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Version: 15.2.0

Best Practices

This section provides best practices and operational strategies for effectively designing and managing Fast Data v2 pipelines.

How to navigate this section​

The Fast Data v2 Best Practices are organized into three main areas to guide you through different stages of your data pipeline lifecycle:

Pipeline Development & Testing​

Start here during the development phase of your Fast Data pipelines. Learn how to:

  • Visualize pipeline architecture as you build it
  • Simulate performance scenarios with pause/resume controls
  • Test system behavior under different load patterns before promoting to production

Initial Load & Full Refresh Operations​

Master the operational strategies for managing data re-ingestion in production. Understand:

  • How to maintain Near Real-Time operational continuity during complex pipeline changes
  • The Full Refresh architectural pattern with NRT and Backup layers
  • Controlled initialization and iterative pipeline activation
  • Consumer lag monitoring and the Leaf-to-Head strategy for aggregations

System Optimization & Reliability​

Ensure your Fast Data infrastructure runs efficiently and reliably. Discover:

  • Strategic resource allocation through granular runtime controls
  • Performance optimization techniques
  • Enhanced system reliability and fault isolation
  • Maintenance strategies and graceful degradation patterns

Key Concepts​

Runtime Control: The ability to pause and resume message consumption at any pipeline stage, enabling precise orchestration of data flows without stopping the entire pipeline.

Near Real-Time (NRT) Continuity: Maintaining continuous processing of new incoming data while performing full refreshes or data reprocessing operations on historical data.

Backup Layer: A dedicated flow that maintains a controlled backup of your messages, enabling full refresh operations without requiring infinite topic retention or direct access to source databases.