Your AI SRE
Production Intelligence

Several tools address AI-driven incident investigation, and the field is growing quickly. OpsWorker is purpose-built with EU teams in mind. It runs fully within EU AWS regions, so your investigation data never crosses regional boundaries. For teams with stricter compliance requirements, OpsWorker also offers a private-cloud deployment model — the full platform can be brought into your own infrastructure, whether that's AWS, Azure, GCP, or an on-premise Kubernetes environment. You own the data, the compute, and the pipeline. No third-party AI providers involved.

Three things. First, OpsWorker is Kubernetes-native. It understands pods, services, deployments, ingresses, and how they connect to each other. Second, it works with your existing stack. Prometheus, CloudWatch, Datadog, Slack, GitHub. No migration, no rip-and-replace. Third, it shows its work. Every investigation produces a full trace of what was checked, what was found, and why the conclusion was reached. You can ask follow-up questions in real-time chat, drill into individual evidence, and provide section-level feedback on the analysis. No black boxes.

OpsWorker runs a multi-agent investigation pipeline with five specialized AI agents. When an alert fires, the extraction agent parses alert metadata. The topology agent discovers affected Kubernetes resources by crawling the resource graph (pod to service to deployment to ingress) and validates wiring between them (selectors, labels, ports). The dependency agent maps service dependencies. The investigation agent gathers live runtime data: logs, events, configurations, resource metrics. The analysis agent synthesizes everything into a root cause with specific remediation commands.

OpsWorker provides specific, copy-paste remediation commands (kubectl commands, configuration changes, resource adjustments) but does not execute them automatically. This is a deliberate design choice. Automated remediation sounds great on a conference stage. In production, it means trusting an AI to modify your running infrastructure without human review. OpsWorker gives you the fix in seconds. You decide when to apply it.

From alert received to root cause analysis complete: under 2 minutes. That includes topology discovery, wiring validation, log collection across all affected pods, event correlation, and LLM analysis. For context, the industry average for manual investigation is 30-80 minutes. Most of that time is spent gathering context, not thinking. OpsWorker eliminates the gathering.

Three things. First, investigation notifications: when an alert fires, OpsWorker posts an Investigating message to your Slack channel, then updates it with the full root cause analysis, findings, and remediation steps when the investigation completes. Second, feedback collection: you can rate investigations directly from Slack using emoji reactions, inline buttons (Accurate / Partially Accurate / Needs Improvement), or a detailed feedback modal. Third, the daily alert summary. Everything happens in threads, so your channel stays clean.

Free-form chat is a conversational AI interface for your Kubernetes cluster, independent of any specific investigation. You can ask it anything: show me pods in the payments namespace, why is this service slow, investigate the pod that keeps restarting in staging. It supports multi-turn conversations with persistent history, has access to your cluster via the same secure agent, and dynamically loads tools from all your connected integrations (GitHub, Slack, Kubernetes). Think of it as an SRE copilot that knows your cluster.

Yes. Every investigation has a built-in chat interface. You can ask questions like why a memory issue was ruled out or request logs from another pod in the service and get real-time responses. The chat has full context of the investigation findings and can run additional live queries against your cluster to answer your questions. You can also restart an investigation with additional context if you have information that wasn't available to the initial analysis.

Multiple ways. From Slack: emoji reactions for quick thumbs-up, buttons for categorization (Accurate / Partially Accurate / Needs Improvement), or a detailed feedback modal. From the portal: section-level feedback on individual parts of the analysis (root cause accuracy, remediation quality, evidence completeness). This feedback helps OpsWorker's team continuously improve investigation quality.

Alert fatigue isn't about getting too many alerts. It's about spending 30 minutes investigating an alert only to find it was a transient blip. OpsWorker investigates every alert the moment it fires, so by the time an engineer looks at it, the root cause analysis is already there. The daily summary gives you a morning overview of what happened overnight without checking dashboards. The alert that took 40 minutes to triage now takes 30 seconds to review. Engineers stop ignoring alerts when the investigation is already done for them.

No. OpsWorker replaces the most tedious part of on-call: the investigation. The 3 AM page still happens. But instead of spending 45 minutes context-switching between dashboards, logs, and kubectl commands while half-asleep, the on-call engineer opens the Slack notification or the portal and sees exactly what went wrong, which resources are affected, and what to do about it. They can ask follow-up questions in chat if they need more detail. The engineer still makes the call. They just make it in minutes instead of an hour.

Alert sources: Prometheus AlertManager, AWS CloudWatch, Datadog. Notification: Slack (investigation results, feedback collection, daily summaries). Code context: GitHub (commits, PRs, code correlation via GitHub App). Kubernetes: lightweight read-only in-cluster agent via Helm chart, communicating over SQS. All integrations are managed per-cluster from the portal, with test/simulate functionality to verify connectivity before going live.

Yes. OpsWorker is designed as an add-on, not a replacement. It ingests alerts from your existing monitoring tools via webhook. It doesn't replace your dashboards, your alerting rules, or your runbooks. It adds an AI investigation layer on top of what you already have. Your Prometheus setup stays exactly the same. You just point a webhook at OpsWorker.

OpsWorker uses a lightweight, read-only agent deployed inside your cluster. The agent operates with least-privilege access — it can observe cluster state but cannot make any changes to your workloads or configuration. All communication between the agent and OpsWorker's backend is outbound-only, so there is no inbound network exposure to your cluster. The deployment process is straightforward and does not require changes to your existing infrastructure or monitoring setup.

Security is a core design principle, not an afterthought. The in-cluster agent is read-only and cannot modify your workloads. Investigation data is processed with strict tenant isolation — no data is shared across organizations. Access to the portal is protected by industry-standard authentication with role-based access control. For teams that require full data sovereignty, OpsWorker supports private-cloud deployments where the entire platform runs inside your own infrastructure.

About 15 minutes per cluster. The portal walks you through a step-by-step setup wizard: register your cluster, deploy the Helm chart, configure your alert source webhook, connect Slack. There's a built-in test that sends a simulated alert through the entire pipeline to verify everything works before you go live. No code changes, no agent installation on individual nodes, no changes to your existing monitoring configuration.

OpsWorker is built for engineering teams of 10-50 engineers with 3-10 people in SRE or DevOps roles, handling 20-200+ alerts per week. That's the sweet spot where alert volume is high enough to cause real pain but the team isn't large enough to throw bodies at the problem. The platform supports multi-organization and multi-cluster setups, so it scales with your infrastructure.

Yes. OpsWorker offers a trial period where you can connect a cluster and see investigation results on real alerts. The onboarding wizard includes a simulated alert test so you can see the full investigation pipeline in action within minutes of signing up. The best way to evaluate an investigation tool is to see it investigate your actual incidents, not a canned demo.