Uptime and availability are two essential metrics that determine the profitability of an online business. In the context of a business such as a SaaS or eCommerce store, user expectations of availability are very high.
In other words, downtime directly translates to the loss of revenue and reputation. That’s why businesses with online components place particular emphasis on minimizing downtime.
This article will explore highly available architecture, a great way of ensuring uptime. We’ll discuss essential technical details, how to measure infrastructure availability, and how RedSwitches helps you build and maintain highly available architecture that adds value to your business operations.
Let’s start with the basic definitions.
Table Of Contents
- How to Measure High- Availability
- The Benefits of Highly Available Architecture
- Best Practices for Maintaining High Availability Infrastructure
- How RedSwitches Helps You Set Up High Availability Architecture
- Conclusion
- FAQ’s – Highly Available Architecture
What Is Highly Available Architecture?
High Availability (HA) architecture is an approach to designing computer systems and networks to ensure maximum uptime and minimal downtime. HA architecture aims to provide continuous access to mission-critical applications and data, even in the face of hardware or software failures or other unexpected events.
This is achieved through redundancy and fault-tolerance mechanisms that eliminate single points of failure and provide failover capabilities. High availability architecture is essential for mission-critical applications, such as financial transaction systems, healthcare applications, and eCommerce websites, that require a very high level of reliability and availability.
HA architecture typically includes redundant components and failover mechanisms to achieve high availability. The list of these redundant components includes multiple servers, storage devices, network switches, power supplies, and other hardware so that if a component starts to fail, another seamlessly takes over. Failover mechanisms may include software-based clustering or load balancing, which automatically redirects traffic to available resources in the event of a failure.
By leveraging technologies such as load balancing, clustering, replication, and automated failover, high availability architecture can ensure that systems remain highly available and responsive to users, even in the face of hardware or software failures, network outages, or other disruptions.
Popular High-Availability Clusters Configuration
Now that you have a theoretical understanding of highly available architecture, it’s time to look into the practical implementation of the idea.
Active-active and active-passive are the most frequently deployed high availability (HA) clustering setups. While both ensure minimum downtime, there are significant differences in how they achieve the objective.
Active-Active Clusters
A typical active-active cluster consists of at least two nodes that are concurrently running the same collection of services. The most common reason behind implementing an active-active cluster is balancing the load on the application. The idea is to distribute the workload among all nodes to avoid any single node becoming overburdened. As more and more nodes are added to the cluster, you’ll see a noticeable improvement in throughput and response times.
Active-Passive Clusters
An active-passive cluster has at least two nodes, just like the Active-Active cluster architecture. However, as the term “active-passive” suggests, not all nodes are active at a time. When there are two nodes, the second node is passive or in standby mode. If the active node goes down, the standby node becomes active.
Shared-Nothing Clusters
Shared-nothing clusters are a type of clustering architecture where each node in the cluster has its own local storage. In addition, a node generally does not share any storage with other nodes.
In a shared-nothing cluster, each node operates independently, processing requests and managing its own data without coordinating or communicating with other nodes. This approach can be very efficient because it avoids the need for nodes to communicate and synchronize with each other, which can create overhead and reduce performance.
However, managing data consistency across multiple nodes can also be challenging, particularly if data needs to be shared between them. Therefore another option for looking at highly available architecture is Shared- Disk clusters.
Shared-Disk Clusters
Shared-disk clusters are a type of clustering architecture where each node in the cluster shares access to the same storage devices, typically through a shared storage area network (SAN) or network-attached storage (NAS). In a shared-disk cluster, nodes can access and modify the same data, simplifying data management and improving consistency.
However, shared-disk clusters can be more complex to configure and manage than shared-nothing clusters, particularly if there are conflicts between nodes accessing shared resources. Additionally, shared-disk clusters can be less scalable than shared-nothing clusters, as the shared storage can become a bottleneck if too many nodes try to access it simultaneously.
How To Measure High-Availability
High-availability is such a central concept that there are multiple ways of measuring it. The following are the metrics you should use to understand the availability of the cluster.
Percentage Uptime
This is the most common way to measure HA and refers to the percentage of time that a system is operational and accessible. For example, a system with 99.99% uptime would be down for less than an hour a year.
Mean Time Between Failures (MTBF)
This metric measures the average time between system failures. A higher MTBF generally indicates a more reliable system.
Mean Time to Repair (MTTR)
This metric measures the average time it takes to repair a system after a failure. A lower MTTR generally indicates a more resilient and recoverable system.
Recovery Time Objective (RTO)
This metric calculates how long it takes to get a system back up and running after a failure. A system with a lower RTO is typically more agile with significantly lower downtime.
Recovery Point Objective (RPO)
This metric measures the maximum amount of data loss acceptable in the event of a failure. A lower RPO generally indicates a more highly available system.
To accurately measure HA, it is essential to define specific metrics and targets that align with the needs and requirements of the system and its users. It is also important to regularly monitor and test the system to ensure it meets its HA goals and identify areas for improvement. This is one of the key benefit of highly available architecture.
The Benefits Of Highly Available Architecture
High Availability (HA) Architecture is designed to provide continuous operation and minimize downtime, ensuring that critical systems and services remain available and accessible.
Let’s look at these benefits in detail.
Load Balancing
Load balancing is one of the key benefits of Highly Available (HA) architecture. The idea of load balancing refers to the distribution of workload across multiple nodes to optimize resource utilization. The expected outcome is a quantifiable improvement in the overall system performance. In an HA infrastructure, load balancing divides incoming traffic among several nodes. This protects all nodes from overload so that no node becomes a single point of failure for the entire system.
Data Scalability
In Highly Available (HA) architecture, data scalability refers to the ability of a system to handle increasing volumes of data without sacrificing performance or availability. Most HA architecture systems achieve this by distributing data across multiple nodes or storage devices. This allows the system to scale and handle increasing data volumes without breaking down.
Geographical Diversity
For enterprises and MNCs, geographical diversity is a significant benefit of Highly Available (HA) architecture. Geographical diversity refers to the ability of a system to maintain a high availability and data accessibility across multiple geographic locations or regions. This is achieved by replicating data and services across multiple data centers or locations.
Best Practices For Maintaining High Availability Infrastructure
Now that you know the options for implementing highly available architecture, it’s important to understand the benefits of HA clusters. Here’re a few:
Leverage Geographic Redundancy
Geo-redundancy is a vital line of defense against natural disasters that can result in service disruptions. The process entails setting up lots of servers in several places to disperse the risk. The load balancers and cluster management components should be robust enough to minimize the impact of geographically dispersed infrastructure.
Use Failover Solutions
A failover solution is the cluster component that actually routes incoming traffic and requests to the next available node. As such, the success of an HA cluster is directly tied to the prompt reaction of the failover component.
Implement Load Balancers
A load balancer disperses incoming traffic among the active nodes to decrease the likelihood of outages. The best practice here is to configure the load balancer to handle distribution and routing that’s tailored to your operational requirements.
Minimize Network Latency
To reduce network latency in highly available systems, consider setting up a dedicated network, implementing load balancing, optimizing network configuration, and distributing data caching and processing.
Avoid Single Points of Failure
Implementing redundancy, a distributed architecture, regular maintenance, failover mechanisms, and a disaster recovery plan are critical ways of avoiding single points of failure in a highly available system.
How RedSwitches Helps You Set Up High Availability Architecture
Load Balancing
Unlike any cloud hosting provider, RedSwitches can set up load balancers that distribute incoming traffic across multiple servers.
Master-Master MySQL Replication
RedSwitches can set up database bidirectional replication, which is a type of MySQL database replication in which two or more MySQL servers act as both master and slave to each other. This means that each server can accept updates from the other server, allowing for bidirectional data flow.
Master-Slave MySQL Replication
RedSwitches may set up MySQL database replication of the Master-Slave kind, in which one server serves as the master and one or more additional servers serve as slaves. The master server receives updates and changes to the database and then replicates those changes to the slave servers.
Clustering
RedSwitches can set up server clustering, which involves grouping multiple servers together to act as a single system. This ensures that if one server fails, the other servers in the cluster can take over, preventing downtime.
Monitoring
RedSwitches can set up monitoring systems that track the performance and health of your servers, databases, and applications. This allows you to detect issues before they cause downtime and take action to prevent them.
Conclusion
Highly available architecture is essential for designing computer systems and networks that require maximum uptime and minimal downtime. High availability architecture can guarantee continuous and uninterrupted service delivery even in the face of hardware or software failures, network outages, or other disturbances thanks to redundancy and failover features, including load balancing, clustering, replication, and automated failover.
There are different highly available architecture clustering setups, such as active-active and active-passive, as well as shared-nothing and shared-disk clusters, each with its own advantages and disadvantages. Measuring highly available architecture requires specific metrics and targets such as percentage of uptime, MTBF, MTTR, RTO, and RPO, which align with the system’s needs and requirements and its users.
The benefits of highly available architecture include load balancing, data scalability, improved performance, and reduced downtime. As technology advances and more organizations rely on mission-critical systems and services, high-availability architecture will become increasingly important in ensuring continuous and reliable service delivery.
FAQ’s – Highly Available Architecture
Q-1) What is the difference between failover and high availability?
High availability (HA) refers to a system’s ability to remain operational and provide services despite hardware, software, or network failures. On the other hand, Failover is the process of automatically or manually switching over to a redundant or backup system in the event of a failure.
Q-2) Which are the three characteristics of a highly available system?
Here are three characteristics of a highly available system:
Redundancy:
A highly available system typically includes redundant components, such as servers, storage devices, and network connections, to ensure that there is no single point of failure. If one component fails, another takes over seamlessly to ensure that the system remains operational.
Automated failover:
A highly available system should be able to recognize and react to faults automatically.
Scalability:
A highly available system should be designed to handle increasing workloads as demand grows.
Q-3) What is 99.99% availability?
99.99% availability, also known as “four nines” availability, refers to a measure of how much time a system is expected to be operational over a given period. Specifically, it means that the system is designed to be available 99.99% of the time, which translates to an expected downtime of approximately 52.56 minutes per year (365 days * 24 hours * 60 minutes * 0.0001).
Q-4) What is an active-active cluster?
A typical active-active cluster consists of at least two nodes that are concurrently running the same type of service on each of them. Load balancing is the main goal of an active-active cluster.
Q-5) What is an active-passive cluster?
An active-passive cluster has at least two nodes, just like the active-active cluster architecture. However, as the term “active-passive” suggests, not all nodes will be active. When there are two nodes, the second node must be passive or in standby mode, for instance, if the first node is currently operational.
