S3

AWS Cloud Migration Services

~ Last updated on : ~ jayendrapatil ~ 6 Comments

AWS Cloud Migration Services

  • AWS Cloud Migration services help to address a lot of common use cases such as
    • cloud migration,
    • disaster recovery,
    • data center decommission, and
    • content distribution.
  • For migrating data from on-premises to AWS, the major aspect for consideration are
    • amount of data and network speed
    • data security in transit
    • existing application knowledge for recreation

Application & Database Cloud Migration Services

AWS Migration Hub

  • provides a centralized, single place to discover the existing servers, plan migrations, and track the status of each application migration.
  • provides visibility into the application portfolio and streamlines planning and tracking.
  • helps visualize the connections and the status of the migrating servers and databases, regardless of which migration tool is used.
  • stores all the data in the selected Home Region and provides a single repository of discovery and migration planning information for the entire portfolio and a single view of migrations into multiple AWS Regions.
  • helps track the status of the migrations in all AWS Regions, provided the migration tools are available in that Region.
  • helps understand the environment by letting you explore information collected by AWS discovery tools and stored in the AWS Application Discovery Service’s repository.
  • supports migration status updates from the following tools:
  • migration tools send migration status to the selected Home Region
  • supports EC2 instance recommendations, that provide you with the ability to estimate the cost of running the existing servers in AWS.
  • supports Strategy Recommendations, that help easily build a migration and modernization strategy for the applications running on-premises or in AWS.

AWS Application Discovery Service

  • AWS Application Discovery Service helps plan migration to the AWS cloud by collecting usage and configuration data about the on-premises servers.
  • helps enterprises obtain a snapshot of the current state of their data center servers by collecting server specification information, hardware configuration, performance data, details of running processes, and network connections
  • is integrated with AWS Migration Hub,
    • which simplifies migration tracking as it aggregates migration status information into a single console.
    • can help view the discovered servers, group them into applications, and then track the migration status of each application.
  • discovered data for all the regions is stored in the AWS Migration Hub home Region.
  • The data can be exported for analysis in Microsoft Excel or AWS analysis tools such as Amazon Athena and Amazon QuickSight.
  • supports both agent and agentless-based on-premises tooling, in addition to file-based import for performing discovery and collecting data about the on-premises servers.

AWS Server Migration Service (SMS)

  • is an agentless service that makes it easier and faster to migrate thousands of on-premises workloads to AWS.
  • helps automate, schedule, and track incremental replications of live server volumes, making it easier to coordinate large-scale server migrations.
  • currently supports migration of virtual machines from VMware vSphere,  Windows Hyper-V and Azure VM to AWS
  • supports migrating Windows Server 2003, 2008, 2012, and 2016, and Windows 7, 8, and 10; Red Hat Enterprise Linux (RHEL), SUSE/SLES, CentOS, Ubuntu, Oracle Linux, Fedora, and Debian Linux OS
  • replicates each server volume, which is saved as a new AMI, which can be launched as an EC2 instance
  • is a significant enhancement of EC2 VM Import/Export service
  • is used to Re-host

AWS Database Migration Service (DMS)

  • helps migrate databases to AWS quickly and securely.
  • source database remains fully operational during the migration, minimizing downtime to applications that rely on the database.
  • supports homogeneous migrations such as Oracle to Oracle, as well as heterogeneous migrations between different database platforms, such as Oracle or Microsoft SQL Server to Amazon Aurora.
  • monitors for replication tasks, network or host failures, and automatically provisions a host replacement in case of failures that can’t be repaired
  • supports both one-time data migration into RDS and EC2-based databases as well as for continuous data replication
  • supports continuous replication of the data with high availability and consolidate databases into a petabyte-scale data warehouse by streaming data to Amazon Redshift and Amazon S3
  • provides free AWS Schema Conversion Tool (SCT) that automates the conversion of Oracle PL/SQL and SQL Server T-SQL code to equivalent code in the Amazon Aurora / MySQL dialect of SQL or the equivalent PL/pgSQL code in PostgreSQL

AWS EC2 VM Import/Export

  • allows easy import of virtual machine images from existing environment to EC2 instances and export them back to on-premises environment
  • allows leveraging of existing investments in the virtual machines, built to meet compliance requirements, configuration management and IT security by bringing those virtual machines into EC2 as ready-to-use instances
  • Common usages include
    • Migrate Existing Applications and Workloads to EC2, allowing preserving of the software and settings configured in the existing VMs.
    • Copy Your VM Image Catalog to EC2
    • Create a Disaster Recovery Repository for your VM images

Data Transfer Services

VPN

  • connection utilizes IPSec to establish encrypted network connectivity between on-premises network and VPC over the Internet.
  • connections can be configured in minutes and a good solution for an immediate need, have low to modest bandwidth requirements, and can tolerate the inherent variability in Internet-based connectivity.
  • still requires internet and be configured using VGW and CGW

AWS Direct Connect

  • provides a dedicated physical connection between the corporate network and AWS Direct Connect location with no data transfer over the Internet.
  • helps bypass Internet service providers (ISPs) in the network path
  • helps reduce network costs, increase bandwidth throughput, and provide a more consistent network experience than with Internet-based connection
  • takes time to setup and involves third parties
  • are not redundant and would need another direct connect connection or a VPN connection
  •  Security
    • provides a dedicated physical connection without internet
    • For additional security can be used with VPN

AWS Import/Export (upgraded to Snowball)

  • accelerates moving large amounts of data into and out of AWS using secure Snowball appliances
  • AWS transfers the data directly onto and off of the storage devices using Amazon’s high-speed internal network, bypassing the Internet
  • Data Migration
    • for significant data size, AWS Import/Export is faster than Internet transfer is and more cost-effective than upgrading the connectivity
    • if loading the data over the Internet would take a week or more, AWS Import/Export should be considered
    • data from appliances can be imported to S3, Glacier and EBS volumes and exported from S3
    • not suitable for applications that cannot tolerate offline transfer time
  •  Security
    • Snowball uses an industry-standard Trusted Platform Module (TPM) that has a dedicated processor designed to detect any unauthorized modifications to the hardware, firmware, or software to physically secure the AWS Snowball device.

Snow Family

  • AWS Snowball
    • is a petabyte-scale data transfer service built around a secure suitcase-sized device that moves data into and out of the AWS Cloud quickly and efficiently.
    • transfers the data to S3 bucket
    • transfer times are about a week from start to finish.
    • are commonly used to ship terabytes or petabytes of analytics data, healthcare and life sciences data, video libraries, image repositories, backups, and archives as part of data center shutdown, tape replacement, or application migration projects.
  • AWS Snowball Edge devices
    • contain slightly larger capacity and an embedded computing platform that helps perform simple processing tasks.
    • can be rack shelved and may also be clustered together, making it simpler to collect and store data in extremely remote locations.
    • commonly used in environments with intermittent connectivity (such as manufacturing, industrial, and transportation); or in extremely remote locations (such as military or maritime operations) before shipping them back to AWS data centers.
    • delivers serverless computing applications at the network edge using AWS Greengrass and Lambda functions.
    • common use cases include capturing IoT sensor streams, on-the-fly media transcoding, image compression, metrics aggregation and industrial control signaling and alarming.
  • AWS Snowmobile
    • moves up to 100PB of data (equivalent to 1,250 AWS Snowball devices) in a 45-foot long ruggedized shipping container and is ideal for multi-petabyte or Exabyte-scale digital media migrations and datacenter shutdowns.
    • arrives at the customer site and appears as a network-attached data store for more secure, high-speed data transfer. After data is transferred to Snowmobile, it is driven back to an AWS Region where the data is loaded into S3.
    • is tamper-resistant, waterproof, and temperature controlled with multiple layers of logical and physical security — including encryption, fire suppression, dedicated security personnel, GPS tracking, alarm monitoring, 24/7 video surveillance, and an escort security vehicle during transit.

AWS Storage Gateway

  • connects an on-premises software appliance with cloud-based storage to provide seamless and secure integration between an organization’s on-premises IT environment and the AWS storage infrastructure
  • provides low-latency performance by maintaining frequently accessed data on-premises while securely storing all of the data encrypted in S3 or Glacier.
  • for disaster recovery scenarios, Storage Gateway, together with EC2, can serve as a cloud-hosted solution that mirrors the entire production environment
  • Data Migration
    • with gateway-cached volumes, S3 can be used to hold primary data while frequently accessed data is cached locally for faster access reducing the need to scale on premises storage infrastructure
    • with gateway-stored volumes, entire data is stored locally while asynchronously backing up data to S3
    • with gateway-VTL, offline data archiving can be performed by presenting existing backup application with an iSCSI-based VTL consisting of a virtual media changer and virtual tape drives
  •  Security
    • Encrypts all data in transit to and from AWS by using SSL/TLS.
    • All data in AWS Storage Gateway is encrypted at rest using AES-256.
    • Authentication between the gateway and iSCSI initiators can be secured by using Challenge-Handshake Authentication Protocol (CHAP).

Simple Storage Service – S3

  • Data Transfer
    • Files up to 5GB can be transferred using single operation
    • Multipart uploads can be used to upload files up to 5 TB and speed up data uploads by dividing the file into multiple parts
    • transfer rate still limited by the network speed
  •  Security
    • Data in transit can be secured by using SSL/TLS or client-side encryption.
    • Encrypt data at-rest by performing server-side encryption using Amazon S3-Managed Keys (SSE-S3), AWS Key Management Service (KMS)-Managed Keys (SSE-KMS), or Customer Provided Keys (SSE-C). Or by performing client-side encryption using AWS KMS–Managed Customer Master Key (CMK) or Client-Side Master Key.

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.
  • 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 must architect the migration of a web application to AWS. The application consists of Linux web servers running a custom web server. You are required to save the logs generated from the application to a durable location. What options could you select to migrate the application to AWS? (Choose 2)
    1. Create an AWS Elastic Beanstalk application using the custom web server platform. Specify the web server executable and the application project and source files. Enable log file rotation to Amazon Simple Storage Service (S3). (EB does not work with Custom server executable)
    2. Create Dockerfile for the application. Create an AWS OpsWorks stack consisting of a custom layer. Create custom recipes to install Docker and to deploy your Docker container using the Dockerfile. Create custom recipes to install and configure the application to publish the logs to Amazon CloudWatch Logs (although this is one of the option, the last sentence mentions configure the application to push the logs to S3, which would need changes to application as it needs to use SDK or CLI)
    3. Create Dockerfile for the application. Create an AWS OpsWorks stack consisting of a Docker layer that uses the Dockerfile. Create custom recipes to install and configure Amazon Kinesis to publish the logs into Amazon CloudWatch. (Kinesis not needed)
    4. Create a Dockerfile for the application. Create an AWS Elastic Beanstalk application using the Docker platform and the Dockerfile. Enable logging the Docker configuration to automatically publish the application logs. Enable log file rotation to Amazon S3. (Use Docker configuration with awslogs and EB with Docker)
    5. Use VM import/Export to import a virtual machine image of the server into AWS as an AMI. Create an Amazon Elastic Compute Cloud (EC2) instance from AMI, and install and configure the Amazon CloudWatch Logs agent. Create a new AMI from the instance. Create an AWS Elastic Beanstalk application using the AMI platform and the new AMI. (Use VM Import/Export to create AMI and CloudWatch logs agent to log)
  2. Your company hosts an on-premises legacy engineering application with 900GB of data shared via a central file server. The engineering data consists of thousands of individual files ranging in size from megabytes to multiple gigabytes. Engineers typically modify 5-10 percent of the files a day. Your CTO would like to migrate this application to AWS, but only if the application can be migrated over the weekend to minimize user downtime. You calculate that it will take a minimum of 48 hours to transfer 900GB of data using your company’s existing 45-Mbps Internet connection. After replicating the application’s environment in AWS, which option will allow you to move the application’s data to AWS without losing any data and within the given timeframe?
    1. Copy the data to Amazon S3 using multiple threads and multi-part upload for large files over the weekend, and work in parallel with your developers to reconfigure the replicated application environment to leverage Amazon S3 to serve the engineering files. (Still limited by 45 Mbps speed with minimum 48 hours when utilized to max)
    2. Sync the application data to Amazon S3 starting a week before the migration, on Friday morning perform a final sync, and copy the entire data set to your AWS file server after the sync completes. (Works best as the data changes can be propagated over the week and are fractional and downtime would be know)
    3. Copy the application data to a 1-TB USB drive on Friday and immediately send overnight, with Saturday delivery, the USB drive to AWS Import/Export to be imported as an EBS volume, mount the resulting EBS volume to your AWS file server on Sunday. (Downtime is not known when the data upload would be done, although Amazon says the same day the package is received)
    4. Leverage the AWS Storage Gateway to create a Gateway-Stored volume. On Friday copy the application data to the Storage Gateway volume. After the data has been copied, perform a snapshot of the volume and restore the volume as an EBS volume to be attached to your AWS file server on Sunday. (Still uses the internet)
  3. You are tasked with moving a legacy application from a virtual machine running inside your datacenter to an Amazon VPC. Unfortunately this app requires access to a number of on-premises services and no one who configured the app still works for your company. Even worse there’s no documentation for it. What will allow the application running inside the VPC to reach back and access its internal dependencies without being reconfigured? (Choose 3 answers)
    1. An AWS Direct Connect link between the VPC and the network housing the internal services
    2. An Internet Gateway to allow a VPN connection. (Virtual and Customer gateway is needed)
    3. An Elastic IP address on the VPC instance
    4. An IP address space that does not conflict with the one on-premises
    5. Entries in Amazon Route 53 that allow the Instance to resolve its dependencies’ IP addresses
    6. A VM Import of the current virtual machine
  4. An enterprise runs 103 line-of-business applications on virtual machines in an on-premises data center. Many of the applications are simple PHP, Java, or Ruby web applications, are no longer actively developed, and serve little traffic. Which approach should be used to migrate these applications to AWS with the LOWEST infrastructure costs?
    1. Deploy the applications to single-instance AWS Elastic Beanstalk environments without a load balancer.
    2. Use AWS SMS to create AMIs for each virtual machine and run them in Amazon EC2.
    3. Convert each application to a Docker image and deploy to a small Amazon ECS cluster behind an Application Load Balancer.
    4. Use VM Import/Export to create AMIs for each virtual machine and run them in single-instance AWS Elastic Beanstalk environments by configuring a custom image.

References

AWS Storage Options – S3 & Glacier

~ Last updated on : ~ jayendrapatil ~ 30 Comments

Amazon S3

  • highly-scalable, reliable, and low-latency data storage infrastructure at very low costs.
  • provides a simple web services interface that can be used to store and retrieve any amount of data, at any time, from within Amazon EC2 or from anywhere on the web.
  • allows you to write, read, and delete objects containing from 1 byte to 5 terabytes of data each.
  • number of objects you can store in an Amazon S3 bucket is virtually unlimited.
  • highly secure, supporting encryption at rest, and providing multiple mechanisms to provide fine-grained control of access to Amazon S3 resources.
  • highly scalable, allowing concurrent read or write access to Amazon S3 data by many separate clients or application threads.
  • provides data lifecycle management capabilities, allowing users to define rules to automatically archive Amazon S3 data to Amazon Glacier, or to delete data at end of life.

Ideal Use Cases

  • Storage & Distribution of static web content and media
    • frequently used to host static websites and provides a highly-available and highly-scalable solution for websites with only static content, including HTML files, images, videos, and client-side scripts such as JavaScript
    • works well for fast growing websites hosting data intensive, user-generated content, such as video and photo sharing sites as no storage provisioning is required
    • content can either be directly served from Amazon S3 since each object in Amazon S3 has a unique HTTP URL address
    • can also act as an Origin store for the Content Delivery Network (CDN) such as Amazon CloudFront
    • it works particularly well for hosting web content with extremely spiky bandwidth demands because of S3’s elasticity
  • Data Store for Large Objects
    • can be paired with RDS or NoSQL database and used to store large objects for e.g. file or objects, while the associated metadata for e.g. name, tags, comments etc. can be stored in RDS or NoSQL database where it can be indexed and queried providing faster access to relevant data
  • Data store for computation and large-scale analytics
    • commonly used as a data store for computation and large-scale analytics, such as analyzing financial transactions, clickstream analytics, and media transcoding.
    • data can be accessed from multiple computing nodes concurrently without being constrained by a single connection because of its horizontal scalability
  • Backup and Archival of critical data
    • used as a highly durable, scalable, and secure solution for backup and archival of critical data, and to provide disaster recovery solutions for business continuity.
    • stores objects redundantly on multiple devices across multiple facilities, it provides the highly-durable storage infrastructure needed for these scenarios.
    • it’s versioning capability is available to protect critical data from inadvertent deletion

Anti-Patterns

Amazon S3 has following Anti-Patterns where it is not an optimal solution

  • Dynamic website hosting
    • While Amazon S3 is ideal for hosting static websites, dynamic websites requiring server side interaction, scripting or database interaction cannot be hosted and should rather be hosted on Amazon EC2
  • Backup and archival storage
    • Data requiring long term archival storage with infrequent read access can be stored more cost effectively in Amazon Glacier
  • Structured Data Query
    • Amazon S3 doesn’t offer query capabilities, so to read an object the object name and key must be known. Instead pair up S3 with RDS or Dynamo DB to store, index and query metadata about Amazon S3 objects
    • NOTE – S3 now provides query capabilities and also Athena can be used
  • Rapidly Changing Data
    • Data that needs to updated frequently might be better served by a storage solution with lower read/write latencies, such as Amazon EBS volumes, RDS or Dynamo DB.
  • File System
    • Amazon S3 uses a flat namespace and isn’t meant to serve as a standalone, POSIX-compliant file system. However, by using delimiters (commonly either the ‘/’ or ‘’ character) you are able construct your keys to emulate the hierarchical folder structure of file system within a given bucket.

Performance

  • Access to Amazon S3 from within Amazon EC2 in the same region is fast.
  • Amazon S3 is designed so that server-side latencies are insignificant relative to Internet latencies.
  • Amazon S3 is also built to scale storage, requests, and users to support a virtually unlimited number of web-scale applications.
  • If Amazon S3 is accessed using multiple threads, multiple applications, or multiple clients concurrently, total Amazon S3 aggregate throughput will typically scale to rates that far exceed what any single server can generate or consume.

Durability & Availability

  • Amazon S3 storage provides provides the highest level of data durability and availability, by automatically and synchronously storing your data across both multiple devices and multiple facilities within the selected geographical region
  • Error correction is built-in, and there are no single points of failure. Amazon S3 is designed to sustain the concurrent loss of data in two facilities, making it very well-suited to serve as the primary data storage for mission-critical data.
  • Amazon S3 is designed for 99.999999999% (11 nines) durability per object and 99.99% availability over a one-year period.
  • Amazon S3 data can be protected from unintended deletions or overwrites using Versioning.
  • Versioning can be enabled with MFA (Multi Factor Authentication) Delete on the bucket, which would require two forms of authentication to delete an object
  • For Non Critical and Reproducible data for e.g. thumbnails, transcoded media etc., S3 Reduced Redundancy Storage (RRS) can be used, which provides a lower level of durability at a lower storage cost
  • RRS is designed to provide 99.99% durability per object over a given year. While RRS is less durable than standard Amazon S3, it is still designed to provide 400 times more durability than a typical disk drive

Cost Model

  • With Amazon S3, you pay only for what you use and there is no minimum fee.
  • Amazon S3 has three pricing components: storage (per GB per month), data transfer in or out (per GB per month), and requests (per n thousand requests per month).

Scalability & Elasticity

  • Amazon S3 has been designed to offer a very high level of scalability and elasticity automatically
  • Amazon S3 supports a virtually unlimited number of files in any bucket
  • Amazon S3 bucket can store a virtually unlimited number of bytes
  • Amazon S3 allows you to store any number of objects (files) in a single bucket, and Amazon S3 will automatically manage scaling and distributing redundant copies of your information to other servers in other locations in the same region, all using Amazon’s high-performance infrastructure.

Interfaces

  • Amazon S3 provides standards-based REST and SOAP web services APIs for both management and data operations.
  • NOTE – SOAP support over HTTP is deprecated, but it is still available over HTTPS. New Amazon S3 features will not be supported for SOAP. We recommend that you use either the REST API or the AWS SDKs.
  • Amazon S3 provides easier to use higher level toolkit or SDK in different languages (Java, .NET, PHP, and Ruby) that wraps the underlying APIs
  • Amazon S3 Command Line Interface (CLI) provides a set of high-level, Linux-like Amazon S3 file commands for common operations, such as ls, cp, mv, sync, etc. They also provide the ability to perform recursive uploads and downloads using a single folder-level Amazon S3 command, and supports parallel transfers.
  • AWS Management Console provides the ability to easily create and manage Amazon S3 buckets, upload and download objects, and browse the contents of your Amazon S3 buckets using a simple web-based user interface
  • All interfaces provide the ability to store Amazon S3 objects (files) in uniquely-named buckets (top-level folders), with each object identified by an unique Object key within that bucket.

Glacier

  • extremely low-cost storage service that provides highly secure, durable, and flexible storage for data backup and archival
  • can reliably store their data for as little as $0.01 per gigabyte per month.
  • to offload the administrative burdens of operating and scaling storage to AWS such as capacity planning, hardware provisioning, data replication, hardware failure detection and repair, or time consuming hardware migrations
  • Data is stored in Amazon Glacier as Archives where an archive can represent a single file or multiple files combined into a single archive
  • Archives are stored in Vaults for which the access can be controlled through IAM
  • Retrieving archives from Vaults require initiation of a job and can take anywhere around 3-5 hours
  • Amazon Glacier integrates seamlessly with Amazon S3 by using S3 data lifecycle management policies to move data from S3 to Glacier
  • AWS Import/Export can also be used to accelerate moving large amounts of data into Amazon Glacier using portable storage devices for transport

Ideal Usage Patterns

  • Amazon Glacier is ideally suited for long term archival solution for infrequently accessed data with archiving offsite enterprise information, media assets, research and scientific data, digital preservation and magnetic tape replacement

Anti-Patterns

Amazon Glacier has following Anti-Patterns where it is not an optimal solution

  • Rapidly changing data
    • Data that must be updated very frequently might be better served by a storage solution with lower read/write latencies such as Amazon EBS or a Database
  • Real time access
    • Data stored in Glacier can not be accessed at real time and requires an initiation of a job for object retrieval with retrieval times ranging from 3-5 hours. If immediate access is needed, Amazon S3 is a better choice.

Performance

  • Amazon Glacier is a low-cost storage service designed to store data that is infrequently accessed and long lived.
  • Amazon Glacier jobs typically complete in 3 to 5 hours

Durability and Availability

  • Amazon Glacier redundantly stores data in multiple facilities and on multiple devices within each facility
  • Amazon Glacier is designed to provide average annual durability of 99.999999999% (11 nines) for an archive
  • Amazon Glacier synchronously stores your data across multiple facilities before returning SUCCESS on uploading archives.
  • Amazon Glacier also performs regular, systematic data integrity checks and is built to be automatically self-healing.

Cost Model

  • Amazon Glacier has three pricing components: storage (per GB per month), data transfer out (per GB per month), and requests (per thousand UPLOAD and RETRIEVAL requests per month).
  • Amazon Glacier is designed with the expectation that retrievals are infrequent and unusual, and data will be stored for extended periods of time and allows you to retrieve up to 5% of your average monthly storage (pro-rated daily) for free each month. Any additional amount of data retrieved is charged per GB
  • Amazon Glacier also charges a pro-rated charge (per GB) for items deleted prior to 90 days

Scalability & Elasticity

  • A single archive is limited to 40 TBs, but there is no limit to the total amount of data you can store in the service.
  • Amazon Glacier scales to meet your growing and often unpredictable storage requirements whether you’re storing petabytes or gigabytes, Amazon Glacier automatically scales your storage up or down as needed.

Interfaces

  • Amazon Glacier provides a native, standards-based REST web services interface, as well as Java and .NET SDKs.
  • AWS Management Console or the Amazon Glacier APIs can be used to create vaults to organize the archives in Amazon Glacier.
  • Amazon Glacier APIs can be used to upload and retrieve archives, monitor the status of your jobs and also configure your vault to send you a notification via Amazon Simple Notification Service (Amazon SNS) when your jobs complete.
  • Amazon Glacier can be used as a storage class in Amazon S3 by using object lifecycle management to provide automatic, policy-driven archiving from Amazon S3 to Amazon Glacier.
  • Amazon S3 api provides a RESTORE operation and the retrieval process takes the same 3-5 hours
  • On retrieval, a copy of the retrieved object is placed in Amazon S3 RRS storage for a specified retention period; the original archived object remains stored in Amazon Glacier and you are charged for both the storage.
  • When using Amazon Glacier as a storage class in Amazon S3, use the Amazon S3 APIs, and when using “native” Amazon Glacier, you use the Amazon Glacier APIs
  • Objects archived to Amazon Glacier via Amazon S3 can only be listed and retrieved via the Amazon S3 APIs or the AWS Management Console—they are not visible as archives in an Amazon Glacier vault.

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 want to pass queue messages that are 1GB each. How should you achieve this?
    1. Use Kinesis as a buffer stream for message bodies. Store the checkpoint id for the placement in the Kinesis Stream in SQS.
    2. Use the Amazon SQS Extended Client Library for Java and Amazon S3 as a storage mechanism for message bodies. (Amazon SQS messages with Amazon S3 can be useful for storing and retrieving messages with a message size of up to 2 GB. To manage Amazon SQS messages with Amazon S3, use the Amazon SQS Extended Client Library for Java. Refer link)
    3. Use SQS’s support for message partitioning and multi-part uploads on Amazon S3.
    4. Use AWS EFS as a shared pool storage medium. Store filesystem pointers to the files on disk in the SQS message bodies.
  2. Company ABCD has recently launched an online commerce site for bicycles on AWS. They have a “Product” DynamoDB table that stores details for each bicycle, such as, manufacturer, color, price, quantity and size to display in the online store. Due to customer demand, they want to include an image for each bicycle along with the existing details. Which approach below provides the least impact to provisioned throughput on the “Product” table?
    1. Serialize the image and store it in multiple DynamoDB tables
    2. Create an “Images” DynamoDB table to store the Image with a foreign key constraint to the “Product” table
    3. Add an image data type to the “Product” table to store the images in binary format
    4. Store the images in Amazon S3 and add an S3 URL pointer to the “Product” table item for each image

References

AWS S3 Data Durability

~ Last updated on : ~ jayendrapatil
Sample Exam Question :-
A customer is leveraging Amazon Simple Storage Service in eu-west-1 to store static content for web-based property. The customer is storing objects using the Standard Storage class. Where are the customers’ objects replicated?
  1. Single facility in eu-west-1 and a single facility in eu-central-1
  2. Single facility in eu-west-1 and a single facility in us-east-1
  3. Multiple facilities in eu-west-1
  4. A single facility in eu-west-1
Answer :-
The question targets the S3 Data Durability which mentions the objects are stored redundantly across multiple facilities in the same Amazon S3 region.

Amazon S3 provides a highly durable storage infrastructure designed for mission-critical and primary data storage. Objects are redundantly stored on multiple devices across multiple facilities in an Amazon S3 region. To help better ensure data durability, Amazon S3 PUT and PUT Object copy operations synchronously store your data across multiple facilities before returning SUCCESS. Once the objects are stored, Amazon S3 maintains their durability by quickly detecting and repairing any lost redundancy.