Operations | Monitoring | ITSM | DevOps | Cloud

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.

When we talk about upgrades here at SolarWinds, we spend a lot of time discussing the beneficial features, performance, and capabilities you can gain. That’s not by accident. The honest-to-goodness truth is, the most compelling reason to upgrade ANYTHING—from our phone to our game console to our monitoring software—is because we’ll be able to do something both new and useful to us.

We are delighted to share news of our partnership with leading, real-time Application Performance Monitoring (APM) vendor Cisco AppDynamics and are now a fully-fledged member of their Integration Partner Program (IPP.) For our mutual enterprise customers service affecting issues can lie undetected in the vast volumes of data generated by the multiple, disconnected tools used to monitor their multi-cloud environments, applications and technical solutions.