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GitOps

The latest News and Information on GitOps and related technologies.

Managing Your Full Application Lifecycle Using #GitOps

#GitOps is nothing new. Or, to be more precise, the principles of GitOps existed long before the term was invented. But hey, that's the pattern in our industry. It is the fate of all good practices to be misunderstood, so we need to come up with new names to get people back on track. That is not to say that we are in a constant loop. Instead, I tend to think of it as a periodic reset trying to eliminate misinterpretations. GitOps is one of those resets. It fosters the practices and the ideas that existed for a while now and builds on top of them.

#GitOps: The Good, The Bad, and The Ugly

We all know what #GitOps is or what it should be. Nevertheless, not everything is full of roses and unicorns. Just as there are many benefits, we have many problems that need to be resolved both from the tooling and process perspectives. Join us in the open discussion with Viktor Farcic from #Codefresh and Adam Sandor from #ContainerSolutions

GitOps Patterns - Auto-Sync Vs. Manual Sync

The conversation usually starts with a question like “should we let ArgoCD/Flux/whatever synchronize the actual state automatically whenever the desired state changes in Git?” Truth be told, the question is usually not that elaborated, and it is more like “should I enable the auto-sync feature?” But, I wanted to save you from follow-up questions that help me better understand what that means, so I gave you a more extended and more precise version of the inquiry.

Implementing GitOps on Kubernetes Using K3s, Rancher, Vault and ArgoCD

As Kubernetes continues to establish itself as the industry standard for container orchestration, finding effective ways to use a declarative model for your applications and tools is critical to success. In this blog, we’ll set up a K3s Kubernetes cluster in AWS, then implement secure GitOps using ArgoCD and Vault. Check out the source for the infrastructure and the Kubernetes umbrella application here.

Applying GitOps And Continuous Delivery (CD) On Infrastructure Using Terraform, Codefresh, And Azure Kubernetes Service (AKS)

There are many articles and videos about practicing Continuous Delivery (CD) with applications, but not nearly as many for infrastructure. The same can be said for GitOps applied to infrastructure. That is a bit strange given that applications and infrastructure are almost the same today. Both are defined as code, and everyone stores code in Git repositories. Hence, GitOps is just as good of a fit for infrastructure as for anything else.

Applying GitOps And Continuous Delivery (CD) On Infrastructure Using Terraform, Codefresh, And AWS Elastic Kubernetes Service (EKS)

There are many articles and videos about practicing Continuous Delivery (CD) with applications, but not nearly as many for infrastructure. The same can be said for GitOps applied to infrastructure. That is a bit strange given that applications and infrastructure are almost the same today. Both are defined as code, and everyone stores code in Git repositories. Hence, GitOps is just as good of a fit for infrastructure as for anything else.

Applying GitOps And Continuous Delivery (CD) On Infrastructure Using Terraform, Codefresh, And Google Kubernetes Engine (GKE)

There are many articles and videos about practicing Continuous Delivery (CD) with applications, but not nearly as many for infrastructure. The same can be said for GitOps applied to infrastructure. That is a bit strange given that applications and infrastructure are almost the same today. Both are defined as code, and everyone stores code in Git repositories. Hence, GitOps is just as good of a fit for infrastructure as for anything else.

Rancher 2.5 Embraces GitOps at Scale with Rancher Continuous Delivery

The ability of Kubernetes to easily deploy and manage containerized software has given organizations tremendous capabilities in their cloud services, with clusters multiplying into the hundreds or thousands and extending out to the edge for any number of purposes. But its growing popularity has also led to challenges in managing complexity in an environment that is conducive to cluster sprawl.