Operations | Monitoring | ITSM | DevOps | Cloud

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.

The Bleemeo Community Edition is the Open Source and self hosted version of the Bleemeo monitoring solution. It is composed of three main components: And some third party components: In this article, we will show you how to install and configure these components to have a fully working monitoring infrastructure.

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.

Serverless developers are undoubtedly familiar with the challenge of cold starts, which describe spikes in latency caused by new function containers being initialized in response to increasing traffic. Though cold starts are usually rare in production deployments, it’s still important to understand their causes and how to mitigate their impact on your workload.

It’s no secret that we’re experiencing a talent shortage in the tech industry. At the same time, the automation of many jobs is near. It’s easy to assume these two realities mitigate each other, but the situation is much more complex. Although automation may replace millions of low-skill jobs, it will create millions of jobs that require skilled tech workers, according to a report by consulting company BCG.

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.

Migrating your workloads to the cloud can bring some undeniable benefits to your organisation. For example, you can leverage cloud automation to significantly improve your time to market. You can also benefit from the ever increasing number of cloud regions to place your workloads close to your clients. This improves the response time of your services and, as a result, your customers’ satisfaction.

The MongoDB document-oriented database is one of the most popular database tools available today. Developed as an open-source project, MongoDB is highly scalable and can be set up in your environment in just a few simple steps. When running and managing databases, monitoring is a key requirement.

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.