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Python Architecture Patterns

You're reading from   Python Architecture Patterns Master API design, event-driven structures, and package management in Python

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Product type Paperback
Published in Jan 2022
Publisher Packt
ISBN-13 9781801819992
Length 594 pages
Edition 1st Edition
Languages
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Author (1):
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Jaime Buelta Jaime Buelta
Author Profile Icon Jaime Buelta
Jaime Buelta
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Table of Contents (23) Chapters Close

Preface 1. Introduction to Software Architecture 2. Part I: Design FREE CHAPTER
3. API Design 4. Data Modeling 5. The Data Layer 6. Part II: Architectural Patterns
7. The Twelve-Factor App Methodology 8. Web Server Structures 9. Event-Driven Structures 10. Advanced Event-Driven Structures 11. Microservices vs Monolith 12. Part III: Implementation
13. Testing and TDD 14. Package Management 15. Part IV: Ongoing operations
16. Logging 17. Metrics 18. Profiling 19. Debugging 20. Ongoing Architecture 21. Other Books You May Enjoy
22. Index

Queue effects

An important element of asynchronous tasks is the effect that introducing a queue may have. As we've seen, the background tasks are slow, meaning that any worker running them will be busy for some time.

Meanwhile, more tasks can be introduced, which may mean that the queue starts building up.

Figure 7.4: Single queue

On the one hand, this can be a capacity problem. If the number of workers is not sufficient to handle the average number of tasks introduced in the queue, the queue will build up until it reaches its limit, and new tasks will be rejected.

But typically, the load doesn't work like a constant influx of tasks. Instead, there are times when there are no tasks to execute, and other times when there's a sudden spike in the number of tasks to be executed, filling the queue. Also, there's a need to calculate the right number of workers to keep running to be sure that the waiting period for those spikes, where a task gets...

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