ControlMonkey is expanding its Cyber Resilience Platform with Data Backup Correlation, a new capability that helps CISOs and cloud teams understand whether critical data sources are protected, whether recovery points are available, and where backup-related recovery risk exists across the cloud.

The first release supports AWS Backup and Azure Backup.

The Problem: Backup Visibility is Still Fragmented

Most enterprises already invest in data backup tools and cloud-native backup services. But CISOs and cloud teams often lack full visibility into backup coverage and available recovery points across critical data sources, including databases, storage accounts, and cloud data services.

If a backup is disabled, a retention policy is changed, or a recovery setup is modified, the right teams may not know until an incident occurs.

That visibility gap can delay recovery, increase RPO exposure, lead to revenue loss, and create compliance risk.

Why this matters now

Data backup posture can change at the worst possible time. Ransomware attacks may target backup coverage before disrupting systems. Over-permissive AI agents or automation can modify cloud resources, policies, or recovery settings faster than teams can manually track. Human error can also disable backups, change retention policies, or leave recovery points missing.

When those changes are not visible across security and cloud teams, recovery plans become assumptions.

What ControlMonkey Data Backup Correlation does

Data Backup Correlation alerts teams when backup coverage changes, retention policies are violated, recovery points are missing, or expected RPO targets are at risk – then helps prioritize what to fix first based on recovery risk and business impact.

The capability also identifies missing backups, monitors RPO compliance, reviews available recovery points, and detects cross-region or cross-account protection gaps.

Why it matters for cyber resilience

Recovery is not only about having backups. Teams need to know:

  • Which data sources are protected
  • Which recovery points are available
  • Which assets are missing backup coverage
  • Which data sources are at risk of breaching RPO targets
  • Which issues should be addressed first

ControlMonkey already helps organizations protect and recover cloud and SaaS configuration, including cloud resources, networking, DNS, identity, security policies, observability dashboards, repositories, and third-party configurations.

With Data Backup Correlation, ControlMonkey adds data backup posture into the same resilience view, helping organizations connect data protection status with the infrastructure, configuration, and services those data assets depend on.

Key capabilities

Unified visibility into backup coverage, available recovery points, and recovery risk across critical cloud data sources. Full Breakdown include:

  • See backup coverage across critical cloud data sources
  • Review available recovery points for databases, storage accounts, and cloud data services
  • Identify unprotected data assets and backup gaps
  • Detect data sources breaching defined RPO targets
  • Monitor backup SLA and recovery policy compliance
  • Identify missing cross-region and cross-account protection
  • Correlate existing data backups with cloud infrastructure and configuration
  • Prioritize recovery planning based on dependencies, business impact, and recovery risk

Supported in the first release – AWS Backup and Azure Backup

Data Backup Correlation is available first for:

  • AWS Backup
  • Azure Backup

Support for additional enterprise backup platforms, including Rubrik, Veeam, Commvault, Cohesity, and others, is planned for future releases.

Built for a broader resilience picture

Data Backup Correlation expands ControlMonkey’s Cyber Resilience Platform by bringing data backup posture into the same recovery view as cloud and SaaS configuration.

The result is a broader recovery picture across configuration and data protection systems – helping teams move from fragmented visibility to a unified control plane for resilience.

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