The new capabilities allow Datadog to hone in on two kinds of metrics: capacity metrics, which allow users to understand the size of their Azure storage units and how close they are to reaching capacity to make sure they don’t outgrow their storage environments; and transaction metrics, which tell the user how long it took to get files from a particular storage account. If there are any errors in pulling a file, users will get a detailed explanation of the error that would be tough to understand otherwise, said Daniel Langer, product manager with Datadog.
“Think of Azure Storage as the equivalent to AWS’ [Amazon Web Services’] S3,” Langer said. “It is the main unit for Azure customers to store files and objects, and everything boils down to storage units.”
In addition to understanding network errors, the integration provides insight into things like connection latency and throttling issues. The data is formatted alongside other metrics Datadog pulls from Azure to create a more linear illustration of the network, its applications, and storage.
Before this integration, Datadog customers were either sending in data from Azure storage for Datadog to sort through, or they built their own custom service to organize the metrics.
The monitoring company boasts several Azure integrations including monitoring classic virtual machines (VMs) deployed on Azure and VMs deployed through Azure Resource Manager (ARM), and monitoring Azure’s SQL database.