Today, automation has shifted from being a luxury to an absolute necessity, especially within the realm of networks. This shift is driven by the rapid evolution of network technologies, compliance standards, and evolving business needs, placing an increasingly daunting burden on network administrators to manage these tasks manually.

In the last decade-plus, the cloud has undergone a torrid evolution. Born in 2006, the cloud didn’t face the same speed limits on evolution that we mortals do. Within years, the cloud had gone from competitive edge to competitive necessity; within a decade, specialized services like Kubernetes, Snowflake, and Datadog had emerged to help us use it more, more flexibly, and with a more data-driven strategy. As the cloud evolved at an exponential rate, so did the costs associated with using it.

Generative AI has already shown its huge potential, but there are many applications that out-of-the-box large language model (LLM) solutions aren’t suitable for. These include enterprise-level applications like summarizing your own internal notes and answering questions about internal data and documents, as well as applications like running queries on your own data to equip the AI with known facts (reducing “hallucinations” and improving outcomes).

The tech landscape is a whirlwind of continuous evolution, making the role of a DevOps engineer more crucial than ever. A "pragmatic" DevOps engineer stands out as a beacon of efficiency and practicality in this dynamic environment.

Site Reliability Engineers (SREs) play a vital role in ensuring the stability and performance of web services and are key in incident management. One of the core skills SREs need is the ability to conduct effective Root Cause Analysis (RCA) when issues arise. This guide is about how to improve your RCA skills for more effective post-incident analysis.Let's dive in.🔖 What is Prometheus Alertmanager? Read here!

The word "cache" is used in many different contexts. Typically, a cache is a small chunk of data stored locally for quick access. In this case, it’s about computer caches, i.e., the data stored in memory. Micro-caching is a technique where a programmer uses this cached data to do some quick computations, which can lead to some amazing solutions. In micro caching, dynamically generated content is cached for only a brief period rather than full-page caching.