When a company works in cloud, Sometimes it's taken for granted that their infrastructure is inherently resilient. But the reality is much more uncomfortable. A misconfiguration, accidental deletion, data corruption, cyberattack, major network issue, or even a regional incident can bring key services to a halt. And when that happens, the question isn't just what broke, but how long it takes the organisation to resume acceptable operations.
There enters the Disaster recovery. Not as a decorative document or a collection of backups, but as the set of decisions, processes, and resources that allow applications, data, and operations to be recovered after a serious interruption. Its value is not in “turning things back on,” but in recovering what's important within the appropriate timeframe and with an acceptable impact on the business.
The cloud offers very clear advantages for this: automation, reproducible deployment, replication between regions, and the ability to set up alternative environments with considerably more agility than with traditional models. But none of this is of any real use if there isn't a defined strategy. You can have copies, tools, and contracted services, and still not have a real recovery capability.
What exactly is a cloud disaster recovery plan
One of the most common mistakes is confusing backup with Disaster recovery. A backup protects data and allows it to be restored to an earlier point. A disaster recovery plan covers considerably more: services, dependencies, recovery order, failover, identities, procedures, responsible parties, validation, and communication. Having backups does not mean you are prepared to resume operations quickly.
It is also advisable to separate this concept from high availability and business continuity. High availability aims to absorb more limited failures within the normal architecture. Business continuity includes how the organisation continues to operate during a crisis. Disaster recovery comes into play when an incident exceeds what the usual architecture can withstand, and operations need to be restored in a structured manner.
That's why the plan shouldn't be defined solely by infrastructure. The correct question is different: what does the company need to recover to continue operating in a reasonable manner. That change of focus, from the technical to the real impact, is what turns a document into a useful tool.
The first step: prioritising by business impact
Before considering secondary regions or replication, it is worth identifying which systems actually underpin the business. A corporate website does not carry the same weight as a transactional platform, an identity system, an academic database or an environment that provides direct services to customers, students or internal teams. Priorities should be determined by the impact on revenue, customer service, reputation, compliance or productivity.
Classifying workloads by criticality helps to avoid two very common mistakes: investing too much in secondary services, or falling short precisely in the systems that would cause the most damage if they were lost. In practice, this requires mapping processes, applications, data, integrations, and technical and operational dependencies. If an application depends on identity, a database, a specific network and certain secrets, its recovery cannot be designed in isolation.
A solid plan understands the complete system, not just loose parts. It also understands what each area of the business can expect in a crisis scenario. The clearer those expectations are before the incident, the less improvisation there will be when it comes to executing the plan.
RTO and RPO: the two decisions that change everything
Any serious plan is based on two well-known metrics: RTO and RPO. RTO is the maximum acceptable time for restoring operations. RPO is the maximum amount of data that the company can afford to lose, measured in time. Put simply: one metric answers the question of how long operations can be down, and the other answers the question of how much data can be lost without the impact becoming unacceptable.
These two variables influence the architecture, the frequency of copies, the type of replication, and, of course, the budget. The more demanding the objectives, the more sophisticated and costly the strategy usually is. This is why it is advisable to define them with the business and not assume them from technology without prior discussion.
It's also worth being cautious with promises. Sometimes “near-instant” recoveries are spoken of as if they were universal. In reality, the actual time depends on the type of incident, the service affected, the deployment pattern, how traffic is switched, and whether the procedures have actually been tested. It's more rigorous to talk about achievable and validated objectives rather than grandiloquent promises.
What strategies exist in the cloud
There are usually four main strategies in the cloud. The first is backup and restore: restoring data, configuration and infrastructure following an incident. It is the most cost-effective option and usually the simplest to maintain, but it is also the one that tends to involve longer recovery times if it is not highly automated.
The second is the ‘pilot light’ approach. Here, the data and a minimal part of the environment are kept on standby at an alternative location, whilst the rest of the components are activated or scaled up as and when required. It is a rather interesting way of reducing costs without having to start from scratch at the critical moment.
The third is warm standby. In this approach, there is a reduced but functional version of the system in another location. This allows for a shorter recovery time because part of the environment is already deployed and operational, even if it doesn't have the same capacity as the main one.
The fourth is active multi-site, where several regions or locations serve traffic simultaneously. It is the most robust strategy, but also the most complex and costly. If implemented correctly, it significantly reduces the impact of a regional outage. However, it does not eliminate the need for backups, nor does it, on its own, protect against logical data corruption or deletions that are not detected in time.
How to draw up a step-by-step plan
The first operational step is to inventory applications, data, services, integrations, and dependencies. It is not enough to list cloud resources; you need to know what each system requires to function and in what order it would be advisable to recover it. If this is not clear, precious time will be lost on the day of the incident deciding on the fly.
Next, we need to define what actually constitutes a disaster. Not every incident triggers the full plan. The team must distinguish between an operational problem, a significant degradation and a situation that requires a disaster recovery declaration. That definition should take into account the impact on users and the business, not just the technical status of a few components.
The disaster recovery architecture is designed below. This is where decisions are made regarding secondary region, active-passive or active-active pattern, copy policies, synchronous or asynchronous replication, geographically redundant storage, DNS, connectivity, identities, secrets, and traffic diversion mechanisms. The selection should not be made on intuition, but rather based on recovery objectives and the criticality level of each workload.
Then comes automation. Infrastructure as code and repeatable deployments help enormously, as they reduce errors and speed up recovery. Of course, automation must be validated. Automating something that has never really been tested provides a false sense of security that can prove costly.
It is then advisable to document runbooks and responsibilities: who declares the disaster, who carries out each step, how the failover is validated, which services are restored first, how the status is communicated, and how decision-making is coordinated. In a crisis, coordination is almost as important as the technology.
And there is one point that deserves special attention: failover and failback are not the same thing. Activating a fallback environment does not mean that returning to the primary one is straightforward. The return process also requires steps, validations and time. If this is not planned in advance, it can become yet another incident within the incident.
Disaster recovery and cloud cost optimisation
A well-thought-out plan does not aim for maximum resilience across the board, but rather the appropriate level of resilience for each specific case. This is a key point when it comes to costs. The most costly mistake is usually to apply the same level of protection to workloads with very different levels of criticality.
The most sensible way to optimise is to align the architecture with business value. A core service may justify continuous replication and pre-deployed environments. A less critical service can be managed using copies, automated deployment and longer recovery times. This segmentation reduces unnecessary expenditure without compromising continuity where it really matters.
It also helps to choose carefully between cold standby, pilot light, warm standby or active/active, depending on the actual objectives. The shorter the acceptable downtime and the lower the tolerable data loss, the higher the cost will normally be. Optimisation is not about providing less protection, but about protecting better and more sensibly.
The most common mistakes
The first is to believe that backups are enough. Restoring data does not guarantee the recovery of applications, identities, configurations, connectivity or boot sequences. When the plan does not cover the entire system, recovery becomes slow and chaotic.
The second is failing to test the plan regularly. An untested plan is merely a hypothesis. And in disaster recovery, hypotheses offer little reassurance when the time comes to act.
The third is to overlook communication. Without clear roles, decision-makers, a defined escalation process and established channels, even a technically sound architecture can fail when put into practice. Often, the problem lies not with the cloud, but with coordination.
What makes a plan a reliable plan
The short answer is simple: testing, continuous review, and real access to the necessary information. A recovery plan has to be checked with drills, partial exercises, real restorations, and time validation. It's not enough to confirm that “something starts”; it must be demonstrated that the company can recover what it needs within the agreed timeframe.
Furthermore, the plan must be kept alive. If the architecture changes, dependencies, timings, scripts, and risks change. It is also important to ensure that documentation, certificates, credentials, and procedures will remain accessible even in significant failure scenarios.
In other words, disaster recovery is not a document that is drawn up once and then filed away. It is an operational capability that is designed, practised and improved over time. That is the difference between hoping that everything will go well and being prepared to respond when it does not.
Conclusion
In the cloud, knowing how to deploy services is important. Knowing how to design them to be resilient and to recover is quite a bit more so. Understanding disaster recovery, architecture, automation, and business continuity is part of the knowledge that many companies today require from cloud profiles with greater technical expertise. At IMMUNE Technology Institute, this knowledge is not only learned, it is practised, so that it can be applied directly in the company.
Preguntas frecuentes
What is the difference between a backup and disaster recovery?
Backups protect data and allow it to be restored. Disaster recovery covers the orderly recovery of services, dependencies, processes, and operations following a major incident.
Do all companies need the same strategy?
No. The strategy must be tailored to the criticality of the service, the business impact and the objectives of Recovery Time Objective (RTO) and Recovery Point Objective (RPO) defined for each load.
Which strategy is more economical?
Usually, backup and restore is the lowest-cost and least complex option, although it typically involves longer recovery times than other alternatives.
Can resilience be improved without increasing expenditure?
Yes. The key is to prioritise loads, choose the right pattern for each case and automate recovery well. Optimisation isn't about making arbitrary cuts, but about adjusting protection to the real value of each system.
Why does the plan need to be tested if it's already documented?
Because a plan without testing is just a guess. Testing allows you to confirm timings, detect forgotten dependencies, and correct steps that seemed correct on paper.
