Five agents. One console.
Each agent owns a workflow you already run — on-call, investigation, cost, SLOs, code. They share one model of your clusters, hand off to each other, and learn from every action you approve.
Wakes up so you don't have to.
Listens to Prometheus and Alertmanager (and Datadog / Splunk / Sentry via MCP). Every firing alert is pre-investigated by the time the human gets paged. Severity-aware grouping silences the cacophony; the agent posts a single thread per incident, ranks likely causes, attaches the evidence, and asks for approval — not for archaeology.
- Pre-investigates every alert (no manual click)
- Posts threaded replies in Slack — escalates like a human would
- Native sinks: PagerDuty, Opsgenie, incident.io
- AI alert suppression cuts noise without dropping signal
- Auto-runs guarded remediations once trust is established
Built with: Prometheus · Alertmanager · Slack · PagerDuty · Opsgenie · incident.io
Returns the root cause, not the symptom.
Click any workload — or let the on-call agent invoke it. Reasons across seven signals: metrics, logs, traces, events, deploys, config and topology. Builds a knowledge graph of cause and effect, drafts the fix as a pull request, and logs everything in the evidence vault so the post-mortem is half-written before the incident resolves.
- Reasons across 7 signals: metrics, logs, traces, events, deploys, config, topology
- BlastRadius DAG — shows what else is at risk
- Investigation Workbench: AI + pinned evidence + scratchpad in one view
- Drafts the fix PR (GitHub or GitLab MR)
- Verifier reranker keeps confidence honest
- Post-mortem auto-generated from the evidence trail
Built with: OpenAI · Anthropic · AWS Bedrock · or your self-hosted model · GitHub · GitLab
Finds the 73% you're paying for and not using.
OpenCost-style allocation per workload, with 7-day trend, idle %, and projected monthly spend. Labels what's starving and what's wasteful; opens right-sizing pull requests with the exact resource changes. Multi-cloud — AWS Cost Explorer, GCP Billing (BigQuery), and Azure Cost Management all roll into one view.
- Per-workload allocation with $-denominated waste
- Idle % + biggest movers + anomaly detection
- 7-day sparklines on every row
- Right-sizing PR drafted from the recommendation
- Multi-cloud: AWS + GCP + Azure unified
- Cost watcher flags new spend before the invoice does
Built with: AWS Cost Explorer · GCP Billing · Azure Cost Management · GitHub · GitLab
Owns the error budget so you can ship.
Pyrra-native SLO definitions, written straight into the cluster as CRDs. Burn-rate watchers fire when the budget is at risk, not after it's gone. Trust budgets govern when the auto-remediation can act on its own — and when a human approval is required. Built so engineering leadership has a real reliability dial, not a graph nobody trusts.
- Pyrra-native SLO CRDs (no separate tool)
- Burn-rate watchers fire on trajectory, not after breach
- Trust budgets gate auto-actions per workload
- Per-cluster + per-namespace + cross-cluster federated
- Error-budget dashboards leadership can actually read
Built with: Pyrra · Prometheus · your existing SLO definitions
Every regression linked to the line that caused it.
Watches your deploys, code repos, and config sources. When a regression appears, it identifies the commit, surfaces the diff, and proposes a rollback or fix as a pull request — with the failing telemetry inlined. The bridge between the SRE who sees the symptom and the engineer who can fix it.
- Deploy → regression attribution via change-window join
- Surfaces the offending commit + PR + author
- Drafts rollback or forward-fix as a PR
- Pre-deploy risk assessor: blocks risky changes
- Code-aware: understands your repo structure
Built with: GitHub · GitLab · ArgoCD · Flux
One model of your clusters. Five voices.
Every agent reads from the same live topology, the same knowledge graph, the same change-attribution table. When the On-call agent escalates, the Investigation agent picks up the same context. When Cost flags waste, the Code agent drafts the right-sizing PR. No tool-stitching, no copy-paste between dashboards.
Put an AI SRE on every cluster.
See oneinfra investigate a live incident, surface idle spend, and draft a fix — in a 20-minute walkthrough on your stack.