When your organization becomes bigger, managing the users and groups lifecycle becomes a significant challenge. Your company grows rapidly, hiring new employees, and giving them access to more and more applications that your organization uses. This means that there are many employee-related actions that need to be taken when an employee changes their team, role, leaves temporarily or permanently (otherwise you may end up with operational, security or compliance issues).

Here at LogicMonitor, we’re really big on extensibility and automation. We’re constantly adding to our catalog of monitoring coverage, and we spend a lot of our time ensuring that setup is as simple as possible. We also monitor almost any data you can expose on a network. People have done way more with LogicMonitor than we would have ever imagined, and I’m extremely excited to announce our next step in that commitment to extensibility and automation.

Secret management is one of the most critical areas in deploying and running applications. Codefresh already had native support for native Kubernetes secrets or custom secrets on the Codefresh Runner, but more and more customers have asked us for native support for Hashicorp Vault. Today we are pleased to announce our native integration with Hashicorp vault as another secret provider for Codefresh pipelines.

As software gets more complex, so do software builds. With applications being composed of multiple services — often developed by separate teams — it can be challenging to automate a unified continuous integration process. JFrog Pipelines is unique among DevOps CI/CD solutions in empowering developers to create highly complex DevOps Pipeline workflows. Pipelines can be defined with multiple paths, trigger points and trigger types.

Docker is a platform for developers and sysadmins to develop, deploy, and run applications using containers. Docker is also referred to as an application packaging tool. This means that enabled applications can be configured and packaged into a Docker image that can be used to spawn Docker containers that run instances of the application. It provides many benefits including runtime environment isolation, consistency via code, and portability.

I talk with many of my fellow engineers at conferences and other events throughout the year. One thing I like demonstrating is how they can implement a continuous integration/continuous deployment (CI/CD) pipeline into a codebase with very little effort. In this post I will walk through some demo code and the CircleCI config that I use in the demonstration. Following these steps will show you how to implement CI/CD pipelines into your code base.

I stepped into the role of Head of Engineering for Bitbucket Cloud in late 2020, having served as one of the team's senior engineering managers for several years. It is an honor and a privilege to lead this team, and I couldn't be prouder of the hard work we've done and continue to do each day to make Bitbucket a world-class product empowering teams to build, test, and deploy software to millions of people around the world. It has been an eventful journey, and the past few weeks are no exception.

At JFrog, we’ve seen DevOps and DevSecOps adoption growing robustly in Asia-Pacific (APAC), as the region’s large enterprises recognize the competitive advantage and importance of DevOps and digital transformation. In fact, by 2025, up to 25% of Asia’s 500 largest companies will become software producers to digitally transform and maintain their A500 status, IDC predicts1.

JFrog and PagerDuty have deepened their technology integration to further boost IT operators’ and developers’ visibility into the software development lifecycle and accelerate incident resolution. The latest integration, which involves the JFrog Pipelines DevOps pipeline automation solution, simplifies and streamlines how to identify faulty builds that impact production environments.

Creating robust, manageable, and reusable functionality is a big part of my job as a CI/CD engineer. Recently, I wrote about managing reusable pipeline configuration by adopting and implementing pipeline variables within pipeline configuration files. As I showed in that tutorial, pipeline variables and orbs have added some flexibility to this process, but they are still a bit limited.