Amazon Relational Database Service – Looking Back at 2017

The Amazon RDS team launched nearly 80 features in 2017. Some of them were covered in this blog, others on the AWS Database Blog, and the rest in What’s New or Forum posts. To wrap up my week, I thought it would be worthwhile to give you an organized recap. So here we go!

Certification & Security


Engine Versions & Features

Regional Support

Instance Support

Price Reductions

And That’s a Wrap
I’m pretty sure that’s everything. As you can see, 2017 was quite the year! I can’t wait to see what the team delivers in 2018.



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AWS Hot Startups for February 2018: Canva, Figma, InVision

Note to readers! Starting next month, we will be publishing our monthly Hot Startups blog post on the AWS Startup Blog. Please come check us out.

As visual communication—whether through social media channels like Instagram or white space-heavy product pages—becomes a central part of everyone’s life, accessible design platforms and tools become more and more important in the world of tech. This trend is why we have chosen to spotlight three design-related startups—namely Canva, Figma, and InVision—as our hot startups for the month of February. Please read on to learn more about these design-savvy companies and be sure to check out our full post here.

Canva (Sydney, Australia)

For a long time, creating designs required expensive software, extensive studying, and time spent waiting for feedback from clients or colleagues. With Canva, a graphic design tool that makes creating designs much simpler and accessible, users have the opportunity to design anything and publish anywhere. The platform—which integrates professional design elements, including stock photography, graphic elements, and fonts for users to build designs either entirely from scratch or from thousands of free templates—is available on desktop, iOS, and Android, making it possible to spin up an invitation, poster, or graphic on a smartphone at any time.

To learn more about Canva, read our full interview with CEO Melanie Perkins here.

Figma (San Francisco, CA)

Figma is a cloud-based design platform that empowers designers to communicate and collaborate more effectively. Using recent advancements in WebGL, Figma offers a design tool that doesn’t require users to install any software or special operating systems. It also allows multiple people to work in a file at the same time—a crucial feature.

As the need for new design talent increases, the industry will need plenty of junior designers to keep up with the demand. Figma is prepared to help students by offering their platform for free. Through this, they “hope to give young designers the resources necessary to kick-start their education and eventually, their careers.”

For more about Figma, check out our full interview with CEO Dylan Field here.

InVision (New York, NY)

Founded in 2011 with the goal of helping improve every digital experience in the world, digital product design platform InVision helps users create a streamlined and scalable product design process, build and iterate on prototypes, and collaborate across organizations. The company, which raised a $100 million series E last November, bringing the company’s total funding to $235 million, currently powers the digital product design process at more than 80 percent of the Fortune 100 and brands like Airbnb, HBO, Netflix, and Uber.

Learn more about InVision here.

Be sure to check out our full post on the AWS Startups blog!


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New – Encryption at Rest for DynamoDB

At AWS re:Invent 2017, Werner encouraged his audience to “Dance like nobody is watching, and to encrypt like everyone is:

The AWS team is always eager to add features that make it easier for you to protect your sensitive data and to help you to achieve your compliance objectives. For example, in 2017 we launched encryption at rest for SQS and EFS, additional encryption options for S3, and server-side encryption of Kinesis Data Streams.

Today we are giving you another data protection option with the introduction of encryption at rest for Amazon DynamoDB. You simply enable encryption when you create a new table and DynamoDB takes care of the rest. Your data (tables, local secondary indexes, and global secondary indexes) will be encrypted using AES-256 and a service-default AWS Key Management Service (KMS) key. The encryption adds no storage overhead and is completely transparent; you can insert, query, scan, and delete items as before. The team did not observe any changes in latency after enabling encryption and running several different workloads on an encrypted DynamoDB table.

Creating an Encrypted Table
You can create an encrypted table from the AWS Management Console, API (CreateTable), or CLI (create-table). I’ll use the console! I enter the name and set up the primary key as usual:

Before proceeding, I uncheck Use default settings, scroll down to the Encrypytion section, and check Enable encryption. Then I click Create and my table is created in encrypted form:

I can see the encryption setting for the table at a glance:

When my compliance team asks me to show them how DynamoDB uses the key to encrypt the data, I can create a AWS CloudTrail trail, insert an item, and then scan the table to see the calls to the AWS KMS API. Here’s an extract from the trail:

  "eventTime": "2018-01-24T00:06:34Z",
  "eventSource": "",
  "eventName": "Decrypt",
  "awsRegion": "us-west-2",
  "sourceIPAddress": "",
  "userAgent": "",
  "requestParameters": {
    "encryptionContext": {
      "aws:dynamodb:tableName": "reg-users",
      "aws:dynamodb:subscriberId": "1234567890"
  "responseElements": null,
  "requestID": "7072def1-009a-11e8-9ab9-4504c26bd391",
  "eventID": "3698678a-d04e-48c7-96f2-3d734c5c7903",
  "readOnly": true,
  "resources": [
      "ARN": "arn:aws:kms:us-west-2:1234567890:key/e7bd721d-37f3-4acd-bec5-4d08c765f9f5",
      "accountId": "1234567890",
      "type": "AWS::KMS::Key"

Available Now
This feature is available now in the US East (N. Virginia), US East (Ohio), US West (Oregon), and EU (Ireland) Regions and you can start using it today.

There’s no charge for the encryption; you will be charged for the calls that DynamoDB makes to AWS KMS on your behalf.



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Give Your WordPress Blog a Voice With Our New Amazon Polly Plugin

I first told you about Polly in late 2016 in my post Amazon Polly – Text to Speech in 47 Voices and 24 Languages. After that AWS re:Invent launch, we added support for Korean, five new voices, and made Polly available in all Regions in the aws partition. We also added whispering, speech marks, a timbre effect, and dynamic range compression.

New WordPress Plugin
Today we are launching a WordPress plugin that uses Polly to create high-quality audio versions of your blog posts. You can access the audio from within the post or in podcast form using a feature that we call Amazon Pollycast! Both options make your content more accessible and can help you to reach a wider audience. This plugin was a joint effort between the AWS team our friends at AWS Advanced Technology Partner WP Engine.

As you will see, the plugin is easy to install and configure. You can use it with installations of WordPress that you run on your own infrastructure or on AWS. Either way, you have access to all of Polly’s voices along with a wide variety of configuration options. The generated audio (an MP3 file for each post) can be stored alongside your WordPress content, or in Amazon Simple Storage Service (S3), with optional support for content distribution via Amazon CloudFront.

Installing the Plugin
I did not have an existing WordPress-powered blog, so I begin by launching a Lightsail instance using the WordPress 4.8.1 blueprint:

Then I follow these directions to access my login credentials:

Credentials in hand, I log in to the WordPress Dashboard:

The plugin makes calls to AWS, and needs to have credentials in order to do so. I hop over to the IAM Console and created a new policy. The policy allows the plugin to access a carefully selected set of S3 and Polly functions (find the full policy in the README):

Then I create an IAM user (wp-polly-user). I enter the name and indicate that it will be used for Programmatic Access:

Then I attach the policy that I just created, and click on Review:

I review my settings (not shown) and then click on Create User. Then I copy the two values (Access Key ID and Secret Access Key) into a secure location. Possession of these keys allows the bearer to make calls to AWS so I take care not to leave them lying around.

Now I am ready to install the plugin! I go back to the WordPress Dashboard and click on Add New in the Plugins menu:

Then I click on Upload Plugin and locate the ZIP file that I downloaded from the WordPress Plugins site. After I find it I click on Install Now to proceed:

WordPress uploads and installs the plugin. Now I click on Activate Plugin to move ahead:

With the plugin installed, I click on Settings to set it up:

I enter my keys and click on Save Changes:

The General settings let me control the sample rate, voice, player position, the default setting for new posts, and the autoplay option. I can leave all of the settings as-is to get started:

The Cloud Storage settings let me store audio in S3 and to use CloudFront to distribute the audio:

The Amazon Pollycast settings give me control over the iTunes parameters that are included in the generated RSS feed:

Finally, the Bulk Update button lets me regenerate all of the audio files after I change any of the other settings:

With the plugin installed and configured, I can create a new post. As you can see, the plugin can be enabled and customized for each post:

I can see how much it will cost to convert to audio with a click:

When I click on Publish, the plugin breaks the text into multiple blocks on sentence boundaries, calls the Polly SynthesizeSpeech API for each block, and accumulates the resulting audio in a single MP3 file. The published blog post references the file using the <audio> tag. Here’s the post:

I can’t seem to use an <audio> tag in this post, but you can download and play the MP3 file yourself if you’d like.

The Pollycast feature generates an RSS file with links to an MP3 file for each post:

The plugin will make calls to Amazon Polly each time the post is saved or updated. Pricing is based on the number of characters in the speech requests, as described on the Polly Pricing page. Also, the AWS Free Tier lets you process up to 5 million characters per month at no charge, for a period of one year that starts when you make your first call to Polly.

Going Further
The plugin is available on GitHub in source code form and we are looking forward to your pull requests! Here are a couple of ideas to get you started:

Voice Per Author – Allow selection of a distinct Polly voice for each author.

Quoted Text – For blogs that make frequent use of embedded quotes, use a distinct voice for the quotes.

Translation – Use Amazon Translate to translate the texts into another language, and then use Polly to generate audio in that language.

Other Blogging Engines – Build a similar plugin for your favorite blogging engine.

SSML Support – Figure out an interesting way to use Polly’s SSML tags to add additional character to the audio.

Let me know what you come up with!



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New AWS Developer Training in Collaboration with

I recently heard my manager (Ariel Kelman, VP of Marketing for AWS) talk about the important role that education plays in our work. In fact, he assigned it a significantly higher priority than traditional marketing activities that focus on leads or conversions. I’ve also heard our other leaders talk about their work to create highly scalable education programs that will allow developers, architects, and other IT professionals to improve their skills and to earn AWS Certifications.

AWS Developer Professional Series
Today I would like to tell you about the new AWS Developer Professional Series. The AWS Training and Certification team has teamed up with edX to create this new three-part series. Founded by MIT and Harvard, edX is the leading non-profit online learning destination, with a global community of over 14 million learners, backed up by 130 global partners including universities, non-profits, and institutions. This collaboration expands our offerings, and gives you another training option!

The new series is designed to help you and your colleagues to build development and DevOps skills on AWS. The courses are self-paced and build on each other in order to help you to create Python applications that run on AWS by way of the AWS SDK for Python (also known as Boto). Here are the courses:

AWS Developer: Building on AWS – This course will give you an introduction to AWS services and to the AWS SDKs. You’ll create and manage an AWS account, learn about Regions, AZs, and VPCs, and install SDKs. Then you will learn how to launch Amazon Elastic Compute Cloud (EC2) instances, set up AWS Lambda functions, and use managed services such as Amazon Relational Database Service (RDS). You’ll also learn how to use our AI services for image analysis and text-to-speech, and wrap up by focusing on availability and durability.

AWS Developer: Deploying on AWS – This course will teach you about the concepts and practices that allow you practice DevOps on AWS. You will learn how to use developer tools like AWS CodeBuild and AWS CodeDeploy, while monitoring your development and production environments using Amazon CloudWatch.

AWS Developer: Optimizing on AWS – This course focuses on performance optimization and tuning of the application that you built in the predecessor courses. You will learn how to use caching and content distribution to increase performance and to improve the end-user experience for your app. You’ll also learn how to use AWS Key Management Service (KMS) to encrypt data at rest and in transit.

The courses are built with the expectation that you already have one to three years of software development experience, including some Python skills. Each course runs for six weeks and requires three to four hours of work per week on your part. Courses start in February (Building), April (Deploying), and May (Optimizing), and you can enroll now at no charge. You can also pursue a Verified Certificate for a fee of $149 per course.



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The Floodgates Are Open – Increased Network Bandwidth for EC2 Instances

I hope that you have configured your AMIs and your current-generation EC2 instances to use the Elastic Network Adapter (ENA) that I told you about back in mid-2016. The ENA gives you high throughput and low latency, while minimizing the load on the host processor. It is designed to work well in the presence of multiple vCPUs, with intelligent packet routing backed up by multiple transmit and receive queues.

Today we are opening up the floodgates and giving you access to more bandwidth in all AWS Regions. Here are the specifics (in each case, the actual bandwidth is dependent on the instance type and size):

EC2 to S3 – Traffic to and from Amazon Simple Storage Service (S3) can now take advantage of up to 25 Gbps of bandwidth. Previously, traffic of this type had access to 5 Gbps of bandwidth. This will be of benefit to applications that access large amounts of data in S3 or that make use of S3 for backup and restore.

EC2 to EC2 – Traffic to and from EC2 instances in the same or different Availability Zones within a region can now take advantage of up to 5 Gbps of bandwidth for single-flow traffic, or 25 Gbps of bandwidth for multi-flow traffic (a flow represents a single, point-to-point network connection) by using private IPv4 or IPv6 addresses, as described here.

EC2 to EC2 (Cluster Placement Group) – Traffic to and from EC2 instances within a cluster placement group can continue to take advantage of up to 10 Gbps of lower-latency bandwidth for single-flow traffic, or 25 Gbps of lower-latency bandwidth for multi-flow traffic.

To take advantage of this additional bandwidth, make sure that you are using the latest, ENA-enabled AMIs on current-generation EC2 instances. ENA-enabled AMIs are available for Amazon Linux, Ubuntu 14.04 & 16.04, RHEL 7.4, SLES 12, and Windows Server (2008 R2, 2012, 2012 R2, and 2016). The FreeBSD AMI in AWS Marketplace is also ENA-enabled, as is VMware Cloud on AWS.


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New – Inter-Region VPC Peering

I’m still catching up with the last couple of AWS re:Invent launches!

Today I would like to tell you about inter-region VPC peering. You have been able to create peering connections between Virtual Private Clouds (VPCs) in the same AWS Region since early 2014 (read New VPC Peering for the Amazon Virtual Cloud to learn more). Once established, EC2 instances in the peered VPCs can communicate with each other across the peering connection using their private IP addresses, just as if they were on the same network.

At re:Invent we extended the peering model so that it works across AWS Regions. Like the existing model, it also works within the same AWS account or across a pair of accounts. All of the use cases that I listed in my earlier post still apply; you can centralize shared resources in an organization-wide VPC and then peer it with multiple, per-department VPCs. You can also share resources between members of a consortium, conglomerate, or joint venture.

Inter-region VPC peering also allows you to take advantage of the high degree of isolation that exists between AWS Regions while building highly functional applications that span Regions. For example, you can choose geographic locations for your compute and storage resources that will help you to comply with regulatory requirements and other constraints.

Peering Details
This feature is currently enabled in the US East (Northern Virginia), US East (Ohio), US West (Oregon), and EU (Ireland) Regions and for IPv4 traffic. You can connect any two VPCs in these Regions, as long as they have distinct, non-overlapping CIDR blocks. This ensures that all of the private IP addresses are unique and allows all of the resources in the pair of VPCs to address each other without the need for any form of network address translation.

Connections are requested by sending an invitation from one VPC to the other and the invitation must be accepted in order to establish the connection. You can set up a peering connection using the AWS Management Console, the VPC APIs, the AWS Command Line Interface (CLI), or the AWS Tools for Windows PowerShell.

Data that passes between VPCs in distinct regions flows across the AWS global network in encrypted form. The data is encrypted in AEAD fashion using a modern algorithm and AWS-supplied keys that are managed and rotated automatically. The same key is used to encrypt traffic for all peering connections; this makes all traffic, regardless of customer, look the same. This anonymity provides additional protection in situations where your inter-VPC traffic is intermittent.

Setting up Inter-Region Peering
Here’s how I set up peering between two of my VPCs. I’ll start with a VPC in US East (Northern Virginia) and request peering with a VPC in US East (Ohio). I start by noting the ID (vpc-acd8ccc5) of the VPC in Ohio:

Then I switch to the US East (Northern Virginia) Region, click on Create Peering Connection, and choose to peer with the VPC in Ohio. I enter the Id and click on Create Peering Connection to proceed:

This creates a peering request:

I switch to the other Region and accept the pending request:

Now I need to arrange to route IPv4 traffic between the two VPCs by creating route table entries in each one. I can edit the main route table or one associated with a particular VPC subnet. Here’s how I arrange to route traffic from Virginia to Ohio:

And here’s how I route it from Ohio to Virginia:

To learn more about how to do this, read Updating Your Route Tables for a VPC Peering Connection.

The private DNS names for EC2 instances (ip-10-90-211-18.ec2.internal and the like) will not resolve across a peering connection. If you need to refer to EC2 instances and other AWS resources in other VPCs, consider creating a Private Hosted Zone using Amazon Route 53:

Unlike VPC peering within a single region, you cannot reference security groups across Inter-Region VPC Peering. Also, jumbo frames cannot be send between regions.



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Recent EC2 Goodies – Launch Templates and Spread Placement

We launched some important new EC2 instance types and features at AWS re:Invent. I’ve already told you about the M5, H1, T2 Unlimited and Bare Metal instances, and about Spot features such as Hibernation and the New Pricing Model. Randall told you about the Amazon Time Sync Service. Today I would like to tell you about two of the features that we launched: Spread placement groups and Launch Templates. Both features are available in the EC2 Console and from the EC2 APIs, and can be used in all of the AWS Regions in the “aws” partition:

Launch Templates
You can use launch templates to store the instance, network, security, storage, and advanced parameters that you use to launch EC2 instances, and can also include any desired tags. Each template can include any desired subset of the full collection of parameters. You can, for example, define common configuration parameters such as tags or network configurations in a template, and allow the other parameters to be specified as part of the actual launch.

Templates give you the power to set up a consistent launch environment that spans instances launched in On-Demand and Spot form, as well as through EC2 Auto Scaling and as part of a Spot Fleet. You can use them to implement organization-wide standards and to enforce best practices, and you can give your IAM users the ability to launch instances via templates while withholding the ability to do so via the underlying APIs.

Templates are versioned and you can use any desired version when you launch an instance. You can create templates from scratch, base them on the previous version, or copy the parameters from a running instance.

Here’s how you create a launch template in the Console:

Here’s how to include network interfaces, storage volumes, tags, and security groups:

And here’s how to specify advanced and specialized parameters:

You don’t have to specify values for all of these parameters in your templates; enter the values that are common to multiple instances or launches and specify the rest at launch time.

When you click Create launch template, the template is created and can be used to launch On-Demand instances, create Auto Scaling Groups, and create Spot Fleets:

The Launch Instance button now gives you the option to launch from a template:

Simply choose the template and the version, and finalize all of the launch parameters:

You can also manage your templates and template versions from the Console:

To learn more about this feature, read Launching an Instance from a Launch Template.

Spread Placement Groups
Spread placement groups indicate that you do not want the instances in the group to share the same underlying hardware. Applications that rely on a small number of critical instances can launch them in a spread placement group to reduce the odds that one hardware failure will impact more than one instance. Here are a couple of things to keep in mind when you use spread placement groups:

  • Availability Zones – A single spread placement group can span multiple Availability Zones. You can have a maximum of seven running instances per Availability Zone per group.
  • Unique Hardware – Launch requests can fail if there is insufficient unique hardware available. The situation changes over time as overall usage changes and as we add additional hardware; you can retry failed requests at a later time.
  • Instance Types – You can launch a wide variety of M4, M5, C3, R3, R4, X1, X1e, D2, H1, I2, I3, HS1, F1, G2, G3, P2, and P3 instances types in spread placement groups.
  • Reserved Instances – Instances launched into a spread placement group can make use of reserved capacity. However, you cannot currently reserve capacity for a placement group and could receive an ICE (Insufficient Capacity Error) even if you have some RI’s available.
  • Applicability – You cannot use spread placement groups in conjunction with Dedicated Instances or Dedicated Hosts.

You can create and use spread placement groups from the AWS Management Console, the AWS Command Line Interface (CLI), the AWS Tools for Windows PowerShell, and the AWS SDKs. The console has a new feature that will help you to learn how to use the command line:

You can specify an existing placement group or create a new one when you launch an EC2 instance:

To learn more, read about Placement Groups.


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New AWS Auto Scaling – Unified Scaling For Your Cloud Applications

I’ve been talking about scalability for servers and other cloud resources for a very long time! Back in 2006, I wrote “This is the new world of scalable, on-demand web services. Pay for what you need and use, and not a byte more.” Shortly after we launched Amazon Elastic Compute Cloud (EC2), we made it easy for you to do this with the simultaneous launch of Elastic Load Balancing, EC2 Auto Scaling, and Amazon CloudWatch. Since then we have added Auto Scaling to other AWS services including ECS, Spot Fleets, DynamoDB, Aurora, AppStream 2.0, and EMR. We have also added features such as target tracking to make it easier for you to scale based on the metric that is most appropriate for your application.

Introducing AWS Auto Scaling
Today we are making it easier for you to use the Auto Scaling features of multiple AWS services from a single user interface with the introduction of AWS Auto Scaling. This new service unifies and builds on our existing, service-specific, scaling features. It operates on any desired EC2 Auto Scaling groups, EC2 Spot Fleets, ECS tasks, DynamoDB tables, DynamoDB Global Secondary Indexes, and Aurora Replicas that are part of your application, as described by an AWS CloudFormation stack or in AWS Elastic Beanstalk (we’re also exploring some other ways to flag a set of resources as an application for use with AWS Auto Scaling).

You no longer need to set up alarms and scaling actions for each resource and each service. Instead, you simply point AWS Auto Scaling at your application and select the services and resources of interest. Then you select the desired scaling option for each one, and AWS Auto Scaling will do the rest, helping you to discover the scalable resources and then creating a scaling plan that addresses the resources of interest.

If you have tried to use any of our Auto Scaling options in the past, you undoubtedly understand the trade-offs involved in choosing scaling thresholds. AWS Auto Scaling gives you a variety of scaling options: You can optimize for availability, keeping plenty of resources in reserve in order to meet sudden spikes in demand. You can optimize for costs, running close to the line and accepting the possibility that you will tax your resources if that spike arrives. Alternatively, you can aim for the middle, with a generous but not excessive level of spare capacity. In addition to optimizing for availability, cost, or a blend of both, you can also set a custom scaling threshold. In each case, AWS Auto Scaling will create scaling policies on your behalf, including appropriate upper and lower bounds for each resource.

AWS Auto Scaling in Action
I will use AWS Auto Scaling on a simple CloudFormation stack consisting of an Auto Scaling group of EC2 instances and a pair of DynamoDB tables. I start by removing the existing Scaling Policies from my Auto Scaling group:

Then I open up the new Auto Scaling Console and selecting the stack:

Behind the scenes, Elastic Beanstalk applications are always launched via a CloudFormation stack. In the screen shot above, awseb-e-sdwttqizbp-stack is an Elastic Beanstalk application that I launched.

I can click on any stack to learn more about it before proceeding:

I select the desired stack and click on Next to proceed. Then I enter a name for my scaling plan and choose the resources that I’d like it to include:

I choose the scaling strategy for each type of resource:

After I have selected the desired strategies, I click Next to proceed. Then I review the proposed scaling plan, and click Create scaling plan to move ahead:

The scaling plan is created and in effect within a few minutes:

I can click on the plan to learn more:

I can also inspect each scaling policy:

I tested my new policy by applying a load to the initial EC2 instance, and watched the scale out activity take place:

I also took a look at the CloudWatch metrics for the EC2 Auto Scaling group:

Available Now
We are launching AWS Auto Scaling today in the US East (Northern Virginia), US East (Ohio), US West (Oregon), EU (Ireland), and Asia Pacific (Singapore) Regions today, with more to follow. There’s no charge for AWS Auto Scaling; you pay only for the CloudWatch Alarms that it creates and any AWS resources that you consume.

As is often the case with our new services, this is just the first step on what we hope to be a long and interesting journey! We have a long roadmap, and we’ll be adding new features and options throughout 2018 in response to your feedback.


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Now Open – Third AWS Availability Zone in London

We expand AWS by picking a geographic area (which we call a Region) and then building multiple, isolated Availability Zones in that area. Each Availability Zone (AZ) has multiple Internet connections and power connections to multiple grids.

Today I am happy to announce that we are opening our 50th AWS Availability Zone, with the addition of a third AZ to the EU (London) Region. This will give you additional flexibility to architect highly scalable, fault-tolerant applications that run across multiple AZs in the UK.

Since launching the EU (London) Region, we have seen an ever-growing set of customers, particularly in the public sector and in regulated industries, use AWS for new and innovative applications. Here are a couple of examples, courtesy of my AWS colleagues in the UK:

Enterprise – Some of the UK’s most respected enterprises are using AWS to transform their businesses, including BBC, BT, Deloitte, and Travis Perkins. Travis Perkins is one of the largest suppliers of building materials in the UK and is implementing the biggest systems and business change in its history, including an all-in migration of its data centers to AWS.

Startups – Cross-border payments company Currencycloud has migrated its entire payments production, and demo platform to AWS resulting in a 30% saving on their infrastructure costs. Clearscore, with plans to disrupting the credit score industry, has also chosen to host their entire platform on AWS. UnderwriteMe is using the EU (London) Region to offer an underwriting platform to their customers as a managed service.

Public Sector -The Met Office chose AWS to support the Met Office Weather App, available for iPhone and Android phones. Since the Met Office Weather App went live in January 2016, it has attracted more than half a million users. Using AWS, the Met Office has been able to increase agility, speed, and scalability while reducing costs. The Driver and Vehicle Licensing Agency (DVLA) is using the EU (London) Region for services such as the Strategic Card Payments platform, which helps the agency achieve PCI DSS compliance.

The AWS EU (London) Region has achieved Public Services Network (PSN) assurance, which provides UK Public Sector customers with an assured infrastructure on which to build UK Public Sector services. In conjunction with AWS’s Standardized Architecture for UK-OFFICIAL, PSN assurance enables UK Public Sector organizations to move their UK-OFFICIAL classified data to the EU (London) Region in a controlled and risk-managed manner.

For a complete list of AWS Regions and Services, visit the AWS Global Infrastructure page. As always, pricing for services in the Region can be found on the detail pages; visit our Cloud Products page to get started.


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