Metrics and logs are different things, and it is important to understand and capture both for all the resources in your deployment. For each Azure service identify additional associated monitoring logs and services.For each Azure service gather the available metrics.You may already have a clear list of monitoring requirements, but it is worth cross checking these with what is available ‘out of the box’ from a metrics and logs perspective for each Azure resource involved in the solution. Create an Azure Resource Listįrom the architecture drawing you can now derive a list of all the Azure resource types involved in this solution as follows: Step 2: Review Available Metrics, Logs and Services The following image depicts a simple network drawing showing hub and spoke network connectivity back to on-prem via a VPN gateway and an Azure Firewall. Create a list of all the Azure resources included in the solution.Create a full architecture diagram of the end-to-end solution.The first step in determining what you need to monitor for your Azure workload is to identify all of the Azure resources included as part of the end-to-end solution. If we continually analyse for every metric, log and alert we will never get anything done! We will also learn over time and include new metrics as we see fit. Remember that we are only aiming to achieve a starting point or baseline. If you are unfamiliar with the concept of the Hub and Spoke then please visit the Microsoft documentation that describes the Azure Landing Zone. This example demonstrates how to apply the six-step process to a simple Hub and Spoke network architecture deployment to create a first pass end-to-end monitoring solution. Today we are discussing a real-world example of how you would monitor networking in Azure. We also said that, in order to cement your understanding, we would be releasing some specific example scenarios to help bring this to life. In the first post of this series, we gave you a high-level overview of the six steps which will help you determine what to monitor in your cloud workloads.

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