Virtualization has been with us since the 1960s. In computer science terms, it is about as old as the hills. Yet this old-school idea has never been more relevant. We all know hardware is expensive. Despite the cost, many businesses squander their precious processing power. All too often, a “one server, one purpose” mindset leads IT departments to waste server capacity. With virtualization, we leave this myopic view of server management in the dust.

Modern software development teams use CI/CD tools to ship features quickly and rely on best practices like shift-left testing to find application errors before they become user-facing bugs. But you still face the risk that any code you deploy could contain errors that your testing did not surface. To help you deploy with confidence and mitigate the effects of a bad deployment, Datadog APM now provides Automatic Faulty Deployment Detection.

I have been in the IT industry for a few decades now and have helped launch waves of technology in the constant pursuit of making computing easier, cheaper and with greater uptime. This all started well before my entry into the IT industry and will continue to well past the time I retire. However, it is always good to understand where we have been and look how far we have come to understand how we can continue to make it even better.

Most interactions with a web application occur at the browser. Users search items, fill forms, create shopping carts, log into their profiles, and perform many other tasks. Unit tests are great, but nothing beats testing an application by interacting with the user-facing frontend. In this tutorial, you will learn and demonstrate how to write tests for the browser using Puppeteer . You will then take this a step further by automating the testing process in a continuous integration flow.

Thousands of secrets leak daily on public git repositories, including over two million corporate secrets in 2020 alone. This can happen to anyone! For example, in January 2021, an Amazon cloud engineer accidentally committed almost a gigabyte worth of sensitive data that included their own personal documents, as well as passwords and cryptographic keys to various AWS environments on his personal GitHub repository.

Back in July I published Encountering some turbulence on Bitbucket's journey to a new platform, sharing with the public for the first time that Bitbucket Cloud is in the final stages of a migration from our data center onto Atlassian's cloud platform—the same internal platform underlying Jira Cloud, Confluence Cloud, Statuspage, and many other internal services. I also shared that because of increased file system latency as a result of this platform move, certain operations have become slower.

Modern, cloud-based software development lifecycles have quickly evolved from waterfall and are fully embracing the agile principles of DevOps. As part of this shift, continuous delivery practices have been adopted, giving organizations the capability to deliver and release code faster and more frequently than ever before. CI/CD tools bring velocity — code is always ready to be deployed, enabling organizations to commit multiple times a day.

In modern software systems, it is common for several developers to work on the same project simultaneously. Siloed working with infrequent merging of code in a shared repository often leads to bugs and conflicts that are difficult and time-consuming to resolve. To solve this problem, we can adopt continuous integration.