Develop AI cloud solutions on Azure (AI-200)

Onderwerpen

Module 1: Implement container application hosting on Azure

You will learn how to store and manage container images and how to host containerized workloads on Azure App Service.

Lessons

• Store and manage containers in Azure Container Registry
• Build and run images with Azure Container Registry Tasks
• Tag and version container images
• Deploy containers to Azure App Service

Module 2: Deploy and manage apps on Azure Container Apps

You will learn how to deploy, manage, and scale containerized applications across their lifecycle on Azure Container Apps.

Lessons

• Deploy containers to Azure Container Apps
• Configure runtime settings with environment variables and secrets
• Manage container images, revisions, and traffic
• Scale containers with HTTP rules and event-driven scaling (KEDA)

Module 3: Deploy and monitor applications on Azure Kubernetes Service

You will learn how to deploy applications to Azure Kubernetes Service (AKS), externalize configuration, and monitor and troubleshoot workloads.

Lessons

• Create Kubernetes deployment manifests and expose applications
• Deploy applications to Azure Kubernetes Service
• Configure applications with ConfigMaps, Secrets, and persistent storage
• Monitor and troubleshoot applications using logs and metrics

Module 4: Develop AI solutions with Azure Cosmos DB for NoSQL

You will learn how to connect to Azure Cosmos DB for NoSQL, query document data, store embeddings, and optimize query performance.

Lessons

• Build queries for Azure Cosmos DB for NoSQL
• Implement vector search with the VectorDistance function
• Combine vector search with metadata filters and hybrid search
• Optimize query performance, indexing, and consistency levels

Module 5: Develop AI solutions with Azure Database for PostgreSQL

You will learn how to build a data foundation in Azure Database for PostgreSQL and implement and optimize vector search with the pgvector extension.

Lessons

• Build and query with Azure Database for PostgreSQL
• Design schemas and integrate applications with secure authentication
• Implement vector search with the pgvector extension
• Optimize vector search performance, indexing, and connection pooling

Module 6: Enhance AI solutions with Azure Managed Redis

You will learn how to use Azure Managed Redis for caching, event messaging, and vector storage.

Lessons

• Implement data operations, caching, expiration, and invalidation
• Implement event messaging with pub/sub and Redis Streams
• Implement vector storage and similarity search

Module 7: Integrate backend services for AI solutions

You will learn how to build and integrate backend services using message-based and event-driven architectures and serverless compute.

Lessons

• Queue and process operations with Azure Service Bus
• Work with queues, topics, subscriptions, and dead-letter queues
• Develop event-driven workflows with Azure Event Grid
• Build serverless backends with Azure Functions

Module 8: Manage application secrets and configuration for AI solutions

You will learn how to secure the secrets and manage the application configuration.

Lessons

• Secure secrets by using Azure Key Vault, including rotation and retrieval
• Store and retrieve app configuration by using Azure App Configuration

Module 9: Observe and troubleshoot apps on Azure

You will learn how to monitor, trace, and troubleshoot your solutions on Azure.

Lessons

• Trace distributed systems by using OpenTelemetry SDKs
• Analyze logs and metrics by writing KQL queries
• Troubleshoot and diagnose application issues