What is disaster recovery?

It encompasses everything from equipment failures and local power outages to criminal or military attacks, cyberattacks and natural disasters. 

Disruptive events cause unplanned downtime and that downtime is expensive. According to Splunk and Oxford Economics’ 2026 Hidden Costs of Downtime report, unplanned downtime now costs the Global 2000 an aggregate USD 600 billion annually, a 50% increase in just two years. For an individual organization, that works out to an average of USD 15,000 per minute, or USD 900,000 per hour. Moreover, a single incident can also trigger an average 3.4% drop in stock price. 

Disaster recovery planning—the process of producing a detailed blueprint for how an organization will respond to a disaster and resume normal operations—can significantly mitigate these risks. While backups are a crucial component of recovery, backup disaster recovery alone does not constitute a comprehensive disaster recovery plan (DRP).

Several factors drive a growing urgency around disaster recovery. Attackers now use artificial intelligence (AI)-enabled malware and other AI-powered techniques to cause disruptions with operational and financial consequences that can span an organization’s entire IT infrastructure. Regulators have taken notice: the European Union’s Digital Operational Resilience Act (DORA), for example, requires financial entities to test their recovery processes and document proof they can restore operations. Disaster recovery capability is now something organizations must demonstrate, not just claim.

Disaster recovery is a foundational piece of cyber resilience, an organization’s ability to prevent, withstand and recover from cybersecurity incidents specifically. Disaster recovery encompasses a lot more than cyberattacks, including human error, hardware failures and natural disasters. Cyber recovery is the part aimed specifically at threats like ransomware.

DR also connects to the broader shift toward operational resilience: an organization’s ability to anticipate, absorb, adapt and recover from disruptions of any kind while continuing to deliver critical services. According to research from BCI and Riskonnect, 70% of organizations already have operational resilience programs in place, with another 10% building them.

Disaster recovery delivers key benefits such as: 

- Business continuity: Helps businesses resume normal operations after an unplanned event.

- High availability (HA): Enables automated, near-instant failover to a redundant system when the primary system fails.

- Reduced downtime: Restores essential systems and applications, providing minimal interruption.

- Cost savings: Reduces financial losses associated with downtime and data loss. 

- Enhanced data security: Strengthens an organization’s overall security posture and limits the impact of incidents by building data protection directly into the recovery process.

- Regulatory compliance: Helps organizations meet privacy laws and industry regulations, including newer mandates like DORA that require documented proof of recovery capability, not just a compliance claim.

- Strengthened customer trust: Maintains customer confidence by ensuring consistent service delivery and keeping customer data safe, even during system failures or disasters.

Business continuity disaster recovery (BCDR) refers to combining business continuity and disaster recovery efforts into one integrated strategy. It’s sometimes called emergency management in business, though it’s distinct from government emergency management programs such as the Federal Emergency Management Agency (FEMA), which focus on civil emergencies and community-wide disaster assistance rather than organizational IT and operations.

Business continuity planning (BCP) consists of systems and processes that ensure all areas of an enterprise can maintain essential operations or resume them quickly during a crisis or emergency.

Disaster recovery planning is a subset of business continuity planning that focuses on recovering IT infrastructure and systems. It involves a disaster recovery plan (DRP) that maps out recovery steps from an unexpected event.

The following seven steps are instrumental to effective disaster recovery planning:

1.    Perform a business impact analysis (BIA)
2.    Analyze risk
3.    Prioritize applications
4.    Document dependencies
5.    Establish RTO, RPO and RCO objectives
6.    Factor in regulatory compliance issues
7.    Implement continuous testing and review

Creating a comprehensive disaster recovery plan often begins with a business impact analysis (BIA). When performing this analysis, organizations create a series of detailed disaster scenarios. These scenarios are used to predict the size and scope of the losses the organization could incur if certain business processes were disrupted. For instance, what if a fire destroys a customer service call center? Or a critical data center outage takes down core systems for hours?

This analysis enables the organization to identify the business functions that are most critical and determine how much downtime each can tolerate. This information helps teams create a plan for maintaining the most critical operations in various scenarios.

IT disaster recovery planning should be based on and support business continuity planning. What if, for instance, a business continuity plan calls for customer service representatives to work from home in the aftermath of a call center closure?? What types of hardware, software and IT resources would need to be available to support that plan?

This is also the stage to assign clear ownership. A disaster recovery team typically includes a leader who coordinates the overall response, IT staff who execute the technical recovery, and a liaison who keeps non-IT departments informed. Each role should have a named alternate, so recovery doesn’t stall if the primary owner is unreachable when disaster strikes.
 

Performing a risk assessment to evaluate the likelihood and potential consequences of the risks a business faces is a crucial component of a disaster recovery strategy. As cyberattacks and ransomware become more prevalent, it’s critical to understand the general cybersecurity risks that all enterprises confront today. Furthermore, it is important to understand the risks that are specific to your industry and geographic location.

An organization might ask questions like:

- What financial losses will we incur from missed sales opportunities or disruptions to revenue-generating activities?

- How might this scenario damage our brand’s reputation? How will customer satisfaction be impacted?

- How will employee productivity be affected? How many labor hours might be lost?

- What risks might the incident pose to human health and safety?

- How will progress toward key business initiatives or goals be impacted?

Not all workloads are equally critical to a business’s ability to maintain operations, and downtime is far more tolerable for some applications than it is for others.

Many organizations separate IT systems and applications into three tiers based on their criticality and the severity of potential data loss:

1.    Mission-critical: Applications that are essential to the business’s survival.
2.    Important: Applications for which the organization could tolerate relatively short periods of downtime.
3.    Non-essential: Applications the organization could temporarily replace with manual processes or do without.

The next step in disaster recovery planning is to create a comprehensive inventory of hardware and software assets. It’s essential to understand critical application interdependencies at this stage. If one software application goes down, which others are going to be affected?

For example, an e-commerce company might run one server for its customer-facing site and payment processing, and a separate server for internal archives and payroll. The first server needs to come back online within minutes; the second can wait hours or days. But if the first server depends on a database or authentication service that’s still down, restoring it first won’t bring the site back. Mapping these dependencies shows engineers the necessary recovery order.

Designing data resiliency and disaster recovery models into systems when they are initially built is often the best way to manage application interdependencies. It’s common with today’s microservices-based architectures to discover processes that can’t be initiated when other systems or processes are down, and vice versa.

It’s vital to uncover such problems—and develop appropriate mitigation plans for systems and processes—before an actual disaster strikes.

Organizations use risk assessments and a business impact analysis to define key recovery objectives such as recovery time objective (RTO), recovery point objective (RPO), and recovery consistency objective (RCO).

-   RTO defines the maximum acceptable time a system or process can be offline after a disruption before the downtime causes unacceptable harm. It’s the span of time from the second a disaster occurs until the business is fully up and running. Though both RPO and RTO are measured in time, such as minutes, hours or days, RPO is a target objective for maximum data loss, while RTO is the goal for downtime.

-   RPO is the maximum amount of data loss that an organization can tolerate. It is used to decide how often to replicate data such as files, databases and applications, and is thus measured in time. If the RPO is set to one hour, that means the system updates its backups once per hour, and in turn, can lose a maximum of one hour’s worth of new data. 

-  RCO is a metric used in data protection services that indicates how many inconsistent entries in business data from recovered processes or systems are tolerable in disaster recovery situations. It describes the integrity of business data across complex application environments.

Disaster recovery software and solutions should align with the organization’s data protection and security regulations. Backup and failover systems should also meet the same standards for confidentiality and integrity as primary systems.

There are also regulatory standards stipulating that all businesses must maintain disaster recovery and business continuity plans. The Sarbanes-Oxley Act (SOX), for instance, requires all publicly held firms in the U.S. to maintain copies of all business records for a minimum of five years.

Failure to comply with this regulation (including neglecting to establish and test appropriate data backup systems) can result in significant financial penalties for companies, even jail time for their leaders.

An untested disaster recovery plan cannot be relied upon. All employees with relevant responsibilities should participate in the disaster recovery test exercise, which can involve maintaining operations from the failover site for a specified period.

Testing can also help teams catch configuration drift, where a system’s live settings gradually diverge from what the disaster recovery plan documents. A server might get patched outside the normal update schedule, or a firewall rule might get changed and never reverted. Either way, the actual restored environment can end up looking different than the DRP predicts.

Disaster recovery plans and related tests should be reviewed and revised on an ongoing basis to reflect changes in the organization, hardware and software assets and threat landscape.

There are two core functions to disaster recovery: maintaining operations, or restoring them as quickly as possible, and protecting data.

Failover is the process of moving workloads to backup systems to prevent or minimize disruptions to production processes and user experience. Failback is the return to primary systems once they are restored. Data protection, the other core function, works through backups, snapshots and other recovery methods.

We will take a closer look at disaster recovery solutions in terms of recovery site readiness, data protection methods, and delivery and operating models.

Building a disaster recovery environment, whether on-premises or in the cloud, means weighing cost against how fast you need to recover.

A hot site is a fully operational, ready-to-go replica of your IT environment that can take over near-instantly if a primary site fails. A cold site is infrastructure-ready space that takes significant time to bring online, since systems still need to be provisioned before recovery can begin. A warm site sits between the two: systems are staged and replicating, but not continuously live, offering faster recovery than a cold site without the ongoing cost of a fully live hot site.

These readiness levels apply to physical data centers and cloud-based environments alike.

Backup and restore methods are part of the disaster recovery plan foundation.

- Tape and early disks: Historically, most enterprises relied primarily on tape for backup, with disk playing a smaller role because it was more expensive for bulk storage. They maintained multiple copies of their data and stored at least one at an offsite location.

- Modern disk-based backups: As disk costs fell, organizations moved away from tape as primary backup storage and disk-based systems became the standard, offering faster backup and recovery. Modern disk-based solutions use hard disk drives or solid-state drives (SSDs) in local storage, network-attached storage (NAS) or storage-area network (SAN) configurations. This change dramatically reduced recovery times because disk allows random access to data while tape must be read sequentially.

- Backup as a service (BaaS): A third-party provider manages regular data backups on an organization’s behalf, a common choice for organizations that lack the resources to run backup infrastructure themselves.

A snapshot captures the state of a disk, volume or application at a specific point in time. Instead of duplicating all data, many snapshot methods preserve the original data blocks and capture only what’s changed. This protects the point-in-time copy while conserving storage space.

Snapshots can be replicated to other locations or stored in the cloud for disaster recovery purposes. Immutable snapshots, which can’t be changed or deleted for a set period, add additional protection against ransomware, accidental deletion, or tampering.

Cloud DR uses cloud-based infrastructure and services to provide an environment for failover where workloads can run during an outage. It also enables organizations to back up and protect application data and entire server infrastructure, including physical or virtual machines (VMs), whether delivered through public cloud or a dedicated service provider. Cloud DR helps reduce the need to maintain physical secondary data centers.

For backup specifically, many organizations rely on hybrid cloud backup to keep some data on-premises while replicating critical systems to the cloud. Such approaches offer flexible scalability to match evolving storage demands, and support organizations undergoing cloud migration.

Disaster recovery as a service (DRaaS) is a third-party, cloud-based solution that provides data protection and DR capabilities on demand and on a pay-as-you-go basis. It is one of the most popular and fastest-growing managed IT service offerings available today. In a report from Fortune Business Insights, the global DRaaS market was valued at USD 18.89 billion in 2025 and is expected to grow from USD 23.08 billion in 2026 to USD 83.15 billion by 2034.

With DRaaS, the service provider documents recovery expectations like RTOs and RPOs in a service-level agreement (SLA) that outlines downtime limits, application recovery expectations and other specifics of the deal. DRaaS offerings also typically include cloud-based application recovery operations.

Depending on an organization’s specific requirements regarding factors like backup schedule, backup volume and data sensitivity, this approach can be more cost effective than maintaining redundant dedicated hardware.

AI tools can strengthen disaster recovery by improving threat detection, automating incident response and streamlining recovery management across an organization’s IT environment.

But AI also expands what needs protecting. According to IBM’s 2026 Cost of a Data Breach Report, organizations that experienced data breaches involving unsanctioned (or “shadow”) AI paid an average of USD 670,000 more in breach costs than those with little to no shadow AI exposure. The same report found that among companies with an AI-related security incident, the large majority lacked proper AI access controls.

AI systems typically run on automated credentials and broad data access, which widens an organization’s attack surface if left ungoverned. That’s the risk side of the equation.

The payoff comes from treating AI governance as part of the overall recovery strategy, not something separate. Organizations that build AI and automation into their security and recovery workflows save an average of USD 1.93 million in breach costs, and identify and contain breaches 80 days faster, according to the same IBM report. 

AI in disaster recovery can deliver the following key benefits:

- Predictive analytics
- Real-time monitoring
- Automated responses
- Generated AI assistance

AI models analyze historical data to predict potential failures or security breaches before they occur, supporting proactive risk mitigation.

Machine learning (ML) algorithms can continuously monitor infrastructure health. Automated alerts help teams detect anomalies and prevent downtime or data loss before an issue escalates.

AI-driven automation can deliver faster recovery procedures than human intervention, significantly reducing RTO and RPO.

Generative AI (gen AI),  particularly large language models (LLMs), can improve DR workflows by analyzing logs for root cause analysis, auto-generating incident documentation and providing conversational interfaces that help teams translate data into actionable recovery steps.