Operations | Monitoring | ITSM | DevOps | Cloud

Sometimes you just want to fetch all Icinga 2 objects of a given type from the API and do something with them. Then you notice that Icinga 2’s memory usage jumps up with every large request and never comes back down, as if each HTTP request leaked a huge chunk of memory. And once enough of these requests run in parallel, no matter how much RAM the machine has, Icinga 2 runs out of memory and crashes. Here’s what was really going on, and how we fixed it in Icinga 2 v2.16.

Every enterprise board now expects an agentic AI plan. Far fewer operating leaders can say which workflow should carry it first, and why. That debate ran through the closed-door roundtable jointly hosted by iOPEX and Soroco in London, with senior operations and transformation leaders from telecom, banking, retail, financial data, and life sciences.

Rule-based routing pages the service that errored. Build a small triage service that reads the alert webhook, finds the origin span in your traces and pages the team that owns it. Last9 is an observability platform built for high-cardinality telemetry. It unifies logs, metrics, and traces with native OpenTelemetry and Prometheus support, real-time alerting, and long-term retention.

Wide events move observability cost instead of removing it. See what each signal is billed in, which question each answers cheapest, and how to size spend against cloud spend. Sejal Pandey works on content and growth at Last9, writing about observability, reliability, and SRE practices.

A data residency security review for observability in your own cloud account: vendor access, connection direction, PII redaction and egress, with what Last9 documents. Last9 is an observability platform built for high-cardinality telemetry. It unifies logs, metrics, and traces with native OpenTelemetry and Prometheus support, real-time alerting, and long-term retention.

AI coding agents lose context once a PR enters the pipeline. See how code context and delivery context work.

Learn how to secure AI agents across development, testing, deployment, and runtime using the OWASP Top 10 for Agentic Applications. A single poisoned web page can be enough to hijack an AI agent. As organizations move from AI assistants that generate responses to autonomous agents that take action, the security risks are changing. An agent can access sensitive data, execute code, modify configurations, and interact with external systems.

Property-based testing is a software testing technique that checks whether a program satisfies general rules, called properties, across many automatically generated inputs. Instead of writing tests for individual examples, developers define how their code should behave and let a testing framework search for inputs that break those rules.

CircleCI Functions are now available in beta, giving developers and coding agents a faster, more reliable way to set up CI pipelines using reusable, tested steps. Functions are the next evolution of CircleCI orbs. They make common CI tasks, like installing programming languages, configuring AWS credentials, and setting up Docker, available as ready-to-use programs that agents can discover, configure, and validate before running a pipeline.

Ask a team running an agent in production whether last week’s change made it better. Most can’t say. They swapped a model or rewrote a skill, eyeballed a few runs, and moved on. That works for a demo. It doesn’t work for an agent that touches production, where customers want two things that pull against each other: precision where a mistake is expensive, and low cost where the work is routine. A root cause someone acts on has to be right.