What Is High Availability?

High availability (HA) is the ability of an application or IT system to operate continuously at a high level, irrespective of the number of users. Organizations require critical systems to remain online at all times to avoid disruptions and ensure customer satisfaction. High availability ensures customers stay connected and data is not lost even during peak system workloads. Depending on the degree of high availability you want, you must take increasingly sophisticated measures throughout the application’s lifecycle.

Businesses must achieve high availability in their systems to avoid downtimes that could impact their company.

Reduced downtime

Periods when your company is inaccessible can lead to revenue loss, decreased customer satisfaction, and a damaged reputation. High availability systems minimize downtime so critical applications and services remain accessible online, even during hardware failures, software crashes, or other disruptions. This resilience helps businesses avoid costly interruptions and maintain compliance with regulatory requirements.

Improved customer experience

Users expect round-the-clock availability, especially for online services. HA systems help meet these expectations, even during peak periods or seasonal high demand. Organizations can ensure their IT systems are robust and handle continuous traffic to offer complete business continuity. Customers also quickly access expected services and are less likely to seek competition. You get higher customer satisfaction and loyalty.

Flexible scalability

High-availability architectures are scalable solutions that can automatically handle increasing workloads. Infrastructure adjusts automatically to provide greater capacity, allowing the system to adapt to growing demands without service degradation. HA systems also have the flexibility to allow technological updates and adjustments without significant downtime.

Competitive advantage

Reliability can be a key differentiator in markets where customers expect high performance and uptime. Organizations with high availability systems maintain a competitive edge by ensuring reliable service delivery. Continuous service availability can also attract new customers looking for dependable solutions.

A high-availability system has several features that allow it to offer continuous service.

Replication

Replication is the practice of duplicating data across different parts of a system. Highly available systems create copies that can quickly replace lost data if the primary system fails. Any changes in the primary system are automatically updated in the secondary system. Replication can be synchronous, where changes are mirrored instantly, or asynchronous, where changes are updated with a small delay. The second system is maintained so it has all the same up-to-date configurations and data as the primary system.

Redundancy

Redundancy in high-availability infrastructure is having several identical components in the system. In a disaster, these duplicate components take over, ensuring the system continues functioning. Every crucial component, such as storage systems, servers, and software components have duplicates. This level of redundancy protection ensures that the system has no single points of failure. Even if many components fail, replacements are present to take over.

Geographical distribution

Another feature of highly available systems is their use of geographical distribution to enhance their resilience. Distributing infrastructure across the globe ensures that natural disasters or unpredictable distributions won’t impact your system. If a natural disaster impacts one region, effective geographical distribution ensures you can switch to components in a different location and continue as usual.

Load balancing

Load balancing is a strategy that helps to optimize system performance, building more resilience to a failover system. A load balancer distributes traffic across all available servers and instances. It ensures traffic is fairly distributed between all available locations. The load balancer can also automatically detect server problems and redirect client traffic to available servers. You can use load balancing to run server maintenance or upgrades without application downtime.

Failover

Failover is an automatic process when one primary system fails, and a secondary system takes over. A failover process contains two main components. The first measures the current health of a system and all its components. The second triggers the system to change from the primary cluster to a backup component upon detecting any failure.

The failover is one of the most important components in high-availability infrastructure. It seamlessly triggers the changing of components without alerting users to the fact that a backend issue is occurring. This system minimizes downtime in high-availability infrastructure.

You typically show high availability as a percentage. A perfect system with 100% uptime would never fail. Of course, even the best systems in the world aren’t perfect, so many businesses use the concept of nines to track availability.

High availability metrics

A three-nines system represents an availability of 99.9%. In practical terms, a 99.9% availability means an annual downtime of about 8 hours. As we scale to a four-nines system (99.99%), the downtime per year falls to around 52 minutes. Then, as we scale to a five-nines system (99.999%), we reach downtimes of only around 5 minutes per year.

Incident repair metrics

Alongside the nines system, there are also essential metrics that relate to downtime and how quickly the service provider fixes IT incidents. For example,

• Mean time between failures (MTBF) takes a system’s total operational time and divide it by the number of failures experienced.

• Mean time to repair (MTTR) is the total time taken by engineers to diagnose, repair, test, and return a broken system to regular activity.

• Mean time to diagnose (MTTD) is the total time between a system failing and your team pinpointing what repair they need to do.

• Mean time to failure (MTTF) is the total time between the end of a repair and there being another failure.

• Recovery point objective (RPO) is the amount of time your business deems acceptable during an outage.

The nines system combined with repair metrics gives the complete overall measure of system availability.

High-availability infrastructure can use one of two main structures to provide redundancy and offer high uptime.

Active-active

Active-active high-availability clusters use many nodes that work together. When new requests arrive, multiple systems use load balancing to distribute traffic and optimize the system’s resources. This approach uses real-time data replication to ensure all nodes are up to date.

Whenever a cluster fails in the active-active system, the other active nodes can distribute their current workload to continue delivering functionality to the system. Engineers can then fix and return the faulty node online while the others continue working.

Active-active architecture is highly resilient and excels in resource usage optimization. This approach is scalable and useful for businesses that need to maintain consistency over long periods of time. However, the additional hardware and software requirements make this a more costly strategy.

Active-passive

The active-passive infrastructure uses two primary nodes. One node remains active and handles all incoming traffic. The other node remains passive but actively synchronizes data with the active node.

The two nodes maintain the same data stores using data replication. If the active node fails, the secondary node takes over and continues the system’s functioning. However, unlike in an active-active system, this takeover is not always instantaneous.

While active-passive nodes don’t provide the same level of redundancy, they are typically more cost-effective to run.

Achieving high availability relies on the fundamental strategies and infrastructure in these systems. Here are some best practices to enhance fault tolerance and provide business continuity.

Clusters

Use clusters of nodes, either in an active-active or active-passive system, to build more resilience into your systems. Deploying your system across several clusters reduces the chance of any one node becoming overloaded and failing.

High availability clusters help ensure your failover systems can instantly select a new node and reduce potential downtime.

Monitoring

Effective failover systems rely on widespread monitoring to check for performance issues and identify node failures. Continuously monitoring the operational workload you place on your systems is vital for business continuity.

Implement security policies

Another critical aspect of ensuring high availability is protecting your systems from cyberattacks and other potential disruptions caused by unauthorized access. Where possible, implement modern security architecture to defend your systems from known threats and data loss and improve their resilience.

High availability and disaster recovery are closely related but not the same.

Disaster recovery relates to the steps and actions you follow in response to large-scale outages or data loss events. A disaster recovery plan outlines your reaction to certain potential events, like a security incident, human error or a natural disaster shutting down your business systems.

In comparison, high availability aims to mitigate single points of failure in your systems to reduce the likelihood of downtime. It minimizes the potential for hardware and software issues to interrupt your system. It uses failover mechanisms, recency, and data replication to increase uptimes.

High-availability systems are not a part of disaster recovery. On the contrary, HA systems aim to prevent shut down due to IT incidents. Disaster recovery is about getting your systems back up and running if your existing HA systems fail, and all related steps you’ll take after shutdown occurs.

Amazon Web Services offers high-availability SQL and NoSQL databases.

For example, Amazon Relational Database Service (Amazon RDS) is a managed service that makes it easy to set up, operate, and scale a relational database in the cloud. It supports two easy-to-use options for ensuring high availability of your relational database.

• You can use Amazon RDS Multi-AZ deployments to create a primary DB instance and synchronously replicate the data to a standby instance in a different Availability Zone (AZ). In case of an infrastructure failure, Amazon RDS performs an automatic failover to the standby DB instance.

• You can choose to run one or more replicas in a cluster. If the primary instance in the DB cluster fails, RDS automatically promotes an existing replica to be the new primary instance and updates the server endpoint

Similarly, Amazon SimpleDB is a highly available NoSQL data store that offloads the work of database administration. Developers simply store and query data items via web services requests and Amazon SimpleDB does the rest. Businesses can also use Amazon DocumentDB Global Clusters to distribute critical workloads across the globe and improve the resilience of their database systems.

In fact, you can achieve high availability and read scaling with any database service on AWS. For example, build a high availability Microsoft SQL Server databases on Amazon EC2 by leveraging AWS infrastructure. You can also build custom high-availability systems on AWS using Amazon EC2 server nodes and assisting services.

Get started with high availability on AWS by signing up for an AWS account today.