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Memory consumption performance issues with large syncs
Addressing architectural things that will further enhance “streaming” syncs
How do we know this is successful?
When a large instance (VF DRC on BCK) can sync with KDP, without getting OOM killed on either side
Who is this for?
Our own sanity
Our users and timely access to their facility data
Are there any assumptions or constraints?
We’re likely not going to make the sync any faster by addressing memory issues
Although, with proactive planning, we can lay out the improvements to later on address the loss of speed with more drastic restructuring of the sync process itself
We should ensure we have locking mechanisms in place to prevent concurrent syncing complications
What approaches/risks were discussed during planning?
Overall, breaking down the syncing process into ETL (extract, transform, load) procedures
Source models →Transform → Store
Store → Transform → Buffer
Buffer → Transfer → Buffer
Buffer → Transform → Store
Store → Transform → Source models
Morango doesn’t differentiate between single field updates and full record updates
Feasibility of progress tracking in queuing, serialization, dequeuing, and deserialization
How the data structure or handling will change with other planned work— possibly integrating CRDTs
Managing foreign keys and data relationships to ensure data integrity
What is out of scope?
Addressing slow queries
Directly addressing speed performance loss
Acceptance Criteria
Backwards compatibility
Improved memory performance for both Postgres and SQLite database backends
Architectural improvements that will enable us to scale it further
What problem are we solving?
How do we know this is successful?
Who is this for?
Are there any assumptions or constraints?
What approaches/risks were discussed during planning?
What is out of scope?
Acceptance Criteria
Workspace & Resources