Monitoring and Scaling

Abstract

In the previous chapters, we covered many important topics related to the initial stages of adopting Azure SQL Hyperscale. Up until now, this book has focused on the design and deployment of a typical highly available Hyperscale environment. However, we now need to start looking at how we continue to effectively operate the Hyperscale environment post-deployment. As your usage of a Hyperscale database grows and changes, being able to proactively prevent issues and reactively diagnose problems will become increasingly important. In this chapter, we will cover the basics of monitoring the performance and health of the Hyperscale database as well as examining how Hyperscale databasesHyperscale databases can be manually or automatically scaled. Over time, the usage patterns and needs of the workloads using a Hyperscale database are likely to change, so understanding how we can scale to support these workloads will be important.