Operations | Monitoring | ITSM | DevOps | Cloud

I'm thrilled to announce the availability of Qovery on the AWS Marketplace. You can now buy and benefit from Qovery right from the AWS Marketplace. Before delving into the specific advantages of purchasing Qovery through the AWS Marketplace, let's first understand what the AWS Marketplace is and why this is something you should consider when purchasing Qovery.

The scalability of the cloud and its inherent variable cost has created financial and operational challenges, which demand the process of tracking varying costs in the dynamic Azure infrastructure at a granular business context level. Unit economics is a process of profit maximization in the cloud based on objective measurements like cost per product. This approach assesses how the organization is performing against its business goals.

Large Language Models (LLMs) fall under the category of Generative AI (GenAI), an artificial intelligence type that produces content based on user-defined context. These models undergo training using an extensive dataset composed of trillions of combinations of words from natural language, enabling them to empower interactive and conversational applications across various scenarios.

Monitoring Jenkins jobs and nodes is foundational to maintaining a robust, efficient, and secure CI/CD pipeline. It enables DevOps teams to stay proactive about system health, optimize performance, manage resources effectively, and adhere to security and compliance standards. In this article, we'll detail how to use the Telegraf agent to collect performance metrics from your Jenkins environment, and forward them to a datasource.

We rarely think about how many processes are running on our systems. Modern CPUs are powerful enough to run thousands of processes concurrently, but at what point do our systems become oversaturated? When you’re running large-scale distributed applications, you might reach this limit sooner than you'd expect. How can you determine what that limit is, and how does that affect the number and complexity of the workloads you deploy?

FireHydrant is mission-critical infrastructure for thousands of engineers. It’s our job to be up – even when everything else is down. Here's a technical look at how we tested Signals alerting and on-call to ensure high availability and speed.

In the complex and fast-paced world of application deployment, getting a handle on the tangle of services and resources can sometimes feel like trying to find your way through a maze without a map. And if something goes wrong, trying to find out what's happening where is even more difficult. With alert emails flooding in and questions flying left and right, identifying the glitch that's causing issues can seem like a Herculean feat.