The need to cater to a global audience has prevented most cloud-based applications from relying on a single cloud service provider. It has led to those applications shifting to multi-cloud architectures with two or more different cloud service providers. Common platforms like Kubernetes and containerized applications have made distributing applications across different service providers a relatively simple task. In this article, let’s see how to manage containerized applications in a Multi-Cloud environment.
Utilizing a Common Platform for Orchestration
Many cloud service providers have their own implementations to run containers, such as Amazon ECS, Google Container Engine, and Azure Container Service. These implementations are unique to each platform. Thus, users need to tailor their containerized applications to suit each service when utilizing these container services. However, it will not be a feasible option in a multi-cloud environment as it will introduce unnecessary complexity to the application.
This is where users turn to a common orchestration platform like Kubernetes, which is a standard service offering for most cloud service providers. It allows users to utilize the same orchestration platform across different cloud services. Moreover, they can use the same configurations across their clusters and ensure that the same container will work when deployed regardless of the underlying service provider. This interoperability and connectivity can be further improved using a service mesh like Istio to facilitate the networking layer.
Why use a Common Platform for Orchestration?
Using platform-agnostic tools like Kubernetes also simplifies the overall infrastructure management responsibilities, as users do not need to learn service-specific implementations. The users are only responsible for managing the provisioning of the cluster, as Kubernetes provides an encapsulated experience to manage the entire application with the cluster, including networking and storage. Infrastructure management responsibilities can be further reduced using a managed Kubernetes service. It also increases the resilience to hardware issues throughout the environment by using hardware from different providers. Thus, users can easily troubleshoot even errors like segmentation faults due to hardware incompatibility as containers can be shifted to an entirely new set of hardware on a different platform.
The next challenge is the management of clusters themselves. Multi-cluster management tools like Rancher, OpenShift, and Cloud Foundry can be good solutions if you are only dealing with Kubernetes. However, you will undoubtedly need to use multiple resource types with complex configurations when dealing with complicated multi-cloud environments. It will require more capabilities than what is available through standard Kubernetes cluster management tools. Google Anthos and Microsoft Azure Arch are two of the most promising solutions to meet these needs.
Google Anthos allows users to extend Google Kubernetes Engine to multi-cloud and hybrid environments. Its Config Management feature lets them sync configurations across clusters, implement policies, and provide binary authorization and hierarchy controllers to manage all the clusters through a single interface. Additionally, the Anthos service mesh provides a native solution to facilitate powerful networking and observability capabilities directly.
Meanwhile, Azure Arc provides similar capabilities to Google Anthos with Azure Lighthouse for RBAC management and Azure Policy to manage governance and compliance across the environment. However, Arc takes this approach a step further by allowing users to run other Azure services like Azure SQL and PostgreSQL Hypercale on other cloud environments. With EKS Anywhere, AWS also allows users to operate on-premise Kubernetes clusters while managing them through the Amazon EKS console.
Relying on multi-cluster management will be the only choice when dealing with a multi-cloud or hybrid environment. These tools can significantly reduce the management complexity while providing a standardized experience for managing clusters and resources across different cloud services.
There is a high chance of over provisioning or mismanaging resources when those resources are spread across multiple providers. It can lead to unnecessary cost increments and security concerns, as these mismanaged resources can be attack vectors. There are two principles for proper infrastructure management in a multi-cloud environment, as explained below.
Infrastructure Capacity Planning
Before provisioning the resources, users should identify the compute, network, and storage requirements of each cloud provider based on the current usage and the expected growth. It ensures that resources are provisioned according to the actual usage, not an arbitrary value, and reduces the operational expenditure. When the need arises, resources can be gradually scaled to meet the increased demands with minimal impact on overall costs.
There should be a way to monitor and keep track of all the resources provisioned across different cloud providers. The ideal way to achieve it is to use an Infrastructure as a Code tool to provision and manage resources. It allows users to keep track of all the resources and eliminates any config drift while ensuring consistent configuration over time. From a monitoring standpoint, users must constantly monitor resource utilization across cloud providers with an aggregative tool like ElasticSearch and scale resources as needed.
Proper monitoring and capability management allow users to easily optimize applications across multi-cloud environments without cost overruns.
Managing containerized applications in a multi-cloud environment boils down to using a common platform and properly managing resources and configurations across the cloud providers. The help of proper multi-cloud multi-cluster management tools for a common platform like Kubernetes combined with proper infrastructure management practices are the key to managing containerized applications across different cloud providers.