Enhance AI solutions with Azure Managed Redis

  • Learning Path
  • 3 Modules

At a glance

Learn how to use Azure Managed Redis to enhance your AI solutions, including caching strategies, data operations, event messaging, and vector storage.

Prerequisites

  • Programming experience with languages such as Python, JavaScript, or C#.
  • Knowledge of caching concepts and data structures.
  • Familiarity with AI embeddings and vector similarity concepts.
  • Basic understanding of message queuing patterns and when to use them for decoupling services.
  • Access to Azure Managed Redis and related tools for hands-on practice.

Modules in this learning path

Implement data operations in Azure Managed Redis

Learn how to implement data operations in Azure Managed Redis. This module covers Azure Managed Redis features, client library best practices, and how to store and retrieve data efficiently.

Implement event messaging with Azure Managed Redis

Learn how to implement event messaging with Azure Managed Redis, including pub/sub for broadcasting notifications and Redis Streams for reliable async task processing. This module covers building real-time notification systems and coordinating multi-step processing pipelines.

Implement vector storage in Azure Managed Redis

Learn how to implement vector storage and similarity search in Azure Managed Redis. This module covers creating vector indexes, querying embeddings, choosing vector types and indexing strategies, and selecting optimal data structures for AI applications.

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