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The latest News and Information on Monitoring for Websites, Applications, APIs, Infrastructure, and other technologies.

Restoring Compliance After Missed SAP Patch Cycles

Avantra restores SAP compliance after missed patch cycles by measuring the real gap on every system, automating the catch-up in risk order, and monitoring continuously afterward. A missed cycle can leave SAP operations out of compliance or exposed to documented vulnerabilities, and until each system is assessed, the impact is unknown. Getting “back to good” requires three steps: The patching itself is rarely the hard part.
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Raygun APM Agent 3.1: async traces that stay with the right request

Raygun APM Agent 3.1 introduces more accurate asynchronous request tracing for Windows, Linux, and Azure App Service. Version 3.0 rebuilt the foundation of the Agent, profiler, installers, and release pipeline. Version 3.1 builds on that work with a focused improvement for ASP.NET Core: automatic request correlation that follows asynchronous execution without requiring developers to instrument their application. The result is a more accurate trace, with less duplication and a clearer view of the work performed for each web request.

On SQLAlchemy 2.1.0 or 2.1.1, Fixing an N+1 Could Change Your Results

The standard fix for an N+1 query in SQLAlchemy is to eager load the relationship with selectinload(). On SQLAlchemy 2.1.0 and 2.1.1, that fix can change your results. A regression in those two releases makes selectinload() ignore part of the join condition on some many-to-many relationships. The query gets faster, and it also returns related rows that the relationship was defined to exclude. It’s fixed in 2.1.2, released October 2.

Observability vs Monitoring: Why Does IT Still Find Out After the Business Does?

✓ operational truth IT finds out late because traditional monitoring is built to detect what goes wrong, not what has quietly stopped happening. Closing that gap requires observability that validates business journeys end to end, detects missing activity, checks its own coverage, and predicts degradation before a threshold is ever crossed.

Azure in Bleemeo: your subscription next to your servers, with one read-only role

Most teams that run on Azure do not run only on Azure. There is a database on a VM nobody wants to move, a Kubernetes cluster somewhere else, a few servers in a rack, and a monitoring setup that grew around all of it. Azure Monitor sees the Azure part very well and nothing else, so the picture of an incident ends up split across two consoles, two alerting configurations and two sets of dashboards. Bleemeo now connects to Azure the same way it already connects to AWS.

Ship faster, improve reliability, and control CI costs with Datadog CI/CD Optimization

AI-assisted development can increase the rate at which teams produce code, but teams only realize those velocity gains if CI can keep pace. More pull requests (PRs) mean more builds, tests, and pipeline executions. Slow jobs leave developers and coding agents waiting for feedback, flaky failures consume time in reruns and investigations, and unnecessary test execution increases runner demand as delivery volume grows.