How Unified Visibility from Datadog Supports Cloud Migrations following the Cloud Adoption Framework

Migrating your applications from on-premises infrastructure to the cloud comes with a number of benefits, including increased agility, resilience, and scalability, as well as potential cost and IT overhead reductions. The Microsoft Cloud Adoption Framework for Azure (CAF) helps ensure a successful migration by providing a set of detailed guidelines, best practices and tools for the key stages of a cloud migration. These include the creation of a strategy and plan, ensuring your environment is ready to move to the cloud, and safely migrate your workloads. These methodologies provide a migration route that help customers adopt cloud with confidence.

But even with the right strategy, incidents can occur, especially if you lack continuous visibility into the health, performance, and makeup of your environment. By partnering with Datadog, they have made it simple to integrate end-to-end monitoring into each recommended phase of a CAF-driven migration. By connecting Datadog with your legacy and Azure resources, you can actively measure the success of your migration and, most importantly, identify issues before impacting users.

In the planning stage, you can enable Datadog's Azure integration and configure it for both your legacy environment and new Azure Landing Zones. This configuration includes standardizing your tagging strategy, customizing executive-summary dashboards, and setting up agreed communication channels so appropriate teams are notified of issues.

Once you have completed the ready stage, you have finalized your Azure Landing Zones and fully configured Datadog for your environment. You can then customize usage tools like Azure Log Analytics and Azure Monitor to avoid observability redundancy.

Now that you have deployed Datadog to your legacy environment and new cloud workloads you can move onto the migration stage. Datadog provides full, continuous visibility into your workloads as you migrate them over to Azure. This entails creating service- and workload-specific dashboards and alerts, and setting up synthetic tests and SLOs. Together, this enables you to get comprehensive, side-by-side visibility into your new and old workloads.

For full details and best practices for implementing Datadog into your migration process, see Datadog’s guide for Microsoft Cloud Adoption Framework for Azure.