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Use case

Turn recurring Splunk checks into governed workflows with scheduled execution

Recurring Splunk runbooks — daily health checks, data-quality audits, certificate sweeps — become workflow agents you schedule, route to chat or email, and replay with full audit metadata. Status, tool calls, duration, and cost attach to every execution so on-call rotations spend less time hand-running familiar checks and more time on the incidents the checks surface.

Last updated .

Outcomes you can expect

  • Recurring checks (daily health, data quality, certificates) run unattended with structured pass/warn/fail reports.
  • Severity-aware routing pushes warnings to triage and criticals to on-call without manual escalation.
  • Every execution carries status, tool calls, duration, and cost for audit and observability.
  • Recurring fixes get promoted into DAP change plans with the supporting evidence attached.

Estimates based on Deslicer customer observations and Splunk practitioner experience for environments running full manual pipelines. Actual results vary by environment complexity, team size, and existing tooling.

How the workflow runs

  1. 1

    Pick a workflow template

    Start from a template — Daily Health Check, Data Quality Check, or a custom workflow you built — or compose a fresh one. Templates ship with sensible scoping defaults so a first run produces a meaningful report without forcing you to learn every parameter the underlying agents accept.

  2. 2

    Configure scope and routing

    Choose the indexes, sourcetypes, or hosts the workflow targets, then pick a notification destination — Slack, email, or both. Workflows can route by severity, so warnings drop into a triage channel while criticals page the on-call rotation directly with the relevant evidence links inline.

  3. 3

    Schedule the run cadence

    Set a cron-style schedule — every weekday at 08:00, or twice an hour for a SOC use case. Enterprise plans expose a Workflow Scheduler view that lists every scheduled task with last-run status so a single page tells you whether your operating rhythm is healthy this week.

  4. 4

    Run, review, iterate

    The first scheduled execution produces a structured report — pass / warn / fail per category — with suggested SPL or config edits for any failure. Review the output, tighten thresholds, and adjust scope. Each iteration is versioned so you can compare reports across weeks instead of comparing screenshots.

  5. 5

    Promote to governed remediation

    When a workflow surfaces a class of issues that recur — a noisy props.conf, a stale forwarder fleet — promote the recommended fix into a DAP change plan. The plan inherits the workflow's evidence chain so the reviewer sees the failing run alongside the proposed remediation in a single confirmation card.

  6. 6

    Audit and replay

    Every execution stores status, tool calls, duration, cost, and the artefacts the agents produced. Replay a past run to verify a regression, export the log for an audit, or wire a downstream alert to the per-step JSON so observability tooling can chart the workflow's reliability over time.

References

Run this use case in your environment

Start free, connect a Splunk environment, and run the workflow with a reviewer-approved DAP change plan from the first execution.

Schedule your first workflow