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Cloud Month in Review – May 2016

This May we’ve seen a ton of action with AWS software updates and we’re eager to see how this impacts users.

Updates to IAAS6172048-Macro-of-printed-circuit-board-computer-motherboard-Stock-Photo

AWS is proud to announce that its fully-managed data warehouse service, Amazon Redshift, has gotten an upgrade: you can now do petabytes-scale data analysis at 2X the speed and 10X the current vacuuming performance.

To cater to clients who need greater compute power, the Amazon EC2 introduced the X1. With its 4 x Intel™ Xeon E7 8880 v3 running at 2.3 GHz and 1,952 GiB of memory, the X1 is great for workloads that need a large amount of memory, such as big data analytics.

In terms of storage, Amazon Elastic Block Storage has similarly improved their hardware by introducing new HDD options:

  • Throughput Optimized HDD (st1)– has burst performance, starting at 250 Mbps for a 1 Tb volume, with an additional 250 Mbps for every additional Terabyte for a max burst throughput of 500Mbps.useful for workloads that require high throughput, like MapReduce, Kafka, and data warehouse.
  • Cold HDD (st1) – Burst values start at 80 Mbps per Tb volume with additional 80 Mbps for every additional Terabyte provisioned, for a max 250 Mbps burst throughput. Useful for the same workloads as the Throughput Optimized HDD, but are used less frequently.

Still on EBS and Storage Gateway, AWS has allowed for longer resource IDs. You can test the new format through AWS Management Console, the AWS Command Line Interface (CLI), the AWS Tools for Windows PowerShell.

Finally, AWS has also vastly improved their S3 Transfer speed and Snowball services. As of last month, you may now transfer up to 80Tb per Snowball appliance. You may also transfer data to S3 and be routed through the locations with the best latency.

Updates to SAAS

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By far, AWS has made improvements to its software services.

Improving Collaboration

The cloud is all about collaboration. And to improve collaboration between services, AWS has introduced additional features to its databases. AWS Aurora now supports cross-account snapshot sharing, while AWS ElastiCache allows exports of Redis snapshots to S3.

To aid with organization, AWS WorkSpaces now supports tagging. Tags let you manage and monitor your WorkSpaces so you can identify what they are for and how much they cost you.

EC2 Run Command is now even more useful with the addition of a sharing functionality. If you have any command documents which you execute using EC2 Run Command, you can now manage and share them. You also now have more predefined commands and a new agent for Linux users.

Database Improvements

The AWS Schema Conversion Tool has raised the bar by supporting SSL connections. This includes both source and target engines, PostgreSQL, Oracle, SQL Server, and any MySQL, including AWS’s own next generation Aurora database.

Elastic MapReduce has also improved with the update to Apache HBase 1.2. HBase is a big data store that can house billions of columns and rows. The update provides benefits in terms of scalability, S3 Backup, Coprocessors, accurate read-write functionality, and finally, graphs and timeseries.

Amazon RDS now supports version 9.5 of PostgreSQL, as well as versions 9.4.7 and 9.3.12. It also supports conversion from one MySQL-compatible engine (such as Amazon Aurora) to another.  Enhanced monitoring is also now available for RDS.

More Software Updates

AWS Elastic Transcoder, a service that allows you to transform media into different formats, now supports MPEG-DASH. This is highly useful for streaming as MPEG-DASH supports different bandwidths and is best for streaming from websites.

Amazon Kinesis also provided its own updates: AWS ElasticSearch support, which lets you run the search engine in the AWS cloud; shard-level metrics such as incoming and outgoing bytes and records, read/write throughput exceeded, and the age of the last record returned by a call on a shard, and; time-based iterators on a shard of your choice and using your preferred starting point.

AWS IoT (Internet of Things) has been updated to interface with Amazon Machine Learning, so you can use machine learning models without having to learn complex coding. It also interfaces with AWS CloudTrail, so you can track each action of your APIs.

AWS has also launched the brand new AWS Discovery Service to help you study your environment and provide you with the data and visibility you need to migrate to the AWS cloud. This service installs an agent in your machines to gather information about its installed hardware and software, and transmit the data to the AWS Discovery Service.

Speaking of agents, the pre-existing AWS Kinesis Agent also helps by doing data pre-processing for you.  This application is capable of monitoring fields for new data, then transmitting them to either Amazon Kinesis Streams or Amazon Firehose.

Finally, good news for Citrix users interested in migrating to the cloud. AWS has set up a Citrix accelerator program to simulate cloud adoption for those running XenApp, XenDesktop, or Netscale onsite. Contact AWS partners now to learn

PAAS

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Lastly, AWS has also provided some improvements to its platforms.

AWS announced that Elastic Beanstalk will now have managed platform updates. This feature gives you more control on when to apply an update by letting you set a maintenance time when you can upgrade to the latest version.

In terms of software quality assurance, AWS Device Farm now also supports remote access interactive testing. Through a secure connection, you may now test your mobile devices as if they were right in front of you.

Finally, AWS has added changesets to its Amazon CloudFormation service. CloudFormation lets you manage and update your AWS resources in the form of “stacks,” which you can update as needed to control your AWS infrastructure. The changesets functionality let you submit changes against the stack you wish to update. CloudFormation then generates a change set based on the comparison between the stack and the new template and/or parameter values. You can review this change set and choose to execute it

Success story

GE Oil & Gas is a relatively new division of General Electric that provides for roughly 85% of offshore oil rigs in the world. Their objectives in going into the cloud were to improve productivity for their manufacturing and shop floors, reduce downtime, speed up their processes, and reduce costs.

And they accomplished all of these things with startling success. For a $14M investment and 18 months of work, the company created 311 cloud apps and $14M YOY savings. AWS has proven to be valuable business partner and profitable investment:

  • 35% reduction in compute assets
  • 50 decommissioned applications
  • $14M Year-on-year savings
  • In terms of cost avoidance, they reported 52% TCO savings
  • 77% faster time to delivery of applications
  • Rapid experimentation
  • Reduced technical debt
  • Streamlined M&A Activity
  • Overall increased productivity and business resilience

Join us later this month’s Review to see what else is in store for the rapidly improving AWS cloud.

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