AI-200: Developing AI Cloud Solutions on Microsoft Azure

Discover Azure Database for PostgreSQL, a managed, open-source object-relational database service, and learn to create resources, interact with it using Python, and perform vector search.

Learn how to configure PostgreSQL as a vector store with pgvector, store embeddings from the Text3 small model in Microsoft Foundry, and perform semantic searches on product data.

Explore Redis eviction policies under memory pressure, including expiration, and understand why in this setup there is no eviction due to the Redis search module.

Explore populating a Redis cache for AI cloud solution, decide what to store (strings, hashes, lists), apply expiry and eviction policies, and refresh stale data by deleting and recreating keys.

Explore how Azure Service Bus can publish messages to a topic and how Azure Event Grid emits events to system topics, enabling event-driven subscriptions via Azure Functions.

Demonstrate integrating Azure Service Bus with Azure Event Grid and Azure Functions, using the Event Grid trigger and event subscriptions to publish messages and trigger functions.

Publish an azure function in vs code using an event grid trigger to handle service bus events. Log cloud event details such as id, type, source, and time.

Learn how to consume service bus messages with Azure functions using the Service Bus client, environment variables, and requirements, and handle Event Grid notifications to process queue messages.

Create a custom topic in Azure Event Grid named AI inference events in East US, configure cloud event schema 1.0, and bind an Azure function to its event subscriptions.

Publish AI inference events to a custom topic with Event Grid, including type, subject, and data such as document id, model, and confidence, and trigger an Azure function.

Filter Azure event grid subscriptions by event type, subject, and advanced data properties to route AI inference events to the right handlers.

Explore Azure Key Vault for secrets, keys, and certificates. Learn about rotation and secure retrieval via apps or Azure functions, plus Azure App Configuration and monitoring.

Learn how Azure App Configuration uses labels for environment-specific values on the same key and how Key Vault references keep secrets securely.

Explore Azure Monitor, Log Analytics, and OpenTelemetry for monitoring Azure and on-premises workloads. Learn to collect metrics and logs in a Log Analytics workspace and query with KQL.

Deploy container images from Azure Container Registry to Azure Kubernetes using manifests for retrieval, inference, and gateway services; gateway uses port 80 and internal services use port 8000.

Learn how to implement open telemetry with Azure Application Insights to create traces and spans that correlate gateway, retrieval, and inference calls, enabling instrumentation and end-to-end telemetry.

Explore how the AZ-204 course structures itself around exam objectives, with sections on Azure compute solutions, virtual machines, and Azure web apps, and provide resources and practice questions.

Use Azure Cloud Shell, a browser-based authenticated terminal, to manage Azure resources with PowerShell or Azure CLI, upload files onto the session, and work with both tools without local installation.

Learn to use PowerShell with the Azure web app service to create a resource group, app service plan, and a web app, then configure the runtime to .NET 10.

Learn to create a deployment slot for an Azure web app with PowerShell, upgrade the app service plan from basic to standard, and verify the new staging slot.

Discover azure cli, a cross-platform command line tool for managing azure resources, including web apps, resource groups, and app service plans, often easier than PowerShell.

Learn how to containerize a dotnet web app by creating a Docker image with a Dockerfile in VS Code, then run a container on the Docker daemon.

Containerize a dotnet web app with a two-stage dockerfile, using the dotnet sdk to restore and publish, then run in an aspnet runtime image and expose port 8080.

Build a docker image from a docker file, tag it as version one, and run a container with port mapping to access the application on localhost 8080.

Deploy a two-container setup with a .NET web app connecting to a custom MySQL image. Launch the containers as an Azure container group on Azure container instance.

Deploy an Azure container group with multiple containers using a YAML file to run a web app and a MySQL database from the container registry.

Deploy a containerized console app on Azure Container Instance using a secure environment variable for the storage connection string to read blob data from an Azure Storage account.

Demonstrates deploying containers to Azure web apps by publishing a docker image, configuring Linux, East US, and a basic plan, and mapping port 8080 to the web app’s port 80.

Deploy an Azure container app environment to securely host multiple container apps, including a .NET web app and a MySQL container, with configurable environment variables, ingress, resources, and scaling.

Deploy a dotnet web app with azure container apps by creating an environment, selecting a v2 container image, configuring secrets, and enabling public ingress for port 80 to 8080.

Deploy the database container in Azure Container Apps, set a revision with a minimum of one replica, enable TCP ingress on port 3306, and run web and database containers together.

Learn to map your own domain names to Azure container apps, configure custom domains under networking, validate ownership by adding records, and attach the certificate.

Explore Azure Container Apps storage options, including ephemeral FML storage for container caches, replica-scoped storage for sharing files between containers in a replica, and Azure Files for permanent data.