Hello Fellow Workato Enthusiasts,
As our Workato projects grow more complex, we have found ourselves spending more time on pre-deployment checks, manually comparing recipe changes, and making mistakes while handling numerous lookup tables. To address these challenges, I developed a validation tool that's been a real time-saver.
This tool fetches recipe metadata from both dev and prod environments, compares them, and provides the differences.
Key Features of this Validation Tool:
- Compare entire projects, recipes, lookup tables etc. in seconds
- Initiate validations directly from Slack
- Receive detailed, step-by-step comparisons via email
It's been incredibly helpful in ensuring our production deployments are accurate and complete.
Have you faced similar challenges with large Workato projects? How do you manage your deployment process?
Yes @jiyu269 ,
AI is the solution to most things :). If we integrate Workato code with AI, it opens up even more possibilities. I created a Slack bot that, after receiving project or recipe details from Slack, generates beautifully formatted technical design documentation for Confluence. It is saving many hours for my team.
We also developed another solution to generate test cases. By providing a recipe and a bit of context to the Slack bot, it automatically creates a spreadsheet with test cases.
This solution is perfect for those who don't have access to AI and want minimal manual intervention.
Like below sheet was create by that slack bot, i had to just fill the job id, output and status column
