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www.aws-senior.com [121]Amazon EventBridge is a serverless event bus that makes it easy to connect applications together. It can use data from AWS services, your own applications, and [122]integrations with Software-as-a-Service (SaaS) partners. Last year at re:Invent, we [123]introduced in preview EventBridge schema registry and discovery, a way to store the structure of the events (the schema) in a central location, and simplify using events in your code by generating the code to process them for Java, Python, and Typescript.

Today, I am happy to announce that the EventBridge schema registry is generally available, and that we added support for resource policies. Resource policies allow to share a schema repository across different AWS accounts and [124]organizations. In this way, developers on different teams can search for and use any schema that another team has added to the shared registry.

Using EventBridge Schema Registry Resource Policies Itâ€™s common for companies to have different development teams working on different services. To make a more concrete example, letâ€™s take two teams working on services that have to communicate with each other: * The CreateAccount development team, working on a frontend API that receives requests from a web/mobile client to create a new customer account for the company. * the FraudCheck development team, working on a backend service checking the data for newly created accounts to estimate the risk that those are fake.

Each team is using their own AWS account to develop their application. Using EventBridge, we can implement the following architecture: * The frontend CreateAccount applications is using the [125]Amazon API Gateway to process the request using a [126]AWS Lambda function written in Python. When a new account is created, the Lambda function publishes the ACCOUNT_CREATED event on a [127]custom event bus. * The backend FraudCheck Lambda function is built in Java, and is expecting to receive the ACCOUNT_CREATED event to call [128]Amazon Fraud Detector (a fully managed service we [129]introduced in preview at re:Invent) to estimate the risk of that being a fake account. If the risk is above a certain threshold, the Lambda function takes preemptive actions. For example, it can flag the account as fake on a database, or post a FAKE_ACCOUNT event on the event bus.

How can the two teams coordinate their work so that they both know the syntax of the events, and use EventBridge to generate the code to process those events?

First, a custom event bus is created with permissions to access within the company organization.

Then, the CreateAccount team uses EventBridge schema discovery to automatically populate the schema for the ACCOUNT_CREATED event that their service is publishing. This event contains all the information of the account that has just been created.

In an event-driven architecture, services can subscribe to specific types of events that theyâ€™re interested in. To receive ACCOUNT_CREATED events, a rule is created on the event bus to send those events to the FraudCheck function.

Using resource policies, the CreateAccount team gives read-only access to the FraudCheck team AWS account to the discovered schemas. The Principal in this policy is the AWS account getting the permissions. The Resource is the schema registry that is being shared. { "Version": "2012-10-17", "Statement": [ { "Sid": "GiveSchemaAccess", "Effect": "Allow", "Action": [ "schemas:ListSchemas", "schemas:SearchSchemas", "schemas:DescribeSchema", "schemas:DescribeCodeBinding", "schemas:GetCodeBindingSource", "schemas:PutCodeBinding" ], "Principal": { "AWS": "123412341234" }, "Resource": [ "arn:aws:schemas:us-east-1:432143214321:schema/discovered-schemas", "arn:aws:schemas:us-east-1:432143214321:schema/discovered-schemas*" ] } ] }

Now, the FraudCheck team can search the content of the discovered schema for the ACCOUNT_CREATED event. Resource policies allow you to make a registry available across accounts and organizations, but they will not automatically show up in the console. To access the shared registry, the FraudCheck team needs to use the [130]AWS Command Line Interface (CLI) and specify the full [131]ARN of the registry: aws schemas search-schemas \ --registry-name arn:aws:schemas:us-east-1:432143214321:registry/discovered-s chemas \ --keywords ACCOUNT_CREATED

In this way, the FraudCheck team gets the exact name of the schema created by the CreateAccount team. { "Schemas": [ { "RegistryName": "discovered-schemas", "SchemaArn": "arn:aws:schemas:us-east-1:432143214321:schema/discover ed-schemas/CreateAccount@ACCOUNT_CREATED", "SchemaName": â€œCreateAccount@ACCOUNT_CREATED", "SchemaVersions": [ { "CreatedDate": "2020-04-28T11:10:15+00:00", "SchemaVersion": 1 } ] } ] }

With the schema name, the FraudCheck team can describe the content of the schema: aws schemas describe-schema \ --registry-name arn:aws:schemas:us-east-1:432143214321:registry/discovered-s chemas \ --schema-name CreateAccount@ACCOUNT_CREATED

The result describes the schema using the [132]OpenAPI specification: { "Content": "{\"openapi\":\"3.0.0\",\"info\":{\"version\":\"1.0.0\",\"title\" :\"CREATE_ACCOUNT\"},\"paths\":{},\"components\":{\"schemas\":{\"AWSEvent\":{\"t ype\":\"object\",\"required\":[\"detail-type\",\"resources\",\"detail\",\"id\",\ "source\",\"time\",\"region\",\"version\",\"account\"],\"x-amazon-events-detail- type\":\"CREATE_ACCOUNT\",\"x-amazon-events-source\":\â€CreateAccount\",\"propert ies\":{\"detail\":{\"$ref\":\"#/components/schemas/CREATE_ACCOUNT\"},\"account\" :{\"type\":\"string\"},\"detail-type\":{\"type\":\"string\"},\"id\":{\"type\":\" string\"},\"region\":{\"type\":\"string\"},\"resources\":{\"type\":\"array\",\"i tems\":{\"type\":\"object\"}},\"source\":{\"type\":\"string\"},\"time\":{\"type\ ":\"string\",\"format\":\"date-time\"},\"version\":{\"type\":\"string\"}}},\"CRE ATE_ACCOUNT\":{\"type\":\"object\",\"required\":[\"firstName\",\"surname\",\"id\ ",\"email\"],\"properties\":{\"email\":{\"type\":\"string\"},\"firstName\":{\"ty pe\":\"string\"},\"id\":{\"type\":\"string\"},\"surname\":{\"type\":\"string\"}} }}}}", "LastModified": "2020-04-28T11:10:15+00:00", "SchemaArn": "arn:aws:schemas:us-east-1:432143214321:schema/discovered-schem as/CreateAccount@CREATE_ACCOUNT", "SchemaName": â€œCreateAccount@ACCOUNT_CREATED", "SchemaVersion": "1", "Tags": {}, "Type": "OpenApi3", "VersionCreatedDate": "2020-04-28T11:10:15+00:00" }

Using the [133]AWS Command Line Interface (CLI), the FraudCheck team can create a code binding if it isnâ€™t already created, using the put-code-binding command, and then download the code binding to process that event: aws schemas get-code-binding-source \ --registry-name arn:aws:schemas:us-east-1:432143214321:registry/discovered-s chemas \ --schema-name CreateAccount@ACCOUNT_CREATED \ --language Java8 CreateAccount.zip

Another option for the FraudCheck team is to copy and paste (after unescaping the JSON string) the Content of the discovered schema to create a new custom schema in their AWS account.

Once the schema is copied to their own account, the FraudCheck team can use the [134]AWS Toolkit IDE plugins to view the schema, download code bindings, and generate serverless applications directly from their IDEs. The EventBridge team is working to add the capability to the AWS Toolkit to use a schema registry in a different account, making this step simpler. Stay tuned!

Often customers have a specific team, with a different AWS account, managing the event bus. For the sake of simplicity, in this post I assumed that the CreateAccount team was the one configuring the EventBridge event bus. With more accounts, you can simplify permissions [135]using IAM to share resources with groups of AWS accounts in AWS Organizations.

Available Now The EventBridge Schema Registry is available now in all commercial regions except Bahrain, Cape Town, Milan, Osaka, Beijing, and Ningxia. For more information on how to use resource policies for schema registries, [136]please see the documentation.

Using Schema Registry resource policies, it is much easier to coordinate the work of different teams sharing information in an event-driven architecture.

Let me know what are you going to build with this!

â€" [137]Danilo

Danilo Poccia

[138]Danilo Poccia

Danilo works with startups and companies of any size to support their innovation. In his role as Chief Evangelist (EMEA) at Amazon Web Services, he leverages his experience to help people bring their ideas to life, focusing on serverless architectures and event-driven programming, and on the technical and business impact of machine aws-senior.com

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NEW BUILDING A CONTINUOUS INTEGRATION WORKFLOW WITH STEP FUNCTIONS

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In the middle of a trans-Nordics trip in early March that took me to Denmark, Finland, and Sweden in the course of a week, Amazon asked me and my coworkers to work from home if possible. I finished my trip, returned to Seattle, and did my best to adapt to these changing times.

In the ensuing weeks, several of my scheduled trips were cancelled, all of my in-person meetings with colleagues and customers were replaced with [118]Amazon Chime video calls, and we decided to start taping Whatâ€™s New with AWS from my home office.

On the personal side, I watched as many of the entertainment, education, and sporting events that I enjoy were either canceled or moved online. Just as you probably did, I quickly found new ways to connect with family and friends that did not require face-to-face interaction.

I thought that it would be interesting to see how these sudden, large-scale changes are affecting our customers. My colleague [119]Monica Benjamin checked in with AWS customers across several different fields and industries and provided me with the source material for this post. Hereâ€™s what we learnedâ€¦

Edmodo â€" Education Education technology company [120]Edmodo provides tools for K-12 schools and teachers. More than 125 million members count on Edmodo to provide a secure space for teachers, students, and parents to communicate and collaborate. As the pandemic began spreading across Europe, Edmodoâ€™s traffic began to grow at an exponential rate. AWS has allowed them to rapidly scale in order to meet this new demand so that education continues across the world. [121]Per Thomsen (Vice President, Engineering) told us:

In early March, our traffic grew significantly with the total number of global learners engaging on the network spiking within a matter of weeks. This required us to increase site capacity by 15 times. With AWS and Amazon EC2 instances, Edmodo has been able to quickly scale and meet this new demand so we could continue to provide teachers and students with our uninterrupted services for their distance learning needs. Having AWS always at our fingertips gives us elastic and robust compute capacity to scale rapidly.

BlueJeans â€" Cloud-Based Video Conferencing Global video provider [122]BlueJeans supports employees working from home, health care providers shifting to telehealth, and educators moving to distance learning. Customers like BlueJeans because it provides high video and voice quality, strong security, and interoperability. [123]Swaroop Kulkarni (Technical Director, Office of the CTO) told us:

With so many people working from home, we have seen explosive growth in traffic since the start of the Coronavirus pandemic. In just two weeks our usage skyrocketed 300% over the pre-COVID-19 average. We have always run a hybrid infrastructure between our datacenters and public cloud and fortunately had already shifted critical workloads to Amazon EC2 services before the Coronavirus outbreak. The traffic surge in March 2020 led us to scale up on AWS. We took advantage of the global presence of AWS and nearly doubled the number of regions and added US East (Ohio), APAC (Mumbai) and APAC (Singapore). We also experimented with various instance types (C,M,R families) and time-of-day scaling and this served us well for managing costs. Overall, we were able to stay ahead of traffic increases smoothly and seamlessly. We appreciate the partnership with AWS.

Netflix â€" Media & Entertainment Home entertainment provider [124]Netflix started to see their usage spike in March, with an increase in stream starts in many different parts of the world. [125]Nils Pommerien (Director, Cloud Infrastructure Engineering) told us:

Like other home entertainment services, Netflix has seen temporarily higher viewing and increased member growth during this unprecedented time. In order to meet this demand our control plane services needed to scale very quickly. This is where the value of AWSâ€™ cloud and our strong partnership became apparent, both in being able to meet capacity needs in compute, storage, as well as providing the necessary infrastructure, such as AWS Auto Scaling, which is deeply ingrained in Netflixâ€™s operations model.

Pinterest â€" Billions of Pins Visual discovery engine [126]Pinterest has been scaling to meet the needs of an ever-growing audience. [127]Coburn Watson (Head of Infrastructure and SRE) told us:

Pinterest has been able to provide inspiration for an expanded global customer audience during this challenging period, whether looking for public health information, new foods to prepare, or projects and crafts to do with friends and family. Working closely with AWS, Pinterest has been able to ensure additional capacity was available during this period to keep Pinterest up and serving our customers.

Finra â€" Financial Services FINRA regulates a critical part of the securities industry â€" brokerage firms doing business with the public in the United States. FINRA takes in as much as 400 billion market events per day that are tracked, aggregated, and analyzed for the purpose of protecting investors. [128]Steve Randich (Executive Vice President and Chief Information Officer) told us:

The COVID-19 pandemic has caused extreme volatility in the U.S. securities markets, and since March we have seen market volumes increase by 2-3x. Our compute resources with AWS are automatically provisioned and can process a record peak and then shut down to nothing, without any human intervention. We automatically turn on and off up to 100,000 compute nodes in a single day. We would have been unable to handle this surge in volume within our on premises data center.

As you can see from what Steve said, scaling down is just as important as scaling up.

Snap â€" Reinventing the Camera The [129]Snapchat application lets people express themselves and helps them to maintain connections with family and close friends. [130]Saral Jain (Director of Engineering) told us:

As the global coronavirus pandemic affected the lives of millions around the world, Snapchat has played an important role in peopleâ€™s lives, especially for helping close friends and family stay together emotionally while they are separated physically. In recent months, we have seen increased engagement across our platform resulting in higher workloads and the need to rapidly scale up our cloud infrastructure. For example, communication with friends increased by over 30 percent in the last week of March compared to the last week of January, with more than a 50 percent increase in some of our larger markets. AWS cloud has been valuable in helping us deal with this significant increase in demand, with services like EC2 and DynamoDB delivering high performance and reliability we need to provide the best experience for our customers.

I hope that you are staying safe, and that you have enjoyed this look at what our customers are doing in these unique and rapidly changing times. If you have a story of your own to share, please let me know.
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INTRODUCTION A AMAZON WEB SERVICES

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Amazon Web Services (AWS) is the favorite among developers in the cloud-native and serverless computing spaces, according to new research by SlashData.

The company's Developer Economics report, titled "[13]The State of Cloud-Native Development," was conducted for the Cloud-Native Computing Foundation (CNCF), a Linux Foundation project. Although based on data from an overall larger survey conducted in the second quarter of last year, the report was just released this month.

Among its findings, the report determined that cloud kingpin AWS is No. 1 in the serverless market with its AWS Lambda offering (51 percent of serverless users are using AWS Lambda), followed by Google Cloud Functions and Azure Functions.

AWS was also a popular choice in other cloud-native development scenarios. "Cloud-native developers are significantly more likely to use AWS as a private cloud vendor with 60 percent of Cloud-Native developers using AWS as their private cloud vendor," the report stated.

Furthermore, 68 percent of developers who use containers-as-a-service but not the Kubernetes container orchestration tool use either Amazon Elastic Container Service (ECS) or Amazon Managed Kubernetes Service (EKS). "Presumably, these are mostly developers using the old ECS which is not built on Kubernetes," the report said. "Azure Container Service is used by 25 percent, and 14 percent are using Docker Swarm."

CNCF, however, contrasted that finding with its own similar survey. "The CNCF report, on the other hand, found that Amazon EKS is the most popular tool for managing containers at nearly 30 percent," CNCF [14]said in its own post publicizing the study that it commissioned.

The CNCF found that the public cloud was the most popular datacenter approach, named by 62 percent of respondents, while "45 percent of respondents indicated they were using private cloud/on-premise. While hybrid was a new response for 2019, it was selected by 38 percent of respondents, indicating that it is a widely used approach."

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RGPD QUEST CE QUE CEST

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for [117]Amazon Elasticsearch Service.
This new low-cost storage tier provides fast, interactive analytics on up to three petabytes of log data at one-tenth of the cost of the current Amazon Elasticsearch Service storage tier.
UltraWarm, complements the existing Amazon Elasticsearch Service hot storage tier by providing less expensive storage for older and less-frequently accessed data while still ensuring that snappy, interactive experience that Amazon Elasticsearch Service customers have come to expect. Amazon Elasticsearch Service stores data in Amazon S3 while using custom, highly-optimized nodes, purpose-built on the [118]AWS Nitro System, to cache, pre-fetch, and query that data.
There are many use cases for the Amazon Elasticsearch Service, from building a search system for your website, storing, and analyzing data from application or infrastructure logs. We think this new storage tier will work particularly well for customers that have large volumes of log data.
Amazon Elasticsearch Service is a popular service for log analytics because of its ability to ingest high volumes of log data and analyze it interactively. As more developers build applications using microservices and containers, there is an explosive growth of log data. Storing and analyzing months or even years worth of data is cost-prohibitive at scale, and this has led customers to use multiple analytics tools, or delete valuable data, missing out on essential insights that the longer-term data could yield.
AWS built [119]UltraWarm to solve this problem and ensures that developers, DevOps engineers, and InfoSec experts can analyze recent and longer-term operational data without needing to spend days restoring data from archives to an active searchable state in an Amazon Elasticsearch Service cluster.
So letâ€™s take a look at how you use this new storage tier by creating a new domain in the AWS Management Console.
Firstly, I go to the Amazon Elasticsearch Service console and click on the button to Create a new domain. This then takes me through a workflow to set up a new cluster, for the most part setting up a new domain with [120]UltraWarm is identical to setting up a regular domain, I will point out the couple of things you will need to do differently.
On Step 1 of the workflow, I click on the radio button to create a Production deployment type and click Next.
I continue to fill out the configuration in Step 2. Then, near the end, I check the box to Enable UltraWarm data nodes and select the Instance type I want to use. I go with the default ultrawarm1.medium.elasticsearch and then ask for 3 of them, there is a requirement to have at least 2 nodes.
Everything else about the setup is identical to a regular Amazon Elasticsearch Service setup. After having set up the cluster, I then go to the dashboard and select my newly created domain. The dashboard confirms that my newly created domain has 3 UltraWarm data nodes, each with 1516 (GiB) free storage space.
As well as using [121]UltraWarm on a new domain, you can also enable it for existing domains using the AWS Management Console, CLI, or SDK.
Once you have [122]UltraWarm nodes setup, you can migrate an index from hot to warm by using the following request. POST _ultrawarm/migration/my-index/_warm
You can then check the status of the migration by using the following request. GET _ultrawarm/migration/my-index/_status { "migration_status": { "index": "my-index", "state": "RUNNING_SHARD_RELOCATION", "migration_type": "HOT_TO_WARM", "shard_level_status": { "running": 0, "total": 5, "pending": 3, "failed": 0, "succeeded": 2 } } }
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