{"id":4127,"date":"2022-07-12T15:45:20","date_gmt":"2022-07-12T19:45:20","guid":{"rendered":"https:\/\/solutionsreview.com\/data-management\/?p=4127"},"modified":"2022-07-15T11:39:32","modified_gmt":"2022-07-15T15:39:32","slug":"demystifying-cloud-native-data-management-layers-of-operation","status":"publish","type":"post","link":"https:\/\/solutionsreview.com\/data-management\/demystifying-cloud-native-data-management-layers-of-operation\/","title":{"rendered":"Demystifying Cloud-Native Data Management: Layers of Operation"},"content":{"rendered":"

\"Demystifying<\/p>\n

This is part of Solutions Review\u2019s Premium Content Series, a collection of contributed columns written by industry experts in maturing software categories. In this submission, Kasten by Veeam<\/a> Gaurav Rishi highlights the four key layers of cloud-native data management and layers of operation.
\n<\/em><\/strong><\/p>\n

\"SRAs containerized applications<\/a><\/strong><\/span> go through an accelerated pace of adoption, Day 2 services have become a here and now problem. These Day 2 services<\/a> include data management functions<\/a><\/strong><\/span> such as backup and disaster recovery<\/a><\/strong><\/span> along with application mobility. In this new world of containerized cloud-native applications, microservices use multiple data services (MongoDB<\/a>, Redis<\/a>, Kafka, etc.) and storage technologies<\/a><\/strong><\/span> to store state and are typically deployed in multiple locations (regions, clouds, on-premises).<\/p>\n

In this environment, where legacy infrastructure or hypervisor-based solutions don\u2019t work<\/a>, what are the right constructs for designing and implementing these data management functions for cloud-native applications? How should you reason about the various data management options<\/a><\/strong><\/span> provided by storage vendors<\/a><\/strong><\/span>, data services vendors, and cloud vendors to decide the right approach for your environment and needs? This piece dives under the covers and addresses the pros and cons of various data management approaches across several attributes including consistency, storage requirements, and performance.<\/p>\n

Defining a Vocabulary To start, we\u2019ll deconstruct and simplify a stack to show where the data may reside in a cloud-native application<\/a>.<\/p>\n

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\"Download<\/a><\/div>\n\t\t<\/div><\/div>\n

\"Kasten<\/p>\n

When thinking of data management, we could be operating on one (or more!) of the layers shown in the figure above. Let\u2019s enumerate these layers:<\/p>\n

1. Physical Storage<\/strong><\/h3>\n

\"Kasten<\/p>\n

This layer includes various storage hardware options that can store state in non-volatile memory with a choice of physical media ranging from NVMe and SSD devices to spinning disks and even tape. They come in different form factors including arrays and stand-alone rack servers.<\/p>\n

Physical storage could be located:<\/p>\n