Mastering Performance: Key Patterns and Anti-Patterns in Microsoft Dynamics 365 Finance and Supply Chain Management

Overview: Common Patterns vs. Anti-Patterns 

In this blog, we will provide a brief guide to common positive and anti-performance patterns in Microsoft Dynamics 365 Finance and Supply Chain Management. Understanding these patterns is key to ensure efficient data management and maintaining overall system health.  

Before diving into detailed strategies, here is a quick reference of key performance practices: 

Positive patterns in data management and processing can enhance system performance and efficiency.  

The Optimized Data Management Framework (DMF) involves the effective use of delta loading and incremental pushes, along with enabling set-based processing for mass imports. Efficient batch processing is achieved through comprehensive 24-hour timetables for batch jobs, grouping batch operations, and utilizing Active Periods. 

• Optimized Query and Index Management is also crucial, replacing row-by-row operations with set-based queries and implementing proper indexing (including clustered indexing) 
• Effective data caching is another key aspect, with correctly configured caching properties to minimize database round trips. Smart Code Practices involve using generic methods wisely and consolidating query operations. 
• Scheduled cleanups and maintenance are essential, regularly purging batch history, staging tables, and other transient data. Staying current with updates is also important, with regular application of critical hotfixes and system updates. 
• Advanced tuning with plan guides involves strategic use of plan guides to enforce consistent query plans. 

Anti-patterns, on the other hand, are bad practices or mistakes that can lead to inefficient or unreliable data model. 

• Misconfigured DMF settings is one anti-pattern and occurs when you fail to enable incremental pushes, delta loading, or set-based processing. Inefficient bulk operations can also hinder your data management as it rely on “all data” processing that handles records one by one. 
• Neglecting batch scheduling is another issue, which overlaps batch and integration processes without a structured timetable. Row-by-row data handling exacerbates the problem, causing excessive database calls due to record-by-record processing. 
• Improper indexing and caching also contribute to inefficiencies with missing or poorly maintained indexing and misconfigured caching properties. Overuse or misuse of OData interfaces could also overload the system, particularly when utilized for high-data volume integrations.  
• Failing to schedule regular cleanup routines for batch history and staging tables lead to inadequate cleanup and maintenance. Lastly, providing reactive updates rather than proactive updates lead you to run outdated code bases without applying critical hotfixes or updates. 

In-depth analysis 

By recognizing and implementing positive performance practices, you can enhance the functionality and responsiveness of your Dynamics 365. Conversely, being aware of anti-performance patterns also helps in identifying and mitigating potential issues that could degrade performance. 

1. Optimizing DMF 
   
   Best practices: 
   • Efficient Imports and Exports: Use delta loading or incremental pushes after a full data push. This minimizes the amount of data processed during each cycle. 
   • Set-Based Processing: Configure your entities to support set-based operations, enabling parallel processing for large-scale imports. 
   • Configuration Tuning: Disable unnecessary validations and configuration keys to reduce processing overhead. 
   • Number Sequence Pre-Allocation: For non-continuous sequences, pre-allocate numbers to reduce frequent database lookups and enhance caching efficiency. 
   • Staging Table Maintenance: Regularly clean up staging tables to prevent excessive growth, which can slow down the system. 
     
     One pitfall to avoid when optimizing DMF is misconfigurations in its settings, which prevents the system from reaching optimal performance thresholds and lead to under-tuned workloads. 
     
2. Balancing Bulk Operations and Data Integrity 
   
   Best practices: 
   • All Data vs. DMF: Handling data row by row is suitable only for small, real-time scenarios (1,000–5,000 lines per hour). For high-volume operations (up to 300,000 rows per hour), DMF should be used to leverage parallelism. 
   • Alternative Reporting Solutions: For heavy Microsoft Power BI integrations, use the Microsoft Fabric solution instead of the transactional database to maintain responsiveness. 
     
3. Effective Batch Processing Strategies 
   
   Best practices: 
   • 24-Hour Timetable: Develop a daily schedule for batch jobs and integration processes. Spreading workloads throughout the day prevents performance bottlenecks. 
   • Batch Groups and Active Periods: Organize batch operations into groups with designated batch servers. Use Active Periods to schedule high-frequency jobs during appropriate times. 
   • Thread Tuning: Since AOS servers serve both batch and interactive workloads, test and adjust the maximum batch threads setting to ensure optimal performance. 
     
4. Query Optimization and Index Management 
   
   Best practices: 
   • Set-Based Operations: Replace record-by-record updates with set-based operations. For example, updating 1,000 rows in one go can drastically reduce the number of database calls. 
   • Proper Indexing: Implement appropriate indexes—including clustered indexes—to improve query performance. This is akin to organizing a library; proper indexes help you locate information quickly. 
   • Data Caching: Ensure that caching is configured correctly by setting the necessary table properties. This minimizes unnecessary database round trips and boosts performance. 
     
5. Code Optimization and Scheduled Cleanups 
   
   Best practices: 
   • Using Generic Methods Wisely: Avoid redundant find operations by consolidating similar queries. This reduces overhead and improves performance. 
   • Scheduled Cleanup Routines: Regularly purge batch history, notification data, and staging tables. Use tools like the Optimization Advisor to schedule cleanups during off-peak hours. 
   • Aggregated Measurements in Reporting: Divide aggregate measurements into categories (e.g., hourly vs. daily refreshes) so that only relevant data is processed. 
     
6. Advanced Tuning with Plan Guides
   
   Best practices: 
   • Strategic Use of Plan Guides: Before creating plan guides, perform a thorough analysis of your code and query plans. Use plan guides only when necessary to resolve issues like parameter sniffing. 
   • Consistency Across Environments: Ensure that any plan guides created in production are also implemented in testing environments. This consistency is crucial for reliable performance validation. 
     
7. Monitoring and Ongoing Maintenance 
   
   Best practices: 
   • Hotfixes and System Updates: Regularly apply critical updates and hotfixes to keep your system running on the latest, most efficient code base. 
   • Index Maintenance: Use tools like SQL Insights in LCS to monitor index fragmentation and schedule maintenance during off-peak hours. 
   • Resource Management: Leverage resource governors to control backend resource consumption, ensuring that high-demand scenarios do not compromise system responsiveness. 
   • Performance Testing: Regular testing in pre-production environments using trace parsers and benchmarks can help detect and mitigate performance issues early. 

Conclusion 

Optimizing performance in Microsoft Dynamics 365 Finance and SCM requires a strategic blend of proactive measures and vigilant maintenance. By understanding and applying the positive patterns while avoiding common anti-patterns, you can significantly enhance your system’s efficiency and reliability. 
 
Review your current Dynamics 365 setup with Hitachi Solutions today. Implement the best practices, schedule regular performance assessments, and work closely with your technical team to fine-tune your environment. For personalized support or further information, contact us or email us at [email protected].