Operations | Monitoring | ITSM | DevOps | Cloud

A practical guide for IT professionals, DevOps, security teams, platform engineers, and anyone who’s dealing with logs. In contemporary distributed systems, telemetry data—logs, metrics, traces, and events—serves as the primary mechanism for understanding internal system behavior. However, as system complexity increases, so does the volume and heterogeneity of telemetry.

Rural America is experiencing a dramatic surge in network demand driven by high-bandwidth applications like 4K video streaming, real-time sports content, and AI workloads. As broadband competition and digital transformation accelerate, service providers must rethink middle-mile network architecture to be scalable, technology-agnostic, and service-aware.

As colocation demand surges, space is becoming increasingly scarce and costly. According to CBRE, the average asking rate in primary wholesale colocation markets for a 250–500 kW requirement has climbed 12.6% year-over-year to a record $184.06 per kW/month, while vacancy rates have dropped to a record-low 1.9%. With vacancy rates low and power costs rising, doing more with less in your data center is essential.

For the last decade, Gremlin has helped Fortune 500 organizations with critical uptime requirements proactively uncover reliability risks and prevent costly outages. We started with Chaos Engineering, then built Reliability Management to help teams standardize and scale their testing efforts. Today, we take another leap forward with the release of Reliability Intelligence. Reliability Intelligence draws on Gremlin expertise with each test to show you what happened and recommend remediation.

The release of OpenAI’s new open-source model, GPT-OOS, has sparked a wave of excitement across the AI community. And rightly so. For organizations that want the benefits of generative AI without sending data out to the web, this is a compelling option. Running locally, GPT-OOS offers a level of privacy, control, and cost-efficiency that’s hard to ignore. It’s fast, lean and at least in its early benchmarks, surprisingly capable in coding, math, and STEM-heavy workloads.

Data sovereignty isn’t just a niche consideration anymore – it’s a central requirement in everything from cloud computing and analytics to software development. The environment of 2025 is significantly different from that of 2015, and even more so from 2005. What was once a patchwork of guidance documents, data privacy laws, and local regulations has given way to massive EU-wide regulations, multinational frameworks, and a greater focus by users on digital identity.