chapter ten

10 Delving into database as service

 

This chapter covers

  • Mastering MongoDB Atlas Database as a Service
  • Differentiating M0, M2, and M5 Atlas Clusters
  • Comprehending dedicated +M10 Atlas Clusters
  • Scaling Atlas Cluster and Storage with Auto Scaling
  • Using Atlas Serverless Clusters
  • Going Multi Cloud with Atlas Multi Cloud and Regions Clusters

In the first part of the book, I intentionally avoided MongoDB server administration issues to focus on Atlas, a managed DBaaS. Atlas takes care of most MongoDB administrative tasks, simplifying database operations and allowing developers to concentrate on application development. It automates critical functions such as deployment, scaling, upgrades, and backups ensuring optimal performance and security. Its features include real-time analytics, comprehensive monitoring, and performance optimization.

Atlas offers various cluster options: M0, M2, and M5 for beginners, M10 and M20 for development, and M30 and higher for production, all with support for replica sets and sharded deployments. It allows automatic adjustments of cluster tiers and storage and provides serverless instances that scale with your application's workload.

10.1 Shared M0, M2, and M5 clusters

10.2 Dedicated Clusters

10.2.1 Atlas Clusters for Low-Traffic Applications

10.2.2 Atlas Clusters for High-traffic Applications

10.2.3 Auto Scaling Clusters and Storage

10.2.4 Customizing Atlas Cluster Storage

10.3 Serverless instances

10.4 Global clusters

10.5 Going Multi-Cloud with Workload Isolation

10.5.1 Adding Electable Nodes for High Availability

10.5.2 Adding read-only nodes for local reads

10.5.3 Using analytics nodes for workload isolation

10.6 Using Predefined Replica Set Tags for Querying

10.6.1 Routing queries to Analytics nodes

10.6.2 Isolating normal application secondary reads from analytics nodes

10.6.3 Routing Local Reads for Geographically Distributed Applications

10.7 Understanding Atlas custom write concern

10.8 Summary