Category: AWS Lambda

Many organizations require durable automated code delivery for their applications. They leverage multi-account continuous integration/continuous deployment (CI/CD) pipelines to deploy code and run automated tests in multiple environments before deploying to Production. In cases where the testing strategy is release specific, you must update the pipeline before every release. Traditional pipeline stages are predefined and […]

It is crucial to examine every functional area when firms reorient their operations toward sustainable practices. Making informed decisions is necessary to reduce the environmental effect of an IT stack when creating, deploying, and maintaining it. To build a sustainable business for our customers and for the world we all share, we have deployed data […]

Everything fails all the time — Werner Vogels, AWS CTO At the moment of imminent failure, you want to avoid an unlucky deployment. I’ll start here with a short story that demonstrates the purpose of this post. The DevOps team has just started a database upgrade with a planned outage of 30 minutes. The team […]

Many developers today seek to improve productivity by finding better ways to collaborate, enhance code quality and automate repetitive tasks. We hear from some of our customers that they would like to leverage services such as AWS CloudFormation, AWS CodeBuild and other AWS Developer Tools to manage their AWS resources while continuing to use their […]

AWS customers, regardless of size and market segment, constantly seek to improve application performance while reducing operational costs. Today, Amazon DevOps Guru generates proactive insights that enable you to reduce the cost and improve the performance of your AWS Lambda application. By proactively analyzing your application and making these cost-saving and/or performance-improving recommendations, DevOps Guru […]

Amazon DevOps Guru is a fully managed service that uses machine learning (ML) to continuously analyze and consolidate operational data streams from multiple sources, such as Amazon CloudWatch metrics, AWS Config, AWS CloudFormation, AWS X-Ray, and provide you with a single console dashboard. This dashboard helps customers improve operational performance and avoid expensive downtime by […]

Applying various transformations to images at scale is an easily parallelized and scaled task. As a Computer Vision research team at Amazon, we occasionally find that the amount of image data we are dealing with can’t be effectively computed on a single machine, but also isn’t large enough to justify running a large and potentially […]

Critical business applications are monitored in order to prevent anomalies from negatively impacting their operational performance and availability. Amazon DevOps Guru is a Machine Learning (ML) powered solution that aids operations by detecting anomalous behavior and providing insights and recommendations for how to address the root cause before it impacts the customer. This post demonstrates how Amazon […]

Amazon CodeGuru Profiler recently began providing recommendations for applications written in Python. Additionally, the new automated onboarding process for Lambda functions makes it even easier to use CodeGuru Profiler with serverless applications built on Lambda. This post highlights these new features by explaining how to set up and utilize Codeguru Profiler on an AWS Lambda function written in Python.

AWS Lambda launched support for packaging and deploying functions as container images at re:Invent 2020. In the post working with Lambda layers and extensions in container images, we demonstrated packaging Lambda Functions with layers while using container images. This post will teach you to use AWS CodePipeline to deploy docker images for microservices architecture involving […]