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When developers and SREs design application tests, they often prioritize user workflows and API availability. Extending that suite with network tests that match your app’s traffic protocols can reveal whether issues originate in the network or application layer. In this post, we’ll explore how you can design effective network tests using the Transmission Control Protocol (TCP), User Datagram Protocol (UDP), or Internet Control Message Protocol (ICMP), including.

We are happy to announce the release of two new versions of Icinga 2 today, 2.16.0 and 2.15.3. The first one includes some new features highlighted below, as well as a number of bug fixes and other improvements. The latter one is a small bug fix release that brings some of the other fixes included in 2.16.0 to the 2.15.x branch as well.

In the wake of 2010s, PaaS felt like magic. You focused on the code, and the platform did the rest. You could ship a production app without knowing anything about networking or, heck, even what a load balancer is. Heroku in particular made deployment a lost thought, especially for early-stage companies. That era is somewhat over, not because platforms got worse overnight, but because the assumptions underneath them quietly stopped being true.

Transform your IT service management data into actionable insights with dashboards that give your team real-time visibility without the setup headache.

If your Apache ActiveMQ deployment has a growing ActiveMQ.DLQ, you are not alone, and you are looking at the right problem. An unbounded, unmonitored dead letter queue is one of the most common root causes of "invisible" message loss in enterprise messaging environments. DLQ messages land without fanfare, nobody notices, and business-critical data quietly disappears from the processing pipeline.

When engineers search for "Apache ActiveMQ vs Apache Artemis," most of what they find is either a shallow feature checklist or a confident recommendation to "just migrate to Apache Artemis." Neither helps a senior architect deciding whether to stay on a stable, battle-hardened Apache ActiveMQ deployment, or a platform team evaluating both options for a new system with clear eyes.

AI has quickly become part of the language of network observability. Many vendors across the observability landscape can describe, summarize, correlate, or explain some data or situation, leveraging basic LLM capabilities. At a distance, many of these offerings sound similar. They promise faster insight, efficient operations, and a more intelligent path through rising complexity. But the industry has reached a point where surface-level similarity is creating noise, not value.

Real production data tells the story better than I can. Juraci Paixão Kröhling, a friend and fellow observability practitioner at OllyGarden, recently shared an example from an anonymized production environment: 1,830 occurrences of http.url and 23,984 occurrences of url.full in the same dataset. Both attributes describe the same thing. Both are actively being written to the same backend at the same time.

Following our 2025 updates, here we recap how VictoriaMetrics Anomaly Detection evolved in Q1 2026. Stay tuned for upcoming content on anomaly detection.

KubeCon + CloudNativeCon Europe in Amsterdam brought together about 13,500 attendees this year, the largest turnout yet. The size of the event showed just how much the cloud-native space has grown, and how central observability, platform engineering, and cost control have become. For VictoriaMetrics, this year’s event was a mix of talks, booth conversations, and a lot of direct feedback from users.