AWS Compute Blog

Bryan Liston

Author: Bryan Liston

Implementing Serverless Manual Approval Steps in AWS Step Functions and Amazon API Gateway

Ali Baghani, Software Development Engineer A common use case for AWS Step Functions is a task that requires human intervention (for example, an approval process). Step Functions makes it easy to coordinate the components of distributed applications as a series of steps in a visual workflow called a state machine. You can quickly build and […]

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Amazon Kinesis Firehose Data Transformation with AWS Lambda

Shiva Narayanaswamy, Solution Architect Amazon Kinesis Firehose is a fully managed service for delivering real-time streaming data to destinations such as Amazon S3, Amazon Redshift, or Amazon Elasticsearch Service (Amazon ES). You configure your data producers to send data to Firehose and it automatically delivers the data to the specified destination. You can send data […]

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Authorizing Access Through a Proxy Resource to Amazon API Gateway and AWS Lambda Using Amazon Cognito User Pools

Ed Lima, Solutions Architect Want to create your own user directory that can scale to hundreds of millions of users? Amazon Cognito user pools are fully managed so that you don’t have to worry about the heavy lifting associated with building, securing, and scaling authentication to your apps. The AWS Mobile blog post Integrating Amazon […]

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Resize Images on the Fly with Amazon S3, AWS Lambda, and Amazon API Gateway

John Pignata, Solutions Architect With the explosion of device types used to access the Internet with different capabilities, screen sizes, and resolutions, developers must often provide images in an array of sizes to ensure a great user experience. This can become complex to manage and drive up costs. Images stored using Amazon S3 are often […]

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Seamlessly Scale Predictions with AWS Lambda and MXNet

Sunil Mallya, Solutions Architect Building AI solutions at scale can be challenging, in this blog we’ll look at how to leverage AWS Lambda and MXNet to build a scalable prediction pipeline. Companies that leverage machine and deep learning invest in much more than just training models. They have sophisticated pipelines that include the following stages: […]

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Managing Your AWS Resources Through a Serverless Policy Engine

Stephen Liedig, Solutions Architect Customers are using AWS Lambda in new and interesting ways every day, from data processing of Amazon S3 objects, Amazon DynamoDB streams, and Amazon Kinesis triggers, to providing back-end processing logic for Amazon API Gateway. In this post, I explore ways in which you can use Lambda as a policy engine […]

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Continuous Deployment for Serverless Applications

With a continuous deployment infrastructure, developers can quickly and safely release new features and bug fixes for their applications without manually triggering any deployment scripts. Amazon Web Services offers a number of products that make the creation of deployment pipelines easier: AWS CodePipeline AWS CodeCommit AWS CodeBuild – newly launched A typical serverless application consists […]

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Scripting Languages for AWS Lambda: Running PHP, Ruby, and Go

Dimitrij Zub, Solutions Architect Raphael Sack, Technical Trainer In our daily work with partners and customers, we see a lot of different amazing skills, expertise and experience in many fields, and programming languages. From languages that have been around for a while to languages on the cutting edge, many teams have developed a deep understanding […]

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Serverless at re:Invent 2016 – Wrap-up

The re:Invent 2016 conference was an exciting week to be working on serverless at AWS. We announced new features like support for C# and dead letter queues, and launched new application constructs with Lambda such as Lambda@Edge, AWS Greengrass, Amazon Lex, and AWS Step Functions. In addition we also added support for surfacing services built […]

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Robust Serverless Application Design with AWS Lambda Dead Letter Queues

Gene Ting, Solutions Architect AWS Lambda is a serverless, event-driven compute service that allows developers to bring their functions to the cloud easily. A key challenge that Lambda developers often face is to create solutions that handle exceptions and failures gracefully. Some examples include: Notifying operations support when a function fails with context Sending jobs […]

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