Share your ALM best practices — March 2025 Community Challenge

Few Best Practices:

• "Keep your Dev model clean! Regular metadata cleanup and module optimization will make deployments smoother." (Emphasizes model health)
• "Always validate your deployment packages before pushing to Production. Prevents unexpected changes." (Highlights pre-deployment checks)
• "Use descriptive names for revisions and deployment tags. Makes tracking changes much easier." (Focuses on clear documentation)
• "Document your ALM process! A clear guide ensures everyone follows the same steps." (Stresses process standardization)
• "Leverage line item subsets for ALM. This helps manage changes to specific line items efficiently." (Highlights a specific technical tip)
• "Always use a development workspace, a test workspace, and a production workspace." (reinforces a three workspace strategy)

Deployment Specific Tips:

• "When deploying, carefully review the impact analysis. It shows what's changing and helps identify potential conflicts." (Emphasizes impact analysis)
• "For large deployments, consider breaking them down into smaller, manageable packages. Reduces risk and troubleshooting time." (Suggests a strategy for large changes)
• "After a deployment, always perform thorough testing in the target environment to ensure everything works as expected." (Stresses post-deployment validation)
• "Use selective import during deployment to only update changed items. This speeds up the process and reduces errors." (Highlights a performance optimization)
• "Be mindful of production data during deployments. Avoid overwriting or corrupting it." (Highlights data integrity)

Revision Tag and Branching Tips:

• "Use clear and consistent revision tag naming conventions. Include date, feature, or bug fix details." (Focuses on clear version control)
• "When branching, clearly define the purpose of each branch. Avoid creating unnecessary branches." (Emphasizes efficient branch management)
• "Merge branches regularly to keep them up-to-date with the main development line." (Highlights the importance of regular merges)
• "Use tags to mark significant milestones or releases. This makes it easy to revert to a previous version if needed." (Emphasizes the use of tags for tracking milestones)

Troubleshooting Tips:

• "If a deployment fails, carefully review the error logs. They often provide clues about the cause." (Highlights error log usage)
• "Use the compare feature to identify differences between revisions or deployment packages." (Suggests a tool for comparison)
• "If you're unsure about a change, test it in a non-production environment first." (Reinforces testing in non-production)

ALM best practice checklist

1.Ideally Have dev and prod models in separate environments (ALM allows segregation of duties so there is complete possibility of different users in different workspaces as per role and requirement)
2. In case dev and prod models are in same workspace , ensure no production user is added or provided access to dev model since any structural change can be made ( ensured using security - roles, selective access)
3.Dev model has to be as lean & small as possible inclined towards Create Model from Revision. Having Production Data in your Dev model is not recommended as you might expose your live data to people.
4. Use revision tags ( capture the model structure at the time - Note history ID) and name RT properly so that other developers understand and relevant RT can be synced to production
5. Ensure any data which is to be updated in production model(live to business users ) is marked as production data and before that it is necessary to ensure that list to be marked as prod is not referenced as item format(item reference protection)
6. while doing compare and sync to sync RT in prod model , do get update as to which RT to push to production ( in case of multiple RT after last sync)
7. Before syncing any functionality which involves change in production data(update in formula or module data) , it is advisable to keep last production data in hand just before sync since data loss may be caused.
8. In case of any import needs to be updated in back end in production model, mark import as production import /source as production data
9.Enable deployed mode in test and production models. Deployed mode locks down your production models so that production users, including Workspace Administrators, can only modify production data, not structural information and deployed mode must not be disabled for production models else compatibility (sync with dev model) can be broken.

@Vivekagarwal007 I like your idea of using History ID.

I myself use just a regular consecutive numbering system in RT Title. And in the description, I would write any notes I feel are related. For example, the name or code of the change request from our tracking system.