Technology Writer and Startup Advisor
Kubernetes is a highly popular container orchestration platform. Multi cloud is a strategy that leverages cloud resources from multiple vendors. Multi cloud strategies have become popular because they help prevent vendor lock-in and enable you to leverage a wide variety of cloud resources. However, multi cloud ecosystems are notoriously difficult to configure and maintain.
This article explains how you can leverage Kubernetes to reduce multi cloud complexities and improve stability, scalability, and velocity.
Maintaining standardized application deployments becomes more challenging as your number of applications and the technologies they are based on increase. As environments, operating systems, and dependencies differ, management and operations require more effort and extensive documentation.
In the past, teams tried to get around these difficulties by creating isolated projects in the data center. Each project, including its configurations and requirements were managed independently. This required accurately predicting performance and the number of users before deployment and taking down applications to update operating systems or applications. There were many chances for error.
Kubernetes can provide an alternative to the old method, enabling teams to deploy applications independent of the environment in containers. This eliminates the need to create resource partitions and enables teams to operate infrastructure as a unified whole.
In particular, Kubernetes makes it easier to deploy a multi cloud strategy since it enables you to abstract away service differences. With Kubernetes deployments you can work from a consistent platform and optimize services and applications according to your business needs.
The Compelling Attributes of Multi Cloud Kubernetes
Multi cloud Kubernetes can provide multiple benefits beyond a single cloud deployment. Below are some of the most notable advantages.
In addition to the built-in scalability, fault tolerance, and auto-healing features of Kubernetes, multi cloud deployments can provide service redundancy. For example, you can mirror applications or split microservices across vendors. This reduces the risk of a vendor-related outage and enables you to create failovers.
Kubernetes supports fast development and deployments by enabling teams to flexibly test and rollout application versions. Since applications and services are packaged with dependencies included, you can easily roll out to any cloud services you may be using. Additionally, since applications are vendor agnostic, your team can utilize proprietary development services and still be able to deploy to other vendors.
Creating a multi cloud system eliminates vendor lock-in and enables you to compare service costs and possibly negotiate pricing freely. Additionally, containerization makes it significantly easier to migrate legacy migrations, reducing your migration time and enabling you to resume operations sooner, meaning less revenue loss.
Management of Kubernetes deployments is consistent and universal, enabling your teams to focus on one system instead of several. Additionally, with Kubernetes you can create single automation workflows that can modify multiple cloud resources. This reduces the amount of time that teams need to spend customizing configurations for vendor native technologies.
Multi cloud Kubernetes can provide significant benefits but it’s not simple to set up or manage and requires additional skills beyond standard deployments. If you’re considering a multi cloud deployment, you should carefully consider your cluster configurations, environmental parity, automation requirements, and security.
When deploying Kubernetes you need to decide on a cluster topology. For multi cloud deployments, and most production deployments, this means multiple nodes and possibly multiple clusters.
With multi cloud, you can run a single cluster with distributed worker nodes or create a cluster for each cloud or service. If you distribute nodes across clouds, you may have to perform additional configurations to customize your node communication and ensure that the correct ports are open.
One of the major benefits of Kubernetes is that it enables you to use declarative methods. This means you can easily standardize environments and deployments using automation from a centralized source of truth. This infrastructure as code system enables you to version control your configurations and push changes with minimal effort.
This standardization is more complex for multi cloud deployments where slight vendor differences can cause issues. Another issue is if the vendors you’re using offer cloud-specific containers. For multi cloud deployments it’s best to avoid these containers in favor of vendor agnostic options, although this may cause you to miss out on optimizations.
The ideal Kubernetes deployment is almost entirely automated with minimal manual work beyond initial configurations. With the right expertise you can manage multi cloud automation however, it’s often simpler to use third-party tools. These tools can help you adapt configurations and automation workflows to fit vendor specific requirements.
Security in distributed environments is always challenging but multi cloud environments add an extra layer of complexity. You need to be able to both visualize your deployment across systems and correlate data regardless of source.
This monitoring and correlation should be in real-time, and if possible, you should automatically respond to detected issues. One method that can help ensure this is implementing a service mesh, a layer over your deployment that facilitates communication and control.
In addition to the above considerations, you can implement several best practices to ensure a successful deployment. These include carefully selecting infrastructure resources, managing your Kubernetes versions, and using policies to standardize your deployment.
Leverage best-of-breed infrastructure
Multi cloud strategies enable you to select from a wide variety of services and capabilities, allowing you to make infrastructure closely to your needs. If services do not exactly match, you can always use an abstraction layer but this increases management complexity.
A better option is to select those services and resources that best offer native support for your applications. For example, in AWS you can use the native Kubernetes Container Network Interface (CNI) plugin rather than having to create an overlay network. Another advantage of this method is that it enables you to take advantage of other native services, like identity management or security groups.
Manage your Kubernetes version
When you deploy Kubernetes you can do so with a managed Kubernetes as a service (KaaS) or independently. As a managed service, the service vendor monitors and implements version updates and upgrades for you. This means less work on your end but also less control over compatibility. While some vendors enable you to defer upgrades, the option may come with reduced support.
Alternatively, if you self deploy it is up to you to ensure that your deployment is patched and upgraded as needed. This grants you greater flexibility but can also put you at risk if you get too far behind in terms of versioning. If you can not manage updates responsibly or in a timely manner, you should consider managed services.
Standardize your clusters with policies
When defining your clusters you should avoid any one-off definitions and focus on policies or templates which can be automated. These policies serve as tools for deployment as well as documentation and can be easily versioned. Additionally, policies enable you to create self-service workflows for developers and testers, eliminating the need to request environments from developers.
When defining your cluster policies, be sure to include the following components:
Traditional deployments involve creating isolated projects in data centers. Configuring and managing these projects is complex and time consuming, especially when trying to distribute across vendors. Kubernetes, on the other hand, offers a more efficient alternative that enables you to easily scale. You containerize the environment, and then make changes as needed.
Kubernetes comes with built-in fault tolerance and auto-healing, which provides the necessary stability for multi cloud operations. In addition, Kubernetes supports fast deployments and testing, consistent and universal management, and monitoring across multiple environments. However, to set up this kind of operation you need to know how to properly use Kubernetes, configure clusters and environments, and automate and secure the entire process.
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