Foundational to successful execution of cloud migration strategies is an understanding of dependencies across your environment so workloads and applications can be mapped and migrated without disruption to business.
Any dramatic change within an IT environment demands a thorough discovery and analysis of current infrastructures before deciding which elements to migrate. This is often the most challenging part of a migration project.
Ironically, enterprise IT organizations have the data they need to execute a cloud migration project; but in fact, there’s often too much data, the data you generate isn’t actionable, or the data is in disparate locations, siloed tools or an array of spreadsheets.
It takes time to uncover issues, document findings and turn them into actionable insight, especially for organizations that spread their infrastructure across a disparate environment. They typically have a plethora of purpose-built tools that work well, but don’t work together to manage change across systems. centers or teams. Yet, many organizations rely on their auto-discovery tools, an outdated CMDB and static spreadsheets to capture, assess and map their current data. This often leads to errors, gaps and potential bottlenecks. And then, by the time the discovery process is complete, the organization’s infrastructure has changed.
A successful cloud migration plan starts with understanding on-premise application workload profiles. A key part of this discovery process is figuring out ‘what talks to what’, or rather, analyzing the dependencies one system, application or server can potentially have on another. Workload intelligence, combined with dependency mapping therefore adds critical insight to the decision-making process, and significantly reduces the possibility of missing dependencies during the move.
Before your create your migration strategy, CIOs should ask themselves some tough questions about their IT environment.
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