Robusta
Robusta is AI SRE software that auto-investigates alerts, groups duplicates, and scales your LLM bill with unique incidents, not alert
Robusta's grouping engine is the reason to shortlist it: per-incident billing turns a runaway LLM observability bill into something finance will actually approve. The read-only default, replayable audit trail and BYO-LLM option make it defensible in regulated shops. Just go in knowing the pricing page is a contact form — you will need a quote before you can model your own numbers.
Verified 18h ago · liveness 69/100 · cite: rightaichoice.com/tools/robusta
- SRE and platform teams handling hundreds of alerts a day who need AI triage before a human is paged
- Regulated organisations that require a read-only agent with a replayable audit trail and SOC 2 controls
- Teams that want to pay per unique incident rather than per alert, and plug in their own LLM keys
- Kubernetes and cloud-native shops already on Prometheus/Grafana or Datadog that want that stack investigated automatically
- Teams that need full-stack APM, end-user monitoring or distributed tracing — Robusta reads those tools, it doesn't replace them
- Buyers who need a published price list before they can evaluate; pricing here starts with a quote request
- Very small teams with simple infrastructure and a handful of alerts per week, where setup won't pay back
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Skip Robusta if you need full-stack APM or log management, have no existing monitoring stack, or don't want to deal with quote-based pricing.
Pricing is quote-based, so you'll need to contact sales; there is no self-serve tier.
Robusta's per-incident pricing can cut AI investigation costs by up to 99% versus per-alert billing. It's best for teams with high alert volume; for smaller teams, simpler and cheaper alternatives may suffice.
In short
Robusta — Robusta is AI SRE software that auto-investigates alerts, groups duplicates, and scales your LLM bill with unique incidents, not alert. Best for SRE and platform teams handling hundreds of alerts a day who need AI triage before a human is paged, Regulated organisations that require a read-only agent with a replayable audit trail and SOC 2 controls, Teams that want to pay per unique incident rather than per alert, and plug in their own LLM keys. Contact Sales pricing.
What's new in Robusta
Checked 16 days agoAcross the latest 1 update: 1 news mention.
Viability Score
How well maintained and how widely used is Robusta? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: September 2026
How we score →Key Features
- AI agent (Holmes) investigates alerts the moment they fire
- Automatic duplicate alert grouping into a single incident
- Per-incident investigation so cost scales with unique problems, not alert volume
- Root cause analysis with blast radius and suggested fixes
- Incident database with shared state across investigations
- Auto-generated skills per datasource, auto-suggested on later investigations
- Auto-generated connectors for HTTP APIs with no MCP server
- Accepts alerts from any webhook, HTTP request, or MCP event
- Read-only by default, enforced by IAM roles and RBAC
- Opt-in write access for auto-remediation
- Replayable audit trail on every query, log line, and conclusion
- Deploy as SaaS, in your own VPC, or fully self-hosted
- Bring your own LLM with your own API keys; disable hosted models
- SOC 2 compliant with independently audited controls
- Escalates to Slack, Microsoft Teams, PagerDuty, Opsgenie, Jira, ServiceNow
About Robusta
Robusta is an AI SRE platform that sits on top of the monitoring and incident tools you already run. It ingests alerts from anything that can fire a webhook, HTTP request, or MCP event — Prometheus AlertManager, Grafana, Datadog, New Relic, Dynatrace, AWS CloudWatch, GCP Monitoring, Azure Monitor, Splunk, Sentry, Coralogix, PagerDuty, Opsgenie, Rootly, Jira, Nagios, SolarWinds — and points its Holmes agent at the alert the moment it fires. Holmes returns root cause, blast radius, and suggested fixes, then escalates to a human only when it has to. On-call starts from an answer instead of a raw page. The core differentiator is the grouping engine. Duplicate alerts collapse into one incident with shared state, so the same fault is not investigated five times. Robusta's own benchmark illustrates the arithmetic: 500 alerts can resolve to roughly 5 investigations, because you pay per unique incident rather than per alert. That is the entire commercial pitch — run frontier models on everything without paying to re-investigate the same problem. DIY Claude-plus-MCP setups process alerts one at a time and remember nothing between them; Robusta keeps an incident database and a skill library that grows as it works. Holmes reaches across your whole stack through native connectors for Kubernetes, OpenShift, Helm, ArgoCD, Crossplane, Cilium, AWS, Azure, GCP, Loki, Tempo, OpenSearch, PostgreSQL, MySQL, MongoDB, ClickHouse, Kafka, RabbitMQ, GitHub, GitLab, Jenkins, Confluence, Notion and Slab, plus any MCP server or HTTP API. Where no connector exists, it auto-generates one — including for raw HTTP APIs with no MCP wrapper. Auto-generated skills for each datasource are then auto-suggested on later investigations, which Robusta measures at 60% fewer tokens. Governance is where enterprise buyers will look first. Read-only is the default, enforced by IAM roles and RBAC, with write access for auto-remediation opt-in only. Every query, log line and conclusion is logged and
Behind the Verdict
The honest framing: Robusta solves a billing problem as much as an SRE problem. Most teams that wire an LLM to their observability stack discover the cost curve is set by alert volume, not incident volume, and duplicates dominate alert volume. Robusta inserts a grouping layer before the model ever runs. If your alert stream is noisy, that layer is the product. Pick Robusta when you already have Prometheus, Grafana, Datadog or a comparable stack and you want it investigated rather than replaced. Teams with hundreds or thousands of daily alerts, regulated industries that need read-only agents and replayable logs, and anyone who wants to plug in their own LLM keys and drop Robusta-hosted models entirely — all three land squarely in the target. The auto-generated connectors matter more than they sound: the long tail of internal HTTP APIs is where DIY agent projects usually stall. Pass if you need full-stack APM, built-in log management or distributed tracing — Robusta reads those systems, it does not replace them. Very small teams with a handful of alerts a week will not recover the setup effort, and anyone shopping for a free open-source alternative should look elsewhere. The closest comparison is rolling your own agent: Claude Code plus MCP servers pointed at your observability tools. That approach works and costs nothing in licence fees, but it investigates every alert individually and forgets what it learned. Robusta's counter is the shared-state incident database and auto-generated skills, which it claims cut tokens 60%. Whether that claim survives your own traffic is the real evaluation question. One practical caveat before you build a business case: the pricing page asks for a quote rather than publishing tiers, so the per-incident rate is a conversation. Get
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Real-world workflow fit
Concrete scenarios for the personas Robusta actually fits — and what changes day-one when you adopt it.
Prometheus alerts flood Slack every minute, but many are duplicates. Robusta groups them into a single incident, investigates root cause, and posts a summary with fix suggestions.
Outcome: On-call engineers respond to one clear alert with actionable context instead of hundreds, slashing MTTR.
A new pod crash pattern appears. Robusta's Holmes investigates, checks logs, and suggests a fix in 60 seconds.
Outcome: Engineer applies the fix and resolves the issue in minutes, avoiding hours of manual debugging.
Multiple teams send alerts from different tools. Robusta ingests them all via webhooks, groups duplicates, and provides a unified incident view with full audit trail.
Outcome: Centralized incident response with compliance-ready audit logs, improving operational efficiency.
Use Cases
- Automatically diagnose pod crashes and suggest fixes in Slack.
- Reduce MTTR by running remediation playbooks on alert triggers.
- Correlate multiple alerts into a single incident with AI root cause.
- Monitor cluster health and proactively detect anomalies before outages.
- Integrate with CI/CD to validate deployments and rollback on errors.
- Create custom automation for recurring Kubernetes issues.
- Investigate network or database latency without manual data collection.
- Compliance-driven incident response with full audit trail.
Models Under the Hood
as of 2026-08-31
Limitations
- Pricing is quote-based and not publicly listed.
- Requires an existing monitoring/alerting stack that can send webhooks or integrate via MCP/HTTP API.
- Self-hosting may require Kubernetes installation.
- Focuses on alert investigation and grouping.
as of 2026-08-30
Verification history
We have re-verified Robusta 17 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
- — re-verified summary, description, our verdict, our analysis, pricing model, pricing tiers, features, integrations, who it suits, who should skip it
Showing the 6 most recent of 17 verification passes.
Free to cite with attribution — this page re-verifies continuously.
Where the pricing makes sense
The company stage and team size where Robusta's pricing actually pencils out — and where peers do it cheaper.
Robusta's per-incident pricing can cut AI investigation costs by up to 99% versus per-alert billing. It's best for teams with high alert volume; for smaller teams, simpler and cheaper alternatives may suffice.
Setup time & first value
How long it actually takes to get something useful out of Robusta — broken out by persona, not the marketing-page minute.
For SaaS, you can connect an alert source via webhook in minutes and see value on the next alert. Self-hosted on Kubernetes takes an hour or two; onboarding support is available.
Switching to or from Robusta
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From Splunk On-Call: Route alerts to Robusta via webhook; configure grouping and escalation.
- ↗To PagerDuty: Export incidents and use its API to recreate alerts if leaving Robusta.
Integrations
Resources & Guides
Tutorials & Learning
YouTube returned 6 videos for “Robusta”, and we withheld 6: 6 could not be judged, because “Robusta” is a single word that other videos use for other things. We are showing none, because we could not prove any of them are about Robusta.
Official links
Tools that pair well with Robusta
Common stack mates teams adopt alongside Robusta, with the specific reason each pairing earns its keep.
Alternatives to Robusta
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