The adoption of Microsoft Azure and the public cloud, in general, grows quickly. There are obvious advantages from moving traditional servers to virtual machines in the Azure cloud, such as provisioning and administration of the servers.
Adopting microservices and elastic resources represent a material change from a traditional server-based or monolithic approach and with different benefits and advantages.
With “lift-and-shift” approaches where the “servers,” applications, or services are not re-designed but “just moved” to a different infrastructure the monitoring challenge should not necessarily be very different.
You can likely apply the same application performance monitoring practice you have today by installing agents to collect data and real-time performance metrics from the VMs that you run in Azure and probably use your existing Azure monitoring tool in the traditional sense.
Alternatively, you can leverage the out-of-the-box performance Azure monitor metrics and analytics made available through the Azure Monitor API. The data from the Azure Monitor API can be consumed by a range of monitoring platforms including Microsoft’s own tools.
A list of Microsoft Partner tools that integrate with the Azure Monitor API is available here.
A hybrid environment with resources across Azure and local data centers or a hybrid cloud set-up using Azure and other public clouds such as Google Cloud and AWS will be a valid option for many companies.
From an application monitoring perspective, it’s imperative to think through the current and future interaction of your infrastructure, applications, and services across technology silos and hybrid environments. Most will see that the dynamics and agility of modern development projects will mean that interaction between data center locations and cloud already happens, or is extremely likely in the future. The ONLY conclusion is that monitoring data needs to be unified across all the hybrid locations (local and cloud).
Get value out of AIMS in days - not months or years
Step 1: Connect
Connect Azure to AIMS to analyze data.
Step 2: Analyze and learn
Access anomalies and correlations within 2 weeks.
Step 3: Scale with confidence
Confidently scale your IT monitoring and operations with almost 0 maintenance as AIMS automatically discovers new resources and adjusts thresholds.
If you recognize the challenges and needs we have outlined in this article, AIMS could be a perfect solution for you.
But, don’t take our word for it. Sign-up for the AIMS Community Edition and experience the AIMS Capabilities for Azure monitoring for free. We should be embarrassed if you spend more than 1 hour on the set-up :)
Verify for yourself how AIMS satisfies automated and future-proof monitoring:
What if Microsoft Azure monitoring can be completely automated, removing the traditional monitoring manual labor of setting up and defining static thresholds and defining alerting scenarios that typically end up only covering a very limited part of the monitoring unit? See how it could be done in less than 15 minutes.