We will be following through the process summarized below to import environment data into MPA:
You will be greeted with following screen. On the left-hand navigation panel is your existing Portfolios, on the right is brief summary of key features of MPA and recent updates.
Click Get started to start creating a portfolio or view an existing portfolio
Test (or non-customer)data only for Data classification
For real customer data, please select Customer data and fill in customer’s
For this lab, we will be downloading CSV and excel files locally and upoload to the MPA.
You can also import partially through CSV/excel and fill the rest through AWS ADS or vice versa. Note that importing duplicate data from ADS will overwrite the existing data in MPA and vice versa. A Quick Guide on how to import from ADS.
servers_table.xlsxand inspect it. The file contains CMDB data on servers we would like to migrate.
Upload local file
servers_table.xlsxfrom file directory
These data template don’t enforce a standard header format. You can configure Header mapping using the upload navigator. This semi-automatic workflow will help reduce the effort required in normalizing the data.
The upload wizard will give recommended header mapping, you can also change
File header to desired mapping. The sample values are shown when you select a file header from the drop down. Leave everything as default.
Review the optional header mapping. Leave everything as default.
Resolve Duplicate in the file: note that the
OS Version is highlighted in red, select the first option,
OS Version = 16.
Preview uploaded data
Navigate to Portfolio data → Assets. Go to the
Servers tab, Verify that server data is imported.
You can ignore the following banner for now. We will explore Data Validation Rules feature further in next module - Data Verification.
Repeat Step 2-3 for the rest of the files following the mapping below:
|Server to application||servertoapp_table.xlsx|
|Database to application||databasetoapp_table.csv|
You can also combine all of these into a single file on different sheets. MPA will automatically read in the sheets. Refer to sample template file provided in upload page.
When doing your own upload, watch for these common mistakes: • Incomplete data • Unreal data (RAM < 1 KB, RAM > 20000GB, CPU > 5000) • Wrong unit of storage/memory (GB,MB,KB) • Wrong unit of utilization attributes • Wrong matched attributes • Data redundancy, and • Wrong Storage IOPS
MPA uses assumptions when some data is not available. These are the important metrics that have major significance for cost estimates. Customers must supply these attributes, and check the data for outliers or unreal values.