For me, the best feature is the log analysis with Azure Monitor's Log Analytics. Without being able to analyze the logs of all the activities that affect the performance of a machine, your monitoring effectiveness will be severely limited.
Among the valuable features of this solution, Application Insights stands out as one of the most significant. It provides insights into application performance and helps identify issues and bottlenecks.
Senior System Administrator at BCBS of Kansas City
Aug 23, 2020
Azure Monitor is really just a source for Dynatrace. It's just collecting data and monitoring the environment and the infrastructure. It is fairly good at that.
Although it's not always the case, the price can sometimes get expensive. This depends on a number of factors, such as how many services you are trying to integrate with Azure Monitor and how much storage they're consuming each month (for example, how large are the log files?).
In terms of pricing, Azure Monitor's billing based on data size can sometimes lead to increased costs, especially when developers need to purge data frequently.
While there are mechanisms in place to track and manage this, there is room for improvement in terms of optimizing data pausing and related processes.
Enhancements in this area could help mitigate potential billing concerns and provide a more seamless experience for users.
Head Cloud Operations at a computer software company with 51-200 employees
Feb 13, 2023
The query builder could be better. In comparison to other monitoring tools, in order to use Azure Monitor, your engineers need to have KQL experience. If they don't, it's not intuitive as a system.
Enhancing and reaching a level of detail that facilitates pinpointing and addressing issues at such a refined level within the application and database components would be helpful.
Senior System Administrator at BCBS of Kansas City
Aug 23, 2020
There are a lot of things that take more time to do, such as charting, alerting, and correlation of data, and things like that. Azure Monitor doesn't tell you why something happened. It just tells you that it happened.
It should also have some type of AI. Environments and applications are becoming more and more complex every day with hundreds or thousands of microservices. Therefore, having to do a lot of the stuff manually takes a lot of time, and on top of that, troubleshooting issues takes a lot of time. The traditional method of troubleshooting doesn't really work for or apply to this environment we're in. So, having an AI-based system and the ability to automate deployments of your monitoring and configurations makes it much easier.
