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BPM,FAQ,Troubleshooting,Common Questions BPM,FAQ,high volume,scalability,performance,millions of transactions How does BPM handle high-volume transactional processes?

How does BPM handle high-volume transactional processes?

How does BPM handle high-volume transactional processes?

Nodinite BPM scales to millions of transactions with efficient log storage, indexing, and search. Configure log retention policies, archive historical data, and use Log Views with filters to manage high-volume processes. Monitor service performance and queue depth directly in BPM to proactively identify bottlenecks.

Scalability Features

  • Efficient log storage - Compressed storage with configurable retention
  • Fast indexing - Optimized for high-throughput event ingestion
  • Quick search - Sub-second search across millions of events using Search Fields
  • Archival policies - Move old data to cold storage, maintain query performance
  • Partitioned storage - Distribute load across multiple databases
  • Caching layers - Frequently-accessed data cached for instant access

Performance Characteristics

  • Event ingestion: 10,000+ events/second per logging service
  • Search response: < 1 second for filtered queries across millions of events
  • BPM rendering: Real-time status updates with sub-second latency
  • Concurrent users: Hundreds of users viewing BPMs simultaneously
  • Data retention: Years of historical data with consistent performance

High-Volume Best Practices

1. Configure Retention Policies

  • Keep 90 days hot storage for active troubleshooting
  • Archive 1-7 years to cold storage for compliance
  • Purge older data beyond regulatory requirements

2. Use Targeted Log Views

  • Filter by date range, domain, or message type
  • Avoid "show all" queries on multi-million record datasets
  • Use Search Field Links for precise correlation

3. Monitor Queue Depth

  • Track service processing rates in BPM
  • Set alerts for queue backlog thresholds
  • Use Remote Actions to scale out when needed

4. Optimize Search Field Expressions

  • Extract only necessary business identifiers
  • Avoid overly complex regex patterns
  • Index frequently-queried fields

Next Step

Explore more in the Troubleshooting Overview or dive into Business Process Model (BPM) to get started.