Category: Intermediate (200)

This post was written in collaboration with Kapil Thangavelu, CTO at Stacklet Amazon DevOps Guru is a machine learning (ML) powered service that helps developers and operators automatically detect anomalies and improve application availability. DevOps Guru utilizes machine learning models, informed by years of Amazon.com and AWS operational excellence to identify anomalous application behavior (e.g., increased […]

Amazon DevOps Guru is an ML powered service that makes it easy to improve an application’s operational performance and availability. By analyzing application metrics, logs, events and traces, DevOps Guru identifies behaviors that deviate from normal operating patterns and creates insights that you can use to improve your application. At re:Invent 2021, we announced a […]

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 […]

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 […]

Many organizations today require their systems to be compliant with the CIS (Center for Internet Security) Benchmarks. Enterprises have adopted the guidelines or benchmarks drawn by CIS to maintain secure systems. Creating secure Linux or Windows Server images on the cloud and on-premises can involve manual update processes or require teams to build automation scripts […]

Developing and deploying applications rapidly to users requires a working pipeline that accepts the user code (usually via a Git repository). AWS CodeArtifact was announced in 2020. It’s a secure and scalable artifact management product that easily integrates with other AWS products and services. CodeArtifact allows you to publish, store, and view packages, list package […]

Many organizations host ideation events to innovate and prototype new ideas faster.  These events usually run for a short duration and involve collaboration between members of participating teams. By the end of the event, a successful demonstration of a working prototype is expected and the winner or the next steps are determined. Therefore, it’s important […]

Take a Well-Architected approach to make an informed decision when choosing to implement CI/CD using open-source tools on AWS services, using managed AWS services, or a combination of both.

We will look at key considerations for evaluating open-source software and AWS Services using the perspectives of a startup company, and a mature company, as examples. These will give you two very different points of view that you can use to compare to your own organization. To make this investigation easier we will use Continuous Integration (CI) and Continuous Delivery (CD) capabilities as the target of our investigation.

In our next two blog posts we will follow two AWS customers Iponweb and BigHat Biosciences as they share their CI/CD journeys, their perspective, the decisions they made, and why.

To end the series, we will explore an example reference architecture showing the benefits AWS provides regardless of your emphasis on open source tools or managed AWS services.

The resource leak detector in CodeGuru Reviewer combines static code analysis algorithms with machine learning to surface only the high confidence leaks. It has a high developer acceptance rate and has alerted developers within Amazon to thousands of leaks before those leaks hit production.