kilo-org/kilo-marketplace

splunk-ingest-processor-setup

>- Render Cisco Data Fabric ingest-time routing workflows and Splunk Cloud Platform Ingest Processor setup plans with SPL2 pipelines, source types, destinations, lifecycle handoffs, queue and monitoring searches, metrics, OCSF, decrypt, S3 archive, custom pipeline templates, AI-powered data management readiness, and downstream readiness checks. Use when the user asks to configure Ingest Processor, author Ingest Processor pipelines, route or transform data at ingest time, validate Ingest Process…

First seen Jun 28, 2026

Installation

$ npx skills add kilo-org/kilo-marketplace --skill splunk-ingest-processor-setup

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

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Repository health

Stars 173
License LICENSE
Default branch main
Open issues 14
Status Active

Skill metadata

Parsed from SKILL.md frontmatter.

More metadata
category
observability
source
{"repository":"https:\/\/github.com\/chambear2809\/splunk-cisco-skills","path":"skills\/splunk-ingest-processor-setup","license_path":"LICENSE","commit":"99b2c778dbeaad84023765d24e1a13f414009f6a"}

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 4,736 B
  • docs SUMMARY.md 748 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 7 installs

SKILL.md

Splunk Ingest Processor Setup

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-kit for 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-doctor when that skill is present.

  • Read reference.md before changing coverage, limits, or lifecycle behavior.

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"

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.md and coverage-report.json.
  • apply-plan.json with ui_handoff actions only.
  • source-types/.json, destinations/.json, and pipelines/*.spl2.
  • spl2-pipeline-kit/ rendered by splunk-spl2-pipeline-kit.
  • monitoring/searches.spl and monitoring/usage-summary-handoff.md.
  • lifecycle/*.md for apply, edit, remove, refresh, delete, and rollback

review.

  • handoffs/*.md for 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 region-gated UI assistance, not an API

automation path.

  • Treat AI-powered data management as UI assistance for onboarding, schema, and

pipeline recommendations until Splunk publishes a stable public API.

  • 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.