Operations | Monitoring | ITSM | DevOps | Cloud

As organizations increasingly embrace Kubernetes for container orchestration, optimizing both cost and performance has become a critical challenge. Kubernetes, with its flexible and powerful features, allows for efficient resource management, but without proper configuration and monitoring, it can also lead to over-provisioning, wasted resources, and skyrocketing costs.

Ah, 2024. The year we promised ourselves we’d finally “work smarter, not harder.” And yet, here we are, looking back at a year filled with reworked errors, late-night firefighting, and a lot of “this could have been avoided.” Let’s relive the chaotic glory of the year that wasn’t and figure out how 2025 can be the year that is.

Edge computing is a decentralized computing approach that processes data and performs computations near the source of the data—local servers, smart devices, or edge nodes—rather than depending on a centralized data center. This reduces latency, which is often a result of data having to travel long distances and improves bandwidth efficiency. Discover how edge computing and Kubernetes revolutionize data processing and deployment.

Learn how to measure, implement, and improve SPACE metrics in DevOps. Get actionable tips and overcome common challenges in team performance tracking. Cortex| January 2, 2025 Software development team performance.

Cloud tracing provides essential visibility into distributed systems, helping track requests, identify bottlenecks, and improve performance. Learn the best practices and tools for effective monitoring.

Protect your apps with AWS WAF! This guide walks you through setup, rules, and keeping threats at bay, step by simple step.

Learn how to integrate Winston for efficient logging in Node.js. Explore features, configurations, and best practices to optimize your app's performance.

Last year, we reflected on the progress that AI made in 2023 with tools like ChatGPT lowering barriers to entry and driving broader adoption across industries. Looking ahead, we anticipated even greater advancements in AI's accessibility and governance, including the democratization of technology, enhanced large language models for specific applications, and growing concerns around the ethical implications of synthetic content and intellectual property rights.