Microsoft ACA updates 2024 - Q2
Within this blog, I want to give an overview of all the feature in Q2 2024 that becomes available in General Availability, Technical Preview or End of Support by Microsoft. This information can be found at Microsoft Azure Updates.
Features that are now supported by Microsoft (GA):
- [General available] Azure Functions can now run on Azure Container Apps
You can now use Azure Functions on Azure Container Apps environment to deploy your multitype services to a cloud-native solution designed for centralized management and serverless scale. Azure Function’s host, runtime, extensions, and Azure Function apps can be developed and deployed as containers using familiar Functions tooling including Core Tools, AzCLI/Portal/code-to-cloud with GitHub actions and DevOps tasks into the Container Apps compute environment. This enables centralized networking, observability, and configuration boundaries for multitype application development when building microservices. Azure Functions on Azure Container Apps can be integrated with DAPR, scaled using KEDA and provisioned to a highly performant serverless plan. This allows you to maximize productivity with a serverless container service built for microservices, robust autoscaling, and fully managed infrastructure. Click here to learn more.
Features that are currently in Public Preview and not yet GA
- [Public Preview] Azure Container Apps available in Azure Government Cloud Virginia
Azure Container Apps, a managed serverless container service, is now available in Azure Government Cloud. Azure Container Apps offers an ideal platform for application developers who want to run apps and microservices in containers without managing infrastructure. Azure Container Apps is built on a foundation of powerful open-source technology including Kubernetes, KEDA, Dapr, and Envoy. To learn more, click getting started. - [Public Preview] Aspire dashboard support in Azure Container Apps
Azure Container Apps now supports .NET 8’s Aspire dashboard in public preview so you can access live data about your project and containers in the cloud to evaluate the performance of your applications and debug errors with comprehensive logs, metrics, traces, and more. Click here to learn more. - [Public Preview] Dynamic sessions in Azure Container Apps
Azure Container Apps now supports dynamic sessions in public preview. This fast, sandboxed, ephemeral compute is suitable for running untrusted code at scale in hostile multi-tenancy scenarios. Each session has full compute isolation using Hyper-V. Two modes are supported for dynamic sessions:- Code interpreter sessions: Dynamic sessions enables fast and simple access to sandboxed code interpreters for executing untrusted code. It allows you to run Python code and is preinstalled with many popular Python packages. More languages and runtimes are planned in the future. To build advanced AI agents or copilots, large language models (LLMs) are often paired with a code interpreter. A code interpreter enables an agent or copilot application to extend an LLM’s abilities to perform complex tasks such as solving mathematical and reasoning problems, analyzing data, and generating graphics and charts. Dynamic sessions’ code interpreter provides sandboxes to securely execute LLM-generated code in production. You can build your own copilots by adding code interpreter sessions to popular frameworks like LangChain, LlamaIndex, and Semantic Kernel in a just few lines of code.
- Custom container sessions: Dynamic sessions also lets you run your own custom container. You can use a custom container to create a code interpreter for your specific needs, such as preinstalling dependencies or supporting a different language. You can also build a custom container to run any application that requires secure sandboxed environments. Some example scenarios include: A web-based code editing sandbox, A SaaS application that can be extended by end users with custom code snippets and A hosted Jupyter Notebook service. Click here to learn more.
- Code interpreter sessions: Dynamic sessions enables fast and simple access to sandboxed code interpreters for executing untrusted code. It allows you to run Python code and is preinstalled with many popular Python packages. More languages and runtimes are planned in the future. To build advanced AI agents or copilots, large language models (LLMs) are often paired with a code interpreter. A code interpreter enables an agent or copilot application to extend an LLM’s abilities to perform complex tasks such as solving mathematical and reasoning problems, analyzing data, and generating graphics and charts. Dynamic sessions’ code interpreter provides sandboxes to securely execute LLM-generated code in production. You can build your own copilots by adding code interpreter sessions to popular frameworks like LangChain, LlamaIndex, and Semantic Kernel in a just few lines of code.
- [Public Preview] Set Java log levels in Azure Container Apps
You can now set Java application log levels in Azure Container Apps without redeploying or restarting your apps. This feature, now available in public preview, allows you to dynamically adjust the verbosity of your logs and troubleshoot issues more easily. Click here to learn more. - [Public Preview] Monitor apps with Java metrics in Azure Container Apps
You can now monitor the performance and health of your apps with Java metrics such as garbage collection and memory usage. These metrics are automatically collected and reported to Azure Monitor, where you can see them in an integrated dashboard. You can also set alerts and troubleshoot issues based on these metrics. Click here to learn more. - [Public Preview] NFS Azure Files volume mount support in Azure Container Apps
Azure Container Apps now supports mounting Network File System (NFS) Azure Files volumes to your containerized applications. This feature is in public preview. NFS Azure Files volumes provide a scalable and high-performance file system for your apps and jobs. You can use NFS Azure Files volumes to share data between multiple containers in your application, or to persist data across container restarts. Click here to learn more. - [Public Preview] Extensibility model in Azure Deployment Environments
Azure Deployment Environments is adding a new extensibility model, now available in public preview, that empowers customers to customize their deployment workflows using Bicep, Terraform, Pulumi, or any other infrastructure-as-code (IaC) framework of their choice. The model further streamlines app infrastructure provisioning and gives platform engineers the flexibility to meet the unique needs of their organization:- Extensibility model: Harness any preferred IaC framework of choice and customize deployment workflows to meet specific needs.
- Terraform support: Directly use Terraform templates in Azure Deployment Environments by configuring a container image.
- Bicep support: Directly use Bicep templates in Deployment Environments with a sample Bicep container image or by building a container image for Bicep deployments.
Click here to learn more.
- Extensibility model: Harness any preferred IaC framework of choice and customize deployment workflows to meet specific needs.
Features that are retired
- [Retired] - None
For more information about the features that are coming out, please refer to the public roadmap of Microsoft ACA team.