Expert knowledge for Azure Energy Data Services development including troubleshooting, decision making, architecture & design patterns, security, configuration, integrations & coding patterns, and deployment. Use when configuring ADME tiers, partitions & zones, DDMS/ACZ/EDS APIs, security controls, or Geospatial CZ on AKS, and other Azure Energy Data Services related development tasks. Not for Azure Data Explorer (use azure-data-explorer), Azure Synapse Analytics (use azure-synapse-analytics), Azure Data Factory (use azure-data-factory), Azure Databricks (use azure-databricks).
global
Requires network access. Uses mcp_microsoftdocs:microsoft_docs_fetch or fetch_webpage to retrieve documentation.
generated_at:2026-06-21
generator:docs2skills/1.0.0
New
Saved Jun 26, 2026
Azure Energy Data Services Skill
This skill provides expert guidance for Azure Energy Data Services. Covers troubleshooting, decision making, architecture & design patterns, security, configuration, integrations & coding patterns, and deployment. It combines local quick-reference content with remote documentation fetching capabilities.
How to Use This Skill
IMPORTANT for Agent: Use the Category Index below to locate relevant sections. For categories with line ranges (e.g., L35-L120), use read_file with the specified lines. For categories with file links (e.g., [security.md](security.md)), use read_file on the linked reference file
IMPORTANT for Agent: If metadata.generated_at is more than 3 months old, suggest the user pull the latest version from the repository. If mcp_microsoftdocs tools are not available, suggest the user install it: Installation Guide
This skill requires network access to fetch documentation content:
Preferred: Use mcp_microsoftdocs:microsoft_docs_fetch with query string from=learn-agent-skill. Returns Markdown.
Fallback: Use fetch_webpage with query string from=learn-agent-skill&accept=text/markdown. Returns Markdown.
Category Index
Category
Lines
Description
Troubleshooting
L35-L39
Diagnosing and fixing manifest ingestion failures in Azure Data Manager for Energy using Airflow logs, including log analysis steps and common error patterns.
Decision Making
L40-L45
Guidance on choosing ADME deployment tiers (Developer vs Standard) and checking which OSDU data/compute services and capabilities are available in each tier.
Architecture & Design Patterns
L46-L50
Guidance on architecting resilient ADME deployments in Azure Energy Data Services, including zone redundancy, disaster recovery strategies, and high-availability design patterns.
Security
L51-L64
Securing ADME: auth tokens, ACLs, encryption, legal tags, user/group entitlements, managed identities, private endpoints, API Management, and support access controls.
Configuration
L65-L73
Configuring Azure Data Manager for Energy: data partitions, analytics zone setup, CORS, audit logging, and milestone upgrade settings.
Integrations & Coding Patterns
L74-L94
Integrating Azure Energy Data Services with Databricks/Fabric, configuring external data/log export, and using DDMS/ACZ/EDS APIs and tools to read, write, and manage subsurface and well data.
Deployment
L95-L99
Guides for deploying Azure Energy Data Services components, including Geospatial Consumption Zone on AKS and the OSDU Admin UI for Azure Data Manager for Energy administration
Troubleshooting
Topic
URL
Troubleshoot manifest ingestion in Azure Data Manager for Energy using Airflow logs