How a Fortune 500 Company Built a Cloud Migration Plan for 1,000 Machines in Less Than One Month

Many large companies go into their cloud migration planning process assuming that the bigger they are, the more likely they are to fall. And in some cases, they may be right—but only if they rely on manual data collection and analysis. You see, assessing your cloud options and planning your migration with a manual process could cost you many man-hours while also increasing the likelihood of missing critical insights that can lead to expensive mistakes.

If you want your company to be among the rare success stories that assembles a plan in one month’s time and executes it without time-consuming trial-and-error or costly mistakes, you can—but only with the power of automated data analysis. This was the outcome a US-based global manufacturer and Fortune 500 company was looking for when they first began to plan their migration. At first, the company’s IT leadership felt overwhelmed and unsure about where to begin and struggled to find answers to these questions: 

  • Which workloads were ideal for the company’s phase 1 migration to the cloud?
  • How much would it cost to migrate their workloads to the cloud? (And how could they avoid going over budget)
  • After identifying ideal workloads for migration, what tactical next steps would the company need to take to make the migration happen without going over time?

It was after they struggled to answer these questions with manual data collection that the company turned to Cloudamize’s automated data analysis platform. Our automated platform helped this global manufacturer build a successful cloud migration plan with concrete next steps, full cost visibility up front, and zero mistakes or costly trial and error upon execution.  Here are the steps they took: 

  1. Prioritize "Quick Win" Migration Targets: First, the organization made critical business decisions about which workloads they would prioritize for their phase 1 migration based on their organizational goals and priorities. They decided to initially migrate development, staging, and disaster recovery environments; hardware reaching end of life; and machines with low utilization that would be candidates for auto-scaling. The workloads also had to be within the company’s phase 1 migration budget.
  2. Discovery and Assessment: This customer needed a comprehensive picture of their existing infrastructure, so they used automated data analysis to discover 5,400 machines and 1,673 applications across 65 data centers. Cloudamize automatically grouped the applications into 74 classes, such as business intelligence, security, and IT Management and then analyzed the performance profile and usage of all machines to identify those with low utilization. The automatic discovery, application classes, and performance analysis enabled the customer to clearly identify which workloads matched their phase 1 migration criteria.
  3. Map Application Dependencies: The manufacturer now had a list of workloads for phase 1 migration. The next challenge was to understand which workloads had to be migrated together. We helped this customer overcome this challenge by identifying which workloads were communicating with one another and would need to be migrated together in order to eliminate application connection breaks during migration. The customer then built "move groups" based on the workload dependency mapping.
  4. Identify Right-Sized Virtual Machines for Each Workload: The automated analysis considered the performance profile and on-premises usage of CPU, memory, and utilization of resources by each move group to identify the optimal virtual machine, storage option, and network settings for each. This analysis ensured performance requirements were met at the lowest possible cost upon migration.
  5. Calculate Cloud Cost: The customer’s goal was to ensure that they only migrated workloads that fit into their phase 1 migration budget. Cloudamize calculated annual costs based on the right-sized configuration for each workload, including compute, storage, and network costs for each workload as well as scheduled turnoff for those workloads taking advantage of auto-scaling. This analysis helped the customer eliminate workloads that were too expensive to migrate during phase 1 and complete their phase 1 migration planning.

After beginning with 5,400 machines, the manufacturer identified 1,000 that were ripe targets for phase 1 of its migration to the cloud—as well as the tactical next steps to migrate development nodes, implement turn on/turn off schedule recommendations, schedule migration for remaining opportunities identified in this engagement, and plan additional analyses to identify the next wave of IaaS and/or PaaS opportunities. This company built a comprehensive migration plan in less than one month and used it to execute a flawless large-scale phase 1 migration free of costly mistakes and time-consuming trial and error – a task that would have been impossible without automated analytics to guide their decision-making.

With thousands of servers and applications spread across multiple business units and locations, many organizations struggled to figure out where to begin. Cloudamize helps organizations like this Fortune 500 global manufacturer use automated data analysis to build an accurate and informed cloud migration plan without spending months on a manual analysis or moving to the cloud with faulty assumptions.

Guide: What To Think About When You're 
Thinking About Moving to the Cloud

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