Splunk AI Assistant Setup

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

• Splunk-ai-assistant, Splunk AI Assistant, Splunk AI Assistant for SPL, AI Assistant for SPL, or the Splunk_AI_Assistant_Cloud app.
• Preview and review the splunk ai assistant 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-ai-assistant-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-ai-assistant-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

Shared add-on completion gate

Whenever this workflow installs, configures, or hands off a registry-listed Splunk app or add-on, follow the shared completion gate. Package delivery alone is not success; capture applicable configuration, data/readiness, and shipped-view evidence, or explicit package evidence that no dashboards ship.

Automates installation, validation, and Enterprise setup assistance for Splunk AI Assistant (Splunk_AI_Assistant_Cloud). The product was formerly branded Splunk AI Assistant for SPL; keep accepting that name in user requests and docs lookups while Splunk finishes the rename.

What This Skill Covers

This skill handles three operator tasks:

1. Install or update the app from Splunkbase with the shared installer
2. Validate that the app is present, reachable, and in a usable setup state
3. Drive the Enterprise cloud-connected onboarding, activation, and proxy flow

The install path is intentionally thin. It delegates package delivery to splunk-app-install and only adds the product-specific rules that matter for this app.

Package Model

• Primary path: Splunkbase app ID 7245
• Internal app name: Splunk_AI_Assistant_Cloud
• Verified Splunkbase release: 2.2.0 (July 22, 2026), which is also the current public release and advertises Splunk 10.5 support
• The earlier 2.0.0 pin (April 9, 2026) is no longer published in the public release API, so it can no longer be fetched from Splunkbase at all
• Install on search heads only
• The shared installer defaults to verified 2.2.0, so the default path needs no review override
• Do not model this as a private-app upload on Splunk Cloud
• Splunkbase lists compatibility with Splunk Enterprise 9.3+ and Splunk Cloud. Agent Mode requires Splunk platform 10.1+.

Package inspection of 2.2.0 confirms the collection and REST surface this skill drives is unchanged from 2.0.0: the same five saia_* modular inputs (saia_field_summary, saia_knowledge_object_summary, saia_macros_dms_modinput, saia_async_jobs, saia_mdc_federated_datasets) with the same disabled-by-default posture, and the same onboarding and validation handlers (/submitonboardingform, /completeonboarding, /version, /cloudconnectedproxysettings). Feature-level statements about Agent Mode, FedRAMP, Context, and Model Runtime were reviewed against 2.0.0 documentation; re-read the 2.2.0 release notes before relying on version-specific feature behavior.

For Splunk Cloud, the shared installer uses ACS Splunkbase install behavior. For Splunk Enterprise, the shared installer downloads from Splunkbase and installs through the management API.

Agent Behavior — Credentials

The agent must NEVER ask for passwords, tokens, or other secrets in chat.

Splunk and Splunkbase credentials are read automatically from the project-root credentials file (falls back to ~/.splunk/credentials). If neither exists, guide the user to create it:

bash skills/shared/scripts/setup_credentials.sh

The agent may ask only for non-secret values such as:

• whether the user wants a pinned app version
• onboarding email, region, company name, or tenant name
• whether the Enterprise target is standalone or part of a search head cluster

Activation codes and proxy passwords must come from local files, not from chat.

Environment

Item	Value
Search-tier API	SPLUNK_SEARCH_API_URI env var (legacy alias: SPLUNK_URI)
Cloud stack	SPLUNK_CLOUD_STACK for Splunk Cloud installs
App name	Splunk_AI_Assistant_Cloud
Splunkbase ID	7245
Credentials	Project-root credentials file (falls back to ~/.splunk/credentials)
Skill scripts	skills/splunk-ai-assistant-setup/scripts/

Remote Splunk Connection

export SPLUNK_SEARCH_API_URI="https://splunk-host:8089"

Setup Workflow

Step 1: Install Or Update The App

bash skills/splunk-ai-assistant-setup/scripts/setup.sh --install

To pin a specific release:

bash skills/splunk-ai-assistant-setup/scripts/setup.sh \
  --install \
  --app-version X.Y.Z

When no flags are passed, the setup script performs install plus validation.

Step 2: Complete Platform-Specific Onboarding

Splunk Cloud

• The app must be installed from the public Splunkbase listing, not as a private upload of a downloaded archive.
• Splunk Cloud self-service installs are supported only on eligible commercial AWS/Azure stacks and supported regions.
• Version 2.0.0 adds limited FedRAMP IL2 support. Agent Mode is not included in the FedRAMP edition, data for training/fine-tuning defaults off, and Model Runtime is fixed to Splunk-hosted models.
• Version 2.0.0 also introduces Agent Mode for supported AWS commercial Cloud regions, renames Personalization to Context, and turns Model Runtime on by default for new installs and upgrades.
• Cloud-side onboarding can require Splunk Web and/or Splunk Support actions, so the skill treats it as a first-class handoff instead of a hidden setup step. Render the handoff plan with:

python3 skills/splunk-ai-assistant-setup/scripts/cloud_onboarding_plan.py \
  --platform cloud \
  --stack my-stack

• The generated plan includes the supported ACS install/update command, validation checks, and the manual Cloud onboarding gates to complete in Splunk Web or a Splunk Support / Cloud App Request.

Splunk Enterprise (cloud connected)

• The search head must be able to reach *.scs.splunk.com on 443
• The shared installer defaults to verified 2.2.0, which is also public latest, so no release override is needed. The Enterprise 9.3+ compatibility statement comes from the Splunkbase listing; confirm it against the release documentation for the exact version you install.
• Optional: configure the outbound proxy first if the search head needs one:

bash skills/splunk-ai-assistant-setup/scripts/setup.sh \
  --set-proxy \
  --proxy-url https://proxy.example.com:8443

• Submit the onboarding form through the app backend:

bash skills/splunk-ai-assistant-setup/scripts/setup.sh \
  --submit-onboarding-form \
  --email ops@example.com \
  --region usa \
  --company-name Example \
  --tenant-name example-prod

• Use the app's region token here. The current US commercial token is usa, and the script normalizes common aliases such as us to usa
• After the form is submitted, the setup script reruns validation so the operator can see the expected pending-activation state immediately
• Save the activation code/token to a local file, then complete activation:

bash skills/splunk-ai-assistant-setup/scripts/setup.sh \
  --complete-onboarding \
  --activation-code-file /tmp/saia_activation_code

• If the target is a search head cluster and deployer-target credentials are configured, the shared installer can deliver through the Deployer bundle path
• Activation still uses Splunk-managed cloud services and may require an activation token obtained from the Splunk onboarding flow
• The remaining blocker after form submission is the Splunk-issued activation code/token, which may not be available immediately
• Proxy credentials and activation codes are read from local files only
• To preview the Enterprise onboarding sequence without making REST calls, run:

python3 skills/splunk-ai-assistant-setup/scripts/cloud_onboarding_plan.py \
  --platform enterprise \
  --region usa

Step 3: Validate

bash skills/splunk-ai-assistant-setup/scripts/validate.sh

Checks:

• app installed and visible
• app configured state and app-owned REST reachability
• Splunk API authentication works
• KV Store health is readable
• Enterprise onboarding state: not started, submitted, or fully onboarded
• Enterprise proxy state

Optional automation assertions:

bash skills/splunk-ai-assistant-setup/scripts/validate.sh \
  --expect-configured true \
  --expect-onboarded true

Notes

• Splunk renamed the app from "Splunk AI Assistant for SPL" to "Splunk AI Assistant" in the 2.0.0 documentation, but the Splunkbase ID and internal app name remain stable.
• Agent Mode is Cloud-limited in 2.0.0; Enterprise validation can confirm app install and Cloud Connected state, but it cannot turn on Agent Mode.
• Chat data for the assistant is stored in the local KV Store on the customer stack, so KV Store readiness matters for validation.
• The validator intentionally avoids the app's /config and /get_feature_flags endpoints for readiness checks because they can error before onboarding is complete.
• SHC delivery depends on the shared installer and deployer-target credentials, not on app-specific SHC logic in this skill.