Operations | Monitoring | ITSM | DevOps | Cloud

Microsoft Azure SQL Database is a platform-as-a-service (PaaS) database offering for modern cloud applications. It’s a fully managed service that runs on the latest version of the SQL Server database engine, enabling you to create highly available and performant database instances without needing to maintain hardware upgrades, patches, or backups.

In Part 1 of this series, we discussed key metrics for monitoring Microsoft Azure SQL databases. We also looked at how your database resource and audit logs complement metrics to provide more insight into database performance, activity, and security. In this post, we’ll show you how to collect metrics and logs from your database instances and monitor them with Azure’s monitoring and reporting tools.

In Part 2 of this series, we showed you how to monitor Azure SQL Database metrics and logs using the Azure platform. In this post, we will look at how you can use Datadog to monitor your Azure SQL databases alongside other technologies in your infrastructure. Datadog provides turn-key integrations for Azure along with more than 500 other technologies, enabling you to track long-term performance trends across all systems in your infrastructure, not just your SQL databases.

The Internet of Things (IoT) market is evolving at a rapid pace and while some of the early predictions for tens of billions of connected devices by 2022 have proved to be wide of the mark, the use cases are so varied that explosive adoption is likely. However, the encroachment of IoT into all aspects of our personal and business lives brings with it plenty of concerns, from security and data ownership, to business models that acknowledge and enable the global nature of connected devices.

gRPC is a remote procedure call framework that has been widely adopted among cloud native applications. It is an attractive choice for engineers needing more capabilities than what REST APIs provide. However, observability and testing tools for gRPC are few and far between. Because of this, triaging or understanding application behavior is potentially time-consuming and overly burdensome.