Operate is a self-hosted AI SRE: an AI agent platform that detects, investigates, and resolves production issues. It runs a four-agent pipeline (Context, Root Cause, Verification, and Resolution) that connects to your logs, database, and codebase, then produces an evidence-backed root cause and a draft pull request for human review.

An AI SRE is an AI system that does the work of a site reliability engineer: watching production for errors and regressions, investigating alerts, finding root causes, and proposing fixes. Operate is a self-hosted AI SRE, so it runs inside your own infrastructure with read-only access and a mandatory human approval gate.

How does Operate find the root cause of a production issue?

When triggered from chat (Slack, MS Teams, and other tools) or by an automated alert, Operate pulls traces from log providers like Datadog, CloudWatch, GCP Cloud Logging, and SolarWinds, queries your MongoDB, PostgreSQL, or MySQL database in read-only mode, and reads your codebase via git including blame and diff. A Context Agent gathers signals, a Root Cause Agent proposes a cause with a confidence score, a Verification Agent independently checks the reasoning with a different model, and a Resolution Agent drafts a fix as a pull request.

Does Operate ship code automatically without a human?

No. Operate stops at a draft pull request. A human engineer must review and merge; nothing ships without approval. Every agent step is auditable so reviewers can see the evidence and reasoning behind each finding.

How is Operate deployed?

Operate is deployed as a Docker image into your existing infrastructure with no new cloud accounts. It runs on port 8080 under the /operate path, requires MongoDB and Redis, and uses an App ID from operate.bettrsw.com. It connects via read-only adapters to logs, databases, and observability stacks, and clones your repo at startup via an init container so agents have full git history.

Which integrations does Operate support?

Operate's context layer spans 60+ integrations across 14 categories: source control (GitHub, GitLab), logs (Datadog, CloudWatch, GCP Cloud Logging, SolarWinds), databases (MongoDB, PostgreSQL, MySQL, read-only), error tracking (Sentry, Rollbar), APM (New Relic, Grafana, OpenTelemetry), CI/CD (GitHub Actions, Jenkins, Vercel), feature flags (LaunchDarkly, Statsig), cloud infrastructure (AWS, GCP, Azure, Kubernetes), queues (Kafka, SQS, RabbitMQ), incident management (PagerDuty, incident.io), issue tracking (Jira, Linear, Asana), support (Zendesk, Intercom), status pages, and docs (Confluence, Notion). Triggers: Slack, MS Teams, and other chat tools for on-demand RCA, plus the observability stack for proactive monitoring. AI providers: Anthropic Claude, OpenAI/Azure Codex, enterprise models, or self-hosted open-source LLMs.

How does Operate avoid hallucinated root causes?

Operate uses a two-model verification step. The Root Cause Agent proposes a cause with specific evidence; the Verification Agent, running on a different model to avoid correlated errors, independently evaluates the reasoning. Speculative or unsupported conclusions are rejected before reaching the team.

Why not just point an LLM at our logs ourselves?

An LLM has no inherent knowledge of your logs, schemas, services, or known-bad patterns. Operate provides the connectors, permissions, query layer, repo context, multi-agent verification, and operational runtime that turn a generic model into a reliable production-investigation system.

Engineering teams that lose 30–40% of capacity to unplanned investigation: support escalations, error alerts, performance regressions. With Operate, support and product teams can trigger an RCA from Slack, MS Teams, or whatever chat tool they use, and only loop in engineers when a decision needs to be made.

← All repos

github

jenkinsci/jenkins

Pick an open issue and Operate will investigate its root cause.

3,436 open issues

#27192 Allow rotation and revocation of individual inbound agent secrets
#27188 ArchiveArtifacts crashes if one of the file being archived does not have the read attribute. Unix only.
#27187 Node extensions (version column, platform labeler, ...) need better support for the Nodes page in the new "Manage Jenkins" page
#27177 Jenkins 2.568.1 + Bitbucket Multibranch jobs causes repeated multibranch rescans on every Job DSL seed run
View investigation
#27164 [BUG] QuotedStringTokenizer.quote(String) Javadoc claims conditional quoting but always quotes
#27157 Proposal: centralize a name-length limit in Jenkins.checkGoodName
#27140 [BUG] Min/max form validation message contradicts the inclusive accepted range
#27115 Proposal: Implement Asynchronous/Buffered Console Log Writing to Reduce Executor Lock Contention
#27112 [BUG] Tab does not confirm highlighted dropdown suggestion
#27071 Problems & Limitations with Jenkins Search
#27061 Parallel Plugin Loading and Initialization
#27059 Parallel User scanning at Jenkins Startup
#27041 New Dashboard View prevents deleting multibranch pipeline jobs
#27009 Completed builds later reload with timestamp=0 duration=0 result=ABORTED while build.xml is correct
#27006 Highlighting Jenkins agent when hovering in output console has 'wrong width'
#26948 add update indicator (badge) to System in Manage Jenkins
#26936 Winstone WAR cleanup recurses through /proc/self/task/.../cwd outside configured webroot
#26935 no read(download) timeout for update-center.json
#26920 Combobox (<f:combobox>) flashes its suggestion list on click and immediately closes; typing works fine
#26919 Autocomplete/combobox suggestion requires a double tap to select on touch devices (single tap is lost)
#26879 Freestyle build interrupted during a post-build publisher reports FAILURE instead of ABORTED
#26862 jenkins-cli.jar build command with -s flag aborts long-running builds after Jenkins LTS upgrade from 2.479.1 to 2.541.2
#26849 'Scan Repository Now' does not display green pop-up from top menu dropdown of a GitHub branch source folder
regression
#26814 Form validation shows full error page instead of return code based message on initial page load
#26800 Missing validation for View name length causes HTTP 414 (URI Too Long)
#26739 Log output is incorrect when log lines delay arrival of new-line character
regression
#26726 Inbound WebSocket Jenkins agent intermittently disconnects with Connection timed out / Read side closed
#26695 Rebuild on experimental Build page shows "This URL requires POST" page
ux
#26692 Creating a new Jenkins node programatically does not replace completely existing node
#26689 Build dialog of parametrized pipeline does not close on "Build"