사용 방법
- 설치 명령을 복사하고 자신의 에이전트 환경에 설치하기 전에 소스 패키지를 확인하세요.
- 필요한 도구, 인증 정보, 지원 환경은 원본 문서에서 확인하세요.
- 입력과 원하는 산출물을 설명하고 출처와 결과를 대조하세요.
npx skills add https://github.com/dynatrace/dynatrace-for-ai --skill dt-obs-log-semantic-mapping시작 전 확인
- 설치에는 모델 구독, API 한도, 파일 접근 권한이 포함되지 않습니다.
- 별점 수와 설치 수는 활동 지표이며 독립적인 품질·보안 검증이 아닙니다.
원본 Skill 문서
원본 저장소의 제목, 예시, 코드, 표, 링크, 이미지를 유지해 표시합니다.
dt-obs-log-semantic-mapping
Build and validate semantic-dictionary-aligned mappings for audit log integrations.
Purpose
Use this skill when a user wants to:
- Suggest a mapping from a raw vendor audit log payload to Dynatrace
fetch logsfields (Workflow A). - Validate a mapping against a pasted ingested log event (Workflow B1 — static).
- Validate against live tenant data via live tenant access (Workflow B2 — runtime: fetches logs by
log.source, then runs B1 on the result).
Log Classes
| Class | Description | Key namespaces | Example sources |
|---|---|---|---|
authentication | Login, logout, MFA, token | audit.*, actor.*, browser.*, device.* | CyberArk, Okta, Azure SignInLogs |
authorization | Access decisions, permission changes | audit.*, actor.*, object.* | CyberArk, Okta |
user_action | CRUD on platform resources | audit.*, actor.*, object.*, product.* | Okta, GitHub, Sonatype |
http | HTTP request/response (WAF, network devices) | http.*, url.*, server.*, geo.*, client.* | Akamai SIEM, Cloudflare |
Workflows
| Mode | Input | Source |
|---|---|---|
| Workflow A — Suggest mapping | Raw vendor log payload | references/mapping-workflow.md § Workflow A |
| Workflow B1 — Static validation | Pasted ingested log event | references/mapping-workflow.md § Workflow B1 |
| Workflow B2 — Runtime validation | log.source value + live tenant access | references/runtime-validation.md — fetches logs, then runs B1 |
Key Concepts
Content field burial: The primary validation concern. Fields in content (the raw vendor payload) that could be promoted to top-level semantic attributes but are not. The skill always inventories buried vs promoted fields and proposes OpenPipeline extraction rules to fix gaps.
Prerequisite: When proposing OpenPipeline processor extraction rules, load thedt-dql-essentialsskill first. OpenPipeline processors use DQL functions (parse,fieldsAdd,splitString, etc.) — using non-DQL syntax produces invalid rules.
Sparse mappings are valid: Integrations like GitHub or Sonatype may only populate core fields. Minimum required: timestamp, log.source, content, loglevel, audit.action, audit.identity.
References
references/data-model-notes.md— Log SD field taxonomy, audit namespace, enums, sample-derived patterns and known discrepanciesreferences/mapping-workflow.md— Intake checklist, Workflow A and B1 procedures, content field analysis, field priority orderreferences/validation-rules.md— Required fields, content/enum/type rules, discrepancy severityreferences/openpipeline-constraints.md— OpenPipeline processor command/function/operator/matcher restrictions;parseJsonunavailability +parse→fieldsFlattenalternative; iterative operators for array castingreferences/report-format.md— Mapping table, diff table, OpenPipeline sketch, Validation Summary templatesreferences/runtime-validation.md— Workflow B2: fetch live records, then run B1samples/audit-logs.json— Mapped samples: CyberArk, Okta, Azure SignInLogs, Sonatype, GitHubsamples/http-logs.json— Mapped samples: Akamai SIEM (WAF/HTTP class)- Dynatrace Log Semantic Dictionary
