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Expert knowledge for Azure Cosmos DB development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment.
3 of 24 test cases passed with the skill.
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Lift withheld: 4 comparable cases; this report requires 8.
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This skill provides expert guidance for Azure Cosmos DB. Covers troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. It combines local quick-reference content with remote documentation fetching capabilities.
IMPORTANT for Agent: Use the Category Index below to locate relevant sections. For categories with line ranges (e.g.,
L35-L120), useread_filewith the specified lines. For categories with file links (e.g.,[security.md](security.md)), useread_fileon the linked reference file
IMPORTANT for Agent: If
metadata.generated_atis more than 3 months old, suggest the user pull the latest version from the repository. Ifmcp_microsoftdocstools are not available, suggest the user install it: Installation Guide
This skill requires network access to fetch documentation content:
mcp_microsoftdocs:microsoft_docs_fetch with query string from=learn-agent-skill. Returns Markdown.fetch_webpage with query string from=learn-agent-skill&accept=text/markdown. Returns Markdown.| Category | Lines | Description |
|---|---|---|
| Troubleshooting | L37-L87 | Diagnosing and fixing Cosmos DB issues across APIs and SDKs: connection and timeout errors, RU/latency problems, encryption/CMK and replication issues, and advanced diagnostics/log queries. |
| Best Practices | L88-L140 | Performance, scaling, partitioning, RU/cost optimization, SDK usage, change feed, resilience/DR, and best practices for Cosmos DB APIs (NoSQL, MongoDB, Cassandra, PostgreSQL, vector). |
| Decision Making | L141-L191 | Guides for choosing Cosmos DB deployment, scaling, consistency, backup, pricing, and migration options across SQL, MongoDB, Cassandra, Table, and PostgreSQL APIs. |
| Architecture & Design Patterns | L192-L217 | Patterns and reference architectures for AI agents, change feed, analytics, multi-region HA, SaaS/multi-tenant design, microservices, and vector/AI search on Cosmos DB and Cosmos DB for PostgreSQL. |
| Limits & Quotas | L218-L252 | Limits, quotas, and behaviors for Cosmos DB throughput, partitions, backup/restore, serverless, APIs (Cassandra, Gremlin, Table), integrated cache, and PostgreSQL clusters. |
| Security | L253-L319 | Securing Cosmos DB across APIs (NoSQL, MongoDB, Cassandra, Gremlin, Table, PostgreSQL): identity/RBAC, networking, encryption/CMK, auditing, policies, TLS, data masking, and Defender protections. |
| Configuration | L320-L446 | Configuring and tuning Azure Cosmos DB and its APIs (NoSQL, Mongo, Cassandra, Gremlin, Table, PostgreSQL): throughput, indexing, backup/restore, monitoring, SDK performance, fleets, emulators, and HA. |
| Integrations & Coding Patterns | L447-L573 | SDK patterns, bulk ops, change feed, vector search, Kafka/Spark/Kafka Connect, language-specific samples, and integrations for NoSQL, Cassandra, Mongo, Gremlin, and PostgreSQL APIs. |
| Deployment | L574-L599 | Deploying and migrating Cosmos DB (NoSQL, MongoDB, Cassandra, PostgreSQL, Table) using Bicep, ARM, Terraform, CI/CD, emulator, AKS, and handling upgrades, restores, and maintenance. |
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