Azure Durable Functions: A Practical Guide

Explore serverless architecture and Azure's options, learn the core concepts of Azure Functions and why to extend them, and introduce durable functions, their workflows, and the four function types.

Understand the serverless model and how Azure Functions and Cosmos DB enable on-demand, scalable backends for apps, in contrast to traditional server-based architectures and provisioning.

Explore Azure's serverless landscape, from functions and durable functions to event-driven architectures, with pay-per-use scaling, container options, storage, monitoring, analytics, and API management.

Learn how Azure functions run code on demand without servers, driven by triggers such as http, timer, blob, and queue, with input and output bindings to connect to services.

durable functions extend Azure functions to build long running, stateful workflows in a serverless environment, manage storage and checkpoints, and provide centralized error handling through orchestrations.

Explore how durable functions enable complex stateful workflows in a serverless environment. Learn the five common patterns—function chaining, fan-out/fan-in, human interaction, monitor, and durable entities—with real-world use cases.

Discover the four durable function types—orchestrator, activity, entity, and durable client functions—and learn how they coordinate, store state, and trigger workflows in Azure durable functions.

Explore the serverless programming model and Azure serverless solutions, introduce durable functions as extensions that enable long running stateful workflows, and present the four function categories forming the durable foundation.

Explore environment options for developing and testing durable functions, set up a local Visual Studio Code environment, implement your first function, and learn how Azure APIs interact with your function and maintain state.

Explore development options for durable functions, extensions of Azure Functions, from the Azure portal to local testing with core tools, VS Code, and Python 3.9.

Install Azure functions core tools and Visual Studio Code, and add Azure Functions extension. Sign in to Azure and configure Python 3.6+ with Python extension to create your first durable function.

Set up Visual Studio Code with Azure extensions, build a Python durable function orchestrator plus durable client and activity functions, and configure storage and bindings for the function app.

Test durable functions locally by connecting a storage account, starting the orchestration via a http start function, and using postman to monitor status, instance id, and results from the orchestrator.

Explore how Azure durable functions use event sourcing to maintain durable, fault-tolerant state, storing orchestrator progress in the task hub history log and replaying events.

Develop a durable function locally with Visual Studio Code and the Azure Functions extension. Learn how the durable runtime uses event sourcing and the storage account to manage state.

Build on a local development setup and boilerplate code to implement Durable Functions, cover five workflows beginning with the function chaining workflow, and outline orchestration rules for the orchestrator function.

Learn how to implement function chaining with durable functions using an orchestrator to call multiple activity functions in a defined order, while the runtime manages intermediate state.

Demonstrate a real-world function chaining workflow with durable functions, where an orchestrator coordinates download, analysis, and storage across Azure Blob storage, Azure Cognitive Service API, and Cosmos DB.

Create a durable function app with an orchestrator and a durable client function in Python, test locally using an Azure storage account and Postman to manage orchestrator instances and status.

Download a random image from pixel dot photos, store it in an Azure blob storage container via a durable function activity, and return the image name to the orchestrator.

Orchestrate an image analysis workflow with Azure durable functions and cognitive service to identify objects in images using the computer vision API.

Store image analysis results in Cosmos DB via a durable function workflow, using images container and image_name partition key; upsert_item handles insert or update, tested end-to-end with Postman.

Learn how orchestrator functions must be deterministic, replaying from the start after waiting, with state stored in Azure storage and non-deterministic work moved to activity functions.

Explore a function chaining workflow in durable functions, where activity functions perform tests and pass results to next function, and observe orchestrator constraints and deterministic timer and date-time api.

Take an overview of fan-out/fan-in workflows in Azure Durable Functions, explain the problem it solves, and demonstrate a real-world use case building on the prior function chaining section.

Learn how durable functions use a fan-out/fan-in workflow to run activity functions in parallel, aggregate results, and expose ordered outputs via the orchestrator.

Implement a fan-out fan-in workflow with durable functions to parallel analyze a folder of cat images, filter out non-cat images, and aggregate results to separate images with and without cats.

Initialize a Python durable function app in Visual Studio Code, build an orchestrator and http client trigger, and an activity function to list images from the cat images container.

Implement a checked image activity and a fan-out, fan-in workflow in a durable function orchestrator to process images in parallel and identify cat objects with the computer vision API.

Create a durable activity function analyze result to filter results list and return image names where contains cat is false, enabling the orchestrator to produce result list of non-cat images.

Implement a fan-out fan-in workflow with durable functions to parallelize processing of images, filter anomalies in a large data set, and aggregate results via the orchestrator and activity functions.

Explore monitoring a workflow with Azure durable functions by passing input data to the orchestrator, using deterministic timer APIs, and managing a custom orchestrator status.

Explore how monitor workflow using durable functions enables dynamic polling intervals, avoids overlapping tasks, and simplifies error handling compared to timer-triggered functions.

Demonstrates a durable function monitor workflow that tracks a location's temperature against a threshold and sends an SMS alert via Twilio, using open weather APIs and a dynamic wait orchestrator.

Learn to build an Azure durable function app in VS Code with Python 3.9, creating a durable orchestrator and a post-only http starter that validates alert temperature and phone number.

Register an open weather API key and use the geocoding API to convert city names to latitude and longitude, then a durable function orchestrates weather data retrieval.

design a deterministic orchestrator using durable timers to monitor city temperature via an activity function, alerting when the threshold is reached and polling every ten minutes.

Build a durable function workflow with a get temp activity that calls the Open Weather API using lat lon and the API key, and monitor temperature against a threshold.

Explore setting custom orchestrator status with the query uri, use set custom status, convert utc timestamps to a human readable format, and test the orchestrator for exact next run times.

Durable functions' orchestrator uses a dynamic polling interval based on the difference between current temperature and the alert threshold, replacing fixed waits with adaptive intervals.

Learn to send alert messages with Twilio binding in an Azure durable functions orchestrator, using output bindings to integrate Twilio SMS and reduce boilerplate.

Implement monitoring workflow logic with durable functions to alert users when a city's temperature hits a threshold, customize dynamic polling and timer duration, and pass input data to the orchestrator.

Interact with the durable function orchestrator by sending events using the durable functions APIs, implement a real-world human interaction workflow, and trigger necessary actions.

Explore how an Azure durable functions orchestrator pauses for external events, handling human interactions like moderation and approvals with timeouts, escalation, and compensation logic.

Demonstrate a phone number verification workflow using Azure Durable Functions, with a client starter invoking an orchestrator that sends Twilio challenge and validates response via external event, canceling on timeout.

Create a durable function in Visual Studio Code, build an HTTP triggered client and orchestrator to validate a phone number using the phone numbers library, returning status and error handling.

Create a zen challenge activity function to generate a four-digit code and send it via Twilio SMS, wired through an output binding and an orchestrator in Azure Durable Functions.

Implement an orchestrator that waits for external events or a timer, verifying a challenge code sent by text, with status updates and cancellation logic.

Send external events to a durable function orchestrator via the rest api, using a post request to trigger a waiting event for an orchestrator instance and verify a phone number.

Implement a challenge-response workflow with an Azure durable function orchestrator that sends a code via Twilio to a phone number and verifies on user reply or timer expiry.

Explore durable entities and how they store state without a database. Define access patterns and implement a durable function to manage entities from an orchestrator and a durable client function.

Explore durable entities in Azure Durable Functions 2.0 and how entity functions manage state. Concurrency is automatic, with read, signal, and call access from orchestrator or durable client functions.

Learn to implement durable entities with an increment counter in a function app, exposing create, read, update, and delete operations across multiple entity instances via a durable client and orchestrator.

Create a durable function app in Visual Studio Code with Python 3.9, define increment counter entity, and manage its state with operations like edit, reset, and get using orchestration context.

Create a durable client to access an increment counter entity via http requests and signals, using the orchestration client to increment and read the entity state.

Access a durable entity from an orchestrator using a two way entity channel. Use an entity ID to increment the counter and verify the updated value.

Explore durable entities, a new durable function type for stateful, scalable, reliable, and event-driven serverless apps, implementing entity functions and accessing entity instances from durable client and orchestrator function.

Learn how to deploy and secure durable functions in production, explore deployment options for the function app, and test a course project on Azure while prioritizing secure function invocations.

Deploy a function app to Azure with Python 3.9 on Linux and a consumption plan, then deploy from Visual Studio Code and test the orchestrator and durable entity via Postman.

Secure http-triggered Azure durable functions with function or host keys, avoid anonymous access, and apply authorization levels. Use API management and Azure AD B2C for token-based access in serverless setup.

Explore Azure durable functions, a serverless, stateful extension that manages state and concurrency for long running workflows, featuring orchestrator, activity, entity, and durable client functions.

This final lecture highlights durable functions and how to implement common workflows using them, thanking learners for their time and inviting feedback.