Operations | Monitoring | ITSM | DevOps | Cloud

Happy new year! 🎉 It's 2022, and even though not much has changed in the past year, I'm happy to know that Monitive is running smoothly and brings value to our customers. For the first quarter of 2022 our main focus is fixing issues, either bugs we know of or small tweaks that make everyone's lives better. There are some feature requests in our backlog that we're jumping on starting February, and also a few surprise updates that are in the works and will be launched when they're ready.

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.

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.

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.

Earlier this year we launched Datadog Apps, which seamlessly integrate functionality from third-party tools into Datadog’s centralized monitoring platform. This project has enabled us to collaborate with some of our partners, such as PagerDuty and LaunchDarkly, to extend the Datadog UI and provide our customers with new solutions for incident management, feature flag optimization, and more.

Supporting large applications with enormous crash volumes can be a real pain in the hindquarters. It is extraordinarily difficult for organizations to optimally dispatch engineering resources without excellent data and proper tooling. At BugSplat, we recently upgraded the tooling we provide to developers so that they can group related crashes and better target their support efforts, deliver more stable applications, and deliver more value to their customers.

A key aspect of my job is to speak to End-User Computing (EUC) professionals on a regular basis—analysts, customers, partners, etc.—to better understand their challenges and objectives. Unsurprisingly, one topic has been coming up a lot lately: Windows 11. Surprisingly, nobody wants to actually deploy it. Or, at least, not right now. Why? After countless discussions, 4 reasons were made clear for their reluctance with Windows 11: These are all valid points.

Unless you are one of the 1% of enterprises that have zero workloads running in the publice cloud, you need a cloud cost optimization tool. Yes, you do. And if you have workloads running in multiple public clouds—which somewhere in the neighborhood of 85% of enterprises do—you really need a cloud cost optimization tool. If I’m preaching to the choir, feel free to skip to the end of this article where you’ll find a link to try Virtana Optimize for free.

The term Site Reliability Engineer (SRE) first appeared in Google in the early 2000s. In Google’s 2016 SRE Book, Benjamin Treynor Sloss wrote that, generally speaking, “an SRE team is responsible for the availability, latency, performance, efficiency, change management, monitoring, emergency response, and capacity planning of their service(s).” This means that the SRE teams at Google decide how a system should run in production as well as how to make it run that way.