Disaster Planning Essentials: High Availability & Fault Tolerance

With advancements in cloud technology, it’s easier than ever to build scalable and reliable infrastructure. But no matter how sturdy our systems seem, they’re still vulnerable to the unexpected. Whether it’s a natural disaster, a cyberattack, or a hardware failure, unexpected events can impact services, affect revenue, and make customers lose trust. That’s where disaster recovery comes in. 

Why disaster recovery matters

The goal is simple: keep things running, avoid losing data, and get back on track as quickly as possible when things go wrong. It’s all about building an infrastructure that can handle disruptions and bounce back. Two key pieces to making this happen are high availability and fault tolerance. Together, they ensure our systems are ready to handle whatever gets thrown their way and recover smoothly from setbacks.

What is disaster recovery?

Disaster recovery means having a plan ready to bring your systems back online after something goes wrong. Whether it’s a data breach, a hardware failure, or a natural disaster, disaster recovery is the set of strategies that ensure data, applications, and infrastructure can be restored to keep things running smoothly and minimize disruption.

One of the challenges with disaster recovery is figuring out who’s responsible. With so many teams involved—like QA, site reliability engineers, and cloud engineers—it can be easy for disaster recovery planning to fall through the cracks if there’s no clear ownership. That’s why it’s so important to have a unified approach where responsibilities are clearly defined. This ensures that disaster recovery stays a priority and everyone knows their role in making it happen.

The role of RPO and RTO in disaster recovery

When it comes to disaster recovery, two numbers really set the tone for everything else: the Recovery Point Objective (RPO) and the Recovery Time Objective (RTO). These metrics define what’s acceptable in terms of data loss and downtime, making sure the recovery plan actually fits your business needs.

Recovery Point Objective

RPO is all about data loss. It’s the answer to the question, “How much data can we afford to lose?” If your RPO is one hour, then you’re committing to backing up data at least every hour, so you’re never more than an hour behind if things go south. In short, the closer you want RPO to be to zero, the more frequently you’ll need to back up. 

“The idea here is to restore to a point in time where business disruption is minimized.” (Chris Faraglia, Webinar: Planning for Failure: Are You Ready for Disaster?).

Recovery Time Objective

RTO defines how quickly you need to get back online after an incident. If your RTO is two hours, your recovery plan needs to have systems back up within that time frame. Essentially, it’s the maximum amount of time your systems can be down before it starts hurting the business. Lower RTOs require more robust and efficient recovery processes to ensure you can meet that target when needed. Lower RTOs mean you’ll need faster failover systems and a solid recovery process in place to meet that target.

“Understanding how long you can afford to be offline is critical. It shapes everything about your recovery process.” (John Hayes, Webinar: Planning for Failure: Are You Ready for Disaster?).

By setting clear RPO and RTO targets, you create a foundation that guides all your decisions on backup frequency, failover processes, and recovery timelines. 

The essentials of disaster recovery

High availability (HA)

High availability is all about keeping systems up and running as much as possible by minimizing single points of failure. Think of it like having a backup generator ready to kick in if the power goes out. By building in redundancy and using failover mechanisms, high availability ensures that services keep going, even when parts of the system run into issues.

Real-world scenario: Consider using load balancers and multi-zone deployments. For example, if one server goes down, load balancers can automatically redirect traffic to other servers in different zones, maintaining service availability. In cloud platforms like AWS, tools like Elastic Load Balancing and multiple availability zone architecture help distribute traffic and prevent any single server from getting overwhelmed.

Fault tolerance (FT)

Fault tolerance takes it a step further by allowing systems to keep working even if certain components fail. Imagine you’re driving and one of your tires goes flat. With fault tolerance, it’s like having a spare tire to keep going until you can safely get to a repair shop. The system reroutes tasks to backup components, so operations continue without a hitch until the problem is fixed.

Example: A multi-region cluster setup with Kubernetes can help with fault tolerance by distributing workloads across various regions. If one region has an outage, the others can step in to keep everything running without missing a beat.

Disaster recovery (DR)

While high availability and fault tolerance are proactive, disaster recovery is more reactive. It’s what you do to bring systems back after an incident. Disaster recovery involves things like restoring data from backups or rolling back to previous versions. It’s all about getting everything back to normal, which makes tools like data backups and point-in-time recovery essential parts of a good disaster recovery plan.

Practical Tip: For example, point-in-time recovery options, such as those available with cloud storage solutions, allow you to roll back to a previous version of your data if something goes wrong. This can be crucial after a data corruption or a security breach, helping restore data to a known, secure state.

Disaster recovery: High availability and fault tolerance

A resilient disaster recovery plan relies on high availability and fault tolerance. These strategies help you keep services running and minimize downtime, even when issues arise. Here are key techniques you can use to make your systems more resilient, along with steps to help you put them into practice:

Techniques for high availability

Multi-zone deployments

Multi-zone deployments involve distributing applications across multiple availability zones (AZs) within a region (or multiple regions) so that if one zone goes offline, others keep the system running. This setup is especially effective in cloud environments, where data centers are located in different geographic areas.

• How to implement: Start by mapping out critical services that require high availability, then identify cloud providers with multi-zone support. For example, AWS offers regions with multiple AZs, allowing you to split workloads.
• Getting started: Use automated deployment tools to replicate your applications across these zones. This way, you can easily scale and ensure consistency.
• Test failovers: Regularly simulate zone outages to confirm that services automatically switch over without manual intervention. Create playbooks for handling these events and ensure teams are trained on the procedures.

Load balancing

Load balancing is the process of distributing incoming traffic across multiple servers to ensure no single server is overwhelmed. This setup improves performance, enhances reliability, and minimizes downtime if a server fails. Load balancers are especially useful for managing spikes in traffic, which can otherwise slow down or crash servers.

• How to implement: Start by choosing a load balancing solution that matches your needs. For example, AWS Elastic Load Balancing offers Application, Network, and Gateway Load Balancers. You can also explore NGINX for a more hands-on approach, which is ideal for on-premises setups or hybrid cloud environments.
• Setup tips: Configure health checks for each server to make sure only healthy servers receive traffic. With this setup, load balancers can automatically reroute traffic if a server goes down.
• Optimize for traffic patterns: Review your traffic logs to understand peak usage times and adjust your load balancer settings accordingly. Set up alerts for unusual traffic spikes so you’re prepared to scale resources as needed.

Auto-scaling

Auto-scaling allows you to automatically adjust the number of servers or instances based on real-time demand. This helps keep systems responsive during high-traffic periods while also cutting costs by scaling down when demand is low. In cloud environments, auto-scaling works in tandem with load balancing to provide an optimal user experience.

• How to implement: Set up auto-scaling policies using your cloud provider’s tools, like AWS Auto Scaling, which lets you specify scaling triggers based on metrics such as CPU usage or request count.
• Define thresholds: Choose thresholds that reflect your typical and peak usage. For example, you could set the system to add instances when CPU usage goes above 70% and remove instances when it drops below 30%.
• Stress test regularly: Simulate high-traffic events to make sure auto-scaling responds fast enough. Running these tests during off-peak times allows you to refine scaling policies without risking service interruptions during busy hours.

These strategies not only help reduce downtime but also ensure that your systems can scale to meet demands, adapt to unexpected events, and maintain a consistent user experience.

Implementing fault tolerance

Fault tolerance means building systems that can keep running smoothly, even when certain parts fail. By incorporating redundancy and failover mechanisms, you can keep operations steady and reduce the impact of unexpected issues. Here’s how to build fault tolerance into your infrastructure:

Redundant infrastructure

Redundant infrastructure includes backup components ready to take over if primary components fail, which ensures continuous operation and avoids single points of failure. Redundancy is crucial for essential systems that need to stay online without interruption.

• Getting started: Identify critical parts of your infrastructure—such as servers, storage, or network paths—and set up backups for each. For example, a RAID configuration mirrors data across multiple drives, so even if one drive fails, data is still accessible.
• Why it matters: Redundant systems are especially valuable for critical business processes where downtime isn’t an option. By designing for redundancy, you’re creating layers of protection that keep your operations running even when issues arise.
• Action step: Regularly test backups by simulating failures to confirm they can seamlessly handle the load when needed.

Multi-region clusters

Deploying applications across different geographic regions adds another layer of fault tolerance. Multi-region clusters distribute workloads, so if one region experiences an outage, another can pick up the slack. This setup is ideal for global services and helps keep latency low by routing users to the closest region.

• How to set up: Use a container orchestration tool like Kubernetes to deploy clusters across multiple regions. Configure global load balancing to automatically distribute traffic across regions based on demand and availability.
• Why it matters: Multi-region clusters help ensure your services remain available, even if an entire data center goes offline. This setup is particularly useful for organizations with a distributed or global user base, as it improves both reliability and performance.
• Plan for failover: Define how traffic will reroute if a region goes offline, and automate this process with tools like AWS Global Accelerator to ensure seamless transitions during outages.

Cross-region replication

Cross-region replication involves duplicating data across multiple regions, so if one region experiences data loss or downtime, the same data is accessible from another location. This strategy reduces the risk of losing critical information and improves recovery speed in case of incidents.

• How to implement: Many cloud providers offer cross-region replication as a feature for their storage services. Set up replication between primary and backup regions to ensure data is duplicated in real time or at regular intervals.
• Why it matters: Cross-region replication helps maintain data availability, especially in disaster recovery scenarios. If a regional incident occurs—such as a natural disaster or a major power outage—you can quickly access data from another region.
• Monitor for consistency: Use monitoring tools provided by your cloud provider to track replication health. Set up alerts for any discrepancies to ensure that data across regions remains consistent and accessible when needed.

Tools and strategies for improved infrastructure resiliency

To build a resilient infrastructure that can withstand disruptions, consider these tools to boost high availability and fault tolerance:

Elastic load balancing (ELB)

Elastic Load Balancing (ELB) distributes traffic across multiple instances within availability zones, minimizing overload risks and downtime by automatically redirecting traffic if a server fails. Tools like ELB are crucial for keeping applications responsive, especially during peak periods, by ensuring that traffic is balanced and rerouted as needed.

Elastic kubernetes service (EKS)

AWS’s Elastic Kubernetes Service (EKS) supports the deployment of containerized applications across multi-region clusters, distributing workloads geographically to avoid single points of failure. Multi-region setups ensure that resources scale based on demand, providing resilience even if one region encounters an issue. EKS leverages auto scaling and load balancing to maintain service availability across locations, optimizing performance and reliability.

AWS auto scaling

AWS Auto Scaling dynamically adjusts resources, such as EC2 instances, according to demand. It scales up during high traffic and down during low traffic, which ensures high availability while optimizing costs. Auto scaling, especially when combined with load balancing, enables infrastructure to automatically adapt to changes in demand, keeping applications efficient and responsive.

Prioritizing high availability and fault tolerance is key to a resilient disaster recovery strategy. By implementing these elements, your organization can minimize downtime, protect data, and ensure continuous service—no matter what comes your way.

For more insights on building resilient infrastructure, watch our full webinar Planning for Failure: Are You Ready for Disaster?, or try TestRail’s free 30-day trial to see how our platform can support your testing needs and improve your disaster recovery plan!