Kubernetes is a powerful platform for deploying and managing containers at scale. But, like all complex systems, it is not without its potential points of failure.
To maintain high availability (HA) for your applications and services running in Kubernetes, you need to understand the different components that make up the system and how they can be configured for high availability.
What is High Availability (HA) in Kubernetes?
As explained by Kubernetes expert Lucas Käldström:
“High availability basically means the elimination of a single point of failure in the cluster.”
As you know, high availability is the property of a system or component that enables it to continue operating properly despite failures or unexpected conditions. This means being able to maintain your desired level of service even in the event of component failures or outages.
In the context of Kubernetes, high availability demands a set of configurations that attempt to maintain a minimum level of service so that even if a part of the cluster goes down, the application will still have service.
Why High Availability (HA) is Important For Your Business
There is a demand that systems be always operational, with no downtime. How many hours can your systems be offline before they impact your business? While downtime is impossible to rule out entirely, the IT team is responsible for minimizing the risk of it happening.
What Can Cause Downtime?
Cloud platforms sometimes fail. There are several things that can cause unplanned downtime in your applications, including:
- System failures (hardware, software, network)
- Natural disasters or unexpected events (floods, fires, power outages)
- Human error (accidental deletion of data, incorrect changes to configurations)
- Malicious attacks (hackers, ransomware)
Unplanned outages bring risks that can be mitigated by deploying a high availability solution. With high availability infrastructure, your company may continue functioning on a failover server while the problem is diagnosed and fixed. The most recent AWS cloud outages are an excellent illustration of this point.
In addition to unplanned outages, there are also a number of reasons why you might need to schedule a planned outage for your applications. For example:
- Updating software or hardware
- Migrating data to new storage infrastructure
- Performing system maintenance
- Conducting tests and evaluations
As your business grows, so does the importance of uptime, and, as a result, your maintenance windows start to shrink. With high availability in place, you can schedule maintenance windows without impacting your users or your business. This enables you to keep your applications up-to-date and running smoothly.
Determining High Availability Requirements
Before you can configure your Kubernetes cluster for high availability, you need to understand your company’s requirements. What services must be available at all times? What are the acceptable levels of downtime?
Once you have determined these requirements, you can design a HA solution that meets them. Configuring Kubernetes for high availability is not a simple task, and there are many factors to consider.
A high availability cluster architecture has four key components:
- Load balancing – To distribute client requests across cluster nodes, a highly available system must have a well-defined load balancing method that specifies the exact failover process in case of node failure.
- Data scalability – Another factor to consider is the scalability of databases or disk storage units. Using a centralized database and making it highly available with replication or partitioning are the two most popular choices for data scaling.
- Geographical diversity – It’s critical to your infrastructure clusters across geographic locations in today’s IT climate, especially with the availability of cloud technology. This ensures that the service or software is resistant to a disaster affecting one physical location since it can failover to a node in a different physical location.
- Backup and recovery – Highly available architectures are still vulnerable to system failures that might bring down the entire service. If and when this occurs, a backup and recovery plan must be in place so that the whole system can be restored within a set time limit (RTO).
Why is Kubernetes Good for High Availability?
Kubernetes is well-suited for high availability deployments, as it can be set up along with its supporting components so that there is no single point of failure.
Kubernetes enables you to schedule containers across multiple nodes and availability zones in the cloud, improving reliability. If one node or availability zone fails, the containers running on that node will automatically be scheduled on another node or availability zone in the cluster.
In addition, Kubernetes has a well-defined API for managing replication and provides a wealth of features to ensure the high availability of your services.
Kubernetes Lacks High Availability (HA) for Stateful Workloads
Kubernetes’ approach to HA usually entails spreading many replicas of an application across many cluster nodes, so when a single node or application instance fails, the impact is lessened.
Stateless applications or those that can live with the latency of shared storage are well suited to this strategy. In contrast, stateful apps frequently do not “sprawl” easily, if at all. As a result, these apps are not candidates for Kubernetes HA without special configuration.
How do you Design Stateful Kubernetes High Availability (HA) with Statehub?
There are a few different ways to design for stateful Kubernetes’ high availability. The first option is to use a storage solution that is designed for stateful applications, such as Statehub. This storage solution replicates your data across multiple nodes and clusters, so if one node or cluster fails, your data will still be available.
Statehub allows you to:
- Have multiple copies of your applications’ data, creating redundancy at any level
- Share and clone data between any Kubernetes clusters on the public cloud, no matter where they are
- Neutralizes data gravity by establishing a seamless app and data mobility, unconstrained by distance or cloud vendor