How I navigated a complex migration project with ease using Cloud Intelligence™ and MCP Server

Cloud migration projects are some of the most complex projects till date based on my experience. When a customer decides to migrate there resources from one cloud provider to another, below are the most important artifacts that are required.

• Assessment of cost and capacity with customer’s current cloud provider.
• Assessment of cost and capacity that customer will incurs after they move there resources to new public cloud provider selected by customer.
• Factoring in growth forecast for cost and capacity calculations with the new cloud provider.

As you can see from above precise number calculations forms a base for a successful migration projects. There are no chances for any errors happening when it comes to numbers. And this is why the analysis use to take huge amount of time approximately 2–3 Months from the kick off date to the date where a customer can actually start the project with lots of meetings, excel sheets number crunching and negotiations back and forth between customer and the cloud providers for approving proper funding for migration projects.

Now below is my experience on how I reduced the time line to 1 month from project kick off to approval from customer side, for a 2 Petabyte data migration project to AWS S3 using Cloud Intelligence™ (DCI) and our MCP server for an existing DoiT customer.

This given customer has a Private Pricing Agreement (PPA) for S3 with AWS, so calculating the numbers using AWS calculator would have taken more time factoring in the special pricing numbers. This is how it would have worked.

Calculate Actual Cost using AWS Calculator > Export the Calculated cost as CSV file > Add a formula that will provide the correct cost based on the the PPA pricing.

And again AWS Calculator only calculates actual numbers, it does not take historic growth data into consideration, for that either we have to do data analysis on the customer historic data using our DCI Product or analyze the CUR files from last 6–12 Months.

Ok now enough talking let me wow you with one scenario:

Customer Query (May 28 2025 7:40 AM) It took customer 2 weeks to analyze and come to this number “1.6–2.5 % monthly”: We are still unsure how the change rate in our S3 storage data monthly will be impacted. Are the monthly ongoing replication costs based on new data or does it charge based on S3 object changes? Our storage increase rate has been from 1.6–2.5 % monthly. We do have a lot of clients that delete photos and videos and add new ones monthly which is not considered storage growth, but I think will be charged monthly for ongoing replication. Is there a way to run a tool and estimate what our change rate has been over the past few months?

My Question to our DoiT MCP Server Leveraging Anthropic Claude 4 that has DCI API Access to customer historic billing and usage data (May 28 2025 9:00 AM): Customer xxxxx.com is asking me “ We are still unsure how the change rate in our S3 storage data monthly will be impacted. Are the monthly ongoing replication costs based on new data or does it charge based on S3 object changes? Our storage increase rate has been from 1.6–2.5 % monthly. We do have a lot of clients that delete photos and videos and add new ones monthly which is not considered storage growth, but I think will be charged monthly for ongoing replication. Is there a way to run a tool and estimate what our change rate has been over the past few months?” Can you provide me the report based on above.

MCP Server Response (May 28 2025 9:05 AM):

Customer Response at (May 28 2025 10:15 AM):

This is great information! Who can I talk to about this today or tomorrow? I want to go back to that PPA formula and figure my final cost based on this information.

Meeting set with customer (May 29 2025) proper calculations completed using the actual PPA number. Customer green lit the project same day.

You can see the above scenario in traditional ways would have taken 1–2 weeks of number crunching and meetings. All above was completed in 24 Hrs time window. And that is how the whole project approval time line took just 1 month to get approval from customer by navigating multiple complex scenarios like the one I described above.

DoiT’s Finops tooling DCI and MCP Server is how DoiT Migration center is growing in a phenomenal way, with super happy customers. These are our live stats when I say “ super happy customers” https://www.doit.com/stats/

References:

• DoiT MCP Server: https://www.doit.com/doit-mcp-server/
• Cloud Intelligence™ API: https://developer.doit.com/
• DoiT MCP Server Github Repo: https://github.com/doitintl/doit-mcp-server