Splunk Ingest Processor Setup
SkillDev tools"Use when the user asks to configure Ingest Processor, author Ingest Processor pipelines, route or
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Splunk Ingest Processor Setup skill
What this skill tells your AI
The instructions your AI receives, as published by chambear2809/splunk-cisco-skills in skills/splunk-ingest-processor-setup/SKILL.md and read by ahel’s review.
Prerequisites
| Tool or access | Purpose | Verify |
|---|---|---|
| Bash and Python 3 | Run bundled setup and validation helpers | bash --version && python3 --version |
| Required product/platform access | Inspect or configure the selected target | Complete the documented preflight |
| Credential files for live modes | Keep secrets out of chat | Verify paths only |
Workflow Overview
┌───────────┐ ┌───────────────┐ ┌───────────────┐ ┌─────────────────┐
│ Preflight │ → │ Render/review │ → │ Apply/handoff │ → │ Validate evidence │
└───────────┘ └───────────────┘ └───────────────┘ └─────────────────┘
When to Activate
- Configure Ingest Processor, author Ingest Processor pipelines, route or transform data at ingest time, validate Ingest Processor readiness, or compare Ingest Processor with Edge Processor and Data Manager, including Cisco Data Fabric or.
- Preview and review the splunk ingest processor setup workflow before any live apply phase.
- Diagnose failed prerequisites, generated assets, configuration, or validation evidence.
Scope
Follow the documented read-only or render-first path whenever it is available. This skill does not imply permission to mutate live systems. Require explicit apply flags, protected credentials, and operator review for state changes.
Examples
Inspect the supported setup modes before selecting one:
bash skills/splunk-ingest-processor-setup/scripts/setup.sh --help
Expected output: usage, supported modes, and required arguments are displayed without changing the target environment.
Inspect validation modes before running completion checks:
bash skills/splunk-ingest-processor-setup/scripts/validate.sh --help
Expected output: offline, live, and completion options are displayed when the skill supports them; help exits without mutation.
Troubleshooting
| Issue | Cause | Resolution |
|---|---|---|
| Preflight fails | A required tool or access path is missing | Resolve it before rendering or applying |
| Rendered assets are incomplete | Required non-secret inputs are absent | Complete intake and render again |
| Apply is blocked | Review, credentials, or explicit acceptance is missing | Use the documented handoff |
| Validation is incomplete | Live evidence is unavailable | Record the gap and keep completion open |
This skill is a render-first workflow for Splunk Cloud Platform Ingest Processor. It prepares the complete operator packet for IP readiness, source-type and destination setup, SPL2 pipeline authoring, monitoring, and post-ingest data usability.
For newer Cisco Data Fabric wording, this is the Splunk Cloud ingest-time
pipeline route. Keep native Observability Metrics Pipeline Management requests
in splunk-observability-deep-native-workflows unless the user needs
source-type, destination, or SPL2 pipeline assets.
Agent Behavior
- Do not claim private or undocumented Ingest Processor CRUD APIs. The apply path is a UI/support handoff unless Splunk publishes a stable public API.
- Keep credentials out of chat and rendered files. Use local chmod 600 files for HEC tokens, Observability access tokens, cloud keys, and private keys.
- Use
splunk-spl2-pipeline-kitfor SPL2 templates and compatibility linting. - Hand off Splunk Enterprise destinations to
splunk-edge-processor-setup; Ingest Processor destinations are Splunk Cloud, Observability Cloud, metrics indexes, and Amazon S3. - Hand off post-ingest ES/ITSI/ARI/CIM/OCSF/dashboard validation to
splunk-data-source-readiness-doctorwhen that skill is present. - Read
reference.mdbefore changing coverage, limits, or lifecycle behavior. - Treat AI-powered Data Management release stages as capability-specific:
Automated Field Extraction was announced in Controlled Availability, while
Guided Onboarding with Auto-Schematization was announced in Alpha. Both were
announced 2026-03-11 and re-checked 2026-08-20 against the Ingest Processor
release notes updated 2026-06-16, which promote neither capability; see
references/research-ledger.mdfor the recorded negative evidence. Verify current tenant access before presenting either workflow. The announcement says three capabilities but publicly names only these two; do not infer a third capability.
Quick Start
Render a complete offline packet:
bash skills/splunk-ingest-processor-setup/scripts/setup.sh \
--phase all \
--tenant-name acme-prod \
--stack-url https://acme-prod.scs.splunk.com \
--source-types "aws:cloudtrail,crowdstrike:fdr,json_app" \
--destinations "splunk_indexer=type=splunk_cloud;default=true,metrics=type=metrics_index;index=metrics,s3_archive=type=s3;format=parquet;bucket=example-bucket" \
--pipelines "redact_auth=template=redact;sourcetype=json_app;destination=splunk_indexer,http_metrics=template=metrics;destination=metrics"
--phase accepts render, doctor, status, validate, and all. Because
Ingest Processor exposes no public REST API for live status, doctor and
status are offline aliases of validate (render plus structural validation);
they do not query a live tenant.
--dry-run parses and reports the complete plan without creating, deleting, or
rewriting the output directory. Refused destinations (including Splunk
Enterprise/HEC targets and S3 Object Lock) emit their concrete handoff and
return nonzero in every phase; a rendered handoff is not a successful setup.
Normal rendering replaces only an empty directory or one carrying this skill's
ownership marker/legacy README; it refuses to recursively delete an unrelated
nonempty path.
Validate the skill offline:
bash skills/splunk-ingest-processor-setup/scripts/validate.sh
Outputs
The default output directory is splunk-ingest-processor-rendered/:
readiness-report.mdandcoverage-report.json.apply-plan.jsonwithui_handoffactions only.source-types/*.json,destinations/*.json, andpipelines/*.spl2.spl2-pipeline-kit/rendered bysplunk-spl2-pipeline-kit.monitoring/searches.splandmonitoring/usage-summary-handoff.md.control-plane-handoffs/ai-powered-data-management.mdwith current availability, access, review, and no-automation guardrails.lifecycle/*.mdfor apply, edit, remove, refresh, delete, and rollback review.handoffs/*.mdfor HEC, Edge Processor, S3 Federated Search, and data-source readiness workflows.
Coverage Rules
- Ingest Processor is Splunk Cloud Platform Victoria Experience only.
- Verify provisioning, subscription/tier, roles, service account access, indexes, lookups, and connection refresh before authoring pipelines.
- Confirm default destination behavior in the UI before applying a pipeline.
- Validate source-type event breaking, sample data, and preview results before apply.
- Treat Automated Field Extraction as a Controlled Availability, region-gated UI suggestion workflow, not an API automation path. Verify tenant entitlement and current feature visibility before use. Announced 2026-03-11, re-checked 2026-08-20: the release notes updated 2026-06-16 list AFE under February 18, 2026 with no release-stage label, label other features "(Controlled Availability release)" and "(General Availability release)" inline when those stages apply, and never state that AFE is generally available.
- Treat Guided Onboarding with Auto-Schematization as an Alpha, enrollment- gated UI workflow. It can recommend CIM mappings and candidate TA or SPL2 outputs, but this skill does not invoke the service, enroll a tenant, generate a TA, install a TA, or apply a generated pipeline. Announced 2026-03-11, re-checked 2026-08-20: the release notes updated 2026-06-16 contain no Auto-Schematization or Guided Onboarding entry, which is equally consistent with still-Alpha and with withdrawal, so the Alpha stance holds.
- Require human review, SPL2 lint/preview, representative sample validation, CIM validation, and an explicit apply decision for every AI-generated recommendation or artifact.
- Treat decrypt as a private-key lookup workflow and warn about throughput.
- Treat S3 Object Lock as unsupported for rendered IP destination plans.
- Render and review known issue guardrails: tenant-admin-only editing, no data
delivery guarantees under high back pressure or destination outages,
single-browser-session editing, forwarder
useACK=false, HEC indexer acknowledgement off, and CIDR lookup matching unsupported.
Signals
- GitHub stars
- 37
- Forks
- 8
- Last commit
- Sep 2026
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splunk-ingest-processor-setup- Source
- github.com/chambear2809/splunk-cisco-skills