Industry use cases of Azure Kubernetes Service

What is Azure Kubernetes Service

Azure Kubernetes Service (AKS) offers serverless Kubernetes, an integrated continuous integration and continuous delivery (CI/CD) experience and enterprise-grade security and governance. Unite your development and operations teams on a single platform to rapidly build, deliver and scale applications with confidence.

Use Cases of Azure Kubernetes Services

Now, let us take a look at the different uses of Azure Kubernetes Service for improving this discussion further.

• AKS is ideal for easy migration of the existing application to containers and running them. The access control comes through integration with Azure Active Directory. You can also access SLA-backed Azure Services such as Azure Database using OSBA (Open Service Broker for Azure).
• AKS is also ideal for simplifying the deployment and management of applications based on microservices. The streamlined horizontal scaling, secret management, self-healing, and load balancing by AKS provide the necessary support.
• AKS is also a reliable instrument for bringing DevOps and Kubernetes together. AKS is ideal for secure DevOps implementation with Kubernetes and improves the speed and security of the development process. The development processes are secure with the use of CI/CD supported by dynamic policy controls.
• Constant monitoring can also help in accelerating the feedback loop. Azure pipelines can help in faster delivery alongside compliance with critical policies specified by Azure. Microsoft Azure also gives features for observing the build and release pipelines in real-time and features for easy application of compliance audit and reconfigurations.
• Azure Kubernetes Service is also applicable in many other use cases. One of them is the ease of scaling by using AKS and Azure Container Instances. Also, you can find the applications of AKS for on-demand IoT device deployment and management. AKS can provide scalable compute resources for IoT solutions according to demand. AKS could also find applications in use cases that involve machine learning model training. Flexible tools in AKS such as Kubeflow and TensorFlow help in simplifying the training of machine learning models.