Tag Archives: AWS Amplify

ICYMI: Serverless Q4 2019

Post Syndicated from Rob Sutter original https://aws.amazon.com/blogs/compute/icymi-serverless-q4-2019/

Welcome to the eighth edition of the AWS Serverless ICYMI (in case you missed it) quarterly recap. Every quarter, we share the most recent product launches, feature enhancements, blog posts, webinars, Twitch live streams, and other interesting things that you might have missed!

In case you missed our last ICYMI, checkout what happened last quarter here.

The three months comprising the fourth quarter of 2019

AWS re:Invent

AWS re:Invent 2019

re:Invent 2019 dominated the fourth quarter at AWS. The serverless team presented a number of talks, workshops, and builder sessions to help customers increase their skills and deliver value more rapidly to their own customers.

Serverless talks from re:Invent 2019

Chris Munns presenting 'Building microservices with AWS Lambda' at re:Invent 2019

We presented dozens of sessions showing how customers can improve their architecture and agility with serverless. Here are some of the most popular.

Videos

Decks

You can also find decks for many of the serverless presentations and other re:Invent presentations on our AWS Events Content.

AWS Lambda

For developers needing greater control over performance of their serverless applications at any scale, AWS Lambda announced Provisioned Concurrency at re:Invent. This feature enables Lambda functions to execute with consistent start-up latency making them ideal for building latency sensitive applications.

As shown in the below graph, provisioned concurrency reduces tail latency, directly impacting response times and providing a more responsive end user experience.

Graph showing performance enhancements with AWS Lambda Provisioned Concurrency

Lambda rolled out enhanced VPC networking to 14 additional Regions around the world. This change brings dramatic improvements to startup performance for Lambda functions running in VPCs due to more efficient usage of elastic network interfaces.

Illustration of AWS Lambda VPC to VPC NAT

New VPC to VPC NAT for Lambda functions

Lambda now supports three additional runtimes: Node.js 12, Java 11, and Python 3.8. Each of these new runtimes has new version-specific features and benefits, which are covered in the linked release posts. Like the Node.js 10 runtime, these new runtimes are all based on an Amazon Linux 2 execution environment.

Lambda released a number of controls for both stream and async-based invocations:

  • You can now configure error handling for Lambda functions consuming events from Amazon Kinesis Data Streams or Amazon DynamoDB Streams. It’s now possible to limit the retry count, limit the age of records being retried, configure a failure destination, or split a batch to isolate a problem record. These capabilities help you deal with potential “poison pill” records that would previously cause streams to pause in processing.
  • For asynchronous Lambda invocations, you can now set the maximum event age and retry attempts on the event. If either configured condition is met, the event can be routed to a dead letter queue (DLQ), Lambda destination, or it can be discarded.

AWS Lambda Destinations is a new feature that allows developers to designate an asynchronous target for Lambda function invocation results. You can set separate destinations for success and failure. This unlocks new patterns for distributed event-based applications and can replace custom code previously used to manage routing results.

Illustration depicting AWS Lambda Destinations with success and failure configurations

Lambda Destinations

Lambda also now supports setting a Parallelization Factor, which allows you to set multiple Lambda invocations per shard for Kinesis Data Streams and DynamoDB Streams. This enables faster processing without the need to increase your shard count, while still guaranteeing the order of records processed.

Illustration of multiple AWS Lambda invocations per Kinesis Data Streams shard

Lambda Parallelization Factor diagram

Lambda introduced Amazon SQS FIFO queues as an event source. “First in, first out” (FIFO) queues guarantee the order of record processing, unlike standard queues. FIFO queues support messaging batching via a MessageGroupID attribute that supports parallel Lambda consumers of a single FIFO queue, enabling high throughput of record processing by Lambda.

Lambda now supports Environment Variables in the AWS China (Beijing) Region and the AWS China (Ningxia) Region.

You can now view percentile statistics for the duration metric of your Lambda functions. Percentile statistics show the relative standing of a value in a dataset, and are useful when applied to metrics that exhibit large variances. They can help you understand the distribution of a metric, discover outliers, and find hard-to-spot situations that affect customer experience for a subset of your users.

Amazon API Gateway

Screen capture of creating an Amazon API Gateway HTTP API in the AWS Management Console

Amazon API Gateway announced the preview of HTTP APIs. In addition to significant performance improvements, most customers see an average cost savings of 70% when compared with API Gateway REST APIs. With HTTP APIs, you can create an API in four simple steps. Once the API is created, additional configuration for CORS and JWT authorizers can be added.

AWS SAM CLI

Screen capture of the new 'sam deploy' process in a terminal window

The AWS SAM CLI team simplified the bucket management and deployment process in the SAM CLI. You no longer need to manage a bucket for deployment artifacts – SAM CLI handles this for you. The deployment process has also been streamlined from multiple flagged commands to a single command, sam deploy.

AWS Step Functions

One powerful feature of AWS Step Functions is its ability to integrate directly with AWS services without you needing to write complicated application code. In Q4, Step Functions expanded its integration with Amazon SageMaker to simplify machine learning workflows. Step Functions also added a new integration with Amazon EMR, making EMR big data processing workflows faster to build and easier to monitor.

Screen capture of an AWS Step Functions step with Amazon EMR

Step Functions step with EMR

Step Functions now provides the ability to track state transition usage by integrating with AWS Budgets, allowing you to monitor trends and react to usage on your AWS account.

You can now view CloudWatch Metrics for Step Functions at a one-minute frequency. This makes it easier to set up detailed monitoring for your workflows. You can use one-minute metrics to set up CloudWatch Alarms based on your Step Functions API usage, Lambda functions, service integrations, and execution details.

Step Functions now supports higher throughput workflows, making it easier to coordinate applications with high event rates. This increases the limits to 1,500 state transitions per second and a default start rate of 300 state machine executions per second in US East (N. Virginia), US West (Oregon), and Europe (Ireland). Click the above link to learn more about the limit increases in other Regions.

Screen capture of choosing Express Workflows in the AWS Management Console

Step Functions released AWS Step Functions Express Workflows. With the ability to support event rates greater than 100,000 per second, this feature is designed for high-performance workloads at a reduced cost.

Amazon EventBridge

Illustration of the Amazon EventBridge schema registry and discovery service

Amazon EventBridge announced the preview of the Amazon EventBridge schema registry and discovery service. This service allows developers to automate discovery and cataloging event schemas for use in their applications. Additionally, once a schema is stored in the registry, you can generate and download a code binding that represents the schema as an object in your code.

Amazon SNS

Amazon SNS now supports the use of dead letter queues (DLQ) to help capture unhandled events. By enabling a DLQ, you can catch events that are not processed and re-submit them or analyze to locate processing issues.

Amazon CloudWatch

Amazon CloudWatch announced Amazon CloudWatch ServiceLens to provide a “single pane of glass” to observe health, performance, and availability of your application.

Screenshot of Amazon CloudWatch ServiceLens in the AWS Management Console

CloudWatch ServiceLens

CloudWatch also announced a preview of a capability called Synthetics. CloudWatch Synthetics allows you to test your application endpoints and URLs using configurable scripts that mimic what a real customer would do. This enables the outside-in view of your customers’ experiences, and your service’s availability from their point of view.

CloudWatch introduced Embedded Metric Format, which helps you ingest complex high-cardinality application data as logs and easily generate actionable metrics. You can publish these metrics from your Lambda function by using the PutLogEvents API or using an open source library for Node.js or Python applications.

Finally, CloudWatch announced a preview of Contributor Insights, a capability to identify who or what is impacting your system or application performance by identifying outliers or patterns in log data.

AWS X-Ray

AWS X-Ray announced trace maps, which enable you to map the end-to-end path of a single request. Identifiers show issues and how they affect other services in the request’s path. These can help you to identify and isolate service points that are causing degradation or failures.

X-Ray also announced support for Amazon CloudWatch Synthetics, currently in preview. CloudWatch Synthetics on X-Ray support tracing canary scripts throughout the application, providing metrics on performance or application issues.

Screen capture of AWS X-Ray Service map in the AWS Management Console

X-Ray Service map with CloudWatch Synthetics

Amazon DynamoDB

Amazon DynamoDB announced support for customer-managed customer master keys (CMKs) to encrypt data in DynamoDB. This allows customers to bring your own key (BYOK) giving you full control over how you encrypt and manage the security of your DynamoDB data.

It is now possible to add global replicas to existing DynamoDB tables to provide enhanced availability across the globe.

Another new DynamoDB capability to identify frequently accessed keys and database traffic trends is currently in preview. With this, you can now more easily identify “hot keys” and understand usage of your DynamoDB tables.

Screen capture of Amazon CloudWatch Contributor Insights for DynamoDB in the AWS Management Console

CloudWatch Contributor Insights for DynamoDB

DynamoDB also released adaptive capacity. Adaptive capacity helps you handle imbalanced workloads by automatically isolating frequently accessed items and shifting data across partitions to rebalance them. This helps reduce cost by enabling you to provision throughput for a more balanced workload instead of over provisioning for uneven data access patterns.

Amazon RDS

Amazon Relational Database Services (RDS) announced a preview of Amazon RDS Proxy to help developers manage RDS connection strings for serverless applications.

Illustration of Amazon RDS Proxy

The RDS Proxy maintains a pool of established connections to your RDS database instances. This pool enables you to support a large number of application connections so your application can scale without compromising performance. It also increases security by enabling IAM authentication for database access and enabling you to centrally manage database credentials using AWS Secrets Manager.

AWS Serverless Application Repository

The AWS Serverless Application Repository (SAR) now offers Verified Author badges. These badges enable consumers to quickly and reliably know who you are. The badge appears next to your name in the SAR and links to your GitHub profile.

Screen capture of SAR Verifiedl developer badge in the AWS Management Console

SAR Verified developer badges

AWS Developer Tools

AWS CodeCommit launched the ability for you to enforce rule workflows for pull requests, making it easier to ensure that code has pass through specific rule requirements. You can now create an approval rule specifically for a pull request, or create approval rule templates to be applied to all future pull requests in a repository.

AWS CodeBuild added beta support for test reporting. With test reporting, you can now view the detailed results, trends, and history for tests executed on CodeBuild for any framework that supports the JUnit XML or Cucumber JSON test format.

Screen capture of AWS CodeBuild

CodeBuild test trends in the AWS Management Console

Amazon CodeGuru

AWS announced a preview of Amazon CodeGuru at re:Invent 2019. CodeGuru is a machine learning based service that makes code reviews more effective and aids developers in writing code that is more secure, performant, and consistent.

AWS Amplify and AWS AppSync

AWS Amplify added iOS and Android as supported platforms. Now developers can build iOS and Android applications using the Amplify Framework with the same category-based programming model that they use for JavaScript apps.

Screen capture of 'amplify init' for an iOS application in a terminal window

The Amplify team has also improved offline data access and synchronization by announcing Amplify DataStore. Developers can now create applications that allow users to continue to access and modify data, without an internet connection. Upon connection, the data synchronizes transparently with the cloud.

For a summary of Amplify and AppSync announcements before re:Invent, read: “A round up of the recent pre-re:Invent 2019 AWS Amplify Launches”.

Illustration of AWS AppSync integrations with other AWS services

Q4 serverless content

Blog posts

October

November

December

Tech talks

We hold several AWS Online Tech Talks covering serverless tech talks throughout the year. These are listed in the Serverless section of the AWS Online Tech Talks page.

Here are the ones from Q4:

Twitch

October

There are also a number of other helpful video series covering Serverless available on the AWS Twitch Channel.

AWS Serverless Heroes

We are excited to welcome some new AWS Serverless Heroes to help grow the serverless community. We look forward to some amazing content to help you with your serverless journey.

AWS Serverless Application Repository (SAR) Apps

In this edition of ICYMI, we are introducing a section devoted to SAR apps written by the AWS Serverless Developer Advocacy team. You can run these applications and review their source code to learn more about serverless and to see examples of suggested practices.

Still looking for more?

The Serverless landing page has much more information. The Lambda resources page contains case studies, webinars, whitepapers, customer stories, reference architectures, and even more Getting Started tutorials. We’re also kicking off a fresh series of Tech Talks in 2020 with new content providing greater detail on everything new coming out of AWS for serverless application developers.

Throughout 2020, the AWS Serverless Developer Advocates are crossing the globe to tell you more about serverless, and to hear more about what you need. Follow this blog to keep up on new launches and announcements, best practices, and examples of serverless applications in action.

You can also follow all of us on Twitter to see latest news, follow conversations, and interact with the team.

Chris Munns: @chrismunns
Eric Johnson: @edjgeek
James Beswick: @jbesw
Moheeb Zara: @virgilvox
Ben Smith: @benjamin_l_s
Rob Sutter: @rts_rob
Julian Wood: @julian_wood

Happy coding!

ICYMI: Serverless re:Invent re:Cap 2019

Post Syndicated from Eric Johnson original https://aws.amazon.com/blogs/compute/icymi-serverless-reinvent-recap-2019/

Thank you for attending re:Invent 2019

In the week before AWS re:Invent 2019 we wrote about a number of service and feature launches leading up to the biggest event of the year for us at AWS. These included new features for AWS Lambda, integrations for AWS Step Functions, and other exciting service and feature launches for related product areas. But this was just the warm-up – AWS re:Invent 2019 itself saw several new serverless or serverless related announcements.

Here’s what’s new.

AWS Lambda

For developers needing greater control over performance of their serverless applications at any scale, AWS Lambda announced Provisioned Concurrency. This feature enables Lambda functions to execute with consistent start-up latency making them ideal for building latency sensitive applications.

AWS Step Functions

Express work flows

AWS Step Functions released AWS Step Functions Express Workflows. With the ability to support event rates greater than 100,000 per second, this feature is designed for high performance workloads at a reduced cost.

Amazon EventBridge

EventBridge schema registry and discovery

Amazon EventBridge announced the preview of the Amazon EventBridge schema registry and discovery service. This service allows developers to automate discovery and cataloging event schemas for use in their applications. Additionally, once a schema is stored in the registry, you can generate and download a code binding that represents the schema as an object in your code.

Amazon API Gateway

HTTP API

Amazon API Gateway announced the preview of HTTP APIs. With HTTP APIs most customers will see an average cost saving up to 70%, when compared to API Gateway REST APIs. In addition, you will see significant performance improvements in the API Gateway service overhead. With HTTP APIs, you can create an API in four simple steps. Once the API is created, additional configuration for CORS and JWT authorizers can be added.

Databases

Amazon Relational Database Services (RDS) announced a previews of Amazon RDS Proxy to help developers manage RDS connection strings for serverless applications.

RDS Proxy

The RDS proxy maintains a pool of established connections to your RDS database instances. This pool enables you to support a large number of application connections so your application can scale without compromising performance. It also increases security by enabling IAM authentication for database access and enabling you to centrally manage database credentials using AWS Secrets Manager.

AWS Amplify

Amplify platform choices

AWS Amplify has expanded their delivery platforms to include iOS and Android. Developers can now build iOS and Android applications using the Amplify Framework with the same category-based programming model that they use for JavaScript apps.

The Amplify team has also improved offline data access and synchronization by announcing Amplify DataStore. Developers can now create applications that allow users to continue to access and modify data, without an internet connection. Upon connection, the data synchronizes transparently with the cloud.

Amazon CodeGuru

Whether you are a team of one or an enterprise with thousands of developers, code review can be difficult. At re:Invent 2019, AWS announced a preview of Amazon CodeGuru, a machine learning based service to help make code reviews more effective and aid developers in writing code that is secure, performant, and consistent.

Serverless talks from re:Invent 2019

re:Invent presentation recordings

We presented dozens of sessions showing how customers can improve their architecture and agility with serverless. Here are some of the most popular.

Videos

Decks

You can also find decks for many of the serverless presentations and other re:Invent presentations on our AWS Events Content.

Conclusion

Prior to AWS re:Invent, AWS serverless had many service and feature launches and the pace continued throughout re:Invent itself. As we head towards 2020, follow this blog to keep up on new launches and announcements, best practices, and examples of serverless applications in action

Additionally, the AWS Serverless Developer Advocates will be crossing the globe to tell you more about serverless, and to hear more about what you need. You can also follow all of us on Twitter to see latest news, follow conversations, and interact with the team.

Chris Munns: @chrismunns
Eric Johnson: @edjgeek
James Beswick: @jbesw
Moheeb Zara: @virgilvox
Ben Smith: @benjamin_l_s
Rob Sutter: @rts_rob
Julian Wood: @julian_wood

Happy coding!

Alejandra’s Top 5 Favorite re:Invent🎉 Launches of 2019

Post Syndicated from Alejandra Quetzalli original https://aws.amazon.com/blogs/aws/alejandras-top-5-favorite-reinvent%F0%9F%8E%89-launches-of-2019/

favorite re:Invent launches of 2019

While re:Invent 2019 may feel well over, I’m still feeling elated and curious about several of the launches that were announced that week. Is it just me, or did some of the new feature announcements seem to bring us closer to the Scifi worlds (i.e. AWS WaveLength anyone? and don’t get me started on Amazon Braket) of the future we envisioned as kids?

The future might very well be here. Can you handle it?

If you can, then I’m pumped to tell you why the following 5 launches of re:Invent 2019 got me the most excited.

[CAVEAT: Out of consideration for your sanity, dear reader, we try to keep these posts to a maximum word length. After all, I wouldn’t want you to fall asleep at your keyboard during work hours! Sadly, this also means I limited myself to only sharing a set number of the cool, new launches that happened. If you’re curious to read about ALL OF THEM, you can find them here: 2019 re:Invent Announcement Summary Page.]

 

1. Amazon Braket: explore Quantum Computing

Backstory of why I picked this one…

First of all, let’s address the 🐘elephant in the room🐘 and admit that 99.9% of us don’t really know what Quantum Computing is. But we want to! Because it sounds so cool and futuristic. So let’s give it a shot…

According to The Internet, a quantum computer is any computational device that uses the quantum mechanical phenomenas of superposition and entanglement to perform data operations. The basic principle of quantum computation is that quantum properties can be used to represent data and perform operations on it. Also, fun fact… in a “normal” computer —like your laptop— that data…that information… is stored in something called bits. But in a quantum computer, it is stored as qubits (quantum bits).

Quantum Computing is still in its infancy. Are you wondering where it will go?

What got launched?

Amazon Braket is a new service that makes it easy for scientists, researchers, and developers to build, test, and run quantum computing algorithms.

Sounds cool, but what does that actually mean?

The way it works is that Amazon Braket provides a development environment that enables you to design your own quantum algorithms from scratch or choose from a set of pre-built algorithms. Once you’ve picked your algorithm of choice, Amazon Braket provides you with a simulation service that helps you troubleshoot and verify your implementation of said algorithm. Once you’re ready, you could also choose to run your algorithm on a real quantum computer from one of our quantum hardware providers (i.e. D-Wave, IonQ, and Rigetti, etc).

So what are you waiting for? Go explore the future of quantum computing with Amazon Braket!

👉🏽Don’t forget to check out the docs: aws.amazon.com/braket
⚠Sign up to get notified when it’s released.

 

2. AWS Wavelength: ultra-low latency apps for 5G

Backstory of why I picked this one…

When I was a kid in the 80s, we were still on the beginning stages of the first wireless technology.

1G.

It had a lot of similarities to an old AM/FM radio. And just like with radio stations, cell phone calls ended up recieving interference from other callers ALL THE TIME. Sometimes, the calls became staticy if you were too far away from cell phone towers.

But it’s no longer the 80s, my dear readers. It’s 2019 and we’re all the way up to 5G now.

[note: When talking about 1,2, 3, 4 or 5G, the G stands for generation.]

What got launched?

AWS Wavelength combines high bandwidth and single-digit millisecond latency of 5G networks with AWS compute and storage services to enable developers to build new kinds of apps.

Phew, that was quite the brain🧠dump🗑, wasn’t it?

Sounds cool, but what does that actually mean?

Every generation of wireless technology has been defined by the speed of data transmission. So just how fast are we hoping 5G will be? Well, to give you a baseline…our fastest current 4G mobile networks offer about 45Mbps (megabits per second). But Qualcomm believes 5G could achieve browsing and download speeds about 10 to 20 times faster!

What makes this speed improvement possible is that 5G technology makes better use of the radio spectrum. It enables a more devices to access the mobile internet at the same time. Thus, it’s much better at handling thousands of devices simultaneously, without the congestion that was experienced in previous wireless generations.

At this speed, access to low latency services is really important. Why? Low latency is optimized to process a high volume of data messages with minimal delay (latency). This is exactly what you want if your business requires near real-time access to rapidly changing data.

Enter AWS Wavelength.

AWS Wavelength brings AWS services to the edge of the 5G network. It allows you to build the next generation of ultra-low latency apps using familiar AWS services, APIs, and tools. To deploy your app to 5G, simply extend your Amazon Virtual Private Cloud (VPC) to a Wavelength Zone and then create AWS resources like Amazon Elastic Compute Cloud (EC2) instances and Amazon Elastic Block Storage (EBS) volumes.

The other neat news is that AWS Wavelength will be in partnership with Verizon starting in 2020, as well as working with other carriers like Vodafone, SK Telecom, and KDDI to expand Wavelength Zones to more locations by the end of 2020.

👉🏽Don’t forget to check out the docs: aws.amazon.com/wavelength
⚠Sign up to get notified when it’s released.

 

3. AWS DeepComposer: learn Machine Learning with a piano keyboard!

Backstory of why I picked this one…

I do not have a Machine Learning (ML) background. At all.

But I do have a piano and musical background. 🎹🎶I learnt how to play the piano at 4, and I first got into composing when I was about 12 years old. Not having a super fancy piano instructor at the time, I remember wondering how an average person could learn how to compose, regardless of your musical background.

What got launched?

AWS DeepComposer is a machine learning-enabled keyboard for developers that also uses AI (Artificial Intelligence) to create original songs and melodies.

Sounds cool, but what does that actually mean?

AWS DeepComposer includes tutorials, sample code, and training data that can be used to get started building generative models, all without having to write a single line of code! This is great, because it helps encourage people new to ML to still give it a whirl.

Now the other neat thing about AWS DeepComposer, is that it opens the door for you to learn about Generative AI — one of the biggest advancements in AI technology . You’ll learn about Generative Adversarial Networks (GANs), a Generative AI technique that puts two different neural networks against each other to produce new and original digital works based on sample inputs. With AWS DeepComposer, you are training and optimizing GAN models to create original music. 🎶

Is that awesome, or what?

👉🏽Don’t forget to check out the docs: aws.amazon.com/deepcomposer
⚠Sign up to get notified when it’s released.

 

4. Amplify: now it’s ready for iOS and Android devs too!

Backstory of why I picked this one…

I used to be a CSS developer. Joining the Back-End world was an accident for me, since I first assumed I’d always be a Front-End developer.

Amplify makes it easy for developers to build and deploy Full-Stack apps that leverage the cloud. It’s a service that really helps bridge the gap between Front and Back-End development. Seeing Amplify now offer SDKs and libraries for iOS and Android devs sounds even more inclusive and exciting!

What got launched?

The Amplify Framework (open source project for building cloud-enabled mobile and web apps) is ready for iOS and Andriod developers! There are now — in preview— Amplify iOS and Amplify Android libraries for building scalable and secure cloud powered serverless apps.

Sounds cool, but what does that actually mean?

Developers can now add capabilities of Analytics, AI/ML, API (GraphQL and REST), DataStore, and Storage to their mobile apps with these new iOS and Android Amplify libraries.

This release also included support for the Predictions category in Amplify iOS that allows developers to easily add and configure AI/ML use cases with very few lines of code. (And no machine learning experience required!) This allows developers to then accomplish other use cases of text translation, speech to text generation, image recognition, text to speech, insights from text, etc. You can even hook it up to services such as Amazon Rekognition, Amazon Translate, Amazon Polly, Amazon Transcribe, Amazon Comprehend, and Amazon Textract.

👉🏽Don’t forget to check out the docs…
📳Android: aws-amplify.github.io/docs/android/start
📱iOS: aws-amplify.github.io/docs/ios/start

 

5. EC2 Image Builder

Backstory of why I picked this one…

In my 1st year at AWS as a Developer Advocate, I got really into robotics and IoT. I’m not giving that up anytime soon, but for 2020, I’m also excited to serve more customers that are new to core AWS services. You know, things like storage, compute, containers, databases, etc.

Thus, it came as no surprise to me when this new launch caught my eye… 👀

What got launched?

EC2 Image Builder is a service that makes it easier and faster to build and maintain secure container images. It greatly simplifies the creation, patching, testing, distribution, and sharing of Linux or Windows Server images.

Sounds cool, but what does that actually mean?

In the past, creating custom container images felt way too complex and time consuming. Most dev teams had to manually update VMs or build automation scripts to maintain these images.

Can you imagine?

Today, Amazon’s Image Builder service simplifies this process by allowing you to create custom OS images via an AWS GUI environment. You can also use it to build an automated pipeline that customizes, tests, and distributes your images in addition to keeping them secure and up-to-date. Sounds like a win-win to me. 🏆

👉🏽Don’t forget to check out the docs: aws.amazon.com/image-builder

 

¡Gracias por tu tiempo!
~Alejandra 💁🏻‍♀️ & Canela 🐾

Amplify DataStore – Simplify Development of Offline Apps with GraphQL

Post Syndicated from Sébastien Stormacq original https://aws.amazon.com/blogs/aws/amplify-datastore-simplify-development-of-offline-apps-with-graphql/

The open source Amplify Framework is a command line tool and a library allowing web & mobile developers to easily provision and access cloud based services. For example, if I want to create a GraphQL API for my mobile application, I use amplify add api on my development machine to configure the backend API. After answering a few questions, I type amplify push to create an AWS AppSync API backend in the cloud. Amplify generates code allowing my app to easily access the newly created API. Amplify supports popular web frameworks, such as Angular, React, and Vue. It also supports mobile applications developed with React Native, Swift for iOS, or Java for Android. If you want to learn more about how to use Amplify for your mobile applications, feel free to attend one the workshops (iOS or React Native) we prepared for the re:Invent 2019 conference.

AWS customers told us the most difficult tasks when developing web & mobile applications is to synchronize data across devices and to handle offline operations. Ideally, when a device is offline, your customers should be able to continue to use your application, not only to access data but also to create and modify them. When the device comes back online, the application must reconnect to the backend, synchronize the data and resolve conflicts, if any. It requires a lot of undifferentiated code to correctly handle all edge cases, even when using AWS AppSync SDK’s on-device cache with offline mutations and delta sync.

Today, we are introducing Amplify DataStore, a persistent on-device storage repository for developers to write, read, and observe changes to data. Amplify DataStore allows developers to write apps leveraging distributed data without writing additional code for offline or online scenario. Amplify DataStore can be used as a stand-alone local datastore in web and mobile applications, with no connection to the cloud, or the need to have an AWS Account. However, when used with a cloud backend, Amplify DataStore transparently synchronizes data with an AWS AppSync API when network connectivity is available. Amplify DataStore automatically versions data, implements conflict detection and resolution in the cloud using AppSync. The toolchain also generates object definitions for my programming language based on the GraphQL schema developers provide.

Let’s see how it works.

I first install the Amplify CLI and create a React App. This is standard React, you can find the script on my git repo. I add Amplify DataStore to the app with npx amplify-app. npx is specific for NodeJS, Amplify DataStore also integrates with native mobile toolchains, such as the Gradle plugin for Android Studio and CocoaPods that creates custom XCode build phases for iOS.

Now that the scaffolding of my app is done, I add a GraphQL schema representing two entities: Posts and Comments on these posts. I install the dependencies and use AWS Amplify CLI to generate the source code for the objects defined in the GraphQL schema.

# add a graphql schema to amplify/backend/api/amplifyDatasource/schema.graphql
echo "enum PostStatus {
  ACTIVE
  INACTIVE
}

type Post @model {
  id: ID!
  title: String!
  comments: [Comment] @connection(name: "PostComments")
  rating: Int!
  status: PostStatus!
}
type Comment @model {
  id: ID!
  content: String
  post: Post @connection(name: "PostComments")
}" > amplify/backend/api/amplifyDatasource/schema.graphql

# install dependencies 
npm i @aws-amplify/core @aws-amplify/DataStore @aws-amplify/pubsub

# generate the source code representing the model 
npm run amplify-modelgen

# create the API in the cloud 
npm run amplify-push

@model and @connection are directives that the Amplify GraphQL Transformer uses to generate code. Objects annotated with @model are top level objects in your API, they are stored in DynamoDB, you can make them searchable, version them or restrict their access to authorised users only. @connection allows to express 1-n relationships between objects, similarly to what you would define when using a relational database (you can use the @key directive to model n-n relationships).

The last step is to create the React app itself. I propose to download a very simple sample app to get started quickly:

# download a simple react app
curl -o src/App.js https://raw.githubusercontent.com/sebsto/amplify-datastore-js-e2e/master/src/App.js

# start the app 
npm run start

I connect my browser to the app http://localhost:8080and start to test the app.

The demo app provides a basic UI (as you can guess, I am not a graphic designer !) to create, query, and to delete items. Amplify DataStore provides developers with an easy to use API to store, query and delete data. Read and write are propagated in the background to your AppSync endpoint in the cloud. Amplify DataStore uses a local data store via a storage adapter, we ship IndexedDB for web and SQLite for mobile. Amplify DataStore is open source, you can add support for other database, if needed.

From a code perspective, interacting with data is as easy as invoking the save(), delete(), or query() operations on the DataStore object (this is a Javascript example, you would write similar code for Swift or Java). Notice that the query() operation accepts filters based on Predicates expressions, such as item.rating("gt", 4) or Predicates.All.

function onCreate() {
  DataStore.save(
    new Post({
      title: `New title ${Date.now()}`,
      rating: 1,
      status: PostStatus.ACTIVE
    })
  );
}

function onDeleteAll() {
  DataStore.delete(Post, Predicates.ALL);
}

async function onQuery(setPosts) {
  const posts = await DataStore.query(Post, c => c.rating("gt", 4));
  setPosts(posts)
}

async function listPosts(setPosts) {
  const posts = await DataStore.query(Post, Predicates.ALL);
  setPosts(posts);
}

I connect to Amazon DynamoDB console and observe the items are stored in my backend:

There is nothing to change in my code to support offline mode. To simulate offline mode, I turn off my wifi. I add two items in the app and turn on the wifi again. The app continues to operate as usual while offline. The only noticeable change is the _version field is not updated while offline, as it is populated by the backend.

When the network is back, Amplify DataStore transparently synchronizes with the backend. I verify there are 5 items now in DynamoDB (the table name is different for each deployment, be sure to adjust the name for your table below):

aws dynamodb scan --table-name Post-raherug3frfibkwsuzphkexewa-amplify \
                   --filter-expression "#deleted <> :value"            \
                   --expression-attribute-names '{"#deleted" : "_deleted"}' \
                   --expression-attribute-values '{":value" : { "BOOL": true} }' \
                   --query "Count"

5 // <= there are now 5 non deleted items in the table !

Amplify DataStore leverages GraphQL subscriptions to keep track of changes that happen on the backend. Your customers can modify the data from another device and Amplify DataStore takes care of synchronizing the local data store transparently. No GraphQL knowledge is required, Amplify DataStore takes care of the low level GraphQL API calls for you automatically. Real-time data, connections, scalability, fan-out and broadcasting are all handled by the Amplify client and AppSync, using WebSocket protocol under the cover.

We are effectively using GraphQL as a network protocol to dynamically transform model instances to GraphQL documents over HTTPS.

To refresh the UI when a change happens on the backend, I add the following code in the useEffect() React hook. It uses the DataStore.observe() method to register a callback function ( msg => { ... } ). Amplify DataStore calls this function when an instance of Post changes on the backend.

const subscription = DataStore.observe(Post).subscribe(msg => {
  console.log(msg.model, msg.opType, msg.element);
  listPosts(setPosts);
});

Now, I open the AppSync console. I query existing Posts to retrieve a Post ID.

query ListPost {
  listPosts(limit: 10) {
    items {
      id
      title
      status
      rating
      _version
    }
  }
}

I choose the first post in my app, the one starting with 7d8… and I send the following GraphQL mutation:

mutation UpdatePost {
  updatePost(input: {
    id: "7d80688f-898d-4fb6-a632-8cbe060b9691"
    title: "updated title 13:56"
    status: ACTIVE
    rating: 7
    _version: 1
  }) {
    id
    title
    status
    rating
    _lastChangedAt
    _version
    _deleted    
  }
}

Immediately, I see the app receiving the notification and refreshing its user interface.

Finally, I test with multiple devices. I first create a hosting environment for my app using amplify add hosting and amplify publish. Once the app is published, I open the iOS Simulator and Chrome side by side. Both apps initially display the same list of items. I create new items in both apps and observe the apps refreshing their UI in near real time. At the end of my test, I delete all items.

I verify there are no more items in DynamoDB (the table name is different for each deployment, be sure to adjust the name for your table below):

aws dynamodb scan --table-name Post-raherug3frfibkwsuzphkexewa-amplify \
                   --filter-expression "#deleted <> :value"            \
                   --expression-attribute-names '{"#deleted" : "_deleted"}' \
                   --expression-attribute-values '{":value" : { "BOOL": true} }' \
                   --query "Count"

0 // <= all the items have been deleted !

When syncing local data with the backend, AWS AppSync keeps track of version numbers to detect conflicts. When there is a conflict, the default resolution strategy is to automerge the changes on the backend. Automerge is an easy strategy to resolve conflit without writing client-side code. For example, let’s pretend I have an initial Post, and Bob & Alice update the post at the same time:

The original item:

{
   "_version": 1,
   "id": "25",
   "rating": 6,
   "status": "ACTIVE",
   "title": "DataStore is Available"
}
Alice updates the rating:

{
   "_version": 2,
   "id": "25",
   "rating": 10,
   "status": "ACTIVE",
   "title": "DataStore is Available"
}
At the same time, Bob updates the title:

{
   "_version": 2,
   "id": "25",
   "rating": 6,
   "status": "ACTIVE",
   "title": "DataStore is great !"
}
The final item after auto-merge is:

{
   "_version": 3,
   "id": "25",
   "rating": 10,
   "status": "ACTIVE",
   "title": "DataStore is great !"
}

Automerge strictly defines merging rules at field level, based on type information defined in the GraphQL schema. For example List and Map are merged, and conflicting updates on scalars (such as numbers and strings) preserve the value existing on the server. Developers can chose other conflict resolution strategies: optimistic concurrency (conflicting updates are rejected) or custom (an AWS Lambda function is called to decide what version is the correct one). You can choose the conflit resolution strategy with amplify update api. You can read more about these different strategies in the AppSync documentation.

The full source code for this demo is available on my git repository. The app has less than 100 lines of code, 20% being just UI related. Notice that I did not write a single line of GraphQL code, everything happens in the Amplify DataStore.

Your Amplify DataStore cloud backend is available in all AWS Regions where AppSync is available, which, at the time I write this post are: US East (N. Virginia), US East (Ohio), US West (Oregon), Asia Pacific (Mumbai), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), Europe (Frankfurt), Europe (Ireland), and Europe (London).

There is no additional charges to use Amplify DataStore in your application, you only pay for the backend resources you use, such as AppSync and DynamoDB (see here and here for the pricing detail). Both services have a free tier allowing you to discover and to experiment for free.

Amplify DataStore allows you to focus on the business value of your apps, instead of writing undifferentiated code. I can’t wait to discover the great applications you’re going to build with it.

— seb

ICYMI: Serverless Q3 2019

Post Syndicated from James Beswick original https://aws.amazon.com/blogs/compute/icymi-serverless-q3-2019/

This post is courtesy of Julian Wood, Senior Developer Advocate – AWS Serverless

Welcome to the seventh edition of the AWS Serverless ICYMI (in case you missed it) quarterly recap. Every quarter, we share all of the most recent product launches, feature enhancements, blog posts, webinars, Twitch live streams, and other interesting things that you might have missed!

In case you missed our last ICYMI, checkout what happened last quarter here.

ICYMI calendar

Launches/New products

Amazon EventBridge was technically launched in this quarter although we were so excited to let you know, we squeezed it into the Q2 2019 update. If you missed it, EventBridge is the serverless event bus that connects application data from your own apps, SaaS, and AWS services. This allows you to create powerful event-driven serverless applications using a variety of event sources.

The AWS Bahrain Region has opened, the official name is Middle East (Bahrain) and the API name is me-south-1. AWS Cloud now spans 22 geographic Regions with 69 Availability Zones around the world.

AWS Lambda

In September we announced dramatic improvements in cold starts for Lambda functions inside a VPC. With this announcement, you see faster function startup performance and more efficient usage of elastic network interfaces, drastically reducing VPC cold starts.

VPC to VPC NAT

These improvements are rolling out to all existing and new VPC functions at no additional cost. Rollout is ongoing, you can track the status from the announcement post.

AWS Lambda now supports custom batch window for Kinesis and DynamoDB Event sources, which helps fine-tune Lambda invocation for cost optimization.

You can now deploy Amazon Machine Images (AMIs) and Lambda functions together from the AWS Marketplace using using AWS CloudFormation with just a few clicks.

AWS IoT Events actions now support AWS Lambda as a target. Previously you could only define actions to publish messages to SNS and MQTT. Now you can define actions to invoke AWS Lambda functions and even more targets, such as Amazon Simple Queue Service and Amazon Kinesis Data Firehose, and republish messages to IoT Events.

The AWS Lambda Console now shows recent invocations using CloudWatch Logs Insights. From the monitoring tab in the console, you can view duration, billing, and memory statistics for the 10 most recent invocations.

AWS Step Functions

AWS Step Functions example

AWS Step Functions has now been extended to support probably its most requested feature, Dynamic Parallelism, which allows steps within a workflow to be executed in parallel, with a new Map state type.

One way to use the new Map state is for fan-out or scatter-gather messaging patterns in your workflows:

  • Fan-out is applied when delivering a message to multiple destinations, and can be useful in workflows such as order processing or batch data processing. For example, you can retrieve arrays of messages from Amazon SQS and Map sends each message to a separate AWS Lambda function.
  • Scatter-gather broadcasts a single message to multiple destinations (scatter), and then aggregates the responses back for the next steps (gather). This is useful in file processing and test automation. For example, you can transcode ten 500-MB media files in parallel, and then join to create a 5-GB file.

Another important update is AWS Step Functions adds support for nested workflows, which allows you to orchestrate more complex processes by composing modular, reusable workflows.

AWS Amplify

A new Predictions category as been added to the Amplify Framework to quickly add machine learning capabilities to your web and mobile apps.

Amplify framework

With a few lines of code you can add and configure AI/ML services to configure your app to:

  • Identify text, entities, and labels in images using Amazon Rekognition, or identify text in scanned documents to get the contents of fields in forms and information stored in tables using Amazon Textract.
  • Convert text into a different language using Amazon Translate, text to speech using Amazon Polly, and speech to text using Amazon Transcribe.
  • Interpret text to find the dominant language, the entities, the key phrases, the sentiment, or the syntax of unstructured text using Amazon Comprehend.

AWS Amplify CLI (part of the open source Amplify Framework) has added local mocking and testing. This allows you to mock some of the most common cloud services and test your application 100% locally.

For this first release, the Amplify CLI can mock locally:

amplify mock

AWS CloudFormation

The CloudFormation team has released the much-anticipated CloudFormation Coverage Roadmap.

Styled after the popular AWS Containers Roadmap, the CloudFormation Coverage Roadmap provides transparency about our priorities, and the opportunity to provide your input.

The roadmap contains four columns:

  • Shipped – Available for use in production in all public AWS Regions.
  • Coming Soon – Generally a few months out.
  • We’re working on It – Work in progress, but further out.
  • Researching – We’re thinking about the right way to implement the coverage.

AWS CloudFormation roadmap

Amazon DynamoDB

NoSQL Workbench for Amazon DynamoDB has been released in preview. This is a free, client-side application available for Windows and macOS. It helps you more easily design and visualize your data model, run queries on your data, and generate the code for your application.

Amazon Aurora

Amazon Aurora Serverless is a dynamically scaling version of Amazon Aurora. It automatically starts up, shuts down, and scales up or down, based on your application workload.

Aurora Serverless has had a MySQL compatible edition for a while, now we’re excited to bring more serverless joy to databases with the PostgreSQL compatible version now GA.

We also have a useful post on Reducing Aurora PostgreSQL storage I/O costs.

AWS Serverless Application Repository

The AWS Serverless Application Repository has had some useful SAR apps added by Serverless Developer Advocate James Beswick.

  • S3 Auto Translator which automatically converts uploaded objects into other languages specified by the user, using Amazon Translate.
  • Serverless S3 Uploader allows you to upload JPG files to Amazon S3 buckets from your web applications using presigned URLs.

Serverless posts

July

August

September

Tech talks

We hold several AWS Online Tech Talks covering serverless tech talks throughout the year. These are listed in the Serverless section of the AWS Online Tech Talks page.

Here are the ones from Q3:

Twitch

July

August

September

There are also a number of other helpful video series covering Serverless available on the AWS Twitch Channel.

AWS re:Invent

AWS re:Invent

December 2 – 6 in Las Vegas, Nevada is peak AWS learning time with AWS re:Invent 2019. Join tens of thousands of AWS customers to learn, share ideas, and see exciting keynote announcements.

Be sure to take a look at the growing catalog of serverless sessions this year. Make sure to book time for Builders SessionsChalk Talks, and Workshops as these sessions will fill up quickly. The schedule is updated regularly so if your session is currently fully booked, a repeat may be scheduled.

Register for AWS re:Invent now!

What did we do at AWS re:Invent 2018? Check out our recap here: AWS re:Invent 2018 Recap at the San Francisco Loft.

Our friends at IOPipe have written 5 tips for avoiding serverless FOMO at this year’s re:Invent.

AWS Serverless Heroes

We are excited to welcome some new AWS Serverless Heroes to help grow the serverless community. We look forward to some amazing content to help you with your serverless journey.

Still looking for more?

The Serverless landing page has much more information. The Lambda resources page contains case studies, webinars, whitepapers, customer stories, reference architectures, and even more Getting Started tutorials.

 

Improve Your App Testing With Amplify Console’s Pull Requests Previews and Cypress Testing

Post Syndicated from Sébastien Stormacq original https://aws.amazon.com/blogs/aws/improve-your-app-testing-with-amplify-consoles-pull-requests-previews-and-cypress-testing/

Amplify Console allows developers to easly configure a Git-based workflow for continuous deployment and hosting of fullstack serverless web apps. Fullstack serverless apps comprise of backend resources such as GraphQL APIs, Data and File Storage, Authentication, or Analytics, integrated with a frontend framework such as React, Gatsby, or Angular. You can read more about the Amplify Console in a previous article I wrote.

Today, we are announcing the ability to create preview URLs and to run end-to-end tests on pull requests before releasing code to production.

Pull Request previews
You can now configure Amplify Console to deploy your application to a unique URL every time a developer submits a pull request to your Git repository. The preview URL is completely different from the one used by the production site. You can see how changes look before merging the pull request into the main branch of your code repository, triggering a new release in the Amplify Console. For fullstack apps with backend environments provisioned via the Amplify CLI, every pull request spins up an ephemeral backend that is deleted when the pull request is closed. You can test changes in complete isolation from the production environment. Amplify Console creates backend infrastructures for pull requests on private git repositories only. This allows to avoid incurring extra costs in case of unsolicited pull requests.

To learn how it works, let’s start a web application with a cloud-based authentication backend, and deploy it on Amplify Console. I first create a React application (check here to learn how to install React).

npx create-react-app amplify-console-demo                                                
cd amplify-console-demo

I initialize the Amplify environment (learn how to install the Amplify CLI first). I add a cloud based authentication backend powered by Amazon Cognito. I accept all the defaults answers proposed by Amplify CLI.

npm install aws-amplify aws-amplify-react
amplify init
amplify add auth
amplify push

I then modify src/App.js to add the front end authentication user interface. The code is available in the AWS Amplify documentation. Once ready, I start the local development server to test the application locally.

npm run start

I point my browser to http://localhost:8080 to verify the scafolding (the below screenshot is taken from my AWS Cloud 9 development environment). I click Create account to create a user, verify the SignUp flow, and authenticate to the app.

After signing up, I see the application page.

There are two important details to note. First, I am using a private GitHub repository. Amplify Console only creates backend infrastructure on pull requests for private repositories, to avoid creating unnecessary infrastructure for unsollicited pull requests. Second, the Amplify Console build process looks for dependencies in package-lock.json only. This is why I added the amplify packages with npm and not with yarn.

When I am happy with my app, I push the code to a GitHub repo (let’s assume I already did git remote add origin ...).

git add amplify
git commit -am "initial commit"
git push origin master

The next step consists of configuring Amplify Console to build and deploy my app on every git commit. I login to the Amplify Console, click Connect App, choose GitHub as repository and click Continue (the first time I do this, I need to authenticate on GitHub, using my GitHub username and password)

I select my repository and the branch I want to use as source:

Amplify Console detects the type of project and proposes a build file. I select the name of my environment (dev). The first time I use Amplify Console, I follow the instructions to create a new service role. This role authorises Amplify Console to access AWS backend services on my behalf.

I click Next. I review the settings and click Save and Deploy. After a few seconds or minutes, my application is ready. I can point my browser to the deployment URL and verify the app is working correctly.

Now, let’s enable previews for pull requests. Click Preview on the left menu and Enable Previews. To enable the previews, Amplify Console requires an app to be installed in my GitHub account. I follow the instructions provided by the console to configure my GitHub account. Once set up, I select a branch, click Manage to enable / disable the pull request previews. (At anytime, I can uninstall the Amplify app from my GitHub account by visiting the Applications section of my GitHub account’s settings.)

Now that the mechanism is in place, let’s create a pull request.

I edit App.js directly on GitHub. I customize the withAuthenticator component to change the color of the Sign In button from orange to green. I save the changes and I create a pull request.

On the Pull Request detail page, I click Show all checks to get the status of the Amplify Console test. I see AWS Amplify Console Web Preview in progress. Amplify Console creates a full backend environment to test the pull request, to build and to deploy the frontend.

Eventually, I see All checks have passed and a green mark. I click Details to get the preview url. In case of an error, you can see the detailled log file of the build phase in the Amplify Console.

I can also check the status of the preview in the Amplify Console.

I point my browser to the preview URL to test my change. I can see the green Sign In button instead of the orange one.

When I try to authenticate using the username and password I created previously, I receive an User does not exist error message because this preview URL points to a different backend than the main application. I can see two Cognito user pools in the Cognito console, one for each environment.

I can control who can access the preview URL using similar access control settings that I use for the main URL.

When I am happy with the proposed changes, I merge the pull request on GitHub to trigger a new build and to deploy the change to the production environment. Amplify Console deletes the preview environment upon merging. The ephemeral backend environment created for the pull request also gets deleted.

Cypress testing
In addition to previewing changes before merging them to the main branch, we also added the capability to run end to end tests during your build process. You can use your favorite test framework to add unit or end-to-end tests to your application and automatically run the tests during the build phase. When you use Cypress test framework, Amplify Console detects the tests in your source tree and automatically adds the testing phase in your application build process.

Only projects that are passing all tests are pushed down your pipeline to the deployment phase. You can learn more about this and follow step by step instructions we posted a few weeks ago.

These two additions to Amplify Console allow you to gain higher confidence in the robustness of your pipeline and the quality of the code delivered to your production environment.

Availability
Web previews are available in all Regions where AWS Amplify Console is available today, at no additional cost on top of the regular Amplify Console pricing. With the AWS Free Usage Tier, you can get started for free. Upon sign up, new AWS customers receive 1,000 build minutes per month for the build and deploy feature, and 15 GB served per month and 5 GB data storage per month for the hosting.

— seb

Amplify Console – Hosting for Fullstack Serverless Web Apps

Post Syndicated from Sébastien Stormacq original https://aws.amazon.com/blogs/aws/amplify-console-hosting-for-fullstack-serverless-web-apps/

AWS Amplify Console is a fullstack web app hosting service, with continuous deployment from your preferred source code repository. Amplify Console has been introduced in November 2018 at AWS re:Invent. Since then, the team has been listening to customer feedback and iterated quickly to release several new features, here is a short re:Cap.

Instant Cache Invalidation
Amplify Console allows to host single page web apps or static sites with serverless backends via a content delivery network, or CDN. A CDN is a network of distributed servers that cache files at edge locations across the world enabling low latency distribution of your web file assets.

Previously, updating content on the CDN required manually invalidating the cache and waiting 15-20 minutes for changes to propagate globally. To make frequent updates, developers found workarounds such as setting lower time-to-live (TTLs) on asset headers which enables faster updates, but adversely impacts performance. Now, you no longer have to make a tradeoff between faster deployments and faster performance. On every commit code to your repository, the Amplify Console builds and deploys changes to the CDN that are viewable immediately in the browser.

“Deploy To Amplify Console” Button

Deploy To Amplify Console

When publishing your project source code on GitHub, you can make it easy for other developers to build and deploy your application by providing a “Deploy To Amplify Console” button in the Readme document. Clicking on that button will open Amplify Console and propose a three step process to deploy your code.

You test this yourself with these example projects and have a look at the documentation. Adding a button to your own code repository is as easy as adding this line in your Readme document (be sure to replace the username and repository name in the GitHub URL):

[![amplifybutton](https://oneclick.amplifyapp.com/button.svg)](https://console.aws.amazon.com/amplify/home#/deploy?repo=https://github.com/username/repository)

Manual Deploy
I think it is a good idea to version control everything, including simple web site where you are the only developer. But just in case you do not want to use a source code repository as source for your deployment, Amplify Console allows to deploy a zip file, a local folder on your laptop, an Amazon S3 bucket or any HTTPS URL, such as a shared repository on Dropbox.

When creating a new Amplify Console project, select Deploy without Git Provider option. 
Then choose your source file (your laptop, Amazon S3 or an HTTPS URI)

AWS CloudFormation Integration
Developers love automation. Deploying code or infrastructure is no different : you must ensure your infrastructure deployments are automated and repeatable. AWS CloudFormation allows you to automate the creation of infrastruture in the cloud based on a YAML or JSON description. Amplify Console added three new resource types to AWS CloudFormation:

  • AWS::Amplify::App
  • AWS::Amplify::Branch
  • AWS::Amplify::Domain

These allows you respectively to create a new Amplify Console app, to define the Git branch, and the DNS domain name to use.

AWS CloudFormation connects to your source code repository to add a webhook to it. You need to include your Github Personal Access Token to allow this to happen, this blog post has all the details. Remember to not hardcode credentials (or OAuth tokens) into your Cloudformation templates, use parameters instead.

Deploy Multiple Git Branches
We believe your CI/CD tools must adapt to your team workflow, not the other way around. Amplify Console supports branch pattern deployments, allowing you to automatically deploy branches that match a specific pattern without any extra configuration. Pattern matching is based on regular expresssions.

When you want to test a new feature, you typically create a new branch in Git. Amplify Console and the Amplify CLI are now detecting this and will provision a separate backend and hosting infrastructure for your serverless app.

To enable branch detection, use the left menu, click on General > Edit and turn on Branch Autodetection:

Custom HTTP Headers
You can customize Amplify Console to send customized HTTP response headers. Response headers can be used for debugging, security, or informational purposes. To add your custom headers, you select App Settings > Build Settings and then edit the buildspec. For example, to enforce TLS transport and prevent XSS attacks, you can add the following headers:

customHeaders:
        - pattern: '**/*'
          headers:
                - key: 'Strict-Transport-Security'
                        value: 'max-age=31536000; includeSubDomains'
                - key: 'X-Frame-Options'
                        value: 'X-Frame-Options: SAMEORIGIN'
                - key: 'X-XSS-Protection'
                        value: 'X-XSS-Protection: 1; mode=block'
                - key: 'X-Content-Type-Options'
                        value: 'X-Content-Type-Options: nosniff'
                - key: 'Content-Security-Policy'
                        value: "default-src 'self'"

The documentation has more details.

Custom Containers for Build
Last but not least, we made several changes to the build environment. Amplify Console uses AWS CodeBuild behind the scenes. The default build container image is now based on Amazon Linux 2 and has Serverless Application Model (SAM) CLI pre-installed. If, for whatever reasons you want to use your own container for the build, you can configure Amplify Console to do so. Select App Settings > Build Settings :

And then edit the build image setting

There are a few requirements on the container image: it has to have cURL, git, OpenSSH and, if you are building NodeJS projects, node and npm. As usual, the details are in the documentation.

Each of these new features has been driven by your feedback, so please continue to tell us what is important for you by submittin, and expect to see more changes coming in the second part of the year and beyond.

— seb

ICYMI: Serverless Q2 2019

Post Syndicated from Eric Johnson original https://aws.amazon.com/blogs/compute/icymi-serverless-q2-2019/

This post is courtesy of Moheeb Zara, Senior Developer Advocate – AWS Serverless

Welcome to the sixth edition of the AWS Serverless ICYMI (in case you missed it) quarterly recap. Every quarter, we share all of the most recent product launches, feature enhancements, blog posts, webinars, Twitch live streams, and other interesting things that you might have missed!

In case you missed our last ICYMI, checkout what happened last quarter here.

April - June 2019

Amazon EventBridge

Before we dive in to all that happened in Q2, we’re excited about this quarter’s launch of Amazon EventBridge, the serverless event bus that connects application data from your own apps, SaaS, and AWS-as-a-service. This allows you to create powerful event-driven serverless applications using a variety of event sources.

Our very own AWS Solutions Architect, Mike Deck, sat down with AWS Serverless Hero Jeremy Daly and recorded a podcast on Amazon EventBridge. It’s a worthy listen if you’re interested in exploring all the features offered by this launch.

Now, back to Q2, here’s what’s new.

AWS Lambda

Lambda Monitoring

Amazon CloudWatch Logs Insights now allows you to see statistics from recent invocations of your Lambda functions in the Lambda monitoring tab.

Additionally, as of June, you can monitor the [email protected] functions associated with your Amazon CloudFront distributions directly from your Amazon CloudFront console. This includes a revamped monitoring dashboard for CloudFront distributions and [email protected] functions.

AWS Step Functions

Step Functions

AWS Step Functions now supports workflow execution events, which help in the building and monitoring of even-driven serverless workflows. Automatic Execution event notifications can be delivered upon start/completion of CloudWatch Events/Amazon EventBridge. This allows services such as AWS Lambda, Amazon SNS, Amazon Kinesis, or AWS Step Functions to respond to these events.

Additionally you can use callback patterns to automate workflows for applications with human activities and custom integrations with third-party services. You create callback patterns in minutes with less code to write and maintain, run without servers and infrastructure to manage, and scale reliably.

Amazon API Gateway

API Gateway Tag Based Control

Amazon API Gateway now offers tag-based access control for WebSocket APIs using AWS Identity and Access Management (IAM) policies, allowing you to categorize API Gateway resources for WebSocket APIs by purpose, owner, or other criteria.  With the addition of tag-based access control to WebSocket resources, you can now give permissions to WebSocket resources at various levels by creating policies based on tags. For example, you can grant full access to admins to while limiting access to developers.

You can now enforce a minimum Transport Layer Security (TLS) version and cipher suites through a security policy for connecting to your Amazon API Gateway custom domain.

In addition, Amazon API Gateway now allows you to define VPC Endpoint policies, enabling you to specify which Private APIs a VPC Endpoint can connect to. This enables granular security control using VPC Endpoint policies.

AWS Amplify

Amplify CLI (part of the open source Amplify Framework) now includes support for adding and configuring AWS Lambda triggers for events when using Amazon Cognito, Amazon Simple Storage Service, and Amazon DynamoDB as event sources. This means you can setup custom authentication flows for mobile and web applications via the Amplify CLI and Amazon Cognito User Pool as an authentication provider.

Amplify Console

Amplify Console,  a Git-based workflow for continuous deployment and hosting for fullstack serverless web apps, launched several updates to the build service including SAM CLI and custom container support.

Amazon Kinesis

Amazon Kinesis Data Firehose can now utilize AWS PrivateLink to securely ingest data. AWS PrivateLink provides private connectivity between VPCs, AWS services, and on-premises applications, securely over the Amazon network. When AWS PrivateLink is used with Amazon Kinesis Data Firehose, all traffic to a Kinesis Data Firehose from a VPC flows over a private connection.

You can now assign AWS resource tags to applications in Amazon Kinesis Data Analytics. These key/value tags can be used to organize and identify resources, create cost allocation reports, and control access to resources within Amazon Kinesis Data Analytics.

Amazon Kinesis Data Firehose is now available in the AWS GovCloud (US-East), Europe (Stockholm), Asia Pacific (Seoul), Asia Pacific (Singapore), Asia Pacific (Sydney), Asia Pacific (Tokyo), and EU (London) regions.

For a complete list of where Amazon Kinesis Data Analytics is available, please see the AWS Region Table.

AWS Cloud9

Cloud9 Quick Starts

Amazon Web Services (AWS) Cloud9 integrated development environment (IDE) now has a Quick Start which deploys in the AWS cloud in about 30 minutes. This enables organizations to provide developers a powerful cloud-based IDE that can edit, run, and debug code in the browser and allow easy sharing and collaboration.

AWS Cloud9 is also now available in the EU (Frankfurt) and Asia Pacific (Tokyo) regions. For a current list of supported regions, see AWS Regions and Endpoints in the AWS documentation.

Amazon DynamoDB

You can now tag Amazon DynamoDB tables when you create them. Tags are labels you can attach to AWS resources to make them easier to manage, search, and filter.  Tagging support has also been extended to the AWS GovCloud (US) Regions.

DynamoDBMapper now supports Amazon DynamoDB transactional API calls. This support is included within the AWS SDK for Java. These transactional APIs provide developers atomic, consistent, isolated, and durable (ACID) operations to help ensure data correctness.

Amazon DynamoDB now applies adaptive capacity in real time in response to changing application traffic patterns, which helps you maintain uninterrupted performance indefinitely, even for imbalanced workloads.

AWS Training and Certification has launched Amazon DynamoDB: Building NoSQL Database–Driven Applications, a new self-paced, digital course available exclusively on edX.

Amazon Aurora

Amazon Aurora Serverless MySQL 5.6 can now be accessed using the built-in Data API enabling you to access Aurora Serverless with web services-based applications, including AWS LambdaAWS AppSync, and AWS Cloud9. For more check out this post.

Sharing snapshots of Aurora Serverless DB clusters with other AWS accounts or publicly is now possible. We are also giving you the ability to copy Aurora Serverless DB cluster snapshots across AWS regions.

You can now set the minimum capacity of your Aurora Serverless DB clusters to 1 Aurora Capacity Unit (ACU). With Aurora Serverless, you specify the minimum and maximum ACUs for your Aurora Serverless DB cluster instead of provisioning and managing database instances. Each ACU is a combination of processing and memory capacity. By setting the minimum capacity to 1 ACU, you can keep your Aurora Serverless DB cluster running at a lower cost.

AWS Serverless Application Repository

The AWS Serverless Application Repository is now available in 17 regions with the addition of the AWS GovCloud (US-West) region.

Region support includes Asia Pacific (Mumbai, Singapore, Sydney, Tokyo), Canada (Central), EU (Frankfurt, Ireland, London, Paris, Stockholm), South America (São Paulo), US West (N. California, Oregon), and US East (N. Virginia, Ohio).

Amazon Cognito

Amazon Cognito has launched a new API – AdminSetUserPassword – for the Cognito User Pool service that provides a way for administrators to set temporary or permanent passwords for their end users. This functionality is available for end users even when their verified phone or email are unavailable.

Serverless Posts

April

May

June

Events

Events this quarter

Senior Developer Advocates for AWS Serverless spoke at several conferences this quarter. Here are some recordings worth watching!

Tech Talks

We hold several AWS Online Tech Talks covering serverless tech talks throughout the year, so look out for them in the Serverless section of the AWS Online Tech Talks page. Here are the ones from Q2.

Twitch

Twitch Series

In April, we started a 13-week deep dive into building APIs on AWS as part of our Twitch Build On series. The Building Happy Little APIs series covers the common and not-so-common use cases for APIs on AWS and the features available to customers as they look to build secure, scalable, efficient, and flexible APIs.

There are also a number of other helpful video series covering Serverless available on the AWS Twitch Channel.

Build with Serverless on Twitch

Serverless expert and AWS Specialist Solutions architect, Heitor Lessa, has been hosting a weekly Twitch series since April. Join him and others as they build an end-to-end airline booking solution using serverless. The final episode airs on August 7th at Wednesday 8:00am PT.

Here’s a recap of the last quarter:

AWS re:Invent

AWS re:Invent 2019

AWS re:Invent 2019 is around the corner! From December 2 – 6 in Las Vegas, Nevada, join tens of thousands of AWS customers to learn, share ideas, and see exciting keynote announcements. Be sure to take a look at the growing catalog of serverless sessions this year.

Register for AWS re:Invent now!

What did we do at AWS re:Invent 2018? Check out our recap here: AWS re:Invent 2018 Recap at the San Francisco Loft

AWS Serverless Heroes

We urge you to explore the efforts of our AWS Serverless Heroes Community. This is a worldwide network of AWS Serverless experts with a diverse background of experience. For example, check out this post from last month where Marcia Villalba demonstrates how to set up unit tests for serverless applications.

Still looking for more?

The Serverless landing page has lots of information. The Lambda resources page contains case studies, webinars, whitepapers, customer stories, reference architectures, and even more Getting Started tutorials.

New – Local Mocking and Testing with the Amplify CLI

Post Syndicated from Danilo Poccia original https://aws.amazon.com/blogs/aws/new-local-mocking-and-testing-with-the-amplify-cli/

The open source Amplify Framework provides a set of libraries, user interface (UI) components, and a command line interface (CLI) that make it easier to add sophisticated cloud features to your web or mobile apps by provisioning backend resources using AWS CloudFormation.

A comment I often get when talking with our customers, is that when you are adding new features or solving bugs, it is important to iterate as fast as possible, getting a quick feedback from your actions. How can we improve their development experience?

Well, last week the Amplify team launched the new Predictions category, to let you quickly add machine learning capabilities to your web or mobile app. Today, they are doing it again. I am very happy to share that you can now use the Amplify CLI to mock some of the most common cloud services it provides, and test your application 100% locally!

By mocking here I mean that instead of using the actual backend component, an API in the case of cloud services, a local, simplified emulation of that API is available instead. This emulation provides the basic functionality that you need for testing during development, but not the full behavior you’d get from the production service.

With this new mocking capability you can test your changes quickly, without the need of provisioning or updating the cloud resources you are using at every step. In this way, you can set up unit and integration tests that can be executed rapidly, without affecting your cloud backend. Depending on the architecture of your app, you can set up automatic testing in your CI/CD pipeline without provisioning backend resources.

This is really useful when editing AWS AppSync resolver mapping templates, written in Apache Velocity Template Language (VTL), which take your requests as input, and output a JSON document containing the instructions for the resolver. You can now have immediate feedback on your edits, and test if your resolvers work as expected without having to wait for a deployment for every update.

For this first release, the Amplify CLI can mock locally:

API Mocking
Let’s do a quick overview of what you can do. For example, let’s create a sample app that helps people store and share the location of those nice places that allow you to refill your reusable water bottle and reduce plastic waste.

To install the Amplify CLI, I need Node.js (version >= 8.11.x) and npm (version >= 5.x):

npm install -g @aws-amplify/cli
amplify configure

Amplify supports lots of different frameworks, for this example I am using React and I start with a sample app (npx requires npm >= 5.2.x):

npx create-react-app refillapp
cd refillapp

I use the Amplify CLI to inizialize the project and add an API. The Amplify CLI are interactive, asking you questions that drive the configuration of your backend. In this case, when asked, I select to add a GraphQL API.

amplify init
amplify add api

During the creation of the API, I edit the GraphQL schema, and define a RefillLocation in this way:

type RefillLocation @model {
  id: ID!
  name: String!
  description: String
  streetAddress: String!
  city: String!
  stateProvinceOrRegion: String
  zipCode: String!
  countryCode: String!
}

The fields that have an exclamation mark ! at the end are mandatory. The other fields are optional, and can be omitted when creating a new object.

The @model you see in the first line is a directive using GraphQL Transform to define top level object types in your API that are backed by DynamoDB and generate for you all the necessary CRUDL (create, read, update, delete, and list) queries and mutations, and the subscriptions to be notified of such mutations.

Now, I would normally need to run amplify push to configure and provision the backend resources required by the project (AppSync and DynamoDB in this case). But to get a quick feedback, I use the new local mocking capability running this command:

amplify mock

Alternatively, I can use the amplify mock api command to specifically mock just my GraphQL API. It would be the same at this stage, but it can be handy when using more than one mocking capability at a time.

The output of the mock command gives you some information on what it does, and what you can do, including the AppSync Mock endpoint:

GraphQL schema compiled successfully.

Edit your schema at /MyCode/refillapp/amplify/backend/api/refillapp/schema.graphql or place .graphql files in a directory at /MyCode/refillapp/amplify/backend/api/refillapp/schema

Creating table RefillLocationTable locally

Running GraphQL codegen

✔ Generated GraphQL operations successfully and saved at src/graphql

AppSync Mock endpoint is running at http://localhost:20002

I keep the mock command running in a terminal window to get feedback of possible errors in my code. For example, when I edit a VTL template, the Amplify CLI recognizes that immediately, and generates the updated code for the resolver. In case of a mistake, I get an error from the running mock command.

The AppSync Mock endpoint gives you access to:

I can now run GraphQL queries, mutations, and subscriptions locally for my API, using a web interface. For example, to create a new RefillLocation I build the mutation visually, like this:

To get the list of the RefillLocation objects in a city, I build the query using the same web interface, and run it against the local DynamoDB storage:

When I am confident that my data model is correct, I start building the frontend code of my app, editing the App.js file of my React app, and add functionalities that I can immediately test, thanks to local mocking.

To add the Amplify Framework to my app, including the React extensions, I use Yarn:

yarn add aws-amplify
yarn add aws-amplify-react

Now, using the Amplify Framework library, I can write code like this to run a GraphQL operation:

import API, { graphqlOperation } from '@aws-amplify/api';
import { createRefillLocation } from './graphql/mutations';

const refillLocation = {
  name: "My Favorite Place",
  streetAddress: "123 Here or There",
  zipCode: "12345"
  city: "Seattle",
  countryCode: "US"
};

await API.graphql(graphqlOperation(createRefillLocation, { input: refillLocation }));

Storage Mocking
I now want to add a new feature to my app, to let users upload and share pictures of a RefillLocation. To do so, I add the Storage category to the configuration of my project and select “Content” to use S3:

amplify add storage

Using the Amplify Framework library, I can now, straight from the browser, put, get, or remove objects from S3 using the following syntax:

import Storage from '@aws-amplify/storage';

Storage.put(name, file, {
  level: 'public'
})
.then(result => console.log(result))
.catch(err => console.log(err));

Storage.get(file, {
  level: 'public'
})
.then(result => {
  console.log(result);
  this.setState({ imageUrl: result });
  fetch(result);
})
.catch(err => alert(err));

All those interactions with S3 are marked as public, because I want my users to share their pictures with each other publicly, but the Amplify Framework supports different access levels, such as private, protected, and public. You can find more information on this in the File Access Levels section of the Amplify documentation.

Since S3 storage is supported by this new mocking capability, I use again amplify mock to test my whole application locally, including the backend used by my GraphQL API (AppSync and DynamoDB) and my content storage (S3).

If I want to test only part of my application locally, I can use amplify mock api or amplify mock storage to have only the GraphQL API, or the S3 storage, mocked locally.

Available Now
There are lots of other features that I didn’t have time to cover in this post, the best way to learn is to be curious and get hands on! You can start using Amplify by following the get-started tutorial.

Here you can find a great walkthrough of the features, and a description of how we collaborated with the open source community for this release.

Being able to mock and test your application locally can help you build and refine your ideas faster, let us know what you think in the Amplify CLI GitHub repository.

Danilo

Amplify Framework Update – Quickly Add Machine Learning Capabilities to Your Web and Mobile Apps

Post Syndicated from Danilo Poccia original https://aws.amazon.com/blogs/aws/amplify-framework-update-quickly-add-machine-learning-capabilities-to-your-web-and-mobile-apps/

At AWS, we want to put machine learning in the hands of every developer. For example, we have pre-trained AI services for areas such as computer vision and language that you can use without any expertise in machine learning. Today we are making another step in that direction with the addition of a new Predictions category to the Amplify Framework. In this way, you can add and configure AI/ML uses cases for your web or mobile application with few lines of code!

AWS Amplify consists of a development framework and developer services that make super easy to build mobile and web applications on AWS. The open-source Amplify Framework provides an opinionated set of libraries, user interface (UI) components, and a command line interface (CLI) to build a cloud backend and integrate it with your web or mobile apps. Amplify leverages a core set of AWS services organized into categories, including storage, authentication & authorization, APIs (GraphQL and REST), analytics, push notifications, chat bots, and AR/VR.

Using the Amplify Framework CLI, you can interactively initialize your project with amplify init. Then, you can go through your storage (amplify add storage) and user authentication & authorization (amplify add auth) options.

Now, you can also use amplify add predictions to configure your app to:

  • Identify text, entities, and labels in images using Amazon Rekognition, or identify text in scanned documents to get the contents of fields in forms and information stored in tables using Amazon Textract.
  • Convert text into a different language using Amazon Translate, text to speech using Amazon Polly, and speech to text using Amazon Transcribe.
  • Interpret text to find the dominant language, the entities, the key phrases, the sentiment, or the syntax of unstructured text using Amazon Comprehend.

You can select to have each of the above actions available only to authenticated users of your app, or also for guest, unauthenticated users. Based on your inputs, Amplify configures the necessary permissions using AWS Identity and Access Management (IAM) roles and Amazon Cognito.

Let’s see how Predictions works for a web application. For example, to identify text in an image using Amazon Rekognition directly from the browser, you can use the following JavaScript syntax and pass a file object:

Predictions.identify({
  text: {
    source: file
    format: "PLAIN" # "PLAIN" uses Amazon Rekognition
  }
}).then((result) => {...})

If the image is stored on Amazon S3, you can change the source to link to the S3 bucket selected when adding storage to this project. You can also change the format to analyze a scanned document using Amazon Textract. Here’s how to extract text from a form in a document stored on S3:

Predictions.identify({
  text: {
    source: { key: "my/image" }
    format: "FORM" # "FORM" or "TABLE" use Amazon Textract
  }
}).then((result) => {...})

Here’s an example of how to interpret text using all the pre-trained capabilities of Amazon Comprehend:

Predictions.interpret({
  text: {
    source: {
      text: "text to interpret",
    },
    type: "ALL"
  }
}).then((result) => {...})

To convert text to speech using Amazon Polly, using the language and the voice selected when adding the prediction, and play it back in the browser, you can use the following code:

Predictions.convert({
  textToSpeech: {
    source: {
      text: "text to generate speech"
    }
  }
}).then(result => {
  var audio = new Audio();
  audio.src = result.speech.url;
  audio.play();
})

Available Now
You can start building you next web or mobile app using Amplify today by following the get-started tutorial here and give us your feedback in the Amplify Framework Github repository.

There are lots of other options and features available in the Predictions category of the Amplify Framework. Please see this walkthrough on the AWS Mobile Blog for an in-depth example of building a machine-learning powered app.

It has never been easier to add machine learning functionalities to a web or mobile app, please let me know what you’re going to build next.

Danilo