Ensuring High Availability with Cloud-Managed Kubernetes

Modern cloud native applications offer multiple potential benefits, from improved scalability and stronger security to faster deployments and more efficient operations – and many other upsides.

Of course, none of those benefits matter if those applications aren’t available when needed. That’s why, among other reasons, we’re seeing increased interest in ensuring high availability (HA) in cloud native environments.

Such environments are typically distributed, both in terms of applications (think: containers and microservices) and their underlying infrastructure (think: multi-cloud and/or hybrid cloud). That’s part of the advantage, but it also stresses the need for redundancy and resiliency that eliminates single points of failure and helps keep applications always available and performant, even if a software component fails or a server instance goes down.

Kubernetes plays a significant role in high availability, especially in cloud-managed environments that can simplify operations and management. In this blog, we’ll explain the difference between cloud-managed Kubernetes and self-managed environments, as well as key strategies and practices for ensuring high availability with cloud-managed Kubernetes.

What is Cloud-Managed Kubernetes?

Kubernetes comes in a wide variety of “flavors” these days, from the raw open source project to commercial solutions built on top of open source code. While some organizations prefer to manage their own Kubernetes environments, others opt for managed Kubernetes service from one of the major cloud platforms. AWS, Google Cloud Platform and Microsoft Azure all offer managed Kubernetes services.

While self-managed Kubernetes deployments also offer significant HA capabilities, including two different topologies for creating highly available clusters, cloud-managed Kubernetes can simplify the initial deployment as well as ongoing operations, reducing the number of knobs and dials – features, configurations, and other settings – that need to be tuned and optimized over time. They also offer additional features already built-in that would have to be added and integrated manually in self-managed deployments.

This includes everything from cluster management to security to storage and more. It also includes high availability.

The Role of High Availability in Kubernetes

While HA principles and practices can apply to any system, they are especially relevant to Kubernetes and cloud native applications.

High availability in Kubernetes enables applications to remain accessible even when an underlying component such as a node – one of the worker machines that keeps containerized applications up and running – fails. In this example, the failed node is removed from the cluster and its work is essentially (and automatically) reassigned to other nodes to ensure continuous application availability.

HA in Kubernetes is fundamentally about removing any single point of failure – no one component of an application or its infrastructure should be able to take down the whole system.

HA is especially crucial to modern enterprise applications, both those relied on internally by employees and externally by customers. As those applications become more distributed, eliminating single points of failure and leveraging redundancy, automation, and other key concepts has become vital to productivity, revenue, customer experience and other metrics.

Key Strategies for Achieving High Availability

Let’s look at several key strategies for achieving high availability in modern cloud native applications.

1. Redundancy: Redundancy is a crucial concept for eliminating single points of failure. It means ensuring there’s a backup ready to automatically take the place of any component that might fail – such as the virtual or physical machine represented by the node in Kubernetes architecture.

In Kubernetes, this includes strategies such as running multiple master nodes in a cluster. This allows control plane resources such as the Kubernetes API and etcd to run on multiple nodes for redundancy if one instance should fail. Take special care to ensure that master nodes are on separate hypervisors and in different availability zones. This is because all master nodes fail if a zone fails or if the shared infrastructure crashes.

2. Disaster Recovery: Disaster recovery (DR) planning is another important facet of maintaining HA. A longtime pillar of business continuity strategies, DR encompasses various technologies and processes for keeping an organization operating normally (or as close to it as possible) when incidents occur. Those incidents could be anything from a network outage or any number of technical snafus to a major disaster such as a hurricane or fire.

Key pieces of a cloud-managed Kubernetes disaster recovery plan include automated backup and restore processes (that leverage Kubernetes persistent storage), automated failover, and multi-region or multi-zone deployments (that mitigate the impact of a datacenter going offline or a natural disaster in a specific region, for example.

3. Load Balancing: Load balancing is the third pillar of HA for cloud-managed Kubernetes environments. Load balancing ensures traffic is distributed evenly in a multi-cluster application environment so that no single machine gets overwhelmed and fails, further enhancing availability.

Cloud-managed Kubernetes environments typically offer robust load balancing capabilities to serve various requirements, including Layer 4 (L4) and Layer 7 (L7) load balancers.

L4 load balancing relies on IP addresses and port numbers to route traffic; L7 load balancing inspects application-layer data, such as HTTP headers and URLs to assign traffic.

Best Practices for Maintaining High Availability

Once HA is achieved with the above strategies, there are several best practices for maintaining it over time. These include:

• Continuous Monitoring and Alerting: Tools like Prometheus, Grafana, and other cloud native options give teams the ability to keep close tabs on their applications and environments and proactively address potential issues when they arrive.

• Consistent Updating and Patching: As with most other IT systems, regularly applying software updates and patches is crucial for fixing bugs, plugging security holes, and remedying other issues that could impact availability. This is yet another benefit of a managed Kubernetes environment, in that the vendor is usually responsible for ensuring timely updates and patches to the system.

• Automating Failover and Recovery: This is an ideal example of why Kubernetes is well-suited to HA strategies: automation is a cornerstone of both. There’s no such thing as a cloud native application where HA is achieved and maintained in an entirely manual fashion. Rather, Kubernetes automation is a great lever for relieving DevOps teams of the burden of putting out fires. If a pod (the smallest deployable unit in K8s architecture) fails, Kubernetes can spin another one up automatically to take its place, with no disruption to the application.

Cloud Provider-Specific HA Features

Again, AWS, GCP and Azure all offer managed Kubernetes solutions, each with built-in features for HA. Below, we’ll share examples from each:

AWS Elastic Kubernetes Service (EKS): multi-region and multi-availability zone deployments, auto-scaling, and built-in load balancers, plus services like RDS, CloudWatch, and Route 53.

Google Kubernetes Engine (GKE): regional clusters, auto-repair (essentially a health check-up for nodes in your cluster), and node auto-upgrades, plus services like Cloud Load Balancing, Cloud Operations, and Persistent Disks for HA.

Azure Kubernetes Service (AKS): availability zones, VM scale sets, and Azure Traffic Manager, plus services like Application Gateway, Monitor, and SQL Database for achieving HA.

Achieve High Availability

High availability is essential for many enterprise applications, especially those running in cloud environments or otherwise distributed across multiple environments. 

Cloud-managed Kubernetes makes achieving HA more approachable, with robust built-in features for must-haves like redundancy, disaster recovery, and load balancing, as well as the ability to maintain requirements around issues like data sovereignty and security.

Kubernetes is a great fit for HA strategies, but achieving HA won’t happen magically. 

Learn more about building a highly-available Kubernetes cluster with Rancher.

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