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Python Architecture Patterns

Python Architecture Patterns

By : Jaime Buelta
4.6 (22)
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Python Architecture Patterns

Python Architecture Patterns

4.6 (22)
By: Jaime Buelta

Overview of this book

Developing large-scale systems that continuously grow in scale and complexity requires a thorough understanding of how software projects should be implemented. Software developers, architects, and technical management teams rely on high-level software design patterns such as microservices architecture, event-driven architecture, and the strategic patterns prescribed by domain-driven design (DDD) to make their work easier. This book covers these proven architecture design patterns with a forward-looking approach to help Python developers manage application complexity—and get the most value out of their test suites. Starting with the initial stages of design, you will learn about the main blocks and mental flow to use at the start of a project. The book covers various architectural patterns like microservices, web services, and event-driven structures and how to choose the one best suited to your project. Establishing a foundation of required concepts, you will progress into development, debugging, and testing to produce high-quality code that is ready for deployment. You will learn about ongoing operations on how to continue the task after the system is deployed to end users, as the software development lifecycle is never finished. By the end of this Python book, you will have developed "architectural thinking": a different way of approaching software design, including making changes to ongoing systems.
Table of Contents (23 chapters)
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2
Part I: Design
6
Part II: Architectural Patterns
12
Part III: Implementation
15
Part IV: Ongoing operations
21
Other Books You May Enjoy
22
Index

Proactively working with metrics

As we've seen, metrics show an aggregated point of view for the status of the whole cluster. They allow you to detect trending problems, but it's difficult to pinpoint a single spurious error.

This shouldn't stop us from considering them as a critical tool for successful monitoring because they can tell whether the whole system is healthy. In some companies, the most critical metrics are on permanent display on screens so the operations team can see them and react quickly to any sudden problem.

Finding the proper balance of what metrics are the key ones for a service is not as straightforward as it seems, and it will require time and experience, perhaps even trial and error.

There are, though, four metrics for online services that are considered always important. They are:

  • Latency: How many milliseconds it takes for the system to respond to a request. Depending on the service, sometimes seconds can be used instead...

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