What is high availability? A tutorial

We’ve all been there: trying to access a website or an app, only to be hit with that dreaded “service unavailable” message. It’s frustrating, right? Whether you’re trying to shop online, check your bank balance, or simply stream your favorite show, downtime can be more than just a hassle – it can hurt your business, your reputation, and your bottom line.

But what if there were a way to ensure that your customers or users could always access your site, no matter what? Enter high availability – an absolutely necessary strategy that keeps your services up and running, even when something goes wrong.

Here, we’ll break down what high availability really means, why it matters, and how you can make it a part of your infrastructure!

Importance of high availability

Think about it: when your services are up and running without interruption, you’re providing your users with a smooth experience:

• For eCommerce sites, this means customers can browse, shop, and checkout without frustration.
• For SaaS companies, it means users can access their data and tools without losing valuable time. 
• For any business, it translates into higher user satisfaction and a boost in brand credibility.

On the flip side, downtime can be costly. In fact, the average cost of downtime for businesses can range from $300,000 to $1 million per hour, depending on the industry. Beyond the financial impact, there’s the long-term damage to your reputation. Customers expect reliability, and if your service goes down frequently, they might just take their business elsewhere.

And here’s something people don’t always associate with high availability: security. But the two go hand-in-hand. Systems designed for high availability often include redundancies, monitoring, and failover mechanisms that make it harder for attacks or failures to bring everything down. That kind of resilience is also a huge plus when it comes to regulatory compliance – especially in industries like healthcare, finance, and government.

High availability clustering

When it comes to achieving high availability, one of the most powerful tools at your disposal is clustering. In simple terms, a cluster is a group of interconnected servers (called nodes) that work together as a single system. If one node fails, another one picks up the slack – ideally so fast your users don’t even notice.

These clusters can range from simple setups with just a couple of servers to complex configurations involving multiple data centers. Regardless of size, the goal is the same: to provide continuous, uninterrupted service to users.

Clusters are designed to provide both redundancy and load sharing. Each system in the cluster is aware of the others, so if one node goes offline due to a hardware failure, software bug, or maintenance window, the rest of the cluster keeps things running. This is known as failover (and it’s automatic). The system detects the problem, reroutes traffic or workloads, and keeps the service available without manual intervention.

Also, a cluster can automatically balance the load between servers, which helps improve overall system performance, prevents overload on any single server, and ensures that no single point of failure can disrupt the entire operation.

There are different types of high availability clusters depending on your needs. For example:

• Active-passive clusters have one or more standby nodes ready to take over when the active one fails.
• Active-active clusters have all nodes actively handling traffic or workloads, which also helps with performance and load balancing.

How high availability works

High availability is built on a series of solid principles and components that work together to ensure your services stay online and reliable – let’s break it down.

Principles of high availability

These are the non-negotiable rules that guide the design and operation of any high-availability system:

• No Single Points of Failure (SPOF): This is rule #1. If one component breaks, it shouldn’t bring the whole system down. Whether it’s a server, network switch, or database, everything needs a backup or a fail-safe in place.
• Reliable failover: When something does go wrong (because it will), the system should automatically reroute traffic or switch to a standby component quickly and without human intervention. This is where clustering, load balancers, and replication come into play.
• Automatic failure detection: Systems need to constantly monitor themselves and each other. This is often done with “heartbeat” signals – frequent check-ins between components. If one stops responding, the system knows something’s wrong and kicks the failover process into gear.
• No data loss: In high availability setups, data is usually replicated across multiple nodes or locations so that no matter where a failure happens, your data isn’t gone with it.

Components of high availability

Now that we understand the principles, let’s look at the key components that make high-availability systems work:

• Redundant servers (multiple nodes): The brains of the operation. Each server in the cluster plays a role in hosting the application, service, or data. They can either be physically located in the same data center or distributed across multiple locations for added resilience.
• Shared or replicated storage: This ensures that all nodes have access to the same data, keeping things consistent.
• Scalability: You want to stay online while growing – that means you should be able to add new nodes, handle traffic spikes, and increase storage without sacrificing stability.
• Fault tolerance: This is the ability of a system to keep operating even when something breaks. It’s what makes high availability possible in the first place. Fault-tolerant systems anticipate failure and are ready to handle it gracefully.
• Load balancing: Load balancers distribute incoming traffic across multiple servers, keeping things running smoothly and helping prevent overload. They also play a role in failover, rerouting traffic when one node goes offline.

Measuring high availability

If you’re going to invest in high availability, you need a way to measure whether your setup is actually, well… highly available. And while 100 percent uptime sounds nice, reality is a little more nuanced. Let’s get into it.

Availability percentages and “the nines”

You’ve probably heard phrases like “five nines availability” tossed around. This refers to the percentage of time a system is expected to be operational over a given period (usually a year). The more “nines” you have, the less downtime your system is likely to experience.

For example:

Even with the best infrastructure, 100 percent uptime is rarely possible – power outages, hardware failures, software bugs, and even maintenance windows make it nearly impossible. That’s why most providers aim for that sweet spot of four to five nines, which keeps downtime minimal while still being technically feasible.

Industry standards, benchmarks, and Service Level Agreements (SLAs)

There are no hard-and-fast rules when it comes to what level of availability is acceptable, as the needs vary from industry to industry. However, certain benchmarks help provide a guideline for setting expectations:

• Banking and financial services often require extremely high availability (99.999 percent or higher) due to the critical nature of their services. Even minor downtime can lead to significant financial loss or legal ramifications.
• For healthcare providers, availability levels of 99.99 percent are typically expected, given that downtime could impact patient care, safety, and privacy.
• For e-commerce platforms or Software-as-a-Service providers, availability of 99.9 percent or higher is generally acceptable. However, even a few hours of downtime could translate into lost revenue or a loss of customer trust.

It’s important to understand these industry benchmarks so you can set realistic availability goals that align with your business needs.

As for SLAs, they are formal contracts that define the level of service you can expect — often in terms of uptime guarantees. For example, if your provider offers “99.99 percent uptime,” your SLA may entitle you to service credits if they don’t meet that.

Key metrics: MTBF, MDT, RTO, RPO

Here are some of the key metrics for measuring high availability:

• MTBF (Mean Time Between Failures): This is the average time between failures in a system. A higher MTBF indicates that your system is more reliable, and failures are less frequent. It’s a great way to assess how robust your infrastructure is over time.
• MDT (Mean Downtime): MDT measures the average amount of time your system is down after a failure. A lower MDT means that when failure does occur, your system can recover quickly and continue operating.
• RTO (Recovery Time Objective): RTO refers to the amount of time it takes to restore services after a failure. A shorter RTO means your team can bring the system back online quickly, reducing the impact on users.
• RPO (Recovery Point Objective): RPO measures how much data loss is acceptable in the event of a failure. If your RPO is set to zero, this means you need real-time replication of data, so no data is lost if a system crashes.

High availability vs disaster recovery

While high availability and disaster recovery may seem similar, they serve distinct purposes in the realm of business continuity. Both are designed to mitigate risk and minimize downtime, but they approach the problem in different ways:

Having both strategies in place ensures that you’re covered for any type of failure – whether it’s a minor glitch that high availability can handle or a catastrophic event that requires a full recovery effort.

Best practices to achieve high availability

Design for redundancy

The first rule of high availability is redundancy. Redundancy means having backup systems in place so that if one component fails, another can take over without causing disruption. This applies not only to servers but also to critical components like power supplies, networks, and storage.

When designing your infrastructure, aim to eliminate single points of failure. For example:

• Use multiple servers in a load-balanced configuration to distribute traffic.
• Implement multi-region or multi-cloud strategies so that if one data center fails, another can pick up the slack.
• Redundant power supplies and network connections ensure that your systems stay online, even if a failure occurs at the hardware or network level.

Regularly test your failover system

Failover is at the core of high availability, but it’s not enough to simply set it up and assume it will work when needed. To ensure that your failover system will function properly in a real emergency, regularly test your failover processes.

Create disaster recovery drills where you simulate failures and verify that your systems can automatically failover to backup servers without issue. Regular testing helps identify weak spots in your failover system and ensures you can resolve issues before they affect your users.

Monitor and automate for proactive issue detection

Use real-time monitoring tools to keep an eye on the health of your infrastructure, including CPU performance, memory usage, network status, and application uptime. The more granular your monitoring, the sooner you’ll detect issues before they become critical.

Automation tools can also play a major role in high availability by allowing for quick, automatic responses to system anomalies. For example, if a server becomes unresponsive, automation can trigger failover processes, restart services, or send alerts to system administrators.

Keep your data safe with replication

In any high-availability setup, data protection is paramount. Replicating your data ensures that in the event of a failure, no information is lost. Set up real-time database replication to ensure that all your data is mirrored across multiple servers or data centers.

This practice ensures that if one server or data center goes down, the backup data is instantly available from another location. It’s essential for protecting both transactional data and system configurations that are critical for service continuity.

Keep your systems updated

To ensure high availability, your systems must be running the latest versions of software, patches, and security updates. Outdated software can introduce vulnerabilities, slow down performance, and even increase the risk of failure. Make it a habit to regularly update your operating systems, applications, and any third-party services or tools that you rely on.

Plan for scalability

High availability goes hand-in-hand with scalability. As your traffic or service demands increase, your systems should be able to scale smoothly without causing downtime. This requires planning for horizontal scaling, where you add more servers or instances to handle the increased load.

Whether you’re scaling up during peak traffic periods or preparing for future growth, having a scalable infrastructure will ensure that your high-availability systems can grow with you without sacrificing performance or reliability.

Use cloud or hybrid infrastructure for flexibility

For many businesses, cloud-based infrastructure offers an excellent way to implement high availability. Cloud providers like AWS, Google Cloud, and Azure offer built-in high availability features such as multi-region failover, auto-scaling, and load balancing.

For even greater flexibility and resilience, consider using a hybrid cloud model, where some of your services are run in the cloud, while others remain on-premises or in private data centers. A hybrid setup gives you the ability to choose the most reliable, cost-effective infrastructure for each part of your operation.

Have a clear recovery plan

Despite best efforts, downtime can still occur. That’s why having a disaster recovery plan in place is just as critical as your high-availability setup. Your disaster recovery plan should include detailed procedures for restoring services in the event of a system failure, including:

• Data restoration procedures from backups.
• Step-by-step instructions for failover and failback processes.
• Contact lists for your IT team and other stakeholders who need to be involved in recovery efforts.

Continuously improve your high availability strategy

High availability isn’t a one-time project – it’s an ongoing process of monitoring, improving, and adapting your systems to meet new challenges. Regularly review your high availability infrastructure to identify areas for improvement. Be proactive about adapting to changes in traffic, technology, and potential failure scenarios.

As your business grows and evolves, so should your high availability strategy. Investing in continual improvement ensures that your systems remain resilient and reliable in the face of new challenges.

Document everything

Seriously. If something goes wrong, having clear, up-to-date documentation can save you hours (or days). Document your architecture, failover processes, escalation paths, and recovery procedures – and make sure your team knows where to find them.

Wrapping up

As you move forward, consider how you can implement these practices into your own business operations. The earlier you start, the more resilient your infrastructure will become, and the more confident you’ll be in your ability to handle any unexpected disruptions.

And if you need help with setting up or optimizing your high-availability systems, Liquid Web specializes in building and managing high-availability solutions tailored to your needs. From high availability clusters and load-balanced environments to fully managed private clouds, redundant storage, and real-time monitoring, we design solutions that are built to stay up – and scale as you grow. You’ll get access to world-class infrastructure, custom architecture, and our 24/7/365 Always-On support from real humans who know your setup inside and out.

Ready to make high availability your new standard? Talk to Liquid Web’s team today to get an infrastructure that’s built to endure and help you thrive!