Operations | Monitoring | ITSM | DevOps | Cloud

Kubernetes is the world’s leading container orchestration platform. Its cloud agnostic status enables you to manage your workloads with ease, whether they reside in the cloud or on-premises. It has reduced the necessity of being locked into services provided by a cloud provider as well as the need for an entire operations team to manage large workloads on-premises on virtualization platforms.

Back in the early days of software development, having multiple developers working on the same application was a tough challenge. That’s why VCS (Version Control System) like Git was created and methodology like Feature Branching was introduced. The basic idea of working per git branch (also known as Feature Branching) is that when you start to work on a feature, you take a branch of your repository (e.g: git) to work on that feature.

IT industry research has repeatedly shown that DevOps-oriented teams that can ship software quickly and effectively routinely outperform their slower counterparts in terms of company profitability, market share, and just about every competitive business metric that matters. That sort of success comes from restructuring teams in ways that empower them to move faster and get closer to their customers.

Have you ever grown tired of running the same kubectl commands again and again? Well the good folks over at the Kubernetes team understand you. With the addition of custom resources and the operator pattern, you can now make use of extensions, or addons as I like to call them, to the Kubernetes API that help you manage applications and components. Operators follow Kubernetes principles including the control loop.

When requirements change for your product, there arises a need to change not only the codebase but also the existing data that already lives in production. If you’re performing the changes locally, the whole process seems fairly simple. You test your new feature against a sparkling clean database, the test suite is green, and the feature looks great. Then you deploy, and everything goes to hell because you forgot that production was in a slightly different state.