In our previous article, we explained some of the issues we see with the current generation of GitOps tools (which we call GitOps 1.0). In this article, we will talk about the solution to those issues and what we expect from GitOps 2.0 – the next generation of GitOps tooling.
In our previous article, we explained the vision behind GitOps 2.0 and the features we expect to be covered by GitOps 2.0 tools. In this article, we will see how the new Codefresh GitOps dashboard is the first step towards this vision and more specifically in the area of observability and traceability.
GitOps as a practice for releasing software has several advantages, but like all other solutions before it, has also several shortcomings. It seems that the honeymoon period is now over, and we can finally talk about the issues of GitOps (and the current generation of GitOps tools) In the article we will see the following pain points of GitOps.
One of our most commonly requested integrations, Datadog cloud monitoring, was announced last week on the Datadog blog! Sleuth organizes your deployments into projects, which collect and organize key data from your code sources and their associated staging environments. This data consists of metrics and errors.
CI/CD is a software development strategy which allows for faster development by introducing automation while still maintaining the quality of code deployed to production. Implementing a CI/CD pipeline not only promotes a safer deployment process but also improves the incident response process. CI/CD is broken down into multiple parts. The CI refers to continuous integration, meanwhile, the CD can refer to continuous delivery and/or continuous deployment.
The Docker infrastructure abstracts a lot of aspects of the creation of images and running them as containers, which we usually do not know about nor interact with. One of those aspects is the handling of the filesystem inside the container. This post is a case study on how we discovered that writing large amounts of data inside a container has side effects with memory caching. Initially, we thought that we had an issue with our source code, but this was never the case.
In this blog, we will go through an example of how you can use the Cloudsmith Terraform Provider to provision resources in Cloudsmith, such as repositories and entitlement tokens. HashiCorp Terraform is an awesome Continuous Configuration Automation tool. It is used to provision, update and manage infrastructure resources such as Cloud instances, containers, physical machines and more. It is a firm favourite among developers, due to its brilliant community and mix of power and simplicity.
Kubernetes can bring a wide collection of advantages to a development organization. Properly leveraging Kubernetes can greatly improve productivity, empower you to better utilize your cloud spend, improve application stability and reliability, and more. On the flip side, if you are not properly leveraging Kubernetes, your would-be benefits become drawbacks. As a developer, this can become especially frustrating when you are focused on delivering quality code, fast.
Our distinguished competition took a puzzling position of “Imagine there’s no versions”. At Cloudsmith we think that’s crazy. Software versions are what makes software development possible. They make deployment possible. They make distribution possible. How else can you understand and navigate complex dependency trees or be sure your code will interact with a third party’s? Hint - you can’t! You must care about versions. And updates.
