The access to the data is controlled by the storage access service key also called a blob token that is issued at the time of writing the blob so that the destination can use that token to import the data and handle the single-cast or multi-cast as appropriate to event handlers or appropriate Kusto Cluster. Data copying and rewrite is avoided by merely exchanging the payload information and blob tokens with the delivery service absorbing the process of fetching the permissions from GCS on behalf of the customer.
The role of the distributed graph might be standing out in the form of a question at this point. It is a service that is used for searching logs and for transformations. It consists of a front-end service and a backend service with each individual component within the FE and BE cloud services as individual micro-services performing a specific task. The front-end service allows the customers to set up query conditions such as job scope and interval period.
All the monitoring services are region-bound and can be repeated in other regions. Availability within the region such as for disaster recovery purposes requires the use of availability zones. The backend service merely schedules the workers for the appropriate handling of the logs to the customer’s storage account.
Many miscellaneous activities are specific to the data and whether the data is logs or metrics such as scrubbing, logs to metrics transformations, normalization, and uploading which are handled by dedicated services and serve to enhance the pipeline described so far. The monitoring architecture is generic and always requiring queues, blobs, collections, schedulers, pub-subs, producer-consumers accounts, analysis and reporting stacks and their configurations.
Most of the resources for Azure monitoring are region scoped. This enables Azure Monitoring to be setup in each region. Some shared data and resources across these regions may exist in a dedicated region which would power use cases of monitoring via the Azure portal.
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