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What is the deployment and testing process for Upsolver versions?

The continuous release cycle at Upsolver consists of constant improvements, up to twice a week, to the data ingestion mechanism and other infrastructure elements.
Below is the process prior to the deployment of each software version to customers' clusters.
Stage
Environment
Details
Requirement
Feature-specific tests
Dev / QA
Based on the requirement of each feature or bug fix, tests are done to validate its performance and stability
All tests are completed successfully
Automated QA sanity tests
QA
Common platform usage scenarios are run to ensure no functionality has been affected by the code changes
All tests are completed successfully
Manual QA interface tests
QA
Main elements of the user interface are tested to ensure usability has not been affected by the code changes
All tests are completed successfully
2 Internal dry runs
Staging
The dry run mechanism runs both the existing and new versions on a small sample data set for each cluster, to verify data is handled correctly
Data processed and written by both versions is consistent and without differences
Customer clusters dry run
Production
The dry run mechanism runs both the existing and new versions on a small sample data set for each cluster, to verify data is handled correctly
Data processed and written by both versions is consistent and without differences
Change logs containing the details of each release:
for app.upsolver.com - here: https://docs.upsolver.com/upsolver-1/change-log​
for sqlake.upsolver.com - here: https://docs.upsolver.com/sqlake/change-log​

Infrastructure

What is a dry-run cluster?

Last modified 6mo ago

Stage	Environment	Details	Requirement
Feature-specific tests	Dev / QA	Based on the requirement of each feature or bug fix, tests are done to validate its performance and stability	All tests are completed successfully
Automated QA sanity tests	QA	Common platform usage scenarios are run to ensure no functionality has been affected by the code changes	All tests are completed successfully
Manual QA interface tests	QA	Main elements of the user interface are tested to ensure usability has not been affected by the code changes	All tests are completed successfully
2 Internal dry runs	Staging	The dry run mechanism runs both the existing and new versions on a small sample data set for each cluster, to verify data is handled correctly	Data processed and written by both versions is consistent and without differences
Customer clusters dry run	Production	The dry run mechanism runs both the existing and new versions on a small sample data set for each cluster, to verify data is handled correctly	Data processed and written by both versions is consistent and without differences