Robusta is live · custom pricing · last verified 23 Oct 2026 · viability monitor
Robusta
Robusta is an AI SRE that groups duplicate alerts into one incident, then has its Holmes agent investigate root cause
Grouping is the whole argument, and Robusta makes it well: per-incident billing is what lets you run frontier models on every alert without the bill exploding — its own calculator puts 500 alerts per day at roughly 5 investigations. Read-only by default, a replayable audit trail, BYO-LLM keys and VPC/self-hosted deployment make it defensible in compliance-heavy shops. It is not APM, not a log store, and you keep your existing incident tool — Robusta makes that tool autonomous rather than replacing it. Compare against incident.io and Rootly if you want the incident workflow itself replaced, and against a DIY Claude-plus-MCP setup if your alert volume is genuinely low.
Verdict generatedVerified 8d ago · liveness 69/100 · cite: rightaichoice.com/tools/robusta
- SRE and platform teams fielding hundreds of alerts a day with heavy duplication
- Regulated organisations needing a read-only agent with a replayable audit trail
- Teams that want to pay per unique incident rather than per duplicate alert
- Kubernetes and cloud-native shops on Prometheus/Grafana, Datadog or a mix of sources
- Teams looking for full-stack APM, end-user monitoring or distributed tracing
- Very small teams with simple infrastructure and a handful of alerts per week
- Organisations wanting built-in log management, storage or a SIEM in the same tool
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Skip Robusta if you have no existing alert pipeline to sit on top of — it investigates what Prometheus, Grafana, Datadog or a webhook already fires, so with a handful of alerts a week the grouping economics never materialise.
Your bill scales with unique incidents, not alerts, so the savings depend on your rules actually deduplicating — noisy alerting that produces genuinely distinct incidents will bill closer to one investigation per alert.
Quote-based, metered per unique incident rather than per seat or per alert, which suits mid-size and large SRE teams with 100+ alerts a day. Against seat-priced peers like incident.io, PagerDuty AIOps or Rootly you're buying investigations, not humans — cheap if duplication is high, less compelling below roughly a few dozen alerts a day, where a DIY Claude-plus-MCP loop may cost less.
In short
Robusta — Robusta is an AI SRE that groups duplicate alerts into one incident, then has its Holmes agent investigate root cause. Best for SRE and platform teams fielding hundreds of alerts a day with heavy duplication, Regulated organisations needing a read-only agent with a replayable audit trail, Teams that want to pay per unique incident rather than per duplicate alert. Pricing is on request (custom quotes).
No head-to-head comparison for Robusta yet — the alternatives below are the closest matches we list.
What is Robusta?
Robusta — Robusta is an AI SRE that groups duplicate alerts into one incident, then has its Holmes agent investigate root cause. Best for SRE and platform teams fielding hundreds of alerts a day with heavy duplication, Regulated organisations needing a read-only agent with a replayable audit trail, Teams that want to pay per unique incident rather than per duplicate alert. Pricing is on request (custom quotes).
Robusta sits between your alert sources and your incident tools. Point Prometheus AlertManager, Grafana, Datadog, New Relic, Dynatrace, Sentry, Splunk, Coralogix, AWS CloudWatch, GCP Monitoring, Azure Monitor, Nagios, SolarWinds, or any webhook, HTTP request or MCP event at it, and the Holmes agent opens an investigation the moment something fires — returning root cause, blast radius, evidence and a suggested fix. Humans get paged only when the agent decides it can't close the loop itself. The grouping engine is the economics. Duplicate alerts collapse into a single incident with shared state, so Robusta's own calculator turns 500 alerts into roughly 5 investigations instead of 500. You pay once per unique incident, and an incident database plus a skill library means results are remembered rather than re-derived on every page. Auto-generated skills per datasource get auto-suggested on later investigations, which Robusta measures at 60% less token spend. Holmes reads across Kubernetes, OpenShift, Helm, ArgoCD, Crossplane, Cilium, AWS, Azure, GCP, Prometheus, Grafana, Datadog, New Relic, Loki, Tempo, OpenSearch, Coralogix, Splunk, Sentry, PostgreSQL, MySQL, MongoDB, SQL Server, ClickHouse, Kafka, RabbitMQ, GitHub, GitLab, Jenkins, Confluence, Notion, Slab and ServiceNow through native connectors, plus any MCP server or HTTP API. For raw HTTP APIs with no MCP wrapper, it auto-generates a connector. Governance targets regulated buyers: read-only is the default and enforced via IAM roles and RBAC, write access for auto-remediation is opt-in, and every query, log line and conclusion is replayable for audit. SOC 2 compliant, no training on your data, and deployment as SaaS, in your own VPC, or fully self-hosted with your own LLM key. It complements incident.io, PagerDuty, FireHydrant and Rootly rather than replacing them.
Key features
- Holmes AI agent investigates alerts the moment they fire
- Duplicate alert grouping collapses repeated alerts into one incident
- Per-incident pricing: 500 alerts can resolve to roughly 5 investigations
- Root cause analysis with blast radius, evidence and suggested fixes
- Incident database keeps shared state across investigations
- Auto-generated skills per datasource, auto-suggested on later investigations
- 60% fewer tokens reported with auto-generated skills
- Native connectors for Kubernetes, OpenShift, Helm, ArgoCD, Crossplane and Cilium
- Native connectors for AWS, Azure and GCP
- Native connectors for Loki, Tempo, OpenSearch, Coralogix and Splunk
- Native connectors for PostgreSQL, MySQL, MongoDB, SQL Server and ClickHouse
- Native connectors for Kafka, RabbitMQ, GitHub, GitLab and Jenkins
- Native connectors for Confluence, Notion, Slab and ServiceNow
- Auto-generates a connector for any HTTP API, even without an MCP server
- Accepts alerts from any webhook, HTTP request or MCP event
Behind the verdict
Robusta's pitch is narrower than the AI-SRE label suggests, and that is a strength. It doesn't sell you dashboards, tracing or log storage — it assumes you already run Prometheus, Grafana, Datadog, New Relic, Dynatrace, Sentry, Splunk or Coralogix, and it assumes you already page through Slack, Teams, PagerDuty, Opsgenie, Jira, ServiceNow or a webhook. What it adds is reasoning on top of those sources plus a grouping layer that decides how often you pay for that reasoning. The grouping engine is the part worth scrutinising in a trial. Robusta's own calculator contrasts 500 alerts per day against a DIY setup connecting LLMs to MCP servers for observability tools, and claims 500 alerts collapse to about 5 investigations — turning a five-figure annual model bill into a four-figure one at its $2.50-per-investigation benchmark. Whether your alert stream actually deduplicates that well depends on how noisy your rules are, so run it against a real week of alerts before believing the ratio. The Holmes agent's reach is genuinely wide: Kubernetes, OpenShift, Helm, ArgoCD, Crossplane and Cilium on the platform side; AWS, Azure and GCP; Loki, Tempo, OpenSearch, Coralogix and Splunk for logs and traces; PostgreSQL, MySQL, MongoDB, SQL Server and ClickHouse for data; Kafka and RabbitMQ for queues; GitHub, GitLab and Jenkins for change history; Confluence, Notion, Slab and ServiceNow for runbooks. That last group matters — correlating a deploy from GitHub or Jenkins with a pod crash is exactly the cross-source step humans do slowly. Auto-generated connectors for HTTP APIs without an MCP server lower the cost of adding the long tail. Governance is where it separates from weekend-built agent stacks. Read-only enforced by IAM roles and RBAC, opt-in write access for auto-remediation, every query and conclusion logged and replayable, SOC 2 with a report on request, no training on your data, and the option to bring your own LLM keys and disable Robusta-hosted models entirely. Deployment as SaaS, in your own VPC, or fully self-hosted covers most data-residency reviews. Weaknesses to weigh: it is an investigation layer only, so the value is capped by the quality of your existing alert rules and monitoring. Pricing is quote-based — the pricing page routes you through a team-details form and a sales reply — so you cannot model cost from a public list before a conversation. And if your alert volume is genuinely low, the grouping advantage shrinks and a simpler DIY agent may be enough.
Limitations
- Robusta is an investigation layer, not a monitoring tool: it reads your existing alert sources (Grafana, Prometheus, Datadog, New Relic, Dynatrace, Sentry, Splunk, Coralogix, webhooks, MCP, HTTP APIs) and routes to destinations (Slack, Teams, PagerDuty, Opsgenie, Jira, ServiceNow), so it depends on an existing monitoring and incident stack.
- It positions itself as complementing rather than replacing incident.io, PagerDuty, FireHydrant and Rootly.
- Robusta does not provide APM, end-user monitoring, distributed tracing, log storage or a SIEM.
- On pricing, the public pricing page collects your team details and infrastructure setup and states it will come back with a quote, so you cannot model cost from a public list before that conversation.
as of 2026-10-23
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Is Robusta still active?
Robusta is live · custom pricing · last verified 23 Oct 2026 · viability monitor.
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: October 2026
How we score →What's new in Robusta
Checked 8 days agoAcross the latest 1 update: 1 news mention.
What do users say about Robusta?
How we verified this
Every listed fact about Robusta— pricing, features, links, status — is re-read from the vendor's own pages by our verification pipeline and each change is logged with a date; the last pass ran on 23 Oct 2026. Pages mix model-assisted synthesis with human review; see how we verify.
Verification history
We have re-verified Robusta 20 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.
- — changed summary, switching in, setup time, hidden costs, switching out, who it suits, features, pricing fit, who should skip it, limitations, use cases, description, our verdict
- — changed description, our verdict, summary
- — changed limitations, pricing page
- — changed SSL certificate
- — changed integrations, description, who should skip it, who it suits, summary, our verdict, features
- — changed use cases, who it suits, description, our verdict, features, hidden costs, limitations, switching in, switching out, who should skip it, pricing fit, setup time, summary
Showing the 6 most recent of 20 verification passes.
Free to cite with attribution — this page re-verifies continuously.
How much does Robusta cost in 2026?
Robusta: Pricing is on request (custom quotes). Pricing last verified 23 Oct 2026.
Where the pricing makes sense
The company stage and team size where Robusta's pricing actually pencils out — and where peers do it cheaper.
Quote-based, metered per unique incident rather than per seat or per alert, which suits mid-size and large SRE teams with 100+ alerts a day. Against seat-priced peers like incident.io, PagerDuty AIOps or Rootly you're buying investigations, not humans — cheap if duplication is high, less compelling below roughly a few dozen alerts a day, where a DIY Claude-plus-MCP loop may cost less.
Has Robusta's pricing changed?
No plan price for Robusta has moved since we began logging in Aug 2026; the pricing page is re-read on every verification pass.
Who should pick Robusta?
Pick Robusta if you are SRE and platform teams fielding hundreds of alerts a day with heavy duplication, Regulated organisations needing a read-only agent with a replayable audit trail, Teams that want to pay per unique incident rather than per duplicate alert, Kubernetes and cloud-native shops on Prometheus/Grafana, Datadog or a mix of sources.
Look elsewhere if you are Teams looking for full-stack APM, end-user monitoring or distributed tracing, Very small teams with simple infrastructure and a handful of alerts per week, Organisations wanting built-in log management, storage or a SIEM in the same tool, Anyone hoping to rip out PagerDuty, incident.io, FireHydrant or Rootly.
Skip it if Skip Robusta if you have no existing alert pipeline to sit on top of — it investigates what Prometheus, Grafana, Datadog or a webhook already fires, so with a handful of alerts a week the grouping economics never materialise.
GeneratedReal-world workflow fit
Concrete scenarios for the personas Robusta actually fits — and what changes day-one when you adopt it.
Alerts fire from Prometheus AlertManager and Grafana during a node drain; instead of the on-call opening five dashboards, Holmes pulls pod events, ArgoCD sync state and recent GitHub commits in one pass.
Outcome: Duplicate alerts collapse into one incident with a single root cause, blast radius and suggested fix posted to Slack; the on-call starts from an answer rather than a raw alert.
Rolls Robusta out in-VPC with their own LLM key, leaving write access off so the agent can only read Kubernetes, AWS and the databases.
Outcome: Every query, log line and conclusion is replayable for the audit team, and read-only enforcement via IAM roles and RBAC satisfies the security review without blocking AI triage.
Points an unsupported internal HTTP API at Robusta alongside Nagios webhooks, letting the agent auto-generate a connector rather than writing an MCP server.
Outcome: The legacy system participates in investigation with no custom integration work, and the resulting skill is auto-suggested on later incidents with roughly 60% fewer tokens spent.
Use cases
- Auto-diagnose pod crashes and get suggested fixes posted to Slack
- Reduce MTTR by running remediation playbooks on alert triggers
- Correlate duplicate alerts into a single incident with AI root cause
- Investigate network or database latency without manual data collection
- Investigate across AWS, Azure and GCP from one agent
- Correlate a GitHub or Jenkins deploy with the alert that followed it
- Keep a replayable audit trail for compliance-driven incident response
- Deploy self-hosted with your own LLM key for data residency
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.
Cluster install plus source wiring is an afternoon for a platform engineer: connect Prometheus or Grafana and Slack, then run a live incident alongside the Robusta team. A regulated VPC or self-hosted deployment with your own LLM key and IAM review is a multi-week project, dominated by the security review rather than the install.
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 a DIY Claude + MCP setup: point the same observability MCP servers at Holmes so alerts are grouped before investigation instead of investigated one at a time.
- →From PagerDuty AIOps or Opsgenie: keep the paging tool as your destination and route alerts through Robusta first to get root cause on the page.
- →From incident.io, FireHydrant or Rootly: leave the incident workflow in place and add Robusta as the investigation layer in front of it.
- ↗To incident.io or Rootly: those replace incident workflow rather than investigating alerts, so you would return to alert-by-alert manual triage unless you pair them with another agent.
- ↗To a DIY Claude plus MCP stack: cheaper to start but each alert gets investigated individually, which is the cost curve Robusta's grouping exists to flatten.
- ↗To full-stack observability with built-in AI (Datadog Bits AI or Dynatrace Davis): consolidates tooling but ties the agent to one vendor's data model.
Integrations
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
What are the best Robusta alternatives?
The closest alternatives to Robusta we list are Rootly, Resolve AI and Deeptrace. Ranked by direct product-type match, not category overlap.
| Alternative | Pricing | Starts at | Last verified |
|---|---|---|---|
| Rootly | Paid | Pricing not published | — |
| Resolve AI | Contact Sales | Custom pricing | — |
| Deeptrace | Freemium | Pricing not published | — |
Alternatives to Robusta
View all
Rootly
AI-native incident management and on-call that pages, scribes, and finds root cause inside Slack, Teams, or Google Chat.
Resolve AI
Resolve AI is an AI SRE platform whose agents go on-call, triage alerts and investigate incidents for you.
Tools that pair well with Robusta
Common stack mates teams adopt alongside Robusta, with the specific reason each pairing earns its keep.
Rootly
AI-native incident management and on-call that pages, scribes, and finds root cause inside Slack, Teams, or Google Chat.
Resolve AI
Resolve AI is an AI SRE platform whose agents go on-call, triage alerts and investigate incidents for you.
Deeptrace
AI SRE agent that investigates every production alert and posts evidence-backed root causes in Slack in 2–3 minutes.
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