Observability Disaster Recovery is the new addtioan to Controlmonkey DR Soultion. Modern cloud operations rely heavily on observability. During incidents, dashboards, alerts, and monitoring rules are often the first place engineers turn to understand what’s happening.
Yet the configurations behind these systems – dashboards, alert policies, monitors, and escalation rules – are rarely protected by disaster recovery.
Introducing Observability Configuration Disaster Recovery
ControlMonkey now extends Cloud Configuration Disaster Recovery to observability platforms, protecting monitoring environments across Datadog, New Relic, Dynatrace, Grafana Cloud, and Splunk.
ControlMonkey automatically captures daily snapshots of observability configurations so teams can restore monitoring environments and maintain operational visibility during incidents.
Observability DR Key capabilities:
- Protect operational knowledge
Backup dashboards, monitors, alert rules, and escalation policies created over years of operational tuning. - Restore monitoring environments quickly
Recover observability configurations from versioned snapshots instead of rebuilding manually. - Detect configuration drift in monitoring systems
Track changes across observability platforms and identify unexpected modifications. - Ensure monitoring visibility during incidents
Maintain access to critical dashboards and alerts when diagnosing outages. - Extend disaster recovery beyond infrastructure
Protect the broader cloud control plane including infrastructure, network, and observability configuration.
How does Observability Configuration Disaster Recovery Works?
ControlMonkey Cloud DR solution continuously captures configuration snapshots from supported observability platforms.
Each snapshot records the structure and settings of monitoring environments, including:
- Dashboards and visualizations
- Alert rules and alert routing policies
- Monitors across metrics, logs, and traces
- Notification channels and escalation policies
- Service monitoring and APM configurations
- Click on the image to enlarge
These configurations are versioned and stored securely, allowing teams to compare changes over time and restore previous configurations when needed.
If dashboards are deleted, alerts are misconfigured, or monitoring rules break during an incident, engineers can restore observability configurations directly from a previous snapshot – without manually rebuilding monitoring environments.
Why Disaster Recovery for the Observability Layer?
Traditional disaster recovery focuses on restoring data, storage, and infrastructure.
But modern cloud environments rely on far more than compute resources. The cloud control plane – including monitoring configuration – contains the operational knowledge engineers depend on to diagnose and resolve incidents.
With ControlMonkey, teams can:
- Maintain versioned backups of observability environments
- Detect configuration changes and drift
- Restore monitoring systems quickly during incidents
- Ensure DR visibility by having clear Resilience Score
By extending configuration disaster recovery to observability, ControlMonkey helps teams maintain operational continuity across the entire cloud environment.
During incidents, engineers rely on monitoring systems to understand what’s happening – yet observability configurations themselves are rarely protected by disaster recovery. As a CTO, I know firsthand how valuable it would have been to restore dashboards and monitoring environments instantly instead of rebuilding them under pressure.
Real-World Impact: Datadog dashboards, monitors, and alerting policies
Our Datadog dashboards, monitors, and alerting policies represent years of operational knowledge and tuning. Losing that configuration during an incident would significantly impact our ability to diagnose issues quickly. With ControlMonkey, we know our observability configurations are versioned and recoverable, ensuring we maintain visibility when it matters most<br />
Ready to be Cyber Resilient?
Explore Cloud Configuration Disaster Recovery for Observability or schedule a demo today.
Reference Table: Key APM Configurations Used in Observability Platforms
| Configuration | Description | Example |
|---|---|---|
| Dashboards & Visualizations | Configurations that define how telemetry data is displayed. | Dashboards Saved views Dashboard layouts Panels / widgets Visualization settings Graph queries Dashboard variables |
| Alerts & Alerting Rules | Configurations that trigger notifications when conditions are met. | Alert rules Alert thresholds Alert policies Alert conditions Alert templates Alert routing rules Alert severity levels Alert suppression rules Alert deduplication settings |
| Monitors | Definitions that evaluate metrics, logs, or traces. | Metric monitors Log monitors Trace monitors Synthetic monitors Service health monitors SLO monitors Infrastructure monitors |
| Notification & Escalation Policies | Configurations controlling how incidents are communicated. | Notification channels Escalation policies PagerDuty integrations Slack / Teams alert routing Email notification rules On-call schedules |
| Service & Application Monitoring | Configurations defining what services are observed. | Service definitions Service maps Application performance monitoring (APM) settings Dependency maps Service tags / metadata Environment tags |
| Metrics Configuration | How metrics are collected, stored, and analyzed. | Custom metrics definitions Metric queries Metric tagging rules Metric retention policies Metric filters Metric rollups / aggregations |
| Synthetic Monitoring | Testing and uptime monitoring configurations. | Synthetic tests API tests Browser tests Uptime monitors Test schedules Test locations |
