What is Kubernetes High Availability?

Picture this: you’re scrolling through Reddit and suddenly everything goes grey. You check your internet- it still works. Other websites- still operational. You come to the conclusion that Reddit is down and go about your day.

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While this outage is a minor inconvenience for you, app and service outages can be the nail in the coffin for some organizations. The truth of the matter is that service outages can drive an organization to financial ruin; Forbes estimates that the average cost of downtime can be as high at $9,000 per minute (depending on industry and organization size).

Many companies are prioritizing the creation of highly available HA systems, or systems that are operational 100% (or close to 100%) of the time, meet user expectations, and don’t require constant intervention. And when things like healthcare systems, military control systems, and industrial systems require 24/7 uptime, it’s no wonder why organizations are bolstering their systems in hordes. 

As with all HA systems, Kubernetes high availability refers to minimizing downtime within Kubernetes, specifically through improving Kubernetes-specific components like worker nodes, containers, and networking. And like all HA systems, HA Kubernetes is achievable taking actions like:

• Scaling your servers
• Backing up your systems
• Replicating your apps and systems to introduce redundancy

With important Kubernetes components like APIs, controller manager, and other control plane components being replicated into each cluster, HA Kubernetes is a process built on redundancy.

With high availability becoming a standard among solutions, achieving it within your Kubernetes deployment is extremely important. But how does Kubernetes even fail in the first place?

Kubernetes HA Benefits

The industry standard for highly available systems is typically 99.9 to 100%; error isn’t tolerated within highly available systems, with much of the work involved in achieving it paying off tenfold. Having continuous uptime offers benefits such as:

Increased Reliability and Scalability

Perhaps the biggest draw to achieving HA with Kubernetes is to improve the reliability of your system. Whether this is by removing a single point of failure or increasing the capacity of data storage, reliability within any system is a must, especially for systems that are critical to the wellbeing of users. Reliable systems don’t just have positive implications towards app and service operations, but even towards companies and users. Providing a reliable service creates trust between users and companies, improves user experience, and makes marketing and sales efforts easier.

One of the major factors in increasing reliability is creating a system that’s highly scalable. Unexpected traffic spikes often crash apps that aren’t well equipped to handle crowds; a tenant within HA systems is building scalable parts to address this. With built-in autoscalers and load balancers, HA Kubernetes systems are able to scale according to real-time demand, and without developer intervention. Whether your networks become crowded or your app itself becomes subject to traffic spikes, HA systems ensure that solutions are operational even during the worst weather.

Seamless Error Solving

Having a highly available Kubernetes cluster doesn’t mean that your systems are completely protected from errors, but it does refer to your system’s ability to solve these problems intuitively. A key aspect of HA systems is preparing for the worst, whether your data becomes corrupted or your application experiences an outage, an HA system will have a seamless solution for that.

Two of the biggest components of HA systems are service backups and app and service redundancy through duplication. Rather than requiring developer intervention, these characteristics are on standby, constantly updating to reflect your current system and data loadout. If any components within your current system fail, that system is isolated and repaired while a duplicate system is deployed without requiring downtime. In addition, any data from your current system is backed up, preventing data loss. HA Kubernetes systems provide another layer of error solving, with Kubernetes clusters having auto-healing capabilities similar to HA redundant systems being baked in. 

By introducing high availability in Kubernetes, your systems will become leagues more fault tolerant.

Maintaining Business Continuity 

Downtime is costly, this isn’t new information. But service downtime creates a ripple effect that affects all facets of your business. Reduced/halted service performance, revenue loss, decreased user satisfaction, and increased competition usage are some of the biggest branches of service downtime. And when it comes to Kubernetes, having this service down can result in organization-wide consequences.

All mission-critical systems should be built with HA components in order to preserve business continuity without intervention and performance delays.

High Availability Kubernetes Components

Before diving into what makes up a highly available Kubernetes system, it’s important to understand what factors can cause a normal Kubernetes system to break.

Despite its fancy name, Kubernetes is like any system at the end of the day. Bugs and faulty code have the ability to crash entire applications for a moment. Forgetting to limit resource consumption can severely slow down your machines. Malware and hackers can cause immense damage. However, Kubernetes specific components like clusters, nodes, and pods can also fall victim to failure- the Reddit outage in the introduction wasn’t just made up! Because of this, it's important to bolster the strength of Kubernetes components AND the system that it’s built on, not just one or the other.

When it comes to building highly available Kubernetes components, organizations follow the core principle of HA systems: building redundancy across applications, hardware, and data. That being said, here are some of the components that can help you achieve high availability Kubernetes:

Replication Controllers / ReplicaSet

One of the most important requirements of HA systems is the ability to replicate your apps and systems, thus introducing redundancy. In Kubernetes, the Replication Controllers and ReplicaSet tools are responsible for this important step.

With the only difference between the tools being that ReplicaSet is a replacement for Replication Controller, both tools are essentially responsible for replicating pods based on a specified number. Both tools run these pods in tandem with the main pods and are deployed once pods fail or are deleted.

Replication Controllers and ReplicaSets are integral to HA Kubernetes systems, offering not only the means of replicating pods, but also management, specific pod selectors for specific nodes, and maintaining pod templates. 

Pods

On the topic of pods, pods are the smallest unit within a Kubernetes system. Pods are a group of containers with shared storage and resources, as well as instructions for running and maintaining containers. Pods are much like white blood cells, designed for a specific function and working with regards to a grand scheme rather than an individual process.

All Kubernetes systems need pods, regardless of high availability or not. What makes pods especially important in HA functions is that they are replicated on a consistent basis, ensuring that redundancy is maintained and that there isn’t a single point of failure within your system. Much like the replication tools creating pods, the Kubernetes control plane is responsible for scheduling and running multiple pods across different nodes in your cluster, ensuring that your system operations are seamless regardless of pod and node failure. 

Load Balancing and Service Discovery

Black Friday and Cyber Monday are some of the biggest shopping days of the year, with companies preparing year round just to optimize their website and maximize sales. The case for many companies, however, is that online traffic is much higher than anticipated. This year, U.S. ecommerce sales increased by 14.6%, with some organizations struggling to keep their service afloat. To combat outages due to traffic spikes, many HA Kubernetes systems rely on their load balancing and service discovery capabilities.

Load balancer and service discovery capabilities are absolutely critical in any Kubernetes deployment. To ensure uptime in times of traffic stress, Kubernetes load balancers will distribute traffic amongst backup servers and different pods, improving overall cluster performance as a result. This not only aids in resource allocation and optimization, but also security measures by isolating traffic to a certain degree.

In order to improve the efforts of Kubernetes LoadBalancers, Kubernetes ran on a microservices infrastructure can engage in service discovery, in which services connect to other services through a shared network. Through communication, services are able to locate other components within a Kubernetes system, allocating traffic to replicas to increase uptime if needed.

ETCD

The one tool to rule over service discovery and distributing systems is ETCD, an open-source key-value store that stores highly available clusters states and data. With stored information ranging from current HA cluster state and desired cluster state, to desired resource configuration, ETCD plays an important role in facilitating node, pod, and cluster replication. Though its uses aren’t just limited there.

ETCD is integral in monitoring all things nodes, from resource allocation to health, including implementing tools that ensure resources are properly allocated. In addition, ETCD helps facilitate communication between services in Kubernetes, allowing better overall synchronization and system fluidity.

Highly Available Kubernetes with Lyrid

Having a system that can weather anything is the goal for many organizations, especially in busier times of the year. Not only are highly available systems the standard, but they also help prevent painful consequences. From lost revenue, damaged customer reputation, service disruption, and more, not having a highly available system is extremely damaging, especially if your system is reliant on Kubernetes.

Having a highly available Kubernetes system is the dream for many, but implementing and maintaining even a simple Kubernetes system is a pain for most. From configuration and operation, to maintenance and troubleshooting, Kubernetes is a beast that many people don’t dare tackle. In order to combat this, we host a Managed Kubernetes service that offers the benefits of Kubernetes and removes the headaches involved.

Lyrid Managed Kubernetes offers all the features of a highly available Kubernetes system, such as:

• Automated resource distribution
• Automated cluster scaling
• Simple cluster provisioning
• Single pane of glass cluster visibility
• Enhanced security measures such as RBAC and IP address-based access

And more

Our Kubernetes service has been proven to reduce application downtime as well- Wolio’s migration to our service resulted in a 90% decrease in application downtime! With a team of professional engineers waiting to aid in migration and configuration, Lyrid Managed Kubernetes is the perfect service for anyone looking for a highly available solution, but don’t have the time or resources to implement their own.

Interested in learning more and changing the way you manage Kubernetes? Book a meeting with one of our product specialists!