Server Redundancy for Uninterrupted Business Operations

There is a difference between the concepts of server redundancy and the types of server redundancy. The core concepts of server redundancy are the different ways multiple servers can be used to ensure that critical applications and data are always available. These include:

Failover is the process of automatically redirecting traffic from a failed server to a healthy, redundant server. This ensures that if the primary server becomes unavailable, the backup server takes over without disruption to services. 

Businesses can implement failover at various levels, including hardware, software, and application layers.

Load balancing refers to the practice of distributing incoming network traffic or workloads across multiple servers or resources. It provides additional capacity during high-traffic periods, preventing performance degradation, maintaining optimal user experiences, and ensuring no single server is overwhelmed. 

The primary goals of load balancing are to optimize resource utilization, enhance system reliability, and ensure that no single server becomes overwhelmed with too much traffic or workload. The load balancer receives all incoming requests and then distributes them to the servers in the pool based on a set of algorithms. The most common load-balancing algorithms are:

• Round robin — With this algorithm, the server requests are distributed, meaning each server gets an equal number of requests.
• Weight-based — This algorithm distributes requests based on the weight of each server. A server with a higher weight will receive more requests than one with a lower weight.
• Fewest connections — This algorithm distributes requests to the server with the fewest connections. This helps to ensure that no server is overloaded.
• Health checks — Load balancers can also perform health checks on servers to ensure they are up and running. If a server is unhealthy, the load balancer will stop sending requests.

The optimal algorithm depends on the specific needs and configuration of your network. Your network may require algorithms to fit the following two needs:

• Network load balancing (NLB) — Incoming traffic is distributed across multiple servers, ensuring even distribution of workloads and preventing any single server from becoming overwhelmed.
• Application load balancing — Load balancers direct requests to specific servers based on factors like server health, capacity, and the type of request.

This proactive approach is critical to maintaining a robust, reliable, high-performing IT infrastructure.

Replication involves copying data from a primary server to one or more secondary servers. This can be synchronous (real time) or asynchronous (with a delay). There’s also semi-synchronous replication, which offers a middle ground between the two. 

Replication enhances data availability but can lead to data inconsistencies in asynchronous setups.

Mirroring involves maintaining an identical dataset in two or more locations. This is typically used with databases, where every transaction performed on the primary is replicated on the mirror. 

This ensures data consistency but requires high network bandwidth for real-time synchronization.

RTO is the targeted duration within which a system should be restored after a failure, while RPO is the maximum tolerable amount of data loss measured in time. 

These concepts help define how quickly the redundancy system needs to kick in and how much data loss is acceptable.

In an active-passive setup, one server (the active) handles the workload while another (the passive) remains on standby. If the active server fails, the passive one takes over. This method ensures seamless service continuity, even if the primary server fails.

Consider a business that runs a critical application that cannot afford downtime but doesn’t need to operate at full capacity all the time. An active-passive redundancy setup would be ideal here, as the standby server ensures continuity if the primary server fails.

Active-active redundancy involves multiple servers actively handling the workload simultaneously. If one server fails, the others continue, ensuring no service interruption.

This setup is beneficial for an eCommerce website experiencing high traffic volumes that must remain available 24/7. Multiple servers share the workload. If one server fails, others continue serving users without interruption.

N+1 redundancy is a general redundancy approach where N represents the number of components (like servers) needed for operation, while +1 is an additional backup. If any of the N components fail, the backup ensures continuity.

For instance, imagine a data center has 10 cooling units but only requires nine to maintain the right temperature. If one cooling unit fails, the backup unit can prevent overheating.

M+N server redundancy provides a higher level of availability than N+1 redundancy. In M+N redundancy, there are N additional servers beyond the minimum number needed to perform the required tasks. This means the system can still function even if M servers fail.

For example, if a website requires three servers to function, an N+1 redundancy scheme would require four servers. This is because one server would be the backup for the other three. However, an M+N redundancy scheme would require seven servers. Three servers would be the minimum number needed to function, and four additional servers would be available as backups.

M+N redundancy is a more expensive and complex solution than N+1 redundancy. However, it provides a higher level of availability and can be a good choice for mission-critical systems.

You can implement the above redundancy concepts by choosing from the following types of redundant servers that best suit your business needs and resources:

Standby servers are backup systems that take over when the primary server fails. Depending on how they’re set up, they can be classified as hot, cold, or warm.

• Hot standby server — This duplicate system runs parallel to the primary system. It can take over immediately in the event of a failure, ensuring no service disruption. However, maintaining a hot standby can be expensive due to the need for duplicate hardware and constant synchronization.
• Cold standby server — This backup system can be started if the primary fails. It might not have the most recent data and may take longer to get online, but it’s less expensive to maintain than a hot standby.
• Warm standby server — This is a middle-ground option between hot and cold. It’s usually up and running but not processing live data. It can take over faster than a cold standby but may still require manual steps.

In a cluster, multiple servers work together and are viewed as a single system. There are two different cluster configurations:

• Active-active clusters — All servers in the cluster run applications and share the workload. This increases performance and availability but requires complex synchronization to prevent data inconsistencies.
• Active-passive clusters —Only one server handles the workload while the others remain on standby. This provides high availability at a lower cost but does not increase performance.