Official agent skill

Observability Onboarding

by elastic in elastic/agent-skills

Onboard an application into Elastic Observability with the Elastic Distribution of OpenTelemetry (EDOT): route on language and runtime, detect and replace a classic Elastic APM agent, apply the…

OfficialApache-2.0Auto-check passedDevOps & Cloud

Install Observability Onboarding

skills CLI
$ npx skills add elastic/agent-skills --skill observability-onboarding -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install elastic/agent-skills observability-onboarding --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/elastic/agent-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/observability/onboarding .claude/skills/observability-onboarding && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
observability-onboarding
GitHub stars
592
Token cost
~4.1k tokens
SKILL.md length
1,863 words
Files
5 (incl. references)
Skills in repo
26
Repo updated
First seen
Licence
Apache-2.0

At a glance

Onboard an application into Elastic Observability with the Elastic Distribution of OpenTelemetry (EDOT): route on language and runtime, detect and replace a classic Elastic APM agent, apply the…

  • Works in 5 steps: Identify the language and runtime. Read… → Detect a classic Elastic APM agent. The… → Resolve the telemetry destination. The… → …
  • Adding observability to a service
  • SKILL.md covers Environment Configuration, Jobs to be done, Output discipline and Process: route the request, plus 5 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Observability Onboarding is an agent skill from elastic/agent-skills, published by the product's own GitHub organization. Onboard an application into Elastic Observability with the Elastic Distribution of OpenTelemetry (EDOT): route on language and runtime, detect and replace a classic Elastic APM agent, apply the required OTLP configuration, and then verify with ES|QL that traces, metrics, and logs actually arrive under the expected service name. Use when adding observability to a service, migrating off the classic Elastic APM agent, or debugging why an instrumented service is not showing up in Elastic.

Its SKILL.md is about 4.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including reference files (for example `references/dotnet.md`, `references/java.md` and `references/php.md`). Compatibility notes: Requires the elastic CLI (= 0.2) with an Elasticsearch context for the verification step, and an OTLP destination reachable from the application — either the…

It sits in DevOps & Cloud, covering Observability and Monitoring and alerting. It works with OpenTelemetry and Elasticsearch. The repository describes itself as: Official Elastic Skills. The licence is Apache-2.0.

When your agent uses it

  • Adding observability to a service
  • Migrating off the classic Elastic APM agent
  • Debugging why an instrumented service is not showing up in Elastic

Example prompts

  • “/observability-onboarding”

Requirements

  • Python 3
  • Compatibility (from SKILL.md): Requires the `elastic` CLI (>= 0.2) with an Elasticsearch context for the verification step, and an OTLP destination reachable from the application — either the Elastic managed OTLP endpoint or an EDOT Collector. ES|QL verification requires Elasticsearch 8.11 or later. Covers Java, Python, .NET, and PHP runtimes.

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. Identify the language and runtime. Read the project's dependency manifest — pom.xml or build.gradle,
  2. Detect a classic Elastic APM agent. The decision: instrument path or migrate path. Each language reference lists
  3. Resolve the telemetry destination. The decision: which URL goes in OTEL_EXPORTER_OTLP_ENDPOINT. Two valid
  4. Apply the shared configuration below, then the language reference. The shared rules are the same for every
  5. Verify. Do not report success from the configuration alone — run the verification process.

What it can do on your machine

Read from SKILL.md and the folder at commit baa5111. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are esql).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • github.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    Requires the `elastic` CLI (>= 0.2) with an Elasticsearch context for the verification step, and an OTLP destination reachable from the application — either the Elastic managed OTLP endpoint or an EDOT Collector. ES|QL verification requires Elasticsearch 8.11 or later. Covers Java, Python, .NET, and PHP runtimes.

    From compatibility in the SKILL.md frontmatter.

Context cost

Observability Onboarding loads about 4.1k tokens when it runs, and up to ~9.1k if it reads all its reference files. Until then it costs about 129 tokens; SKILL.md has 1,863 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~129
When it runs · the whole SKILL.md, loaded when a task matches
~4.1k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~9.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from elastic/agent-skills at commit baa5111, republished under its Apache-2.0 licence (© elastic). 1,863 words, ~4,066 tokens.

Download SKILL.mdSave it as .claude/skills/observability-onboarding/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
observability-onboarding
description
Onboard an application into Elastic Observability with the Elastic Distribution of OpenTelemetry (EDOT): route on language and runtime, detect and replace a classic Elastic APM agent, apply the required OTLP configuration, and then verify with ES|QL that traces, metrics, and logs actually arrive under the expected service name. Use when adding observability to a service, migrating off the classic Elastic APM agent, or debugging why an instrumented service is not showing up in Elastic.
compatibility
Requires the `elastic` CLI (>= 0.2) with an Elasticsearch context for the verification step, and an OTLP destination reachable from the application — either the Elastic managed OTLP endpoint or an EDOT Collector. ES|QL verification requires Elasticsearch 8.11 or later. Covers Java, Python, .NET, and PHP runtimes.
metadata.author
elastic
metadata.version
0.3.0
metadata.universal
true

Observability Onboarding

Instrument an application with the Elastic Distribution of OpenTelemetry (EDOT) and prove the telemetry arrived. The instrumentation change is only half the job: an application can be configured perfectly and still emit nothing, so this skill ends by querying Elasticsearch for the service's data rather than declaring success from a config diff.

The scope is application instrumentation with the EDOT SDKs. Deploying an EDOT Collector, collecting logs from files or infrastructure, and onboarding data through Elastic Agent, Fleet, or integration packages are separate ingest paths that this skill does not cover.

Once telemetry is flowing, use the observability-sre-triage skill to assess service health, observability-k8s-investigation for Kubernetes-layer failures, observability-service-reliability to define SLOs and alerts on the new signals, and observability-llm-obs for GenAI and agentic workloads.

<!-- begin-partial: preamble -->

Environment Configuration

This skill executes Elasticsearch operations through the elastic CLI. If the elastic CLI is not installed, tell the user what it is needed for. Do not guess credentials, call the HTTP API directly, or attempt other workarounds.

This skill references operations in HTTP-shorthand form (e.g., GET /, GET /_cat/indices, GET /{index}/_mapping, GET /{index}/_settings/index.mode, POST /_query). The Operations table at the end of this document maps each shorthand to the equivalent elastic CLI command — always use the CLI rather than calling the HTTP API directly.

<!-- end-partial: preamble -->
Analysis without cluster access

The CLI check above gates querying the cluster — it does not gate analysis. When the user has already supplied the evidence in their question (metric values, counts, status reasons, log lines, alert payloads, configuration), reason from that evidence and deliver the conclusion.

When you genuinely do need data the user has not provided, still say what you would check and how — name the specific query, index, and field that would settle the question — and then ask for CLI setup. An answer that names the check is useful without a cluster; one that only asks for setup is not.

Only the verification step in this skill talks to Elasticsearch; it runs through POST /_query. Everything else edits application code and configuration in the user's workspace.

Jobs to be done

  • Decide whether a service needs fresh instrumentation or a migration off the classic Elastic APM agent
  • Apply the EDOT configuration for the service's language and runtime
  • Point telemetry at the correct OTLP destination and reject APM Server URLs
  • Verify that traces, metrics, and logs land in Elasticsearch under the expected service.name
  • Diagnose an instrumented service that is reporting nothing, or reporting from the wrong agent

Output discipline

Applies to every response produced under this skill.

  • Make the edit. When the language, the current agent, and the destination are known, apply the change. Do not narrate a plan and ask for approval on each file; ask only when a decision genuinely cannot be inferred.
  • Do not dump documentation. Link the relevant page and state the two or three rules that apply to this service. Pasting a whole setup guide into the reply is a defect.
  • Verify before reporting success. "Configured correctly" is not the finding; "telemetry is arriving" is. If verification returns no rows, say the service is not reporting and give the most likely cause.
  • Do not speculate past the evidence. If the verification query is empty, that is one fact with several possible causes — name the likeliest and how to distinguish it, rather than asserting one.
  • End on the result. No trailing offers such as "want me to set up dashboards next?". Follow-up work belongs in a recommendations list, phrased as a recommendation.

Process: route the request

  1. Identify the language and runtime. Read the project's dependency manifest — pom.xml or build.gradle, requirements.txt or pyproject.toml, *.csproj, composer.json. The decision: which language reference to open. Also note how the process starts (a Dockerfile ENTRYPOINT, a Kubernetes pod spec, a systemd unit), because that is where the agent attaches and where the environment variables must be set.

    RuntimeReferenceHow EDOT attaches
    Javareferences/java.md-javaagent: flag or JAVA_TOOL_OPTIONS
    Pythonreferences/python.mdopentelemetry-instrument entrypoint wrapper
    .NETreferences/dotnet.mdbuilder.AddElasticOpenTelemetry() in startup
    PHPreferences/php.mdnative extension via OS package, then full process restart

    For a language not listed, follow the same shape — the required configuration and the following verification step are language-independent — and use the upstream EDOT SDK documentation for the attach mechanism.

  2. Detect a classic Elastic APM agent. The decision: instrument path or migrate path. Each language reference lists the markers; the common ones are ELASTIC_APM_* environment variables and a language-specific Elastic APM package. If any marker is present, take the migrate path — do not layer EDOT on top.

  3. Resolve the telemetry destination. The decision: which URL goes in OTEL_EXPORTER_OTLP_ENDPOINT. Two valid answers, and one common wrong one:

    • The Elastic managed OTLP endpoint for the deployment or Serverless project. Correct default.
    • An EDOT Collector the user already runs, when telemetry must be enriched, sampled, or fanned out before it reaches Elastic.
    • Never an APM Server URL. If the candidate contains apm-server, ends in port 8200, or has an /intake/v2/events path, it is the classic ingest endpoint and EDOT cannot use it. On the migrate path this is the single most common mistake — the old ELASTIC_APM_SERVER_URL value must not be carried over.
  4. Apply the shared configuration below, then the language reference. The shared rules are the same for every runtime; the reference covers only what is language-specific.

  5. Verify. Do not report success from the configuration alone — run the verification process.

Required configuration

Identical across every EDOT SDK. Set exactly three environment variables:

VariableValue
OTEL_SERVICE_NAMEThe service's name. This becomes service.name in Elasticsearch and is how every other Observability skill finds it.
OTEL_EXPORTER_OTLP_ENDPOINTThe managed OTLP endpoint or EDOT Collector URL resolved in step 3.
OTEL_EXPORTER_OTLP_HEADERSThe credential, in Authorization=ApiKey <key> or Authorization=Bearer <token> form.

Two rules that hold for every language:

  • Do not set OTEL_TRACES_EXPORTER, OTEL_METRICS_EXPORTER, or OTEL_LOGS_EXPORTER. The defaults are already correct. Setting them is the usual reason a service reports traces but no metrics or logs.
  • Never run a classic Elastic APM agent and EDOT together on the same process. They double-instrument and produce inconsistent traces. Removal and replacement belong in the same change.
Show full SKILL.md (924 more words)Show less

Process: verify telemetry arrives

Run this after every instrument or migrate change, and as the entry point when a user reports that an instrumented service is missing. Give the pipeline a minute or two after the deployment restarts before concluding anything.

  1. Confirm documents are landing for the service. Query POST /_query, scoping to the service name that was set in OTEL_SERVICE_NAME. The decision: is anything arriving at all, and across which signals.

    esql
    FROM traces-*,metrics-*,logs-* METADATA _index
    | WHERE @timestamp > NOW() - 15 minutes AND service.name == "<service>"
    | STATS docs = COUNT(*), last_seen = MAX(@timestamp) BY _index
    | SORT docs DESC
    | LIMIT 20

    A healthy result has rows from a traces data stream, a metrics data stream, and a logs data stream, with last_seen inside the last minute or two. Missing signals are diagnostic, not cosmetic: traces only, with no metrics or logs, usually means an OTEL_*_EXPORTER variable was set.

  2. If nothing came back, find out what name the service is reporting under. An empty result is ambiguous between "no telemetry at all" and "telemetry arriving under a different name" — a typo in OTEL_SERVICE_NAME, or the SDK default of unknown_service. Drop the service filter and look at what is actually arriving.

    esql
    FROM traces-*,metrics-*,logs-*
    | WHERE @timestamp > NOW() - 15 minutes
    | STATS docs = COUNT(*), last_seen = MAX(@timestamp) BY service.name
    | SORT docs DESC
    | LIMIT 25

    The decision: if the service appears under an unexpected name, fix OTEL_SERVICE_NAME. If it does not appear at all, the exporter is not reaching the destination — go back to step 3 of the routing process and re-check the endpoint and credential.

  3. Confirm EDOT is the reporter, not something else. This is what distinguishes a correct migration from a half-finished one, and vanilla OpenTelemetry from EDOT.

    esql
    FROM traces-*
    | WHERE @timestamp > NOW() - 15 minutes AND service.name == "<service>"
    | STATS spans = COUNT(*) BY telemetry.sdk.language, telemetry.sdk.name, telemetry.distro.name, telemetry.distro.version
    | SORT spans DESC
    | LIMIT 10

    telemetry.distro.name is elastic when an EDOT SDK is reporting. A null distro with telemetry.sdk.name == "opentelemetry" means the application is on the upstream OpenTelemetry SDK rather than EDOT. Two rows for one service — one with the Elastic distro and one without, or two different telemetry.sdk.language values — means more than one agent is attached, or an old deployment is still running.

  4. Diagnose from the shape of the result.

    Verification resultMost likely cause
    No rows for the service, and the name is absent everywhereExporter never reached the destination — wrong endpoint or bad credential
    Service appears under a different nameOTEL_SERVICE_NAME unset or misspelled; SDK fell back to its default
    Traces only, no metrics or logsAn OTEL_*_EXPORTER variable was set and overrode the default
    Rows present but last_seen is staleThe process exited, or the deployment was rolled back
    Two distro values for one serviceClassic agent and EDOT both attached, or an old replica still running

    If the field names above are absent from the mapping, confirm what is available with GET /<index>/_mapping before concluding the telemetry is wrong.

Examples

"Add observability to my Spring Boot service" — read pom.xml to confirm Java, check for co.elastic.apm and ELASTIC_APM_* markers, and finding none, take the instrument path in references/java.md. Add the -javaagent flag to the container entrypoint, set the three environment variables against the managed OTLP endpoint, then run the verification query and report which signals arrived.

"We're moving off the Elastic APM agent to EDOT, we're on .NET" — this is the migrate path. Remove the Elastic.Apm.* packages, the AddAllElasticApm() call, and the ElasticApm block from appsettings.json in the same change that adds Elastic.OpenTelemetry and builder.AddElasticOpenTelemetry(). Translate the configuration rather than copying it — in particular do not reuse ELASTIC_APM_SERVER_URLS as the OTLP endpoint. Verify with step 3 and confirm exactly one distro is reporting.

"I instrumented my Python app but nothing shows up in Elastic" — start at the verification process, not at the configuration. Run step 1; if it is empty, run step 2 to see whether the service is reporting under a different name. If the service is absent entirely, the two candidates are an unwrapped entrypoint (opentelemetry-instrument missing) and an endpoint still pointing at APM Server. Check the entrypoint first — it is the more common of the two.

"Our service sends traces but we have no logs or metrics" — this is the OTEL_*_EXPORTER signature. Confirm it with step 1, which will show a traces data stream and nothing else, then remove the OTEL_TRACES_EXPORTER, OTEL_METRICS_EXPORTER, or OTEL_LOGS_EXPORTER variable from the deployment and re-verify.

Guidelines

  • Read the setup or migration guide for the language before editing. The per-language references link the authoritative page; the attach mechanism differs enough between runtimes that pattern-matching from another language produces broken configurations.
  • Removal and replacement go in one change. A window where both the classic agent and EDOT are attached produces double-instrumented traces that are worse than either alone.
  • Never carry the classic server URL forward. ELASTIC_APM_SERVER_URL points at APM Server; OTEL_EXPORTER_OTLP_ENDPOINT must point at the managed OTLP endpoint or an EDOT Collector.
  • Set the three variables and no more. Additional OTEL_* tuning is occasionally justified, but the exporter variables specifically should be left at their defaults.
  • Treat an empty verification result as unknown, not as failure of a specific component. Distinguish the causes with step 2 before recommending a fix.
  • Never place a credential in the skill's output or in a committed file. OTEL_EXPORTER_OTLP_HEADERS belongs in the deployment's secret mechanism.
  • Attribution: the per-language EDOT guidance consolidated here originates with the apm-agent-devs team.

Operations

HTTP API (shorthand)elastic CLI command
GET /elastic es info
POST /_queryelastic es esql query --format tsv --query '<esql>'
GET /<index>/_mappingelastic es indices get-mapping --index '<index>'

© elastic, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 4 other files (references) in skills/observability/onboarding of elastic/agent-skills.

  • SKILL.md
  • references/dotnet.md
  • references/java.md
  • references/php.md
  • references/python.md

Open the folder on GitHubat commit baa5111

Compare with similar skills

Observability Onboarding next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Observability Onboarding compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Observability Onboarding this skillelastic/agent-skills592—~4.1kAutomated safety check: PassApache-2.0
UModel Root Cause Analysisalibaba/UnifiedModel412—~1.9kAutomated safety check: PassCustom licence
OpenTelemetry Pipeline Metrics Speccomet-ml/opik22k—~3.2kAutomated safety check: PassApache-2.0
Exploring Apm TracesPostHog/posthog40k—~3.5kAutomated safety check: PassCustom licence
Logfire Instrumentationbasicmachines-co/basic-memory4.1k—~2.3kAutomated safety check: PassAGPL-3.0
Developing Funboost Mixinydf0509/funboost892—~2.1kAutomated safety check: PassNone

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Categories

Questions about Observability Onboarding

What does Observability Onboarding do?

Onboard an application into Elastic Observability with the Elastic Distribution of OpenTelemetry (EDOT): route on language and runtime, detect and replace a classic Elastic APM agent, apply the…. Observability Onboarding is an agent skill from elastic/agent-skills, published by the product's own GitHub organization. Onboard an application into Elastic Observability with the Elastic Distribution of OpenTelemetry (EDOT): route on language and runtime, detect and replace a classic Elastic APM agent, apply the required OTLP configuration, and then verify with ES|QL that traces, metrics, and logs actually arrive under the expected service name.

When should I use Observability Onboarding?

Observability Onboarding fits situations like: adding observability to a service; migrating off the classic Elastic APM agent; debugging why an instrumented service is not showing up in Elastic.

How do I install Observability Onboarding in Claude Code?

Run `npx skills add elastic/agent-skills --skill observability-onboarding -a claude-code`. Or copy the skill folder (skills/observability/onboarding in elastic/agent-skills) into .claude/skills/observability-onboarding in your project. Claude Code loads it when a task matches its description.

How do I install Observability Onboarding in Codex?

Run `npx skills add elastic/agent-skills --skill observability-onboarding -a codex`. Or copy the skill folder (skills/observability/onboarding in elastic/agent-skills) into .agents/skills/observability-onboarding in your project. Codex loads it when a task matches its description.

Can I use Observability Onboarding in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add elastic/agent-skills --skill observability-onboarding -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/observability-onboarding, .gemini/skills/observability-onboarding, .github/skills/observability-onboarding and .opencode/skills/observability-onboarding in your project.

What does Observability Onboarding need to run?

SKILL.md names no scripts, command-line tools or credentials: Observability Onboarding is instructions for the agent only. Our summary lists: Python 3. Compatibility (from SKILL.md): Requires the `elastic` CLI (>= 0.2) with an Elasticsearch context for the verification step, and an OTLP destination reachable from the application — either the Elastic managed OTLP endpoint or an EDOT Collector. ES|QL verification requires Elasticsearch 8.11 or later. Covers Java, Python, .NET, and PHP runtimes. .

Does Observability Onboarding access the network?

SKILL.md names 1 domain. As links in the text: github.com. This is read from the text; nothing was executed.

Is Observability Onboarding safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Observability Onboarding use?

Observability Onboarding is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Observability Onboarding use?

About 4.1k tokens (SKILL.md is roughly 16k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 5k tokens, read only when the agent opens those files.

What are the alternatives to Observability Onboarding?

Skills that share tags, products or a category with Observability Onboarding: UModel Root Cause Analysis (alibaba/UnifiedModel, 412 stars), OpenTelemetry Pipeline Metrics Spec (comet-ml/opik, 22k stars), Exploring Apm Traces (PostHog/posthog, 40k stars) and Logfire Instrumentation (basicmachines-co/basic-memory, 4.1k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Observability Onboarding?

elastic (a GitHub organization, an official publisher) maintains it in elastic/agent-skills, which has 592 GitHub stars. The repository holds 26 skills in this directory. The repository was last updated on October 7, 2026.

Source: elastic/agent-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.