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Jira tickettickets: 

Background Jiras:

Background

See Use Case 1 in Service to migrate content at the S3/Storage Level: Use Cases for use case notes.

In Synapse, the top 10 projects by file size account for about 3/4 of our total S3 bucket. These projects can be very expensive, so there is a need to determine the costs of projects. By moving this content into new buckets, we can leverage AWS Cost Allocation Tags to facet S3 costs by bucket (and thus, groups of content).

API

We can create a new Cost Allocation Using file metadata, we can determine approximate size very easily. Egress is more difficult to determine, but per the analysis in PLFM-5009, storage counts for approximately 80% of our bill. There is not currently a need to be incredibly precise/accurate, so we may simply ignore egress for now. At the moment, cost of egress can be assumed to be distributed proportionally to costs of storage.

API

Create a new Storage Report asynchronous service in Synapse that can be used by members of a "Synapse Cost Allocation Reports Team", a bootstrapped team with users that have the authority to manage create these cost allocationsreports.

The members A member of the Cost Allocation Team can create new cost allocations with a descriptive name (e.g. ampad, nih-r01-12345) that matches how costs should be broken down in Synapse. When a new cost allocation being created, a new bucket is provisioned with an AWS Cost Allocation Tag.After a cost allocation is created, a project can be assigned to it. Cost allocations can have many projects, but a project can be assigned to at most one cost allocation. When a project is assigned to a cost allocation, the underlying files associated with that project (that is, the file handles pointed to by all versions of all file entities in a project, and their previews) will eventually be moved to the new S3 bucket, and the file handles will be updated. After all files have been moved, the AWS bill and cost explorer tools can facet costs by the cost allocations, as desired.Reports team can make an asynchronous query to retrieve a CSV report about the usage of the Synapse S3 bucket with project-level resolution across all projects. 

Sample Report

Type: ALL_PROJECTS

Implementation Details

Workflow

This gives a general overview of the process required to apply a cost allocation to a project.

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Detailed Requirements 

• Creation of a new bootstrapped "Cost Allocation Reports Team" to have access to these APIs.
• Retrieval of file handle metadata, particularly project association and file size 
  • File Replication Table
    • Columns from File Table: ID, ETAG, PREVIEW_ID, CREATED_ON, CREATED_BY, METADATA_TYPE, CONTENT_TYPE, CONTENT_SIZE, CONTENT_MD5, BUCKET_NAME, NAME, KEY, STORAGE_LOCATION_ID, ENDPOINT
    • Primary key ID
  • Creation of this table allows retrieval of file metadata by joining it with the entity replication table. This allows us to find all of the file handles and metadata for a particular project in one database call. Without this table, we must query the tables database to find the entities in a project, and then separately query the repo database to retrieve the metadata of those files.

  • Jira Legacy
    server System JIRA columns key,summary,type,created,updated,due,assignee,reporter,priority,status,resolution serverId ba6fb084-9827-3160-8067-8ac7470f78b2 key PLFM-4148

     is another issue that may benefit from this
• Enumeration of cost allocations
  • Cost allocation table: ID, NAME, BUCKET, CREATED_BY, CREATED_ON
• Associate cost allocations and projects
  • Cost Allocation association table
    • Columns: COST_ALLOCATION_ID, PROJECT_ID
    • Primary key: PROJECT_ID (a project may have no more than one cost allocation)
• Overriding uploads to default Synapse storage to redirect to the cost allocation bucket.
• An eventually consistent algorithm to move files to a new bucket, and then modifying the file handle to reflect the move
  
  • Worker that is not a part of the stack scans file replication table for files that are in the project with the cost allocation AND are in Synapse storage AND are not in the correct cost allocation bucket
    • This worker creates bundles of files that should be updated and sends these bundles to another asynchronous worker
    • This cannot be part of the stack because it is possible for file handles on different stacks to point to the same underlying file (e.g. prod and staging). If a cost allocation were created on staging, then it would break the files in prod.
  • Asynchronous worker finds each file in the bundle in the files table and verifies that it is not in the correct cost allocation bucket
    • The file is copied to the new S3 bucket and updates the file handle
    • The old underlying file is stored in an Amazon Glacier instance for 12 months where the file is stored in a folder /key/filename. These files can be restored manually if necessary, and can be found using the updated file handle, which will have the same key and filename.
    • The actual copying may be fairly trivial with AWS Batch Operations for S3 Buckets and Copy Objects Between S3 Buckets With Lambda 
• Depending on the performance/reliability of the operation, a way to report progress of the job to ensure it has been completed.
  • This may be as simple as noting CloudWatch metrics like the decreasing size of a prod bucket

Concerns

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Concerns

• This method will not accurately capture egress. It simply calculates proportions of cost based on storage.