The demand for a fast and low-risk Datadog migration tool has grown sharply, especially as organisations try to escape vendor lock-in and regain control over their observability costs. Because legacy platforms make switching expensive and time-consuming, many teams simply stay put. However, a new approach from groundcover is beginning to change that dynamic, offering a migration path designed to remove complexity instead of adding to it.
How the pressure for a Datadog migration tool emerged
For years, enterprises built their observability stacks around large commercial platforms. These systems delivered powerful features, yet they also created a long-term dependency that became difficult to break. As organisations scaled, so did their monitoring bills. Moreover, moving away usually required months of manual work, countless engineering hours and costly consulting engagements.
Consequently, even teams dissatisfied with pricing models found themselves unable to justify switching. Migration had become the moat that kept customers locked in. However, the industry’s move toward Bring Your Own Cloud (BYOC) shifted expectations. Companies wanted cost transparency, data ownership and architectures that could support emerging AI workloads. Therefore, migration tools became a priority rather than an afterthought.
The new Datadog migration tool from groundcover
A growing number of teams are now evaluating groundcover’s fully automated Datadog migration tool, which aims to remove the largest barriers holding organisations back. Instead of requiring teams to manually rebuild dashboards, rewrite alerts or remap metrics, the tool handles these tasks automatically. As a result, organisations can evaluate alternatives without committing months of engineering resources.
One of the central promises is simplicity. After connecting with a read-only Datadog API key, the system scans dashboards, monitors and integrations. It then builds full dependency graphs, identifies all relevant components and prepares them for transfer. Because everything is automated, companies avoid the downtime and operational disruption typically associated with migration projects.
Why metric translation matters
During most migrations, metric discrepancies cause major delays. Different naming conventions, formats and schemas force engineers to rewrite queries by hand. However, groundcover pre-built a library containing hundreds of metric translations, allowing Datadog metrics to be converted into Prometheus or OpenTelemetry formats automatically.
For example, a Datadog CPU usage metric can become a Prometheus counter without any manual intervention. Moreover, if a team uses custom naming rules, they can define their own translation patterns. Once added, the system applies them across dashboards and alerts, ensuring consistent results. Consequently, engineers spend far less time cleaning up mismatches.
A dashboard engine designed for accuracy
Dashboards are often the heart of an observability stack. Because of this, losing layout accuracy or visual fidelity can cause friction when switching tools. To address this, groundcover redesigned its dashboard rendering engine so that migrated dashboards match their Datadog versions closely — not only in content, but also in structure.
For instance, multi-column layouts, grouped charts and floating widgets recreate exactly as before. If a widget type has no equivalent, the tool flags it clearly instead of silently breaking the layout. Meanwhile, a side-by-side preview lets teams compare every panel before completing the migration. This greatly reduces risk, since decisions are made with full visibility rather than guesswork.
The rising relevance of a Datadog migration tool
Several macro trends explain why interest in migration is accelerating. For one, many enterprises now demand BYOC models for cost-efficiency and data privacy. Legacy vendors recently introduced their own BYOC offerings, yet these tend to be incomplete or limited to high-tier customers. Consequently, organisations view alternatives like groundcover as more aligned with long-term strategies.
Furthermore, budgets are tightening. As observability costs rise, leadership teams are increasingly questioning volume-based pricing models. Migration, once unthinkable, is now seen as a viable way to reduce spend without compromising visibility. Additionally, community discussions — especially from developer forums — highlight frustration with unclear pricing structures and inflexible contracts. All of these factors strengthen the need for a simplified, automated option.
A lower-risk path for complex environments
Traditional migrations can take half a year and require external consultants. Instead, groundcover positions its Datadog migration tool as a product feature included at no additional cost. Because the automation handles most of the heavy lifting, teams experience a shorter migration timeline with significantly less operational risk.
In practice, the tool discovers all dashboards, alerts, integrations and custom metrics. It then reconstructs them inside groundcover, while highlighting unsupported items so teams can review them before making the switch. As a result, migrations feel incremental rather than disruptive. This reduces uncertainty and encourages more organisations to evaluate alternatives.
What to expect next
The migration tool is currently in private preview, with general availability planned for early December. This timing coincides with a period when many companies reassess budgets, consider new platforms and plan infrastructure updates for the coming year. Therefore, the launch could influence how teams approach observability decisions going forward.
Conclusion
The Datadog migration tool has long been the missing link for organisations that wanted to leave legacy monitoring systems but felt unable to do so. groundcover’s automated solution challenges that reality by drastically reducing the time, cost and complexity associated with switching platforms. As more companies prioritise BYOC, financial transparency and AI readiness, automated migrations may soon become a standard expectation rather than a rare convenience.
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