Operations | Monitoring | ITSM | DevOps | Cloud

Ask Olly to audit your alert coverage and it pulls the whole set through the API, works through it with a script, and hands back the gaps as a report you can send to the team. DataPrime and PromQL already answer the questions that fit a query language, and Olly has been answering those for a long time. The sandbox is for everything else: the sources that have no query language of their own, the correlations that span two languages at once, and the analysis that needs a script rather than a filter.

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.

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.

Improving an AI agent often involves changing its prompts, models, retrieval methods, or tools. But determining whether those changes actually improve performance can be difficult. A revised prompt might produce better answers for a handful of test cases but perform poorly on unexpected user requests. A cheaper model might reduce token costs while introducing tool-calling errors or longer execution times.

I used to joke that I got my best parenting ideas from management books, and my best management ideas from parenting books. Now, I'm extending it to agents. Hear me out. When you're teaching a teen how to drive, you don't hand them the car keys on day one. You start in an empty parking lot. You ride along and ask them to talk through what they're doing.

The best alert is the one that never fires. Picture an idyllic Tuesday afternoon: last night's release nudged checkout p99 up 41%, but an agent noticed. Nobody got paged, and your SLOs didn't start burning. Instead, the agent acted and already narrowed it down to one retry change. It filed a ticket for the Payments team and flagged the PR. By the time anyone would have noticed, the fix is in review. That's what SRE was always supposed to feel like.

Teams that build agents on open models hosted on Fireworks AI, such as GPT-OSS, Kimi, GLM, Qwen, and MiniMax, need a reliable way to measure whether their LLM applications and agents are giving accurate, safe, and helpful answers efficiently. Datadog Agent Observability now supports Fireworks AI as a model provider, so you can get end-to-end visibility into your agents built on Fireworks AI, from traces and token usage to quality evaluations.