AWS DevOps & Developer Productivity Blog
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A new Spark plugin for CPU and memory profiling
Introduction Have you ever wondered if there are low-hanging optimization opportunities to improve the performance of a Spark app? Profiling can help you gain visibility regarding the runtime characteristics of the Spark app to identify its bottlenecks and inefficiencies. We’re excited to announce the release of a new Spark plugin that enables profiling for JVM […]
Leverage DevOps Guru for RDS to detect anomalies and resolve operational issues
The Relational Database Management System (RDBMS) is a popular choice among organizations running critical applications that supports online transaction processing (OLTP) use-cases. But managing the RDBMS database comes with its own challenges. AWS has made it easier for organizations to operate these databases in the cloud, thereby addressing the undifferentiated heavy lifting with managed databases […]
How to unit test and deploy AWS Glue jobs using AWS CodePipeline
This post is intended to assist users in understanding and replicating a method to unit test Python-based ETL Glue Jobs, using the PyTest Framework in AWS CodePipeline. In the current practice, several options exist for unit testing Python scripts for Glue jobs in a local environment. Although a local development environment may be set up […]
Smithy Server and Client Generator for TypeScript (Developer Preview)
We’re excited to announce the Developer Preview of Smithy’s server and client generators for TypeScript. This enables developers to write concise, type-safe code in the same model-first manner that AWS has used to develop its services. Smithy is AWS’s open-source Interface Definition Language (IDL) for web services. AWS uses Smithy and its internal predecessor to […]
Chaos experiments on Amazon RDS using AWS Fault Injection Simulator
Performing controlled chaos experiments on your Amazon Relational Database Service (RDS) database instances and validating the application behavior is essential to making sure that your application stack is resilient. How does the application behave when there is a database failover? Will the connection pooling solution or tools being used gracefully connect after a database failover […]
Deploy .NET Blazor WebAssembly Application to AWS Amplify
AWS Amplify is a set of purpose-built tools and features that lets developers quickly and easily build CI/CD Pipeline for full-stack applications on AWS. Blazor can run your client-side C# code directly in the browser, using WebAssembly. It is a .NET running on WebAssembly, and you can reuse code and libraries from the server-side parts […]
Building Blue/Green application deployment to Micro Focus Enterprise Server
Organizations running mainframe production workloads often follow the traditional approach of application deployment. To release new features of existing applications into production, the application is redeployed using the new version of software on the existing infrastructure. This poses the following challenges: The cutover of the application deployment from testing to production usually takes place during […]
Automate code reviews with Amazon CodeGuru Reviewer
A common problem in software development is accidentally or unintentionally merging code with bugs, defects, or security vulnerabilities into your main branch. Finding and mitigating these faulty lines of code deployed to the production environment can cause severe outages in running applications and can cost unnecessary time and effort to fix. Amazon CodeGuru Reviewer tackles […]
Deploy and Manage Gitlab Runners on Amazon EC2
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 […]
Monitor AWS resources created by Terraform in Amazon DevOps Guru using tfdevops
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 […]




