The Azure Serverless Framework helps develop and deploy serverless applications via Azure Functions (serverless compute service that enables you to run code on-demand without having to provision an infrastructure).
Azure Serverless solutions are divided into the following platforms:
- Compute
- Workflows and integration
- DevOps and Developer tools
- AI and machine learning
- Database
- Storage
- Monitoring
- Analytics
Each of these has its own sub-categories. I will explain each one by one.
Compute
The following Azure Serverless features falls under the Compute platform:
- Serverless Kubernetes: Kubernetes enables you to build, deliver, and scale containerised (microservices packaged with their dependencies and configurations) applications faster.
- Serverless Functions: Azure Functions is an event-driven serverless compute platform that can solve complex orchestration problems.
- Serverless application environment: With the help of Azure App Service, you can build, deploy, and scale Web apps created with frameworks such as .NET, .NET Core, Node.js, Java, PHP, Ruby, and Python, in containers or on any operating system.
Workflows and Integration
The following Azure Serverless features fall under the Workflows and integration platform:
- Serverless workflow orchestration: Azure Logic Apps automates workflows without writing a single line of code.
- Serverless API management: With Azure API Management, you can create consistent API gateways for existing back-end services hosted anywhere and expose, publish, and manage microservices architectures such as APIs.
- Serverless messaging: Azure Event Grid is a single service for managing the routing of all events from any source to any destination. Azure Event Grid also supports events in the CloudEvents (open specification for describing event data) JSON schema natively.
DevOps and Developer Tools
Some tools include:
- CI/CD (continuous integration/continuous delivery) for serverless: DevOps can provide Cloud-hosted private git repos, continuous integration/continuous delivery (CI/CD), package management, trigger builds, and deploy to Kubernetes and Azure Functions.
- App development tools: Build, run, and debug serverless applications with Visual Studio, Visual Studio Code, SDKs, and CLIs.
AI and Machine Learning
Ready-to-use AI and machine learning algorithms include the following:
- Cognitive computing: Serverless apps can see, hear, speak, understand, and interpret your user needs through Azure Cognitive Services.
- Conversation bots: The Azure Bot Service enables you to build bots that interact naturally with your users through text/SMS, Skype, Microsoft Teams, Slack, Office 365, and Twitter.
- Machine learning models: Build, train, and deploy models on the Azure Machine Learning service.
Database
Azure Cosmos DB is a globally distributed, scalable, multi-model database service for creating database triggers and input-output bindings.
Storage
Azure Blob storage can be used as a massively scalable storage solution for unstructured data.
Monitoring
Azure Monitor is an extensible application performance management service that monitors your applications. It collects, analyses, and acts on telemetry from your Cloud and on-premises environments.
Analytics
Use Azure Stream Analytics to develop and run massively parallel real-time analytics on multiple streams of data (including IoT data).
Conclusion
Azure Serverless is becoming increasingly powerful. All the tools exist to manipulate data any way you like, and hopefully this article has helped you move in the right direction.
