How it works
One self-correcting loop, from alert to fix
Reflexion is Agentic SRE: it reasons like a senior on-call engineer, but it checks its own work before it touches your cluster — and it's safe by default.
1. Observe
Reflexion ingests the live signal — Prometheus metrics, Loki logs, Alertmanager alerts, and Kubernetes state — and assembles a context snapshot of what's actually happening.
2. Propose (Actor)
The Actor reasons over the snapshot and your runbooks to propose a concrete remediation hypothesis — a scale, rollback, restart, config change, or HPA adjustment — with a pre-computed rollback.
3. Validate (Critic)
The Critic checks the hypothesis against SLO impact and policy. It catches logical flaws and policy violations before anything runs, and can require human approval for high-risk actions.
4. Execute
Only approved actions execute — via a GitOps pull request or kubectl — with the rollback stored atomically. Every decision is recorded immutably for audit and replay.
5. Learn
The outcome of each action becomes a training signal. The Avirka SRE models are fine-tuned on your incidents, so the loop gets sharper every time it runs.
Engagement model
From first conversation to production partner
We start small and prove value before asking you to commit — the same incremental, verify-before-you-act approach Reflexion takes with your cluster.
1. Discovery
We map your incident history, tooling, and policy constraints to see where Reflexion fits.
2. POC
A scoped proof of concept runs against real (or shadowed) signals in your environment.
3. Engineering deliverables
Integrations, runbooks, and policy guardrails are hardened for production use.
4. Strategy
We align on rollout scope, ownership, and success metrics for broader adoption.
5. Partnership
Reflexion runs as an ongoing part of your SRE practice, with support as it scales.