Robusta
home.robusta.dev
What it is
Robusta is an AI SRE offered through SaaS, a customer VPC deployment, or full self-hosting with the customer’s own LLM key. It learns an environment, groups duplicate alerts, filters noise, and surfaces new issues. When an alert arrives, its AI investigates root cause and blast radius, proposes a fix, and escalates to a human when needed. Alerts can enter through webhooks, HTTP requests, or MCP events, with listed tools including Prometheus AlertManager, Grafana, Datadog, PagerDuty, and Jira. Holmes provides native integrations for Kubernetes, OpenShift, AWS, Azure, GCP, Prometheus, Grafana, PostgreSQL, GitHub, and ServiceNow. Other sources can connect through MCP servers or HTTP APIs, including generated HTTP connectors. Customers may use their own models and API keys and disable Robusta-hosted models. The agent is read-only by default; write access for auto-remediation is optional. Queries, log lines, and conclusions are logged and replayable. Robusta says customer data is not used for model training and that it is SOC 2 compliant. Pricing is on request.
Spec sheet
- Purpose
- Robusta describes itself as an AI SRE that learns an environment, groups duplicate alerts, filters noise, and surfaces new issues.Read 4 Oct 2026 · home.robusta.dev
- Deployment
- Robusta is offered as SaaS, can be deployed in a customer's VPC, or can be fully self-hosted with the customer's own LLM key.Read 4 Oct 2026 · home.robusta.dev
- Compliance
- Robusta says it is SOC 2 compliant and that its report is available on request.Read 4 Oct 2026 · home.robusta.dev
- Support
- Robusta offers to help install the product on a customer's cluster and walk through a live incident.Read 4 Oct 2026 · home.robusta.dev
- Access controls
- The agent is read-only by default, with write access for auto-remediation available as an opt-in.Read 4 Oct 2026 · home.robusta.dev
- Alert sources
- Robusta says it can receive alerts through webhooks, HTTP requests, or MCP events, and lists tools including Prometheus AlertManager, Grafana, Datadog, PagerDuty, and Jira.Read 4 Oct 2026 · home.robusta.dev
- Audit
- Robusta says every query, log line, and conclusion is logged and replayable.Read 4 Oct 2026 · home.robusta.dev
- Custom data sources
- Holmes can connect to data sources through MCP servers or HTTP APIs and can auto-generate a connector for an HTTP API.Read 4 Oct 2026 · home.robusta.dev
- Data integrations
- Holmes supports native integrations including Kubernetes, OpenShift, AWS, Azure, GCP, Prometheus, Grafana, PostgreSQL, GitHub, and ServiceNow.Read 4 Oct 2026 · home.robusta.dev
- Data use
- Robusta says customer logs, traces, and incidents are used to answer questions and are never used to train models.Read 4 Oct 2026 · home.robusta.dev
- Incident response
- Its AI investigates alerts, identifies root cause, blast radius, and a fix, then escalates to a human when needed.Read 4 Oct 2026 · home.robusta.dev
- LLM choice
- Customers can use their own models and API keys and disable Robusta-hosted models.Read 4 Oct 2026 · home.robusta.dev
- Open source
- Robusta says its core is open source and used by thousands of engineering teams.Read 4 Oct 2026 · home.robusta.dev
- Pricing
- The pricing page asks prospective customers for team and infrastructure details to receive a quote.Read 4 Oct 2026 · home.robusta.dev
Plans and prices
Strong points and limits
Strong points
- Groups duplicate alerts and filters noise
- Native integrations across cloud and monitoring tools
- SaaS, VPC, and self-hosted deployment options
- Read-only default with optional remediation writes
- Queries and conclusions are logged and replayable
Limits
- Pricing requires a quote
- Auto-remediation write access is opt-in
- Customer setup may require cluster installation support
- Full self-hosting requires the customer's LLM key
Who it suits
It suits engineering teams managing cloud and Kubernetes infrastructure that need alert investigation, integrations, and configurable deployment or model control.
Verdict
Robusta combines alert triage, AI investigation, broad infrastructure integrations, and deployment flexibility. Teams should review its quote process, model-key requirements, and desired write permissions before choosing a setup.
Where Specifiction places it
- Cloud Monitoring#21 of 316.9
- Kubernetes Monitoring#43 of 547.0