May 2021
Intermediate to advanced
311 pages
9h 20m
English
Content preview from Design Patterns for Cloud Native Applications
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Chapter 4. Data Management Patterns
Data is the key for all applications. Even a simple echo service depends on the data in the incoming message in order to send a response. This chapter is all about data and its management in cloud native applications.
First, we’ll focus on data architecture, explaining how data is collected, processed, and stored in cloud native applications. Then, we’ll look at understanding data by categorizing it through multiple dimensions, based on how it is used in an application, its structure, and its scale. We’ll discuss possible storage and processing options and how to make the best choice given a specific type of data.
We’ll then move on to explaining various patterns related to data, focusing on centralized and decentralized data, data composition, caching, management, performance optimization, reliability, and security. The chapter also covers various technologies currently used in the industry to effectively implement these cloud native applications’ development patterns.
This knowledge of data, patterns, and technologies together will help you design cloud native applications for your specific use case and for the type of data that your applications deal with.
Data Architecture
Cloud native applications should be able to collect, store, process, and present data in a way that fulfills our use cases (Figure 4-1).
Here, data sources are cloud native applications that feed data such as user inputs and sensor readings. They sometimes feed data into ...
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.