Operations | Monitoring | ITSM | DevOps | Cloud

As an open-source container management system, the Kubernetes (commonly referred to as K8s) platform’s constant growth warrants an intricate cluster network, making it challenging to gain system-wide visibility. Even a tiny disruption within the network could collapse the entire operation, resulting in the failure of dependent applications. Businesses that rely on such containerized applications may experience a huge impact in revenue.

A mock server can prove useful in many circumstances. Imagine you’re an engineer working on optimizing a feature inside of an existing API that relies on multiple other microservices to function properly. To fully test the optimizations, you’ll have to set up test versions of all the dependencies, which quickly proves to be quite a task in and of itself. This is where a mocks—a server that simulates the behavior of a real server—can be very beneficial.

Nowadays, when most people think about the term “machine learning,” they think of advanced, refined applications such as Chat-GPT, the chatbot-based deep learning text generator, or AlphaGo, the computer program that’s currently the “world's best player” of the board game Go.

Deploying an application is an intricate process that requires managing environment variables and secrets. These variables and secrets help applications access essential resources such as API keys, database credentials, and more. However, manually managing these variables and secrets can be challenging and time-consuming, especially for engineering teams that manage multiple applications. Fortunately, Qovery has a solution for this.

The default pod provisioning mechanism in Kubernetes has a substantial attack surface, making it susceptible to malevolent exploits and container breakouts. To achieve effective runtime security, your containerized workloads in Kubernetes require multi-layer process monitoring within the container.

Content As we already discussed in previous articles, the Kubernetes control plane is made up of a few key components playing different roles. Those are necessary to ensure both Kubernetes and applications are functional and behaving properly.

Monitoring is not a goal, but a path. Depending on the maturity of your project, it can be labeled in one of these six steps of the cloud monitoring journey. You will find best practices for all of them and examine what companies get from each one. From classic virtual machines to large Kubernetes clusters or even serverless architectures, companies have adopted the cloud as a mainstream way to provide their online services.