The strong trend in application development involving microservice-based architectures make containers perfect for efficiently deploying software and operating at scale. containers can work on windows operating systems, Linux and Mac, on virtual machines or bare metal, in on-premise data centers and, obviously, in the public cloud. Microsoft is certainly a leading provider that enables enterprise-level container execution in the public cloud. This article provides an overview of the main solutions that can be adopted to run containers in a Microsoft Azure environment.
IaaS virtual machines in Azure environment can provide maximum flexibility to run Docker containers. Indeed, on Windows and Linux virtual machines it is possible to install the Docker runtime and thanks to the availability of different combinations of CPU and RAM you can have the necessary resources to run one or more containers. This approach is typically recommended in DevTest environments, as the cost of configuring and maintaining the virtual machine is not negligible.
Azure Container Instances (ACI)
Azure Container Instances (ACI) is the easiest and fastest way in Azure to run on-demand containers in a managed serverless environment. All this is made possible without having to activate specific virtual machines and the necessary maintenance is almost negligible. The solution Azure Container Instances is suitable in scenarios that require isolated containers, without the need to adopt a complex orchestration system. ACI is in fact able to provide only some basic scheduling features offered by the orchestration platforms and, although it does not cover the valuable services provided by such platforms, can be seen as a complementary solution.
Top-level resources in Azure Container Instances are the Container group, a collection of containers that are scheduled on the same host machine. Containers within a container group share the lifecycle, resources, the local network and storage volumes. Container group concept is similar to pod concept in Kubernetes environment.
The service Azure Container Instances involves costs that depend on the number of vCPUs and GBs of memory allocated per second. For more details on costs please visit the Microsoft official page.
Azure Web App for Containers
For web-based workloads, there is the ability to run containers from Azure App Service, the Azure web hosting platform, using the service Azure Web App for Containers, with the advantage of being able to exploit the distribution methodologies, scalability and monitors inherent in the solution.
Azure Batch and Containers
If workloads require you to scale with multiple job batches, you can put them in containers and manage scaling through Azure Batch. In this scenario, the combination of Azure Batch and containers turns out to be a winner. Azure Batch allows the execution and resizing of a large number of batch processing processes in Azure, while containers provide an easy way to perform Batch tasks, without having to manage the environment and its dependencies, required to run applications. In these scenarios, it is possible to envisage the adoption of low-priority VMs with Azure Batch to reduce costs.
The automation and management tasks of a large number of containers and the ways in which they interact with each other is known as orchestration. In case therefore there is a need to orchestrate more containers it is necessary to adopt more sophisticated solutions such as: Azure Kubernetes Service (AKS) or Azure Service Fabric.
Azure Kubernetes Service (AKS)
Azure Kubernetes Service (AKS) is the fully managed Azure service that allows the activation of a Kubernetes cluster.
Kubernetes, also known as “k8s”, provides automated orchestration of containers, improving its reliability and reducing the time and resources required in the DevOps field. Kubernetes tends to simplify deployments, allowing you to automatically perform implementations and rollbacks. Furthermore, it allows to improve the management of applications and to monitor the status of services to avoid errors in the implementation phase. Among the various functions there are services integrity checks, with the ability to restart containers that are not running or that are blocked, allowing to advertise to clients only the services that have started correctly. Kubernetes also allows you to automatically scale based on usage and exactly like containers, allows you to manage the cluster environment in a declarative way, allowing version-controlled and easily replicable configuration.
Azure Service Fabric
Another possibility to orchestrate containers is the adoption of the reliable and flexible platform Azure Service Fabric. This is Microsoft's container orchestrator that allows the deployment and management of microservices in highly intensive cluster environments with very fast deployment times. With this solution you have the opportunity, for the same application, to combine services residing in processes and services within containers. The unique and scalable architecture of Service Fabric allows you to perform data analysis almost in real time, computational calculations in memory, parallel transactions and event processing in applications. Service Fabric provides a sophisticated and lightweight runtime that supports stateless and stateful microservices. A key differentiator of Service Fabric is its robust support for creating stateful services, adopting built-in programming models of Service Fabric or stateful containerized services. For more information on the application scenarios that can take advantage of Service Fabric stateful services you can consult this document.
Azure Service Fabric can boast of hosting many Microsoft services, including Azure SQL Database, Azure Cosmos DB, Cortana, Microsoft Power BI, Microsoft Intune, Azure Event Hubs, Azure IoT Hub, Dynamics 365, Skype for Business, and many core Azure services.
Microsoft offers a range of options for running containers in its public cloud. The choice of the solution that best suits your needs among all those offered, despite requiring careful evaluation, allows to have a high flexibility. From the adoption of serverless approaches, the management of cluster environments for orchestration, up to the creation of your own infrastructure based on virtual machines, you can find the ideal solution to run containers in the Microsoft Azure environment.