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The #1 Most Overlooked Piece of Your Cloud Resiliency Plan

John Gray
InterVision

Cloud resiliency plans are vital to an enterprise's overall cloud strategy. These plans prepare organizations for unexpected disruptions and safeguard critical systems and data. However, many leaders neglect to implement another essential component of a resiliency plan: disaster recovery strategies and protocols.

According to industry research, only about half of organizations have drafted a formal disaster recovery strategy, and less than half of that 54% test their disaster recovery protocols annually. Worse, 7% of organizations never test their plan, making it highly likely their strategy is outdated.

A solid, up-to-date backup and data recovery system is critical for maintaining business continuity and mitigating the potential impacts of unforeseen events. Here’s why disaster recovery is an integral part of any enterprise's cloud strategy.

The Basics of Disaster Recovery (DR)

DR is necessary for a robust cloud resiliency strategy because it shifts the focus from "if” to "when.” In other words, DR centers on the aftermath of data loss instead of preventative strategies. Leaders who adopt DR protocols can prepare a holistic risk avoidance and mitigation strategy.

In its simplest form, DR protects organizations from common scenarios like data or backup loss. Disaster-ready leaders will be prepared for these events because they’ve stress-tested and ascertained the strength of their systems by answering the following:

■ How quickly can backup data be recovered after a disaster?

■ Where is the backup data hosted?

■ What protections are in place for the backup server?

Leaders protect their service continuity by regularly asking and answering these questions. As a result, their consumers or clients face fewer disruptions, and isolated events won't tarnish their reputations.

The most prepared leaders should also be confident about their responses to unique events like natural disasters. Hurricanes, tornados, extreme weather, blizzards, ice storms, earthquakes, floods and fires can irrevocably damage your data — and these events are increasing in frequency.

Making DR Work for Your Cloud Infrastructure

Unfortunately, there's no one-size-fits-all approach to DR. Every organization has a different data architecture, so their protection and response strategies must also differ. But that doesn't mean every leader has to start at the drawing board.

IT and security leaders can prepare a DR plan by assessing their organization’s risk profile. Does a particular system exhibit vulnerabilities, and if so, why? Could a disaster break through these weak points?

Threats that could jeopardize business continuity should be prioritized. For example, systems harboring personal consumer data can cause serious losses should they fail. Alternatively, robust consumer data protections can be a competitive advantage in our digital age. Either way — protecting critical data systems benefits businesses.

As they lay the groundwork for their DR plan, leaders will identify their organization’s most critical assets and dependencies. Data in these systems should be protected thoroughly with robust backup and recovery strategies.

Implementing, Maintaining and Perfecting Your DR Plan

Although its manifestations will differ based on your cloud strategy, a robust DR plan should include all of the following:

Regular backups — Critical data and applications should frequently be backed up, both off-site and on-site. Doing so will minimize data loss during a disaster and ensure minimal business interruption. The number of backups will differ based on industry and compliance requirements. (Pro tip: 3-2-1 backups are the leading standard.)

Data replication and redundancy measures — There’s "just in case” data, and then there’s data hoarding. Craft a strategy for data replication that eradicates frivolous data and keeps your cloud infrastructure running optimally. For reference, many organizations adopt a data model that deletes consumer information after a federally mandated period.

Multi-site replication — Distributing data and applications across multiple locations adds a layer of protection against regional disasters. Additionally, some leaders may want to consider a hybrid strategy employing physical and cloud-based data centers.

Testing and simulation — DR plans require consistent and frequent updating. Leaders should regularly test their plans by simulating disaster scenarios at scheduled intervals. Regular maintenance will ensure the plan is effective and the team remains prepared to execute.

Alongside these measures, leaders can implement key performance metrics like recovery point objective (RPO) and recovery time objective (RTO). RPO tracks the interval of time organizations have before a network outage or disruption impedes business operations. Say an organization maintains access to backup data for 24 hours — in this case, they have one day to restore normal data operations before the disruption impacts stakeholders. On the other hand, RTO tracks the time it takes a disaster recovery team to restore lost data.

It's helpful to use both RPO and RTO when testing your program and team for disaster readiness, as these benchmarks can inform your evolving DR plan.

Finally, many leaders find it useful to draft a "lessons learned” playbook after each successive vulnerability test. These retrospective observations detail how a team can increase their RPO and decrease their RTO, thus improving disaster response protocols in successive drills (or during a real disaster).

Leaders who feel overwhelmed by their data architecture or need help determining where to start may want to consider third-party options for DR, including disaster recovery as a service (DRaaS) or a managed service provider (MSP). DRaaS is a subscription-based service that drafts and executes an organization’s cloud DR plan, while an MSP is an IT and security expert who will guide organizations through the many steps of cloud resiliency — from disaster planning and recovery to cloud migration.

Regardless of which preparedness protocols match your organization, one fact is clear: Today is the best day to draft a DR plan. Leaders should reevaluate their cloud resiliency plan and determine where cracks may emerge during a crisis. Without taking this step, organizations are woefully unprepared for the increasingly complex digital age.

John Gray is CPO at InterVision

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The #1 Most Overlooked Piece of Your Cloud Resiliency Plan

John Gray
InterVision

Cloud resiliency plans are vital to an enterprise's overall cloud strategy. These plans prepare organizations for unexpected disruptions and safeguard critical systems and data. However, many leaders neglect to implement another essential component of a resiliency plan: disaster recovery strategies and protocols.

According to industry research, only about half of organizations have drafted a formal disaster recovery strategy, and less than half of that 54% test their disaster recovery protocols annually. Worse, 7% of organizations never test their plan, making it highly likely their strategy is outdated.

A solid, up-to-date backup and data recovery system is critical for maintaining business continuity and mitigating the potential impacts of unforeseen events. Here’s why disaster recovery is an integral part of any enterprise's cloud strategy.

The Basics of Disaster Recovery (DR)

DR is necessary for a robust cloud resiliency strategy because it shifts the focus from "if” to "when.” In other words, DR centers on the aftermath of data loss instead of preventative strategies. Leaders who adopt DR protocols can prepare a holistic risk avoidance and mitigation strategy.

In its simplest form, DR protects organizations from common scenarios like data or backup loss. Disaster-ready leaders will be prepared for these events because they’ve stress-tested and ascertained the strength of their systems by answering the following:

■ How quickly can backup data be recovered after a disaster?

■ Where is the backup data hosted?

■ What protections are in place for the backup server?

Leaders protect their service continuity by regularly asking and answering these questions. As a result, their consumers or clients face fewer disruptions, and isolated events won't tarnish their reputations.

The most prepared leaders should also be confident about their responses to unique events like natural disasters. Hurricanes, tornados, extreme weather, blizzards, ice storms, earthquakes, floods and fires can irrevocably damage your data — and these events are increasing in frequency.

Making DR Work for Your Cloud Infrastructure

Unfortunately, there's no one-size-fits-all approach to DR. Every organization has a different data architecture, so their protection and response strategies must also differ. But that doesn't mean every leader has to start at the drawing board.

IT and security leaders can prepare a DR plan by assessing their organization’s risk profile. Does a particular system exhibit vulnerabilities, and if so, why? Could a disaster break through these weak points?

Threats that could jeopardize business continuity should be prioritized. For example, systems harboring personal consumer data can cause serious losses should they fail. Alternatively, robust consumer data protections can be a competitive advantage in our digital age. Either way — protecting critical data systems benefits businesses.

As they lay the groundwork for their DR plan, leaders will identify their organization’s most critical assets and dependencies. Data in these systems should be protected thoroughly with robust backup and recovery strategies.

Implementing, Maintaining and Perfecting Your DR Plan

Although its manifestations will differ based on your cloud strategy, a robust DR plan should include all of the following:

Regular backups — Critical data and applications should frequently be backed up, both off-site and on-site. Doing so will minimize data loss during a disaster and ensure minimal business interruption. The number of backups will differ based on industry and compliance requirements. (Pro tip: 3-2-1 backups are the leading standard.)

Data replication and redundancy measures — There’s "just in case” data, and then there’s data hoarding. Craft a strategy for data replication that eradicates frivolous data and keeps your cloud infrastructure running optimally. For reference, many organizations adopt a data model that deletes consumer information after a federally mandated period.

Multi-site replication — Distributing data and applications across multiple locations adds a layer of protection against regional disasters. Additionally, some leaders may want to consider a hybrid strategy employing physical and cloud-based data centers.

Testing and simulation — DR plans require consistent and frequent updating. Leaders should regularly test their plans by simulating disaster scenarios at scheduled intervals. Regular maintenance will ensure the plan is effective and the team remains prepared to execute.

Alongside these measures, leaders can implement key performance metrics like recovery point objective (RPO) and recovery time objective (RTO). RPO tracks the interval of time organizations have before a network outage or disruption impedes business operations. Say an organization maintains access to backup data for 24 hours — in this case, they have one day to restore normal data operations before the disruption impacts stakeholders. On the other hand, RTO tracks the time it takes a disaster recovery team to restore lost data.

It's helpful to use both RPO and RTO when testing your program and team for disaster readiness, as these benchmarks can inform your evolving DR plan.

Finally, many leaders find it useful to draft a "lessons learned” playbook after each successive vulnerability test. These retrospective observations detail how a team can increase their RPO and decrease their RTO, thus improving disaster response protocols in successive drills (or during a real disaster).

Leaders who feel overwhelmed by their data architecture or need help determining where to start may want to consider third-party options for DR, including disaster recovery as a service (DRaaS) or a managed service provider (MSP). DRaaS is a subscription-based service that drafts and executes an organization’s cloud DR plan, while an MSP is an IT and security expert who will guide organizations through the many steps of cloud resiliency — from disaster planning and recovery to cloud migration.

Regardless of which preparedness protocols match your organization, one fact is clear: Today is the best day to draft a DR plan. Leaders should reevaluate their cloud resiliency plan and determine where cracks may emerge during a crisis. Without taking this step, organizations are woefully unprepared for the increasingly complex digital age.

John Gray is CPO at InterVision

Hot Topics

The Latest

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply ...