Category: Learning Levels

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 […]

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 […]

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 […]

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 […]

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 […]

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 CodeGuru is a developer tool that provides intelligent recommendations for identifying security risks in code and improving code quality. To help you find potential issues related to logging of inputs that haven’t been sanitized, Amazon CodeGuru Reviewer now includes additional checks for both Python and Java. In this post, we discuss these updates and […]

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 […]

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 […]

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 […]