Cloud Native

Chapter 4. Working with Data

Cloud computing has made a big impact on how we build and operate software today, including how we work with the data. The cost of storing data has significantly decreased, making it cheaper and more feasible for companies to keep vastly larger amounts of data. The operational overhead of database systems is considerably less with the advent of managed and serverless data storage services. This has made it easier to spread data across different data storage types, placing data into the systems better suited to manage the classification of data stored. A trend in microservices architectures encourages the decentralization of data, spreading the data for an application across multiple services, each with its own datastores. It’s also common that data is replicated and partitioned in order to scale a system. Figure 4-1 shows how a typical architecture will consist of multiple data storage systems with data spread across them. It’s not uncommon that data in one datastore is a copy derived from data in another store, or has some other relationship to data in another store.

Cloud native applications take advantage of managed and serverless data storage and processing services. All of the major public cloud providers offer a number of different managed services to store, process, and analyze data. In addition to cloud provider–managed database offerings, some companies provide managed databases on the cloud provider of your choice. MongoDB, for example, offers ...