Firetiger Service Monitors automatically bootstraps best-practice observability for your entire application. Firetiger discovers your application’s architecture, breaks it down into logical Services, and then recommends Service Level Objectives that are continuously grounded in historical telemetry and behavior. Unhealthy Objectives get automatically Investigated, triaged, and escalated to you as

A case study on production objective hill climbing Firetiger runs a few hundred large language model (LLM) agents in production, and prompt caching is a critical tool to manage the cost of running such a workload. Properly setting cache time-to-live (TTL), how long a cached prefix survives before

The Problem With Long-Running Agents Firetiger has many agents with long task horizons (persistent goals which evolve over months). Some are user-defined: “I want my api service to get healthier…” or “I want to ensure our agent output doesn’t degrade…” Agents monitor the system, propose changes, see

Today, we're making Change Monitors generally available for all Firetiger customers. Firetiger Change Monitors pair with every pull request to form a per-change safety net: an agent reads your diff, studies the systems it touches and how they behave in prod, and drafts a targeted post-deploy

Today we're shipping Agent SLOs, a new feature that gives every Firetiger agent a structured way to track the health of the missions it's assigned. Agents now define their own service level objectives (SLOs), evaluate them every session, and use those evaluations to triage the issues