Category: Compute

Gitlab CI is a tool utilized by many enterprises to automate their Continuous integration, continuous delivery and deployment (CI/CD) process. A Gitlab CI/CD pipeline consists of two major components: A .gitlab-ci.yml file describing a pipeline’s jobs, and a Gitlab Runner, an application that executes the pipeline jobs. Setting up the Gitlab Runner is a time-consuming […]

Observability in a container-centric environment presents new challenges for operators due to the increasing number of abstractions and supporting infrastructure. In many cases, organizations can have hundreds of clusters and thousands of services/tasks/pods running concurrently. This post will demonstrate new features in Amazon DevOps Guru to help simplify and expand the capabilities of the operator. […]

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 […]

Monitoring is fundamental to operating an application in production, since we can only operate what we can measure and alert on. As an application evolves, or the environment grows more complex, it becomes increasingly challenging to maintain monitoring thresholds for each component, and to validate that they’re still set to an effective value. We not […]

Many different operating systems and architectures could end up as the destination for our applications. By using a AWS CodeBuild batch build, we can run builds for a Go application targeted at multiple platforms concurrently. Cross-compiling Go binaries for different platforms is as simple as setting two environment variables $GOOS and $GOARCH, regardless of the […]

This blog post will demonstrate how to leverage Jenkins with Amazon Elastic Kubernetes Service (EKS) by running a Jenkins Manager within an EKS pod. In doing so, we can run Jenkins workloads by allowing Amazon EKS to spawn dynamic Jenkins Agent(s) in order to perform application and infrastructure deployment. Traditionally, customers will setup a Jenkins Manager-Agent […]

This post is written by Pritam Pal, Sr EC2 Spot Specialist SA & Dan Kelly, Sr EC2 Spot GTM Specialist Customers are using Amazon Web Services (AWS) to build CI/CD pipelines and follow DevOps best practices in order to deliver products rapidly and reliably. AWS services simplify infrastructure provisioning and management, application code deployment, software […]

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.