supports raw images in .jpg or .png format.

IP Insights

    • is an unsupervised learning algorithm that learns the usage patterns for IPv4 addresses.
    • designed to capture associations between IPv4 addresses and various entities, such as user IDs or account numbers

K-means algorithm

    • is an unsupervised learning algorithm for clustering
    • attempts to find discrete groupings within data, where members of a group are as similar as possible to one another and as different as possible from members of other groups

K-nearest neighbors (k-NN) algorithm

    • is an index-based algorithm.
    • uses a non-parametric method for classification or regression.
    • For classification problems, the algorithm queries the k points that are closest to the sample point and returns the most frequently used label of their class as the predicted label.
    • For regression problems, the algorithm queries the k closest points to the sample point and returns the average of their feature values as the predicted value.

Latent Dirichlet Allocation (LDA) algorithm

    • is an unsupervised learning algorithm that attempts to describe a set of observations as a mixture of distinct categories.
    • used to discover a user-specified number of topics shared by documents within a text corpus.

Linear Learner

    • are supervised learning algorithms used for solving either classification or regression problems

Neural Topic Model (NTM) Algorithm

    • is an unsupervised learning algorithm that is used to organize a corpus of documents into topics that contain word groupings based on their statistical distribution
    • Topic modeling can be used to classify or summarize documents based on the topics detected or to retrieve information or recommend content based on topic similarities.

Object2Vec algorithm

    • is a general-purpose neural embedding algorithm that is highly customizable
    • can learn low-dimensional dense embeddings of high-dimensional objects.

Object Detection algorithm

    • detects and classifies objects in images using a single deep neural network.
    • is a supervised learning algorithm that takes images as input and identifies all instances of objects within the image scene.

Principal Component Analysis

    • is an unsupervised machine learning algorithm that attempts to reduce the dimensionality (number of features) within a dataset while still retaining as much information as possible

Random Cut Forest (RCF)

    • is an unsupervised algorithm for detecting anomalous data points within a data set.

Semantic segmentation algorithm

    • provides a fine-grained, pixel-level approach to developing computer vision applications

SageMaker Sequence to Sequence (seq2seq)

    • is a supervised learning algorithm where the input is a sequence of tokens (for example, text, audio) and the output generated is another sequence of tokens.
    • key uses cases are machine translation (input a sentence from one language and predict what that sentence would be in another language), text summarization (input a longer string of words and predict a shorter string of words that is a summary), speech-to-text (audio clips converted into output sentences in tokens)

XGBoost (eXtreme Gradient Boosting)

    • is a popular and efficient open-source implementation of the gradient boosted trees algorithm.
    • Gradient boosting is a supervised learning algorithm that attempts to accurately predict a target variable by combining an ensemble of estimates from a set of simpler, weaker models

AWS Certified Big Data -Speciality (BDS-C00) Exam Learning Path

Clearing the AWS Certified Big Data – Speciality (BDS-C00) was a great feeling. This was my third Speciality certification and in terms of the difficulty level (compared to Network and Security Speciality exams), I would rate it between Network (being the toughest) Security (being the simpler one).

Big Data in itself is a very vast topic and with AWS services, there is lots to cover and know for the exam. If you have worked on Big Data technologies including a bit of Visualization and Machine learning, it would be a great asset to pass this exam.

AWS Certified Big Data – Speciality (BDS-C00) exam basically validates

  • Implement core AWS Big Data services according to basic architectural best practices
  • Design and maintain Big Data
  • Leverage tools to automate Data Analysis

Refer AWS Certified Big Data – Speciality Exam Guide for details

                              AWS Certified Big Data – Speciality Domains

AWS Certified Big Data – Speciality (BDS-C00) Exam Summary

  • AWS Certified Big Data – Speciality exam, as its name suggests, covers a lot of Big Data concepts right from data transfer and collection techniques, storage, pre and post processing, analytics, visualization with the added concepts for data security at each layer.
  • One of the key tactic I followed when solving any AWS Certification exam is to read the question and use paper and pencil to draw a rough architecture and 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 to the right answer or atleast have a 50% chance of getting it right.
  • Be sure to cover the following topics
    • Whitepapers and articles
    • Analytics
      • Make sure you know and cover all the services in depth, as 80% of the exam is focused on these topics
      • Elastic Map Reduce
        • Understand EMR in depth
        • Understand EMRFS (hint: Use Consistent view to make sure S3 objects referred by different applications are in sync)
        • Know EMR Best Practices (hint: start with many small nodes instead on few large nodes)
        • Know Hive can be externally hosted using RDS, Aurora and AWS Glue Data Catalog
        • Know also different technologies
          • Presto is a fast SQL query engine designed for interactive analytic queries over large datasets from multiple sources
          • D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG, and CSS
          • Spark is a distributed processing framework and programming model that helps do machine learning, stream processing, or graph analytics using Amazon EMR clusters
          • Zeppelin/Jupyter as a notebook for interactive data exploration and provides open-source web application that can be used to create and share documents that contain live code, equations, visualizations, and narrative text
          • Phoenix is used for OLTP and operational analytics, allowing you to use standard SQL queries and JDBC APIs to work with an Apache HBase backing store
      • Kinesis
        • Understand Kinesis Data Streams and Kinesis Data Firehose in depth
        • Know Kinesis Data Streams vs Kinesis Firehose
          • Know Kinesis Data Streams is open ended on both producer and consumer. It supports KCL and works with Spark.
          • Know Kineses Firehose is open ended for producer only. Data is stored in S3, Redshift and ElasticSearch.
          • Kinesis Firehose works in batches with minimum 60secs interval.
        • Understand Kinesis Encryption (hint: use server side encryption or encrypt in producer for data streams)
        • Know difference between KPL vs SDK (hint: PutRecords are synchronously, while KPL supports batching)
        • Kinesis Best Practices (hint: increase performance increasing the shards)
      • Know ElasticSearch is a search service which supports indexing, full text search, faceting etc.
      • Redshift
        • Understand Redshift in depth
        • Understand Redshift Advance topics like Workload Management, Distribution Style, Sort key
        • Know Redshift Best Practices w.r.t selection of Distribution style, Sort key, COPY command which allows parallelism
        • Know Redshift views to control access to data.
      • Amazon Machine Learning
      • Know Data Pipeline for data transfer
      • QuickSight
      • Know Glue as the ETL tool
    • Security, Identity & Compliance
    • Management & Governance Tools
      • Understand AWS CloudWatch for Logs and Metrics. Also, CloudWatch Events more real time alerts as compared to CloudTrail
    • Storage
    • Compute
      • Know EC2 access to services using IAM Role and Lambda using Execution role.
      • Lambda esp. how to improve performance batching, breaking functions etc.

AWS Certified Big Data – Speciality (BDS-C00) Exam Resources

AWS Organizations Service Control Policies

AWS Organizations Service Control Policies

  • are one type of policy that help manage the organization.
  • offers central control over the maximum available permissions for all accounts in your organization, ensuring member accounts stay within the organization’s access control guidelines
  • are available only in an organization that has all features enabled
  • are NOT sufficient for granting access in the accounts in the organization.
  • defines a guardrail for what actions accounts within the organization root or OU can do, but IAM policies need to be attached to the users and roles in the organization’s accounts to grant permissions to them
  • with an SCP attached to member accounts, identity-based and resource-based policies grant permissions to entities only if those policies and the SCP allow the action

Effects on Permissions

  • SCP never grants permissions
  • limits permissions for entities in member accounts, including each AWS account root user
  • does not limit actions performed by the master account.
  • does not affect any service-linked role. Service-linked roles enable other AWS services to integrate with AWS Organizations and can’t be restricted by SCPs.
  • affect only principals that are managed by accounts that are part of the organization. They don’t affect users or roles from accounts outside the organization
  • Users and roles must still be granted permissions with appropriate IAM permission policies. A user without any IAM permission policies has no access at all, even if the applicable SCPs allow all services and all actions.

Strategies for Using SCPs

  • By default, an SCP named FullAWSAccess is attached to every root, OU, and account, which allows all actions and all services.
  • Blacklist Strategy
    • actions are allowed by default, and specify what services and actions are prohibited
    • blacklist permissions using deny statements can be assigned in combination with the default FullAWSAccess SCP
    • using deny statements in SCPs require less maintenance, because they don’t need to updated when AWS adds new services.
    • deny statements usually use less space, thus making it easier to stay within SCP size limits.
  • Whitelist Strategy
    • actions are prohibited by default, and you specify what services and actions are allowed
    • whitelist permissions can be assigned, by removing the default FullAWSAccess SCP
    • allows SCP that explicitly permits only those allowed services and actions

Testing Effects of SCPs

  • don’t attach SCPs to the root of the organization without thoroughly testing the impact that the policy has on accounts.
  • Create an OU that the accounts can be moved into one at a time, or at least in small numbers, to ensure that users are not inadvertently locked out of key services.

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. Your company is planning on setting up multiple accounts in AWS. The IT Security department has a requirement to ensure that certain services and actions are not allowed across all accounts. How would the system admin achieve this in the most EFFECTIVE way possible?
    1. Create a common IAM policy that can be applied across all accounts
    2. Create an IAM policy per account and apply them accordingly​
    3. Deny the services to be used across accounts by contacting AWS​ support
    4. Use AWS Organizations and Service Control Policies
  2. You are in the process of implementing AWS Organizations for your company. At your previous company, you saw an Organizations implementation go bad when an SCP (Service Control Policy) was applied at the root of the organization before being thoroughly tested. In what way can an SCP be properly tested and implemented?
    1. Back up your entire Organization to S3 and restore rollback and restore if something goes wrong
    2. The SCP must be verified with AWS before it is implemented to avoid any problems.
    3. Mirror your Organizational Unit in another region. Apply the SCP and test it. Once testing is complete, attach the SCP to the root of your organization.
    4. Create an Organizational Unit (OU). Attach the SCP to this new OU. Move your accounts in one at a time to ensure that you don’t inadvertently lock users out of key services.

AWS Cloud Migration – Certification

AWS Cloud Migration

Some of the key drivers to moving to cloud is

  • Operational Costs – Key components of operational costs are unit price of infrastructure, the ability to match supply and demand, finding a pathway to optionality, employing an elastic cost base, and transparency
  • Workforce Productivity – getting up and ready in seconds and various service availability.
  • Cost Avoidance – eliminating the need for hardware refresh programs and constant maintenance programs
  • Operational Resilience – increases resilience and thereby reducing organization’s risk profile
  • Business Agility – react to market conditions more quickly 

Cloud Stages of Adoption

Cloud Stages of Adoption

PROJECT

  • In the project phase, execute projects to get familiar and experience benefits from the cloud.

FOUNDATION

  • After experiencing the benefits of cloud, build the foundation to scale the cloud adoption.
  • This includes creating a landing zone (a pre-configured, secure, multi-account AWS environment), Cloud Center of Excellence (CCoE), operations model, as well as assuring security and compliance readiness.

MIGRATION

  • Migrate existing applications including mission-critical applications or entire data centers to the cloud as you scale your adoption across a growing portion of the IT portfolio. 

REINVENTION

  • Now that the operations are in the cloud, focus on reinvention by taking advantage of the flexibility and capabilities of AWS to transform business by speeding time to market and increasing the attention on innovation.

Migration Process

Migration Process

Phase 1: Migration Preparation and Business Planning

  • Determine the right objectives and begin to get an idea of the types of benefits you will see.
  • Starts with some foundational experience and developing a preliminary business case for a migration, which requires taking objectives into account, along with the age and architecture of the existing applications, and their constraints.

Phase 2: Portfolio Discovery and Planning

  • Understand the IT portfolio, the dependencies between applications, and begin to consider what types of migration strategies needed to meet the business case objectives.
  • With the portfolio discovery and migration approach, you are in a good position to build a full business case.

Phase 3 & Phase 4: Designing, Migrating, and Validating Application

  • Move focus from the portfolio level to the individual application level and design, migrate, and validate each application.
  • Each application is designed, migrated, and validated according to one of the six common application strategies (“The 6 R’s”).
  • Once you have some foundational experience from migrating a few apps and a plan in place that the organization can get behind – it’s time to accelerate the migration and achieve scale.
  • AWS provides migration services that help for moving applications and data from on-premises to AWS – AWS Server Migration Service (SMS)AWS Database Migration Service (DMS)

Phase 5: Operate

  • Once applications are migrated, iterate on the new foundation, turn off old systems, and constantly iterate toward a modern operating model.
  • Operating model becomes an evergreen set of people, process, and technology that constantly improves as you migrate more applications.

Application Migration Strategies

Migration strategies depend upon what is in your environment and the what is suitable for the portfolio, taking into account the business and technical requirements.

Below are the Six common migration strategies employed and build upon “The 5 R’s” that Gartner outlined in 2011.

Application Migration Strategies

1. Rehost (“lift and shift”)

  • Moving your application as is to the Cloud.
  • helps to quickly implement the migration and scale to meet a business case
  • provides better opportunity for re-architect the applications once they are already running in cloud, with the organization having already developed cloud skills and the application with its data is migrated and handling traffic.
  • Rehosting can be automated with tools such as AWS Server Migration Service, or can be done manually

2. Replatform (“lift, tinker and shift”)

  • Moving your application to the Cloud with optimizations, without any major changes.
  • Replatform helps achieve some tangible benefit without changing the core architecture of the application. For e.g., using RDS for database or Elastic Beanstalk for applications.

3. Repurchase (“drop and shop”)

  • Dropping the application and Moving to a complete new Solution
  • More of an Buy in a Build vs Buy model, might be expensive in short team but faster time to market.
  • Move to a different product, which likely means the organization is willing to change the existing used licensing model

4. Refactor / Re-architect

  • Moving the application to Cloud, with major changes.
  • More of a Build in a Build vs Buy model, and would take time.
  • driven by a strong business need to add features, scale, or performance with agility and improvement in business continuity that would otherwise be difficult to achieve in the application’s existing environment.

5. Retire

  • Decommission the applications, not needed anymore.
  • Identifying IT assets that are no longer useful and can be turned off will help boost your business case and direct your attention towards maintaining the resources that are widely used.

6. Retain

  • Keep the applications as is in the current environment
  • Retain portions of the IT portfolio, which have tight dependencies, difficult, not in priority or ready for migration

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 planning the migration of several lab environments used for software testing. An assortment of custom tooling is used to manage the test runs for each lab. The labs use immutable infrastructure for the software test runs, and the results are stored in a highly available SQL database cluster. Although completely rewriting the custom tooling is out of scope for the migration project, the company would like to optimize workloads during the migration. Which application migration strategy meets this requirement?
    1. Re-host
    2. Re-platform
    3. Re-factor/re-architect
    4. Retire

References

Amazon EMR Best Practices

Best Practices for Using Amazon EMR

Amazon has made working with Hadoop a lot easier. You can launch an EMR cluster in minutes for big data processing, machine learning, and real-time stream processing with the Apache Hadoop ecosystem. You can use the Management Console or the command line to start several nodes with ease.

The EMR pricing has now changed from pay-per-hour to pay-per-second, which results in lower costs and you no longer have to worry about the hourly boundary.

EMR makes a whole bunch of the latest versions of open source software available to you. Currently, there are 19 open source projects and new releases are made every 4 to 6 weeks, so the latest versions of the open source projects are available. This is very useful, especially for rapidly evolving open source projects such as Apache Spark where each release contains critical bug fixes and features. However, you are not forced to upgrade; a new release is made available if you choose to use it. With EMR, you can spin up a bunch of instances and you could process massive volumes of data residing on S3 at a reasonable cost.

A variety of cluster management options are supported, including YARN. You can run the following:

  • HBase
  • Presto (low latency, distributed SQL engine)
  • Spark
  • Tez
  • ganglia
  • Zeppellin
  • Notebooks
  • SQL editors

AWS Connectors

Additionally, connectors to different AWS services are also available; for example, you can use Spark to load Redshift (using the Redshift connector, which Redshift commands under the hood to get a good throughput). You can access DynamoDB for analytics applications, Sqoop to access relational data, and so on.

AWS Glue

One particularly interesting connector is AWS Glue. AWS Glue comprises three main components:

AWS Glue

  • ETL service: This lets you drag things around to create serverless ETL pipelines.
  • AWS Glue Data Catalog: This is a fully managed Hive metastore-compliant service. Earlier, the systems ran an external Hive metastore database in RDS or Aurora. This was great. If you shut down your cluster, all your metadata was persisted so you didn’t have to recreate your tables with extra durability and availability (in case something happened to your metastore with MySQL on the master node). With Glue, all that is fully managed. You have an intelligent metastore—you don’t have to write DDL to create a table; you can just make Glue crawl your data, infer what the schema is, and create those tables for you. You can also make it add partitions, which can be painful otherwise—if you are constantly updating your Hive tables, you need a process to load that partition in—Glue catalog can do it for you. It also supports a variety of complex data types.
  • Crawlers: The crawlers let you crawl the data to infer the schema.

AWS Glue is a managed service, so you spend less time monitoring. As a fully managed service, it is also responsible for replacing unhealthy nodes and autoscaling. Enabling security options in AWS Glue is pretty easy. It supports full customization and control, and you don’t have to waste time creating and configuring the cluster. In most cases, the default settings are good enough, but even if you wanted to change them or install custom components, you have root access over all the boxes, so you can make any changes you need.

Common EMR use cases

EMR

Using HBase for random access at a massive scale involves a lot of customers who are running HBase with HDFS. Now there is support for HBase using S3 object store for HFiles. Also, there is the ability to use the Read Replica HBase cluster in another AZ. Shifting to S3 can save you 50% or higher on storage costs. Instead of sizing the cluster for HDFS, they can now size it for the amount of processing power required for the HBase Region Servers. The S3 option is also good for load balancing and disaster recovery across AZs. As S3 is available across a region, you don’t have to replicate the data twice; that is, you don’t need two full HDFS clusters. Now you can set up a smaller cluster for the Read Replicas that point to the same HFiles and you can drive the read traffic through there.

Real-time and batch processing involves utilizing EMR; you can use Kinesis for pushing data to Spark. Use Spark Streaming for real-time analytics or processing data on-the-fly and then dump that data into S3. If you don’t have real-time processing use cases, then Kinesis Firehose is a great alternative too. The data can be cataloged in the Glue Data Catalog and then you can have the data accessible via a variety of different analytical engines. EMR supports several analytical engines including Hive, Tez, and Spark. Once the data is in the Data Catalog on S3, you can use Athena (serverless SQL queries), Glue ETL (serverless ETL), and Redshift Spectrum.

Data exploration with Spark using Zeppelin or Jupyter notebook allows you to arm your data scientists with a way to explore large amounts of data (instead of using one node, you can now spread the data across the cluster). This also makes it easier to move it to production.

There is a big rise in the use of Presto for ad hoc SQL queries (in combination with Athena). They approach the same thing from two different angles. Presto gives you advanced configurations and a way to build exactly what you need for your use case but you have to deal with the cluster management versus Athena where you just go to the console and start writing SQL. Now, many BI tools support Presto as well for supporting low latency dashboards. You can also perform traditional batch processing workloads using Spark.

Deep learning with GPU instances is where you can launch GPU hardware for EMR. There’s support for MxNet. You can do end-to-end data engineering work. Support for TensorFlow is coming.

Typical ML projects implement a multi-step process, including ETL, feature engineering, model training, model evaluation, model deployment, and model scoring and updates. Such pipelines need to support batch model training and real-time ML model serving. Using Apache Spark for implementing ML pipelines is very popular as it supports each step in an ML pipeline, scales for small and large jobs, good ML libraries, and has an active user base.

There are several options for deploying Spark on AWS. For example, you can use EC2 as it can support for batch/streaming, integrates with tooling, spin up/down clusters, larger/smaller clusters. Additionally, it also has support for different versions of Hadoop and Spark. However, using EC2 for Spark deployment places a huge management burden on us. Hence, EMR can be a simpler and better alternative here. It is simple to provision and you can use a wizard (and then generate the commands for the command line from it if required). You can create tags for cost management and send logs to S3.

Lowering EMR costs

If you are paying for Hadoop nodes that are not doing anything, then you are just burning money. There are ways you can batch up your workloads. Take an inventory of the jobs you have and tweak them to run in a batch mode and shutdown the cluster in-between those times. You can separate out clusters with auto-scaling instead of sizing and running it for all your workloads. You should shut down the cluster when you can, to stop paying for it unnecessarily. You can use Amazon Linux AMI with preinstalled customizations for faster cluster creation and use auto-scaling to minimize costs for long-running clusters.

AWS Services Overview – Whitepaper – Certification

AWS Services Overview

AWS consists of many cloud services that can be use in combinations tailored to meet business or organizational needs. This section introduces the major AWS services by category.


NOTE – This post provides a brief overview of AWS services. Its is good introduction to start all certifications. However, It is more relevant and most important for AWS Cloud Practitioner Certification Exam.


Common Features

  • Almost the features can be access control through AWS Identity Access Management – IAM
  • Services managed by AWS are all made Scalable and Highly Available, without any changes needed from the user

AWS Access

AWS allows accessing its services through unified tools using

  • AWS Management Console – a simple and intuitive user interface
  • AWS Command Line Interface (CLI) – programatic access through scripts
  • AWS Software Development Kits (SDKs) – programatic access through Application Program Interface (API) tailored for programming language (Java, .NET, Node.js, PHP, Python, Ruby, Go, C++, AWS Mobile SDK) or platform (Android, Browser, iOS)

Security, Identity, and Compliance

Amazon Cloud Directory

  • enables building flexible, cloud-native directories for organizing hierarchies of data along multiple dimensions, whereas traditional directory solutions limit to a single directory
  • helps create directories for a variety of use cases, such as organizational charts, course catalogs, and device registries.

AWS Identity and Access Management

  • enables you to securely control access to AWS services and resources for the users.
  • allows creation of AWS users, groups and roles, and use permissions to allow and deny their access to AWS resources
  • helps manage IAM users and their access with individual security credentials like access keys, passwords, and multi-factor authentication devices, or request temporary security credentials to provide users
  • helps role creation & manage permissions to control which operations can be performed by the which entity, or AWS service, that assumes the role
  • enables identity federation to allow existing identities (users, groups, and roles) in the enterprise to access AWS Management Console, call AWS APIs, access resources, without the need to create an IAM user for each identity.

Amazon Inspector

  • is an automated security assessment service that helps improve the security and compliance of applications deployed on AWS.
  • automatically assesses applications for vulnerabilities or deviations from best practices
  • produces a detailed list of security findings prioritized by level of severity.

AWS Certificate Manager

  • helps provision, manage, and deploy Secure Sockets Layer/Transport Layer Security (SSL/TLS) certificates for use with AWS services like ELB
  • removes the time-consuming manual process of purchasing, uploading, and renewing SSL/TLS certificates.

AWS CloudHSM

  • helps meet corporate, contractual, and regulatory compliance requirements for data security by using dedicated Hardware Security Module (HSM) appliances within the AWS Cloud.
  • allows protection of encryption keys within HSMs, designed and validated to government standards for secure key management.
  • helps comply with strict key management requirements without sacrificing application performance.

AWS Directory Service

  • provides Microsoft Active Directory (Enterprise Edition), also known as AWS Microsoft AD, that enables directory-aware workloads and AWS resources to use managed Active Directory in the AWS Cloud.

AWS Key Management Service

  • is a managed service that makes it easy to create and control the encryption keys used to encrypt your data.
  • uses HSMs to protect the security of your keys.

AWS Organizations

  • allows creation of AWS accounts groups, to more easily manage security and automation settings collectively
  • helps centrally manage multiple accounts to help scale.
  • helps to control which AWS services are available to individual accounts, automate new account creation, and simplify billing.

AWS Shield

  • is a managed Distributed Denial of Service (DDoS) protection service that safeguards web applications running on AWS.
  • provides always-on detection and automatic inline mitigations that minimize application downtime and latency, so there is no need to engage AWS Support to benefit from DDoS protection.
  • provides two tiers of AWS Shield: Standard and Advanced.

AWS WAF

  • is a web application firewall that helps protect web applications from common web exploits that could affect application availability, compromise security, or consume excessive resources.
  • gives complete control over which traffic to allow or block to web application by defining customizable web security rules.

AWS Compute Services

Amazon Elastic Compute Cloud (EC2)

  • provides secure, resizable compute capacity
  • provide complete control of the computing resources (root access, ability to start, stop, terminate instances etc.)
  • reduces the time required to obtain and boot new instances to minutes
  • allows quick scaling of capacity, both up and down, as the computing requirements changes
  • provides developers and sysadmins tools to build failure resilient applications and isolate themselves from common failure scenarios.
  • Benefits
    • Elastic Web-Scale Computing
      • enables scaling to increase or decrease capacity within minutes, not hours or days.
    • Flexible Cloud Hosting Services
      • flexibility to choose from multiple instance types, operating systems, and software packages.
      • selection of memory configuration, CPU, instance storage, and boot partition size
    • Reliable
      • offers a highly reliable environment where replacement instances can be rapidly and predictably commissioned.
      • runs within AWS’s proven network infrastructure and data centers.
      • EC2 Service Level Agreement (SLA) commitment is 99.95% availability for each Region.
    • Secure
      • works in conjunction with VPC to provide security and robust networking functionality for your compute resources.
      • allows control of IP address, exposure to Internet (using subnets), inbound and outbound access (using Security groups and NACLs)
      • existing IT infrastructure can be connected to the resources in the VPC using industry-standard encrypted IPsec virtual private network (VPN) connections
    • Inexpensive – pay only for the capacity actually used
  • EC2 Purchasing Options and Types
    • On-Demand Instances
      • pay for compute capacity by the hour with no long-term commitments
      • enables to increase or decrease compute capacity depending on the demands and only pay the specified hourly rate for used instances
      • frees from the costs and complexities of planning, purchasing, and maintaining hardware and transforms what are commonly large fixed costs into much smaller variable costs.
      • also helps remove the need to buy “safety net” capacity to handle periodic traffic spikes.
    • Reserved Instances
      • provides significant discount (up to 75%) compared to On-Demand instance pricing.
      • provides flexibility to change families, operating system types, and tenancies with Convertible Reserved Instances.
    • Spot Instances
      • allow you to bid on spare EC2 computing capacity.
      • are often available at a discount compared to On-Demand pricing, helping reduce the application cost, grow it’s compute capacity and throughput for the same budget
    • Dedicated Instances – that run on hardware dedicated to a single customer for additional isolation.
    • Dedicated Hosts
      • are physical servers with EC2 instance capacity fully dedicated to your use.
      • can help you address compliance requirements and reduce costs by allowing you to use your existing server-bound software licenses.

Amazon EC2 Container Service

  • is a highly scalable, high-performance container management service that supports Docker containers.
  • allows running applications on a managed cluster of EC2 instances
  • eliminates the need to install, operate, and scale cluster management infrastructure.
  • can use to schedule the placement of containers across the cluster based on the resource needs and availability requirements.
  • custom scheduler or third-party schedulers can be integrated to meet business or application-specific requirements.

Amazon EC2 Container Registry

  • is a fully-managed Docker container registry that makes it easy for developers to store, manage, and deploy Docker container images.
  • is integrated with Amazon EC2 Container Service (ECS), simplifying development to production workflow.
  • eliminates the need to operate container repositories or worry about scaling the underlying infrastructure.
  • hosts images in a highly available and scalable architecture
  • pay only for the amount of data stored and data transferred to the Internet.

Amazon Lightsail

  • is designed to be the easiest way to launch and manage a virtual private server with AWS.
  • plans include everything needed to jumpstart a project – a virtual machine, SSD-based storage, data transfer, DNS management, and a static IP address- for a low, predictable price.

AWS Batch

  • enables developers, scientists, and engineers to easily and efficiently run hundreds of thousands of batch computing jobs on AWS.
  • dynamically provisions the optimal quantity and type of compute resources (e.g., CPU or memory-optimized instances) based on the volume and specific resource requirements of the batch jobs submitted.
  • plans, schedules, and executes the batch computing workloads across the full range of AWS compute services and features

AWS Elastic Beanstalk

  • is an easy-to-use service for deploying and scaling web applications and services developed with Java, .NET, PHP, Node.js, Python, Ruby, Go, and Docker on familiar servers such as Apache, Nginx, Passenger, and Internet Information Services (IIS)
  • automatically handles the deployment, from capacity provisioning, load balancing, and auto scaling to application health monitoring.
  • provides full control over the AWS resources with access to the underlying resources at any time.

AWS Lambda

  • enables running code without zero administration, provisioning or managing servers, and scaling for high availability
  • pay only for the compute time consumed – there is no charge when the code is not running
  • can be setup to be automatically triggered from other AWS services, or called it directly from any web or mobile app.

Auto Scaling

  • helps maintain application availability
  • allows scaling EC2 capacity up or down automatically according to defined conditions or demand spikes to reduce cost
  • helps ensure desired number of EC2 instances are running always
  • well suited both to applications that have stable demand patterns and applications that experience hourly, daily, or weekly variability in usage.

Storage

Simple Storage Service

  • is object storage with a simple web service interface to store and retrieve any amount of data from anywhere on the web.
  • S3 Features
    • Durable
      • designed for durability of 99.999999999% of objects
      • data is redundantly stored across multiple facilities and multiple devices in each facility.
    • Available – designed for up to 99.99% availability (standard) of objects over a given year and is backed by the S3 Service Level Agreement
    • Scalable – can help store virtually unlimited data
    • Secure
      • supports data in motion over SSL and data at rest encryption
      • bucket policies and IAM can help manage object permissions and control access to the data
    • Low Cost
      • provides storage at a very low cost.
      • using lifecycle policies, the data can be automatically tiered into lower cost, longer-term cloud storage classes like S3 Standard – Infrequent Access and Glacier for archiving.

Elastic Block Store (EBS)

  • provides persistent block storage volumes for use with EC2 instance
  • offers the consistent and low-latency performance needed to run workloads.
  • allows scaling up or down within minutes – all while paying a low price for only what is provisioned
  • EBS Features
    • High Performance Volumes – Choose between SSD backed or HDD backed volumes to deliver the performance needed
    • Availability
      • is designed for 99.999% availability
      • automatically replicates within its Availability Zone to protect from component failure, offering high availability and durability.
    • Encryption – provides seamless support for data-at-rest and data-in-transit between EC2 instances and EBS volumes.
    • Snapshots – protect data by creating point-in-time snapshots of EBS volumes, which are backed up to S3 for long-term durability.

Elastic File System (EFS)

  • provides simple, scalable file storage for use with EC2 instances
  • storage capacity is elastic, growing and shrinking automatically as files are added and removed
  • provides a standard file system interface and file system access semantics, when mounted on EC2 instances
  • works in shared mode, where multiple EC2 instances can access an EFS file system at the same time, allowing EFS to provide a common data
    source for workloads and applications running on more than one EC2 instance.
  • can be mounted on on-premises data center servers when connected to the VPC with AWS Direct Connect.
  • can be mounted on on-premises servers to migrate data sets to EFS, enable cloud bursting scenarios, or backup on-premises data to EFS.
  • is designed for high availability and durability, and provides performance for a broad spectrum of workloads and applications, including big data and analytics, media processing workflows, content management, web serving, and home directories.

Glacier

  • provides secure, durable, and extremely low-cost storage service for data archiving and long-term backup
  • To keep costs low yet suitable for varying retrieval needs, Glacier provides three options for access to archives, from a few minutes to several hours.

AWS Storage Gateway

  • seamlessly enables hybrid storage between on-premises storage environments and the AWS Cloud
  • combines a multi-protocol storage appliance with highly efficient network connectivity to AWS cloud storage services, delivering local
    performance with virtually unlimited scale.
  • use it in remote offices and data centers for hybrid cloud workloads involving migration, bursting, and storage tiering

Databases

Aurora

  • is a MySQL and PostgreSQL compatible relational database engine
  • provides the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases.
  • Benefits
    • Highly Secure
      • provides multiple levels of security, including
        • network isolation using VPC
        • encryption at rest using keys created and controlled through AWS Key Management Service (KMS), and
        • encryption of data in transit using SSL.
      • with an an encrypted Aurora instance, automated backups, snapshots, and replicas are also encrypted
    • Highly Scalable – automatically grows storage as needed
    • High Availability and Durability
      • designed to offer greater than 99.99% availability
      • recovery from physical storage failures is transparent, and instance failover typically requires less than 30 seconds
      • is fault-tolerant and self-healing. Six copies of the data are replicated across three AZs and continuously backed up to S3.
      • automatically and continuously monitors and backs up your database to S3, enabling granular point-in-time recovery.
    • Fully Managed – is a fully managed database service, and database management tasks such as hardware provisioning, software patching, setup, configuration, monitoring, or backups is taken care of

Relational Database Service (RDS)

  • makes it easy to set up, operate, and scale a relational database
  • provides cost-efficient and resizable capacity while managing time-consuming database administration tasks
  • supports various, including Amazon Aurora, PostgreSQL, MySQL, MariaDB, Oracle, and Microsoft SQL Server
  • Benefits
    • Fast and Easy to Administer – No need for infrastructure provisioning, and no need for installing and maintaining database software.
    • Highly Scalable
      • allows quick and easy scaling of database’s compute and storage resources, often with no downtime.
      • allows offloading read traffic from primary database using Read Replicas, for few RDS engine types
    • Available and Durable
      • runs on the same highly reliable infrastructure
      • allows Multi-AZ DB instance, where RDS synchronously replicates the data to a standby instance in a different Availability Zone (AZ).
      • enhances reliability for critical production databases, by enabling automated backups, database snapshots, and automatic host replacement.
    • Secure
      • provides multiple levels of security, including
        • network isolation using VPC
        • connect to on-premises existing IT infrastructure through an industry-standard encrypted IPsec VPN
        • encryption at rest using keys created and controlled through AWS Key Management Service (KMS), and
        • offer encryption at rest and encryption in transit.
      • with an an encrypted instance, automated backups, snapshots, and replicas are also encrypted
    • Inexpensive – pay very low rates and only for the consumed resources, while taking advantage of on-demand and reserved instance types

DynamoDB

  • fully managed, fast and flexible NoSQL database service for applications that need consistent, single-digit millisecond latency at any scale.
  • supports both document and key-value data models.
  • flexible data model and reliable performance make it a great fit for mobile, web, gaming, ad-tech, Internet of Things (IoT), and other applications
  • Benefits
    • Fast, Consistent Performance
      • designed to deliver consistent, fast performance at any scale
      • uses automatic partitioning and SSD technologies to meet throughput requirements and deliver low latencies at any scale.
    • Highly Scalable – it manages all the scaling to achieve the specified throughput capacity requirements
    • Event-Driven Programming – integrates with AWS Lambda to provide Triggers that enable architecting applications that automatically react to data changes.

ElastiCache

  • is a web service that makes it easy to deploy, operate, and scale an in-memory cache in the cloud.
  • helps improves the performance of web applications by caching results and allowing to retrieve information from fast, managed, in-memory caches, instead of relying entirely on slower disk-based databases.
  • supports two open-source in-memory caching engines: Redis and Memcached

Migration

AWS Application Discovery Service

  • helps systems integrators quickly and reliably plan application migration projects by automatically identifying applications running in on-premises
    data centers, their associated dependencies, and performance profiles
  • automatically collects configuration and usage data from servers, storage, and networking equipment to develop a list of applications, how they
    perform, and how they are interdependent
  • information is retained in encrypted format in an AWS Application Discovery Service database, which you can export as a CSV or XML file into your preferred visualization tool or cloud migration solution to help reduce the complexity and time in planning your cloud migration.

AWS Database Migration Service

  • helps migrate databases to AWS easily and securely
  • source database remains fully operational during the migration, minimizing downtime to applications that rely on the database.
  • supports homogenous migrations such as Oracle to Oracle, as well as heterogeneous migrations between different database platforms, such as Oracle to Amazon Aurora or Microsoft SQL Server to MySQL.
  • allows streaming of data to Redshift from any of the supported sources including Aurora, PostgreSQL, MySQL, MariaDB, Oracle, SAP ASE, and SQL Server, enabling consolidation and easy analysis of data in the petabyte-scale data warehouse
  • can also be used for continuous data replication with high availability.

AWS Server Migration Service

  • is an agentless service which makes it easier and faster to migrate thousands of on-premises workloads to AWS

Snowball

  • is a petabyte-scale data transport solution that uses secure appliances to transfer large amounts of data into and out of AWS.
  • addresses common challenges with large-scale data transfers including high network costs, long transfer times, and security concerns.
  • uses multiple layers of security designed to protect the data including tamper resistant enclosures, 256-bit encryption, and an industry-standard Trusted Platform Module (TPM) designed to ensure both security and full chain of custody of your data.
  • performs a software erasure of the Snowball appliance, once the data transfer job has been processed

Snowball Edge

  • is a 100 TB data transfer device with on-board storage and compute capabilities.
  • can be used to move large amounts of data into and out of AWS, as a temporary storage tier for large local datasets, or to support local workloads in remote or offline locations.
  • multiple devices can be clustered together to form a local storage tier and process the data on-premises, helping ensure the applications continue to run even when they are not able to access the cloud

Snowmobile

  • is an exabyte-scale data transfer service used to move extremely large amounts of data to AWS.
  • provides secure, fast, and cost effective transfer of data
  • data cane be imported into S3 or Glacier, once data loaded
  • uses multiple layers of security designed to protect the data including dedicated security personnel, GPS tracking, alarm monitoring, 24/7 video surveillance, and an optional escort security vehicle while in transit.
  • all data is encrypted with 256-bit encryption keys managed through KMS and designed to ensure both security and full chain of custody of the data

Networking and Content Delivery

Virtual Private Cloud (VPC)

  • helps provision a logically isolated section of the AWS Cloud where AWS resources can be launched in a virtual network that you define
  • provides complete control over the virtual networking environment, including selection of IP address range, creation of subnets (public and private), and configuration of route tables and network gateways.
  • allows use of both IPv4 and IPv6 for secure and easy access to resources and applications
  • allows multiple layers of security, including security groups and network access control lists, to help control access resources
  • allows creation of a hardware virtual private network (VPN) connection between the corporate data center and VPC and leverage the AWS Cloud as an extension of corporate data center.

CloudFront

  • is a global content delivery network (CDN) service that accelerates delivery of websites, APIs, video content, or other web assets.
  • can be used to deliver entire website, including dynamic, static, streaming, and interactive content using a global network of edge locations.
  • allows requests for the content to be automatically routed to the nearest edge location, so content is delivered with the best possible performance.
  • is optimized to work with other services in AWS, such as S3, EC2, ELB, and Route 53 as well as with any non-AWS origin server that stores the original, definitive versions of your files.

Route 53

  • is a highly available and scalable Domain Name System (DNS) web service
  • effectively connects user requests to infrastructure running in AWS – such as EC2 instances, ELB, or S3 buckets—and can also be used to route users to infrastructure outside of AWS.
  • helps configure DNS health checks to route traffic to healthy endpoints or to independently monitor the health of your application and its endpoints.
  • allows traffic management globally through a variety of routing types, including latency-based routing, Geo DNS, and weighted round robin – all of which can be combined with DNS Failover in order to enable a variety of low-latency, fault-tolerant architectures.
  • is fully compliant with IPv6 as well
  • offers Domain Name Registration service

Direct Connect

  • makes it easy to establish a dedicated network connection with on- premises to AWS
  • helps establish private connectivity between AWS and data center, office, or co-location environment,
  • helps increase bandwidth throughput, reduce network costs, , and provide a more consistent network experience than Internet-based connections

Elastic Load Balancing (ELB)

  • automatically distributes incoming application traffic across multiple EC2 instances
  • enables achieve greater levels of fault tolerance by seamlessly providing the required amount of load balancing capacity needed to distribute application traffic.
  • offers two types of load balancers that both feature high availability, automatic scaling, and robust security.
    • Classic Load Balancer
      • routes traffic based on either application or network level information
      • ideal for simple load balancing of traffic across multiple EC2 instances
    • Application Load Balancer
      • routes traffic based on advanced application-level information that includes the content of the request
      • ideal for applications needing advanced routing capabilities, microservices, and container-based architectures.
      • offers the ability to route traffic to multiple services or load balance
        across multiple ports on the same EC2 instance.

Management Tools

AWS CloudWatch

  • is a monitoring and logging service for AWS Cloud resources and the applications running on AWS.
  • can be used to collect and track metrics, collect and monitor log files, set alarms, and automatically react to changes in the AWS resources.

AWS CloudFormation

  • allows developers and systems administrators to implement “Infrastructure as Code”
  • provides an easy way to create and manage a collection of related AWS resources, provisioning and updating them in an orderly and predictable fashion
  • handles the order for provisioning AWS services or the subtleties of making those dependencies work.
  • allows applying version control to the AWS infrastructure the same way its done with software

AWS CloudTrail

  • helps records AWS API calls for the account and delivers log files
  • including API calls made using the AWS Management Console, AWS SDKs, command line tools, and higher-level AWS services (such as AWS CloudFormation),
  • recorded information includes the identity of the API caller, the time of the API call, the source IP address of the API caller, the request parameters, and the response elements returned by the AWS service.
  • enables security analysis, resource change tracking, compliance auditing

AWS Config

  • provides an AWS resource inventory, configuration history, and configuration change notifications to enable security and governance
  • provides Config Rules feature, that enables rules creation that automatically check the configuration of AWS resources
  • helps discover existing and deleted AWS resources, determine overall compliance against rules, and dive into configuration details of a resource at any point in time.
  • enables compliance auditing, security analysis, resource change tracking, and troubleshooting.

AWS OpsWorks

  • configuration management service that uses Chef, an automation platform that treats server configurations as code.
  • uses Chef to automate how servers are configured, deployed, and managed across the EC2 instances or on-premises compute environments.
  • has two offerings, OpsWorks for Chef Automate and OpsWorks Stacks

AWS Service Catalog

  • allows organizations to create and manage catalogs of IT services that are approved for use on AWS.
  • helps centrally manage commonly deployed IT services and helps to achieve consistent governance and meet compliance requirements, while enabling users to quickly deploy only approved IT services they need
  • can include everything from virtual machine images, servers, software, and databases to complete multi-tier application architectures.

AWS Trusted Advisor

  • is an online resource to help reduce cost, increase performance, and improve security by optimizing the AWS environment.
  • provides real-time guidance to help provision the resources following AWS best practices.

AWS Personal Health Dashboard

  • provides alerts and remediation guidance when AWS is experiencing events that might affect you.
  • displays relevant and timely information to help you manage events in progress, and provides proactive notification to help you plan for scheduled activities.
  • alerts are automatically triggered by changes in the health of AWS resources, providing event visibility and guidance to help quickly diagnose and resolve issues.
  • provides a personalized view into the performance and availability of the AWS services underlying the AWS resources.
  • Service Health Dashboard displays the general status of AWS services,

AWS Managed Services

  • provides ongoing management of the AWS infrastructure so the focus can be on applications.
  • helps reduce the operational overhead and risk, by implementing best practices to maintain the infrastructure
  • automates common activities such as change requests, monitoring, patch management, security, and backup services, and provides full-lifecycle services to provision, run, and support the infrastructure.
  • improves agility, reduces cost, and unburdens from infrastructure operations

Developer Tools

AWS CodeCommit

  • is a fully managed source control service that makes to host secure and highly scalable private Git repositories

AWS CodeBuild

  • is a fully managed build service that compiles source code, runs tests, and produces software packages that are ready to deploy
  • also helps provision, manage, and scale the build servers.
  • scales continuously and processes multiple builds concurrently, so the builds are not left waiting in a queue.

AWS CodeDeploy

  • is a service that automates code deployments to any instance, including EC2 instances and instances running on premises.
  • helps to rapidly release new features, avoid downtime during application deployment, and handles the complexity of updating the applications.

AWS CodePipeline

  • is a continuous integration and continuous delivery service for fast and reliable application and infrastructure updates.
  • builds, tests, and deploys the code every time there is a code change, based on the defined release process models

AWS X-Ray

  • helps developers analyze and debug distributed applications in production or development, such as those built using a microservices architecture
  • provides an end-to-end view of requests as they travel through the application, and shows a map of its underlying components.
  • helps understand how the application and its underlying services are performing, to identify and troubleshoot the root cause of performance issues and errors.

Messaging

Amazon SQS

  • is a fast, reliable, scalable, fully managed message queuing service.
  • makes it simple and cost-effective to decouple the components of a cloud application.
  • includes standard queues with high throughput and at-least-once processing, and FIFO queues
  • provides FIFO (first-in, first-out) delivery and exactly-once processing.

Amazon SNS

  • fast, flexible, fully managed push notification service to send individual messages or to fan-out messages to large numbers of recipients.
  • makes it simple and cost effective to send push notifications to mobile device users, email recipients or even send messages to other distributed services
  • notifications can be sent to Apple, Google, Fire OS, and Windows devices, as well as to Android devices in China with Baidu Cloud Push.
  • can also deliver messages to SQS, Lambda functions, or HTTP endpoint

Amazon SES

  • is a cost-effective email service built on the reliable and scalable infrastructure that Amazon.com developed to serve its own customer
  • can send transactional email, marketing messages, or any other type of high-quality content to the customers.
  • can receive messages and deliver them to an S3 bucket, call your custom code via an AWS Lambda function, or publish notifications to SNS.

Analytics

Amazon Athena

  • is an interactive query service that helps to analyze data in S3 using standard SQL.
  • is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run.
  • removes the need for complex extract, transform, and load (ETL) jobs

Amazon EMR

  • provides a managed Hadoop framework that makes it easy, fast, and costeffective to process vast amounts of data across dynamically scalable EC2 instances.
  • enables you to run other popular distributed frameworks such as Apache Spark, HBase, Presto, and Flink, and interact with data in other AWS data stores such as S3 and DynamoDB.
  • securely and reliably handles a broad set of big data use cases, including log analysis, web indexing, data transformations (ETL), machine learning, financial analysis, scientific simulation, and bioinformatics.

Amazon CloudSearch

  • is a managed service and makes it simple and costeffective to set up, manage, and scale a search solution for website or application.
  • supports 34 languages and popular search features such as highlighting, autocomplete, and geospatial search.

Amazon Elasticsearch Service

  • makes it easy to deploy, operate, and scale Elasticsearch for log analytics, full text search, application monitoring, and more.
  • is a fully managed service that delivers Elasticsearch’s easy-to-use APIs and real-time capabilities along with the availability, scalability, and security required by production workloads.

Amazon Kinesis

  • is a platform for streaming data on AWS, offering powerful services to make it easy to load and analyze streaming data,
  • provides the ability to build custom streaming data applications for specialized needs.
  • offers three services:
    • Amazon Kinesis Firehose,
      • helps load streaming data into AWS.
      • can capture, transform, and load streaming data into Amazon Kinesis Analytics, S3, Redshift, and Elasticsearch Service, enabling near real-time analytics with existing business intelligence tools and dashboards
      • helps batch, compress, and encrypt the data before loading it, minimizing the amount of storage used at the destination and increasing security.
    • Amazon Kinesis Analytics
      • helps process streaming data in real time with standard SQL
    • Amazon Kinesis Streams
      • enables you to build custom applications that process or analyze streaming data for specialized needs.

Amazon Redshift

  • provides a fast, fully managed, petabyte-scale data warehouse that makes it simple and cost-effective to analyze all your data using your existing business intelligence tools.
  • has a massively parallel processing (MPP) data warehouse architecture, parallelizing and distributing SQL operations to take advantage of all available resources.
  • provides underlying hardware designed for high performance data processing, using local attached storage to maximize throughput between the CPUs and drives, and a 10GigE mesh network to maximize throughput between nodes.

Amazon QuickSight

  • provides fast, cloud-powered business analytics service that makes it easy to build visualizations, perform ad-hoc analysis, and quickly get business insights from your data.

AWS Data Pipeline

  • helps reliably process and move data between different AWS compute and storage services, as well as on-premises data sources, at specified intervals
  • can regularly access your data where it’s stored, transform and process it at scale, and efficiently transfer the results to AWS services such as S3, RDS, DynamoDB, and EMR.
  • helps create complex data processing workloads that are fault tolerant, repeatable, and highly available.
  • also allows you to move and process data that was previously locked up in on-premises data silos.

AWS Glue

  • is a fully managed ETL service that makes it easy to move data between data stores.
  • helps simplifies and automates the difficult and time-consuming tasks of data discovery, conversion, mapping, and job scheduling.
  • helps schedules ETL jobs and provisions and scales all the infrastructure
  • required so that ETL jobs run quickly and efficiently at any scale.

Application Services

AWS Step Functions

  • makes it easy to coordinate the components of distributed applications and microservices using visual workflows.
  • automatically triggers and tracks each step, and retries when there are errors, so the application executes in order and as expected.

Amazon API Gateway

  • is a fully managed service that makes it easy for developers to create, publish, maintain, monitor, and secure APIs at any scale.
  • handles all the tasks involved in accepting and processing up to hundreds of thousands of concurrent API calls, including traffic management, authorization and access control, monitoring, and API version management.

Amazon Elastic Transcoder

  • is media transcoding in the cloud
  • is designed to be a highly scalable, easy-to-use, and cost-effective way for developers and businesses to convert (or transcode) media files from their source format into versions that will play back on devices like smartphones, tablets, and PCs.

Amazon SWF

  • helps developers build, run, and scale background jobs that have parallel or sequential steps.
  • is a fully-managed state tracker and task coordinator in the cloud.

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. Which AWS services belong to the Compute services? Choose 2 answers
    1. Lambda
    2. EC2
    3. S3
    4. EMR
    5. CloudFront
  2. Which AWS service provides low cost storage option for archival and long-term backup?
    1. Glacier
    2. S3
    3. EBS
    4. CloudFront
  3. Which AWS services belong to the Storage services? Choose 2 answers
    1. EFS
    2. IAM
    3. EMR
    4. S3
    5. CloudFront
  4. A Company allows users to upload videos on its platform. They want to convert the videos to multiple formats supported on multiple devices and platforms. Which AWS service can they leverage for the requirement?
    1. AWS SWF
    2. AWS Video Converter
    3. AWS Elastic Transcoder
    4. AWS Data Pipeline
  5. Which analytic service helps analyze data in S3 using standard SQL?
    1. Athena
    2. EMR
    3. Elasticsearch
    4. Kinesis
  6. What features does AWS’s Route 53 service provide? Choose the 2 correct answers:
    1. Content Caching
    2. Domain Name System (DNS) service
    3. Database Management
    4. Domain Registration
  7. You are trying to organize and import (to AWS) gigabytes of data that are currently structured in JSON-like, name-value documents. What AWS service would best fit your needs?
    1. Lambda
    2. DynamoDB
    3. RDS
    4. Aurora
  8. What AWS database is primarily used to analyze data using standard SQL formatting with compatibility for your existing business intelligence tools? Choose the correct answer:
    1. Redshift
    2. RDS
    3. DynamoDB
    4. ElastiCache
  9. A company wants their application to use pre-configured machine image with software installed and configured. which AWS feature can help for the same?
    1. Amazon Machine Image
    2. AWS CloudFormation
    3. AWS Lambda
    4. AWS Lightsail
  10. What AWS service can be used for track API event calls for security analysis, resource change tracking?
    1. AWS CloudWatch
    2. AWS CloudFormation
    3. AWS CloudTrail
    4. AWS OpsWorks
  11. Which AWS service can help Offload the read traffic from your database in order to reduce latency caused by read-heavy workload?
    1. ElastiCache
    2. DynamoDB
    3. S3
    4. EFS
  12. What service allows system administrators to run “Infrastructure as code”?
    1. CloudFormation
    2. CloudWatch
    3. CloudTrail
    4. CodeDeploy

References

AWS_Overview_Whitepaper

AWS Support Plans – Certification

AWS Support Plans

AWS provides 4 AWS support plans with additional features with extra costs. The plans are in order of features and the features for lower support plans are available for higher one and not repeated.

NOTE – This post is more relevant for AWS Cloud Practitioner Certification

Basic

Developer

  • Business hours access to Cloud Support Associates via email
  • One primary contact can open Unlimited cases
  • Case Severity/Response times SLA (is in business hours)
    • General guidance < 24 business hours
    • System impaired < 12 business hours
  • General Guidance on Architecture support

Business

  • 24×7 access to Cloud Support Engineers via email, chat & phone
  • Access to Personal Health Dashboard Health API
  • Access to full set of Trusted Advisor checks
  • Allows Unlimited contacts/Unlimited cases (IAM supported) to open cases
  • Case Severity/Response times SLA (is in hours)
    • General guidance < 24 hours
    • System impaired < 12 hours
    • Production system impaired < 4 hours
    • Production system down < 1 hour

Enterprise

  • 24×7 access to Sr. Cloud Support Engineers via email, chat & phone
  • Architecture support with Consultative review and guidance based on your applications
  • Access to a Well-Architected Review delivered by AWS Solution Architects
  • Operations Support for Operational reviews, recommendations, and reporting
  • Access to online self-paced labs
  • Account Assistance by Assigned Support Concierge
  • Proactive Guidance by Designated Technical Account Manager
  • Case Severity/Response times SLA
    • Business-critical system down < 15 minutes

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. Which AWS support plan has a dedicated technical account manager assigned for proactive guidance?
    1. AWS Basic support plan
    2. AWS Developer support plan
    3. AWS Business support plan
    4. AWS Enterprise support plan
  2. Which feature is available for all the AWS support plans?
    1. Technical Account Manager
    2. Assigned Support Concierge
    3. 24×7 access to customer service
    4. Access to Cloud Support resources

References

AWS_Support_Plans

Architecting for the Cloud – AWS Best Practices – Whitepaper – Certification

Architecting for the Cloud – AWS Best Practices

Architecting for the Cloud – AWS Best Practices whitepaper provides architectural patterns and advice on how to design systems that are secure, reliable, high performing, and cost efficient

AWS Design Principles

Scalability

  • While AWS provides virtually unlimited on-demand capacity, the architecture should be designed to take advantage of those resources
  • There are two ways to scale an IT architecture
    • Vertical Scaling
      • takes place through increasing specifications of an individual resource for e.g. updating EC2 instance type with increasing RAM, CPU, IOPS, or networking capabilities
      • will eventually hit a limit, and is not always a cost effective or highly available approach
    • Horizontal Scaling
      • takes place through increasing number of resources for e.g. adding more EC2 instances or EBS volumes
      • can help leverage the elasticity of cloud computing
      • not all the architectures can be designed to distribute their workload to multiple resources
      • applications designed should be stateless,
        • that needs no knowledge of previous interactions and stores no session information
        • capacity can be increased and decreased, after running tasks have been drained
      • State, if needed, can be implemented using
        • Low latency external store, for e.g. DynamoDB, Redis, to maintain state information
        • Session affinity, for e.g. ELB sticky sessions, to bind all the transactions of a session to a specific compute resource. However, it cannot be guaranteed or take advantage of newly added resources for existing sessions
      • Load can be distributed across multiple resources using
        • Push model, for e.g. through ELB where it distributes the load across multiple EC2 instances
        • Pull model, for e.g. through SQS or Kinesis where multiple consumers subscribe and consume
      • Distributed processing, for e.g. using EMR or Kinesis, helps process large amounts of data by dividing task and its data into many small fragments of works

Disposable Resources Instead of Fixed Servers

  • Resources need to be treated as temporary disposable resources rather than fixed permanent on-premises resources before
  • AWS focuses on the concept of Immutable infrastructure
    • servers once launched, is never updated throughout its lifetime.
    • updates can be performed on a new server with latest configurations,
    • this ensures resources are always in a consistent (and tested) state and easier rollbacks
  • AWS provides multiple ways to instantiate compute resources in an automated and repeatable way
    • Bootstraping
      • scripts to configure and setup for e.g. using data scripts and cloud-init to install software or copy resources and code
    • Golden Images
      • a snapshot of a particular state of that resource,
      • faster start times and removes dependencies to configuration services or third-party repositories
    • Containers
      • AWS support for docker images through Elastic Beanstalk and ECS
      • Docker allows packaging a piece of software in a Docker Image, which is a standardized unit for software development, containing everything the software needs to run: code, runtime, system tools, system libraries, etc
  • Infrastructure as Code
    • AWS assets are programmable, techniques, practices, and tools from software development can be applied to make the whole infrastructure reusable, maintainable, extensible, and testable.
    • AWS provides services like CloudFormation, OpsWorks for deployment

Automation

  • AWS provides various automation tools and services which help improve system’s stability, efficiency and time to market.
    • Elastic Beanstalk
      • a PaaS that allows quick application deployment while handling resource provisioning, load balancing, auto scaling, monitoring etc
    • EC2 Auto Recovery
      • creates CloudWatch alarm that monitors an EC2 instance and automatically recovers it if it becomes impaired.
      • A recovered instance is identical to the original instance, including the instance ID, private & Elastic IP addresses, and all instance metadata.
      • Instance is migrated through reboot, in memory contents are lost.
    • Auto Scaling
      • allows maintain application availability and scale the capacity up or down automatically as per defined conditions
    • CloudWatch Alarms
      • allows SNS triggers to be configured when a particular metric goes beyond a specified threshold for a specified number of periods
    • CloudWatch Events
      • allows real-time stream of system events that describe changes in AWS resources
    • OpsWorks
      • allows continuous configuration through lifecycle events that automatically update the instances’ configuration to adapt to environment changes.
      • Events can be used to trigger Chef recipes on each instance to perform specific configuration tasks
    • Lambda Scheduled Events
      • allows Lambda function creation and direct AWS Lambda to execute it on a regular schedule.

Loose Coupling

  • AWS helps loose coupled architecture that reduces interdependencies, a change or failure in a component does not cascade to other components
    • Asynchronous Integration
      • does not involve direct point-to-point interaction but usually through an intermediate durable storage layer for e.g. SQS, Kinesis
      • decouples the components and introduces additional resiliency
      • suitable for any interaction that doesn’t need an immediate response and an ack that a request has been registered will suffice
    • Service Discovery
      • allows new resources to be launched or terminated at any point in time and discovered as well for e.g. using ELB as a single point of contact with hiding the underlying instance details or Route 53 zones to abstract load balancer’s endpoint
    • Well-Defined Interfaces
      • allows various components to interact with each other through specific, technology agnostic interfaces for e.g. RESTful apis with API Gateway 

Services, Not Servers

Databases

  • AWS provides different categories of database technologies
    • Relational Databases (RDS)
      • normalizes data into well-defined tabular structures known as tables, which consist of rows and columns
      • provide a powerful query language, flexible indexing capabilities, strong integrity controls, and the ability to combine data from multiple tables in a fast and efficient manner
      • allows vertical scalability by increasing resources and horizontal scalability using Read Replicas for read capacity and sharding or data partitioning for write capacity
      • provides High Availability using Multi-AZ deployment, where data is synchronously replicated
    • NoSQL Databases (DynamoDB)
      • provides databases that trade some of the query and transaction capabilities of relational databases for a more flexible data model that seamlessly scales horizontally
      • perform data partitioning and replication to scale both the reads and writes in a horizontal fashion
      • DynamoDB service synchronously replicates data across three facilities in an AWS region to provide fault tolerance in the event of a server failure or Availability Zone disruption
    • Data Warehouse (Redshift)
      • Specialized type of relational database, optimized for analysis and reporting of large amounts of data
      • Redshift achieves efficient storage and optimum query performance through a combination of massively parallel processing (MPP), columnar data storage, and targeted data compression encoding schemes
      • Redshift MPP architecture enables increasing performance by increasing the number of nodes in the data warehouse cluster
  • For more details refer to AWS Storage Options Whitepaper

Removing Single Points of Failure

  • AWS provides ways to implement redundancy, automate recovery and reduce disruption at every layer of the architecture
  • AWS supports redundancy in the following ways
    • Standby Redundancy
      • When a resource fails, functionality is recovered on a secondary resource using a process called failover.
      • Failover will typically require some time before it completes, and during that period the resource remains unavailable.
      • Secondary resource can either be launched automatically only when needed (to reduce cost), or it can be already running idle (to accelerate failover and minimize disruption).
      • Standby redundancy is often used for stateful components such as relational databases.
    • Active Redundancy
      • requests are distributed to multiple redundant compute resources, if one fails, the rest can simply absorb a larger share of the workload.
      • Compared to standby redundancy, it can achieve better utilization and affect a smaller population when there is a failure.
  • AWS supports replication
    • Synchronous replication
      • acknowledges a transaction after it has been durably stored in both the primary location and its replicas.
      • protects data integrity from the event of a primary node failure
      • used to scale read capacity for queries that require the most up-to-date data (strong consistency).
      • compromises performance and availability
    • Asynchronous replication
      • decouples the primary node from its replicas at the expense of introducing replication lag
      • used to horizontally scale the system’s read capacity for queries that can tolerate that replication lag.
    • Quorum-based replication
      • combines synchronous and asynchronous replication to overcome the challenges of large-scale distributed database systems
      • Replication to multiple nodes can be managed by defining a minimum number of nodes that must participate in a successful write operation
  • AWS provide services to reduce or remove single point of failure
    • Regions, Availability Zones with multiple data centers
    • ELB or Route 53 to configure health checks and mask failure by routing traffic to healthy endpoints
    • Auto Scaling to automatically replace unhealthy nodes
    • EC2 auto-recovery to recover unhealthy impaired nodes
    • S3, DynamoDB with data redundantly stored across multiple facilities
    • Multi-AZ RDS and Read Replicas
    • ElastiCache Redis engine supports replication with automatic failover
  • For more details refer to AWS Disaster Recovery Whitepaper

Optimize for Cost

  • AWS can help organizations reduce capital expenses and drive savings as a result of the AWS economies of scale
  • AWS provides different options which should be utilized as per use case –
    • EC2 instance types – On Demand, Reserved and Spot
    • Trusted Advisor or EC2 usage reports to identify the compute resources and their usage
    • S3 storage class – Standard, Reduced Redundancy, and Standard-Infrequent Access
    • EBS volumes – Magnetic, General Purpose SSD, Provisioned IOPS SSD
    • Cost Allocation tags to identify costs based on tags
    • Auto Scaling to horizontally scale the capacity up or down based on demand
    • Lambda based architectures to never pay for idle or redundant resources
    • Utilize managed services where scaling is handled by AWS for e.g. ELB, CloudFront, Kinesis, SQS, CloudSearch etc.

Caching

  • Caching improves application performance and increases the cost efficiency of an implementation
    • Application Data Caching
      • provides services thats helps store and retrieve information from fast, managed, in-memory caches
      • ElastiCache is a web service that makes it easy to deploy, operate, and scale an in-memory cache in the cloud and supports two open-source in-memory caching engines: Memcached and Redis
    • Edge Caching
      • allows content to be served by infrastructure that is closer to viewers, lowering latency and giving high, sustained data transfer rates needed to deliver large popular objects to end users at scale.
      • CloudFront is Content Delivery Network (CDN) consisting of multiple edge locations, that allows copies of static and dynamic content to be cached

Security

  • AWS works on shared security responsibility model
    • AWS is responsible for the security of the underlying cloud infrastructure
    • you are responsible for securing the workloads you deploy in AWS
  • AWS also provides ample security features
    • IAM to define a granular set of policies and assign them to users, groups, and AWS resources
    • IAM roles to assign short term credentials to resources, which are automatically distributed and rotated
    • Amazon Cognito, for mobile applications, which allows client devices to get controlled access to AWS resources via temporary tokens.
    • VPC to isolate parts of infrastructure through the use of subnets, security groups, and routing controls
    • WAF to help protect web applications from SQL injection and other vulnerabilities in the application code
    • CloudWatch logs to collect logs centrally as the servers are temporary
    • CloudTrail for auditing AWS API calls, which delivers a log file to S3 bucket. Logs can then be stored in an immutable manner and automatically processed to either notify or even take action on your behalf, protecting your organization from non-compliance
    • AWS Config, Amazon Inspector, and AWS Trusted Advisor to continually monitor for compliance or vulnerabilities giving a clear overview of which IT resources are in compliance, and which are not
  • For more details refer to AWS Security Whitepaper

References

Architecting for the Cloud: AWS Best Practices – Whitepaper

 

AWS Pricing – Whitepaper – Certification

AWS Pricing Whitepaper Overview

AWS pricing features include

  • Pay as you go
    • No minimum contracts/commitments or long-term contracts required
    • Pay only for services you use that can be stopped when not needed
    • Each service is charged independently, providing flexibility to choose services as needed
  • Pay less when you reserve
    • some services like EC2 provide reserved capacity, which provide significantly discounted rate and increase in overall savings
  • Pay even less by using more
    • some services like storage and data services, the more the usage the less you pay per gigabyte
    • consolidated billing to consolidate multiple accounts and get tiering benefits
  • Pay even less as AWS grows
    • AWS works continuously to reduce costs by reducing data center hardware costs, improving operational efficiencies, lowering power consumption, and generally lowering the cost of doing business
  • Free services
    • AWS offers lot of services free like AWS VPC, Elastic Beanstalk, CloudFormation, IAM, Auto Scaling, OpsWorks, Consolidated Billing
  • Other features
    • AWS Free Tier for new customers, which offer free usage of services within permissible limits

AWS Pricing Resources

  • AWS Simple Monthly Calculator tool to effectively estimate the costs, which provides per service cost breakdown, as well as an aggregate monthly estimate.
  • AWS Economic Center provides access to information, tools, and resources to compare the costs of AWS services with IT infrastructure alternatives.
  • AWS Account Activity to view current charges and account activity, itemized by service and by usage type. Previous months’ billing statements are also available.
  • AWS Usage Reports provides usage reports, specifying usage types, timeframe, service operations, and more can customize reports.

AWS Pricing Fundamental Characteristics

  • AWS basically charges for
    • Compute,
    • Storage and
    • Data Transfer Out – aggregated across EC2, S3, RDS, SimpleDB, SQS, SNS, and VPC and then charged at the outbound data transfer rate
  • AWS does not charge
    • Inbound data transfer across all AWS Services in all regions
    • Outbound data transfer charges between AWS Services within the same region

AWS Elastic Cloud Compute – EC2

EC2 provides resizable compute capacity in cloud and the cost depends on –

  • Clock Hours of Server Time
    • Resources are charged for the time they are running
    • AWS updated the EC2 billing from hourly basis to Per Second Billing (Circa Oct. 2017). It takes cost of unused minutes and seconds in an hour off of the bill, so the focus is on improving the applications instead of maximizing usage to the hour
  • Machine Configuration
    • Depends on the physical capacity and Instance pricing varies with the AWS region, OS, number of cores, and memory
  • Machine Purchase Type
    • On Demand instances – pay for compute capacity with no required minimum commitments
    • Reserved Instances – option to make a low one-time payment – or no payment at all – for each reserved instance and in turn receive a significant discount on the usage
    • Spot Instances – bid for unused EC2 capacity
  • Auto Scaling & Number of Instances
    • Auto Scaling automatically adjusts the number of EC2 instances
  • Load Balancing
    • ELB can be used to distribute traffic among EC2 instances.
    • Number of hours the ELB runs and the amount of data it processes contribute to the monthly cost.
  • CloudWatch Detailed Monitoring
    • Basic monitoring is enabled and available at no additional cost
    • Detailed monitoring, which includes seven preselected metrics recorded once a minute, can be availed for a fixed monthly rate
    • Partial months are charged on an hourly pro rata basis, at a per instance-hour rate
  • Elastic IP Addresses
    • Elastic IP addresses are charged only when are not associated with an instance
  • Operating Systems and Software Packages
    • OS prices are included in the instance prices. There are no additional licensing costs to run the following commercial OS: RHEL, SUSE Enterprise Linux,  Windows Server and Oracle Enterprise Linux
    • For unsupported commercial software packages, license needs to be obtained

AWS Lambda

AWS Lambda lets running code without provisioning or managing servers and the cost depends on

  • Number of requests for the functions and the time for the code to execute
    • Lambda registers a request each time it starts executing in response to an event notification or invoke call, including test invokes from the console.
    • Charges are for the total number of requests across all the functions.
    • Duration is calculated from the time the code begins executing until it returns or otherwise terminates, rounded up to the nearest 100 milliseconds.
    • Price depends on the amount of memory allocated to the function.

AWS Simple Storage Service – S3

S3 provides object storage and the cost depends on

  • Storage Class
    • Each storage class has different rates and provide different capabilities
    • Standard Storage is designed to provide 99.999999999% durability and 99.99% availability.
    • Standard – Infrequent Access (SIA) is a storage option within S3 that you can use to reduce your costs by storing  than Amazon S3’s standard storage.
    • Standard – Infrequent Access for storing less frequently accessed data at slightly lower levels of redundancy, is designed to provide the same 99.999999999% durability as S3 with 99.9% availability in a given year.
  • Storage
    • Number and size of objects stored in the S3 buckets as well as type of storage.
  • Requests
    • Number and type of requests. GET requests incur charges at different rates than other requests, such as PUT and COPY requests.
  • Data Transfer Out
    • Amount of data transferred out of the S3 region.

AWS Elastic Block Store – EBS

EBS provides block level storage volumes and the cost depends on

  • Volumes
    • EBS provides three volume types: General Purpose (SSD), Provisioned IOPS (SSD), and Magnetic, charged by the amount provisioned in GB per month, until its released
  • Input Output Operations per Second (IOPS)
    • With General Purpose (SSD) volumes, I/O is included in the price
    • With EBS Magnetic volumes, I/O is charged by the number of requests made to the volume
    • With Provisioned IOPS (SSD) volumes, I/O is charged by the amount of provisioned, multiplied by the % of days provisioned for the month
  • Data Transfer Out
    • Amount of data transferred out of the application and outbound data transfer charges are tiered.
  • Snapshot
    • Snapshots of data to S3 are created for durable recovery. If opted for EBS snapshots, the added cost is per GB-month of data stored.

AWS Relational Database Service – RDS

RDS provides an easy to set up, operate, and scale a relational database in the cloud and the cost depends on

  • Clock Hours of Server Time
    • Resources are charged for the time they are running, from the time a DB instance is launched until terminated
  • Database Characteristics
    • Depends on the physical capacity and Instance pricing varies with the database engine, size, and memory class.
  • Database Purchase Type
    • On Demand instances – pay for compute capacity for each hour the DB Instance runs with no required minimum commitments
    • Reserved Instances – option to make a low, one-time, up-front payment for each DB Instance to reserve for a 1-year or 3-year term and in turn receive a significant discount on the usage
  • Number of Database Instances
    • multiple DB instances can be provisioned to handle peak loads
  • Provisioned Storage
    • Backup storage of up to 100% of a provisioned database storage for an active DB Instance is not charged
    • After the DB Instance is terminated, backup storage is billed per gigabyte per month.
  • Additional Storage
    • Amount of backup storage in addition to the provisioned storage amount is billed per gigabyte per month.
  • Requests
    • Number of input and output requests to the database.
  • Deployment Type
    • Storage and I/O charges vary, depending on the number of AZs the RDS is deployed – Single AZ or Multi-AZ
  • Data Transfer Out
    • Outbound data transfer costs are tiered.
    • Inbound data transfer is free

AWS CloudFront

CloudFront is a web service for content delivery and an easy way to distribute content to end users with low latency, high data transfer speeds, and no required minimum commitments.

  • Traffic Distribution
    • Data transfer and request pricing vary across geographic regions, and pricing is based on edge location through which the content is served
  • Requests
    • Number and type of requests (HTTP or HTTPS) made and the geographic region in which the requests are made.
  • Data Transfer Out
    • Amount of data transferred out of the CloudFront edge locations

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. How does AWS charge for AWS Lambda?
    1. Users bid on the maximum price they are willing to pay per hour.
    2. Users choose a 1-, 3- or 5-year upfront payment term.
    3. Users pay for the required permanent storage on a file system or in a database.
    4. Users pay based on the number of requests and consumed compute resources.

References

AWS Pricing Whitepaper – 2016

 

 

AWS EC2 Container Service ECS – Certification

AWS EC2 Container Service ECS

  • AWS EC2 Container Service (ECS) is a highly scalable, high performance container management service that supports Docker containers and allows running applications on a managed cluster of EC2 instances
  • ECS eliminates the need to install, operate, and scale the cluster management infrastructure.
  • ECS is a regional service that simplifies running application containers in a highly available manner across multiple AZs within a region
  • ECS helps schedule the placement of containers across the cluster based on the resource needs and availability requirements.
  • ECS allows integration of your own custom scheduler or third-party schedulers to meet business or application specific requirements.

ECS Elements

ECS with EC2 launch type

ECS Overview Standard

ECS with AWS Fargate

ECS Overview

Containers and Images

  • Applications deployed on ECS must be architected to run in docker containers, which is a standardized unit of software development, containing everything that the software application needs to run: code, runtime, system tools, system libraries, etc.
  • Containers are created from a read-only template called an image.
  • Images are typically built from a Dockerfile, and stored in a registry from which they can be downloaded and run on your container instances.
  • ECS can be configured to access a private Docker image registry within a VPC, Docker Hub or is integrated with EC2 Container Registry (ECR)

Clusters

  • Cluster is a logical grouping of EC2 container instances to run tasks using ECS
  • ECS downloads the container images from the specified registry, and runs those images on the container instances within your cluster.

Task Definitions

  • Task definition is a description of an application that contains one or more docker containers
  • Task definition is needed to prepare application to run on ECS
  • Task definition is a text file in JSON format that describes one or more containers that form your application.
  • Task definitions specify various parameters for the application, such as containers to use, their repositories, ports to be opened, and data volumes

Tasks and Scheduling

  • A task is the instantiation of a task definition on a container instance within the cluster.
  • After a task definition is created for the application within ECS, you can specify the number of tasks that will run on the cluster.
  • ECS task scheduler is responsible for placing tasks on container instances, with several different scheduling options available

ECS Service

  • ECS Service helps to run and maintain a specified number of instances of a task definition simultaneously.

Container Agent

  • Container agent runs on each instance within an ECS cluster
  • Container Agent sends information about the instance’s current running tasks and resource utilization to ECS, and starts and stops tasks whenever it receives a request from ECS

ECS vs Elastic Beanstalk

  • ECS helps in having a more fine-grained control for custom application architectures.
  • Elastic Beanstalk is ideal to leverage the benefits of containers but just want the simplicity of deploying applications from development to production by uploading a container image.
  • Elastic Beanstalk is more of an application management platform that helps customers easily deploy and scale web applications and services.
  • With Elastic Beanstalk, specify container images to be deployed, with the CPU & memory requirements, port mappings and container links.
  • Elastic Beanstalk abstracts the finer details and automatically handles all the details such as provisioning an ECS cluster, balancing load, auto-scaling, monitoring, and placing the containers across the cluster.

ECS vs Lambda

  • EC2 Container Service is a highly scalable Docker container management service that allows running and managing distributed applications in Docker containers.
  • AWS Lambda is an event-driven task compute service that runs code (Lambda functions) in response to “events” from event sources like SES, SNS, DynamoDB & Kinesis Streams, CloudWatch etc.

Labs

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. You need a solution to distribute traffic evenly across all of the containers for a task running on Amazon ECS. Your task definitions define dynamic host port mapping for your containers. What AWS feature provides this functionally?
    1. Application Load Balancers support dynamic host port mapping.
    2. CloudFront custom origins support dynamic host port mapping.
    3. All Elastic Load Balancing instances support dynamic host port mapping.
    4. Classic Load Balancers support dynamic host port mapping.
  2. Your security team requires each Amazon ECS task to have an IAM policy that limits the task’s privileges to only those required for its use of AWS services. How can you achieve this?
    1. Use IAM roles for Amazon ECS tasks to associate a specific IAM role with each ECS task definition
    2. Use IAM roles on the Amazon ECS container instances to associate IAM role with each ECS task on that instance
    3. Connect to each running amazon ECS container instance and add discrete credentials
    4. Reboot each Amazon ECS task programmatically to generate new instance metadata for each task

References