AI agents are generating telemetry at machine speed — and your observability infrastructure wasn’t built for it. Here’s why legacy platforms will break at agentic scale, and what it means for your IT infrastructure.
You’re paying to store data your team won’t use. Here’s how to stop that before it hits your Datadog bill.
Most enterprises deploying AI agents in production have no idea what those agents are actually doing — and the telemetry that could tell them is getting lost, dropped, or never captured at all.
Apica 2.15.2 brings Grafana Loki forwarding, improved OTel data integrity, and a round of workflow refinements across Flow, Synthetics, and Observe — keeping your telemetry pipeline and monitoring experience running smoothly.
Migrating observability platforms is never just a technical lift-and-shift — it’s a chance to eliminate debt, modernize your telemetry practice, and build an architecture that can handle the data volumes AI workloads are already generating.
Not every organization needs a centralized telemetry pipeline — but this six-dimension self-assessment will tell you honestly whether you’re already paying the complexity tax without realizing it.
Before you evaluate a single telemetry pipeline vendor, there’s critical preparation work that will make or break your implementation and most organizations skip it entirely.
Most organizations don’t decide to invest in a centralized telemetry pipeline. They get pushed into it after cycling through increasingly painful DIY workarounds. Here’s how to recognize where you are in that journey.
The observability industry’s cost crisis isn’t a pricing problem. It’s an architectural one, and pairing OpenTelemetry with intelligent pipeline processing is how you flip the equation so costs scale with value, not volume.
