Chameseddine discusses hands-on solutions for managing state and avoiding race conditions in Azure serverless data pipelines, sharing lessons learned and design patterns from a real-world ETL challenge.

Handling Race Conditions and State in Serverless Data Pipelines on Azure

Author: Chameseddine

Recently, I faced a data engineering challenge involving nearly 2 million Parquet records that needed to be ingested, transformed, and separated into distinct entities—using only Azure Functions, Azure Data Factory (ADF), and Azure Storage.

The Core Problem

  • Requirement: Generate globally unique, sequential IDs for certain columns, under a 2-hour processing window.
  • Constraint: Need for parallel processing to meet SLAs, but parallelism risks breaking sequential ID generation (race conditions on counters).

Architecture Patterns Tested

  1. Sequential Processing with Azure Data Factory (ADF)
    • Pros: Simple and safe for state consistency
    • Cons: Failed the 2-hour limit due to processing time
  2. Parallel Processing with External Locking / e-Tags on Table Storage
    • Pros: Can enable parallelism
    • Cons: Complex implementation and persistent issues with insert consistency/race conditions
  3. Fan-Out/Fan-In Pattern with Azure Durable Functions & Durable Entities
    • Pros: Durable Entities act as stateful actors—track and update unique counters in memory across concurrent executions
    • Transformation workloads run in parallel, while ID state remains consistent
    • Result: Solved race conditions without compromising performance

Why Durable Entities?

Durable Entities in Azure Functions maintain in-memory state, letting multiple parallel transformations update unique, sequential IDs safely and efficiently. This approach removed the need for complicated locking logic or slower sequential execution.

Lessons & Trade-offs

  • Performance: Durable Entities support parallelization without race conditions
  • Simplicity: Avoids external locking mechanics
  • Scalability: Scales with workload, up to the throughput limits of Durable Functions
  • For external database sequence generation, you’d lose some of the benefits of serverless architecture and increase operational complexity

Read the full breakdown and implementation details here.

Community Question

Has anyone else used Durable Entities or a similar serverless actor pattern for ETL workloads? Do you prefer external sequences for ID generation, or have you solved race conditions a different way when forced to stay inside the Azure serverless toolset?

Thanks for reading! — Chameseddine

This post appeared first on “Microsoft Tech Community”. Read the entire article here