Operations | Monitoring | ITSM | DevOps | Cloud

Mock services are a powerful tool for accelerating software development. Learn the top use cases for mock APIs in our blog.

As technology takes the driver’s seat in our lives, Kubernetes is taking center stage in IT operations. Google first introduced Kubernetes in 2014 to handle high-demand workloads. Today, it has become the go-to choice for cloud-native environments. Kubernetes’ primary purpose is to simplify the management of distributed systems and offer a smooth interface for handling containerized applications no matter where they’re deployed.

Kubernetes, with its robust, flexible, and extensible architecture, has rapidly become the standard for managing containerized applications at scale. However, Kubernetes presents its own unique set of access control and security challenges. Given its distributed and dynamic nature, Kubernetes necessitates a different model than traditional monolithic apps.

Containerization has become a cornerstone of modern software development and deployment. Docker, a leading containerization platform, has revolutionized the way applications are built, shipped, and deployed. As a DevOps engineer, mastering Docker and understanding best practices for Dockerfile creation is essential for efficient and scalable containerized workflows. Let’s delve into some crucial best practices to optimize your Dockerfiles.

Freedom of choice can make choosing harder. Since a JFrog cloud (SaaS) account provides the same functionality as a self-hosted JFrog Software Supply Chain Platform how will you decide which is right for you? Choice without tradeoffs is one of the key ways JFrog enables you to be cloud-nimble, and run the mission-critical heart of your DevSecOps process wherever you need it to be — in any cloud, public or private, as SaaS, BYOL, or on-prem. So how will you decide?

Recently, we wrote a great article about Platform Engineering and how to get started; well, now that you know much more about it, you might want to explore the best Platform Engineering tools to use in 2024. If that’s the case, this article is for you.

Cost optimization in cloud environments is no longer a luxury — it’s a necessity. As businesses increasingly migrate to AWS, they are met with the difficult task of ensuring robust performance and scalability, all while keeping an eagle eye on costs. How does one achieve this delicate balance? How can organizations ensure that their AWS architectures are both high-performing and cost-efficient?

Whenever it comes to a small-scale private cloud infrastructure project roll-out, organisations usually face a serious dilemma. The implementation process often seems complex due to a lack of knowledge, tricky migrations and an immediate need from management to run various extensions, such as Kubernetes, on top.