We've been using OpenClaw for a few months to scan our IaC and cloud configs. The findings are solid, but having them stuck in a dashboard meant they were often ignored by our dev and ops teams. We needed to force accountability by piping critical and high-severity issues directly into Jira for tracking and Slack for immediate visibility.
Here’s the workflow we built and hardened over the last quarter. The goal was zero manual steps from OpenClaw finding to assigned ticket.
**Step 1: Filtering the noise**
* OpenClaw's default alert rules are too broad. We created a custom policy in OpenClaw that only forwards findings matching:
* Severity: CRITICAL or HIGH
* Status: NEW or REOPENED
* Resource Type: Aligned to our actual cloud services (e.g., S3, IAM, K8s deployments)
* This cut the alert volume by ~70%, making the signal actionable.
**Step 2: Building the bridge to Jira**
* We use OpenClaw's webhook capability. On a matching finding, it POSTs a JSON payload to a small internal orchestration service (a simple Python Flask app).
* The orchestration service maps the finding to Jira fields. Key mapping includes:
* OpenClaw severity → Jira Priority
* Resource ID → Jira Summary/Description
* OpenClaw recommendation → Jira Acceptance Criteria
* The service then uses the Jira REST API to create the ticket, automatically assigning it based on the project team mapped to the cloud account.
**Step 3: Slack notification and context**
* The same orchestration service that creates the Jira ticket also posts to a dedicated Slack channel.
* The Slack message is formatted to include:
* Jira ticket key and link
* Short description of the misconfiguration
* The affected environment (prod/staging/dev)
* This gives everyone real-time visibility and a direct link to the work item.
**Key lessons learned:**
* You must tune the OpenClaw alert policy aggressively. Without this, you'll flood your systems and the workflow will be muted.
* The orchestration service is critical. It lets you transform the data and add logic (like assignment rules) that native webhooks can't handle.
* Uptime of your orchestration service is now part of your security SLA. If it goes down, findings are missed. We monitor it like any other critical service.
This took about two sprints to get stable. The main benefit isn't just automation—it's that every finding now has a clear owner and ticket status, which we can report on. Has anyone else built something similar? I'm particularly interested in how you handle de-duplication of recurring findings.
—Chloe
SLA is not a suggestion.