center

AIOps / MLOps / LLMOps

This is a massive article for learning and exploring how to build AI Models for scaling with high workloads. It involves numerous stages and techniques, essentially serving as a comprehensive guide for acquiring or updating your knowledge.
You’ll receive a detailed walkthrough of each phase, including what to do, thorough explanations, comparisons, and solutions. It’s up to you to decide which technologies to apply, and you’ll find code snippets illustrating their implementation.
If you’re a newbie, I believe this article provides an excellent roadmap for your journey, which you can leverage to build your own scalable AI system.

Architecture

Kafka is no longer the default solution for building pub/sub, event-driven, or streaming systems. It faces strong competition from numerous alternatives, including Pulsar, RedPanda, and Nats, among others.
In this article, the author explains the reasons for choosing or not choosing an alternative solution over Kafka, detailing the trade-offs involved and the efficiency gains you might realize after migrating. The numbers presented in this article are truly compelling, providing ample evidence to help you make the best decision.

This article provides excellent insights for building high fault-tolerance architectures. It demonstrates how to segment and integrate multiple services for distinct purposes—edge, write, and read—while combining them with powerful technologies like Kafka/Nats for pub/sub, Redis for caching, and High Availability (HA) databases (featuring one primary and multiple read replicas).
The author highlights the weaknesses and shortcomings of monolithic architectures, illustrating how modern architectural approaches can overcome these issues. It’s a great article due to its practical use-case examples, code snippets, and proven results. Additionally, the author offers suggestions for further enhancing your architecture, emphasizing that the best approach depends on your specific insights, workloads, and how you apply these concepts to your use cases.

This article offers an excellent walkthrough for using dmesg in a Linux environment. It’s a perfect tool for monitoring events within the Kernel Ring Buffer , allowing you to detect and intercept a wealth of information from hardware, daemons, and more.
With this guide, you’ll also gain a list of essential debugging tools for Linux, including journalctl, systemctl, and dmesg. Believe me, mastering these will save you in numerous situations.

If you’re looking for an IDP (Internal Developer Platform) for your project, this blog is for you. It surveys multiple available solutions and specifically highlights what kubriX offers to support your system from scratch.
Additionally, this article is quite engaging due to its numerous illustrations and images, which effectively showcase the results after fully setting up the platform.

This article offers valuable insights for working with CoreDNS, a Kubernetes component often perceived as mysterious and complex. It focuses on tuning CoreDNS performance to the next level by leveraging specific plugins for different scenarios to achieve high-quality domain resolution.
The accompanying tutorial, complete with a demo, is exceptionally elaborate. It provides a visual understanding of how CoreDNS plugins function, both with and without their application. Additionally, the author details the environment setup for testing; if you’re skeptical, you can try proving it with the AutoPath CoreDNS plugin for a clear explanation of this intriguing feature.
However, this optimization is a double-edged sword. You should carefully consider applying these changes based on your cluster’s specific needs, such as frequent external API calls, having fewer than 5000 pods, or aiming to reduce DNS queries to CoreDNS. Alternatively, solutions like NodeLocal DNSCache and NDOTS tuning can serve as substitutes.
This article also provides a valuable “free ticket” to understand how to troubleshoot CoreDNS problems. While these issues are typically significant and not easily resolved, taking a closer look at this guide might help you conquer some truly strange occurrences.

If you’re looking for something interesting about the Kernel, this blog is for you. You can use it to learn, hunt bugs, or simply for kernel research. This blog offers a walkthrough that teaches you how to build a custom kernel version, load it into QEMU, and debug within that kernel.