What Is Redundancy? Best Practices and Considerations

When you hear the word “redundancy,” what’s the first thought that comes to mind? Maybe it’s someone losing their job. Maybe it’s someone saying the same thing over and over. But in the IT word, redundancy has more of a positive connotation.

Redundancy in the tech world means the ability to have more of a resource than is minimally required to perform a task. Without redundancy, IT teams would have a tough time safeguarding data, hardware, and networks against all kinds of trouble.

In the context of web hosting, redundancy is when you use multiple servers to keep your website online in case one of those servers breaks or needs maintenance.

In this guide, I’ll provide the lay of the land when it comes to the many types of redundancy, the benefits, the challenges, and everything in between.

Redundancy is your safety net, basically. It checks that all your data is correct and helps recover it quickly if something goes wrong. I’ll explain how it achieves that.

The Basics

In the IT world, the concept of redundancy refers to duplicating essential system components — whether hardware, virtual machines, or cloud-based resources — to ensure business continues uninterrupted even if one of the components fails. This can range from simple user-level measures to complex enterprise-wide solutions.

For example, copying the contents of your PC to an external drive is a form of redundancy. Big companies do it on a much bigger scale with extra computers that do the same thing as the main ones. They also have extra ways to connect to the internet through multiple routers or switches so if one connection fails, there’s another one ready to go.

By investing in redundant IT systems, businesses can significantly reduce the risk of a server or network going kaput (and any kind of operational disruptions, for that matter) caused by system failures. Think of redundancy as a top proactive measure that you hope you never need, but is good to have. As such, it’s a vital element of disaster recovery planning.

Redundancy vs. Backups

While the two are routinely lumped together, both serve distinct purposes and offer different solutions to operational challenges.

Redundancy is kinda like a backup, which is where people can get confused. The difference is that a backup is a recovery mechanism – it comes to the rescue after a problem emerges. Redundancy, on the other hand, stops problems from happening in the first place.

Redundancy improves operational efficiency and reduces service interruptions caused by failures. A backup has its uses, of course, as it prompts complete system restoration when things actually go wrong — unforeseen accidents, cyberattacks, hardware breakdowns, and the lot.

In other words, redundancy is a preventative action that complements backup solutions by making sure there is always a backup in the event of any error or malfunction in the system.

Now I will provide context for the different types of redundancy. To help keep things straight, I’ll group them into three categories:

Hardware Redundancy

When building redundancy into an IT project or strategy, hardware redundancy will be the most likely centerpiece of conversation as it’s the most common type.

Working parallel to the primary system, hardware redundancy involves deploying a duplicate device alongside the primary one. In case a critical malfunction, the backup activates while the primary unit undergoes repair.

Let’s say a server fails, and it’s impossible to access its data without a backup. With a redundant server continuously mirroring it, operations can continue as normal and you won’t even notice the difference while the main server is repaired.

This is where you’ll run into the term RAID — Redundant Array of Independent Disks. It’s a type of data storage technology that spreads and/or copies data across several drives to protect it from potential drive failure. There are multiple levels of RAID, each befitting specific needs in terms of performance, redundancy, and storage capacity

Standard RAID levels:

• RAID 0: Offers maximum performance by striping data (splitting it into multiple blocks) across multiple disks but provides no fault tolerance, making it unsuitable for critical data.

• RAID 1: Mirrors data across multiple disks, ensuring high data availability but sacrificing storage efficiency and write performance.

• RAID 5: Distributes data and parity information (method of encoding the data so it can be reconstructed) across all disks, providing a balance of performance and fault tolerance by allowing recovery from a single disk failure.

• RAID 6: Improves on RAID 5 by using dual parity information, enabling recovery from two simultaneous disk failures at the expense of reduced write performance.

• RAID 10: Combines mirroring (RAID 1) and striping (RAID 0), offering high performance and fault tolerance by protecting against disk failures within a mirrored set.

Perhaps the biggest advantage of RAID is that it protects data by distributing it across many disks. To keep your data safer, some RAID levels create redundant copies of it. For instance, RAID 1 mirrors data, while RAID 5 and RAID 6 employ parity calculations to reconstruct lost data in case of disk failure.

Beyond data protection, RAID can vastly improve performance. RAID 0 is the obvious example, as it distributes data evenly across disks, enabling faster read and write speeds. RAID 10 combines mirroring and striping for optimal performance and data redundancy.

While RAID cannot directly boost processor power, it significantly reduces the risk of data loss and downtime by providing fault tolerance and increased performance.

That’s why it’s commonly used in media storage and backup, as well as enterprise storage for critical business data.

Software Redundancy

Given the complexity of most software, you can reasonably assume it contains bugs or will manifest errors at some point. To stop that from ruining everything, software redundancy steps in.

Software redundancy addresses bugs or errors by either executing the same task using different (but very similar) software applications or versions of the same software.

Both approaches guarantee uninterrupted service by enabling a secondary application to swiftly take over if the primary software encounters an error. Of course, SaaS vendors that supply most of the tech stack also have their backups and redundancies.

In such a distributed system, load balancing plays a vital role. It watches how busy each server is, sends incoming traffic to the least-loaded one, and then repeats the process. This way, no single server gets overwhelmed, and the performance is consistent because any server becoming a bottleneck is immediately nipped in the bud.

Benefits of load balancing:

• Built-in redundancy: Protects your service from disruptions by steering traffic to operational servers, strengthening the system’s ability to withstand challenges.

• Uninterrupted service: Maintains continuous operations by rerouting traffic to available resources in case of server failures or maintenance.

• Enhanced system stability: Minimizes bottlenecks and maintains consistent performance through optimal resource allocation.

• Scalable system: When you evenly spread out the workload on servers, you can scale horizontally (add more servers to your hosting configuration) to meet higher demand without any drop in performance.

The distribution method is defined by a dynamic or static load balancing algorithm or type, which determines how requests are assigned to available servers.

Dynamic load balancing (algorithms include least connection, weighted least connection, and resource-based) adapts traffic distribution based on real-time server conditions. On the other hand, static load balancing (round robin, IP hash) distributes traffic evenly in a predetermined order or randomly, regardless of server status.

Data Redundancy

Data redundancy refers to the practice of storing identical data in numerous locations within a database or storage system. This practice sees to it that your data remains accessible because you’ll have alternative data sources in case of data loss or corruption. It’s applied to various data systems, including databases and file storage.

At the core of data redundancy is data replication, the very process of creating copies of data and storing them in different locations.

It aims to enhance data availability and consistency, particularly in large-scale systems where data loss and mismanagement can have severe consequences. This is about as good a guarantee of continued data access as you’ll get, even in the event of a server conking out.

Data replication techniques:

• Synchronous: Simultaneous copying of data to multiple servers, resulting in immediate data consistency across all locations.

• Asynchronous: Copies data to secondary servers in batches after it has been written to the primary server, allowing for potential data loss in case of a primary server failure before replication completion.

You’ll find data replication in all sorts of data management processes, particularly apps that require high availability (HA) and disaster recovery. This includes real-time analytics of sales data and financial transactions, data warehousing for reporting and auditing, and media streaming, to name a few.

Implementing some level of redundancy is a smart move. I can think of plenty of perks that come with it. Let’s go over some of the biggest benefits.

Improved Reliability

It’s an unfortunate reality that, for the majority of businesses, system reliability hinges on the provider’s fault tolerance and backups. I say “unfortunate” because these safeguards are not always dependable, even when vendors use top-tier robust cloud infrastructure.

Implementing redundancies improves a system’s ability to handle failures and threats, including cyberattacks and data breaches.

High availability minimizes downtime by swiftly transitioning to a backup system when the primary system malfunctions. That way, critical applications and services are always available, without any noticeable interruptions for end-users.

Continuity and Disaster Recovery

In mission-critical systems, where the cost of downtime is sky-high (to say the least), redundancy represents the foundation of both business continuity planning (BCP) and disaster recovery.

Business continuity planning is a comprehensive disaster recovery strategy designed to maintain and restore entire business operations during significant disruptions, such as hurricanes and fires.

Unlike disaster recovery plans that focus solely on restoring IT systems after a crisis, BCP encompasses broader strategies to ensure the continued functioning of the entire business.

I should note that redundancy is specifically designed to restore IT systems and data in the aftermath of a disaster. By having backups of essential systems and data, your business can quickly resume operations from a secondary site. No need to panic.

Scalability and Performance

Redundancy measures can also enhance scalability and bolster network and system performance by distributing workloads across multiple servers. This is particularly beneficial during periods of heightened demand and resource strain on IT infrastructure.

Multiple redundant components make it easier to expand your system as your user base grows.

By incorporating redundant servers and load balancers, you can distribute workload across several servers, amplifying system capacity and responsiveness.

The same principle applies to boosting performance. For instance, in distributed database environments with nodes spread across different locations, local access to replicated data accelerates query response times by cutting down on remote data retrieval. This reduction in latency enhances application performance, and it can boost user satisfaction as well.

While redundancy offers significant benefits, physical and operational complexities can sometimes impede its implementation.

Design Considerations

The math is fairly simple: redundancy requires careful design at both the hardware and application levels to sustain system operation for prolonged periods in challenging environments.

Here are key areas of focus:

• Risk assessment: You shouldn’t have a redundancy strategy for everything because that isn’t a sensible solution for a myriad of reasons. A thorough analysis is crucial to identify critical systems and potential points of failure that could compromise system integrity. Focus on elements that absolutely must be up and running at all times.

• Redundancy levels: The resulting risk assessment will determine the appropriate level of redundancy, along with cost considerations. Sadly, redundancy can be ridiculously expensive, especially for small businesses where money is tight. So, a dedicated redundant infrastructure may be best left aside for bigger fish. SaaS often presents a more advantageous option, where you can work with the vendor to make sure their SLA aligns with your specific requirements.

• Testing: There is no valid reason for you to ever get caught off guard if (and only if) you make a concentrated effort to implement regular testing and validation of redundancy configurations and failover procedures. Simulate failures, ensure data synchronization and consistency, and put the system through its paces every so often (experts say you should do it at least every 30 days). It’s also a good idea to establish automatic monitoring systems for backup software, hardware, and networks — better be safe than sorry!

Ideally, redundancy should be incorporated into the initial design phase, which emphasizes the need for proactive planning (as is usually the case in IT). Take time to understand all the options since that’s the only way you can end up with a cost-effective approach that doesn’t go way above or below what’s absolutely needed.

Redundancy in Different Systems

While the general principle is the same, redundant systems vary in speed and manner by which they jump into action. Some systems transition instantly upon failure, while others require a reboot period.

Network Infrastructure

Here, I will go over all the virtual and physical components that comprise a network. Key methods of redundant network infrastructure include:

• Redundant paths: It helps to visualize your network(s) as interconnected highways. In case one fails, traffic can be seamlessly rerouted through alternative paths, leading to minimal disruption. Thanks to multiple physical connections and load balancing, it’s possible to create alternative pathways for data transmission. These can be static by following predefined backup paths that are activated manually or automatically in case of a failure, or dynamic where network devices automatically detect failures and reroute traffic to available paths.

• Failover mechanisms: Failover is a backup operational mode that kicks in when something goes wrong. It automatically transfers operations to a backup system in the event of primary failure or planned shutdown. This feature is critical to keeping essential systems working without any interference. That said, there are three primary approaches to network hardware failover: cold standby, warm standby, and hot standby.

Cold standby requires someone to manually approve failover activation, while warm standby involves an automated failover process with a backup system running in the background and synchronizing data. Do note that some transactions might be lost during the transition, though the network typically recovers within a reboot time frame.

Finally, hot standby offers fully automated failover with synchronized primary and backup systems operating side by side. This setup requires complete data mirroring and client access to multiple servers.

Beyond the software and hardware level, don’t forget to take into account environmental factors. Power supply and all kinds of weather can pose significant risks to network uptime. That’s why redundant electrical sources like UPSs and backup generators, along with redundant cooling systems and environmental sensors, should be part of your implementation plans if you have the means.

Server Architecture

To establish an efficient redundant server architecture, you must first settle on appropriate tools and technologies. Proven options are:

Clustered servers

Clustered servers combine multiple servers to work as a single unit. For instance, several servers can be interconnected to operate as a solitary server, sharing a single IP address. Doing so can build up resilience and performance since each server is a node with its own resources. If one fails, the others can keep on truckin’ because the data is distributed.

You can build four types of server clusters:

• high availability
• load balancing
• high performance
• storage

In a redundancy context, the first two are of more interest as they prioritize reliability and scalability to handle varying workloads.

High availability clusters help prevent single points of failure through redundant hardware and software. You could say they are essential for load balancing, system backups, and failover, with multiple hosts ready to take over in case of a server shutdown.

Load-balancing clusters are server groups that distribute user requests across multiple active servers.

Separating functions and dividing workloads among servers makes the most out of available resources, which makes these clusters highly beneficial for better performance, redundancy, and optimized workload distribution.

Virtualization

Virtualization takes resource utilization and flexibility to a whole new level thanks to redundancy strategies specifically aimed at virtualized environments.

One of these is hypervisors with built-in HA capabilities. They can autonomously detect host failures and seamlessly migrate virtual machines to alternative hosts without service interruption.

Then, there is VM replication that duplicates and synchronizes virtual machines across multiple hosts. This is crucial for rapid service restoration as these “mirror” VMs continuously monitor primary server health, automatically assuming control if an issue emerges.

Such a setup eliminates the rebuilding of servers, OSs, and apps thanks to having exact replicas ready to go.

In conjunction, snapshot technology captures virtual machine states at specific points in time, which is rather useful for data recovery.

Despite budgetary and resource limitations that come with the territory in any deployment, server redundancy enables IT managers to address resilience and performance challenges.

However, for it to truly be effective, it will require threading a fine line between organizational priorities and available resources — which is a topic for another time, I’m afraid.

Implementing redundancy ain’t exactly a walk in the park, even if it seems like all you have to do is double critical systems and pieces of equipment. Here’s what could, perhaps, maybe, convince you not to pull the trigger on your decision.

Complexity and Management

This is somewhat of a “too many cooks” situation where configuring and managing redundant systems can be overwhelmingly convoluted due to the number of components involved. You have to keep a close eye to make sure everything is synchronized and functioning as intended.

That’s why risk assessment and planning are so important — not every form of redundancy will warrant the additional complexity, more so if time and specialized expertise are in short supply.

The good news is that you can automate enough background processes for them to not be a persistent headache. You can also streamline management with tools that provide a comprehensive overview of redundant configurations.

I’m not the one to leave you hanging, so give these a look:

• AppDynamics and New Relic for server and application monitoring
• Nagios and Zabbix for network monitoring
• Ansible and Puppet for automating infrastructure
• VMware vCenter and Hyper-V Manager for monitoring virtual environments

As for best practices for detecting failures, nothing beats routine checks of hardware, software, and network components. It’s also wise to establish benchmarks of normal performance to identify deviations and potential issues, as is to execute automated tests every so often to simulate failures and verify system behavior.

Cost Considerations

I’ve already touched upon the potential price tag of redundancy. Make no mistake — it’s worth every penny you drop into it, if only for the peace of mind you’ll get. Nonetheless, the situation can turn ugly fast if you go overboard.

For starters, you’ll have to pony up serious cash for additional hardware, software licenses, and potentially increased cloud service fees. Then, take into account ongoing expenses for system monitoring, management, and component replacement, as well as operational costs — especially possible increases as data will keep flowing in, rest assured.

At the end of the day, the smartest thing you can do is balance the cost of implementing redundancy with potential downtime costs.

It’s on you to figure out if initial and ongoing costs are worth the prevention of data loss, reduced downtime, and greater system reliability. For some, it may not justify the investment as potential downtime costs may not be that bad. After all, it’s redundant infrastructure — you don’t really need it in massive quantities.

Much like every tech segment, IT redundancy is in a state of constant flux, driven by the latest breakthroughs and changing business needs. Here are a few educated guesses on where things will stand a few years from now.

The unsung hero of IT, redundancy is undoubtedly paramount. Just think about all the downtime and money lost if your systems went down — what else works tirelessly to keep everything going through the motions with ease?

Yet, gaining C-suite approval can be challenging due to resource constraints. So, the name of the game is to maximize availability while minimizing complexity. In other words — you need to have a simple configuration that will make your job as stress-free as machinely possible.

In today’s climate, business continuity is imperative more than ever for success and survival — and redundancy is the insurance policy that pays off when you least expect it.