Operations | Monitoring | ITSM | DevOps | Cloud

You're producing more trace data than you want to pay to store, so you sample. A fixed 1-in-100 rate cuts your bill, but it's blind. It keeps 1% of your errors, 1% of the requests to that rarely-hit route, and 1% of the health checks, all at the same rate. The noisy traffic you care about least dominates what you keep while the traces you need during an incident are the ones most likely to be gone.

Comparisons of SAP observability tools often evaluate which platforms can see inside SAP.Today, that’s nearly all of them. Dynatrace, Datadog, New Relic and Splunk can all get SAP telemetry. None of them are likely the best choice for an SAP-centric application, and we will document why. The questions teams evaluating SAP observability solutions should consider: That last one is where most of these platforms stop, and it is the difference between observability and operations.

Legacy systems, cloud growth, and AI are reshaping government IT. See how connected visibility helps teams respond faster and keep essential services running.

Datadog has been named the Company to Beat for observability platforms in the August 2026 Gartner AI Vendor Race research. Datadog has also been named a Leader in the 2026 Gartner Magic Quadrant for Observability Platforms for the sixth consecutive year. We believe that these recognitions reflect what we have been building toward for more than a decade: a single platform where teams can observe, secure, and act on everything that matters across their technology stack.

For teams building AI agents, the feedback loop should already be a familiar idea: watch how the agent behaves, find what needs improvement, ship a change, and measure the result. In theory, each turn builds on the last until the loop becomes a flywheel and your agent is getting more effective with each turn. In practice, many of us are still in reaction mode. A user reports something strange, costs spike, or an eval score drops.