The Azure Monitor Log Analytics API response is a JSON string that contains an array of table objects.
The tables property is an array of tables that represent the query result. Each table contains name, columns, and rows properties:
The name property is the name of the table.
The columns property is an array of objects that describe the schema of each column.
The rows property is an array of values. Each item in the array represents a row in the result set.
In the following example, we can see that the result contains two columns: Category and count_. The first column, Category, represents the value of the Category column in the AzureActivity table. The second column, count_ is the count of the number of events in the AzureActivity table for the specific category.
If a fatal error occurs during query execution, an error status code is returned with a OneAPI error object that describes the error.
If a non-fatal error occurs during query execution, the response status code is 200 OK. It contains the query results in the tables property as described. The response also contains an error property, which is a OneAPI error object with the code PartialError. Details of the error are included in the details property.
The Azure Monitor Log Analytics API response is a JSON string that contains an array of table objects. The tables property is an array of tables that represent the query result. Each table contains name , columns , and rows properties: The name property is the name of the table.
Azure Monitor collects and aggregates the data from every layer and component of your system across multiple Azure and non-Azure subscriptions and tenants. It stores it in a common data platform for consumption by a common set of tools that can correlate, analyze, visualize, and/or respond to the data.
Hover over the response code to get a short description of the code and what it means. Some API responses also contain custom messages that can help you understand response codes. For example, if you receive a 401 Unauthorized response, the message might tell you to check the token you used in the request.
In conclusion, Azure Monitor and Log Analytics collectively offer a robust solution for monitoring Azure resources. While Azure Monitor provides a lot of features including aggregation of logs, real-time insights and performance metrics, Log Analytics allows advanced query capabilities and extensive log data analysis.
Azure Monitor Logs collects logs and performance data where they can be retrieved and analyzed in different ways by using log queries. You must create a Log Analytics workspace to collect log data. Use Log Analytics to analyze data from Azure Monitor Logs.
Which two data types should you use? Explanation: Azure Monitor provides two primary data types for monitoring and analysis: Metrics and Logs. Metrics provide a numerical view of performance data, while Logs provide a detailed record of events and activities.
Metrics are numerical values that are collected at regular intervals and describe some aspect of a system at a particular time. Azure Monitor Metrics is one half of the data platform that supports Azure Monitor. The other half is Azure Monitor Logs, which collects and organizes log and performance data.
Log Analytics workspace has the limit of only 30000 rows. To achieve your requirement, you can try Azure Data explorer as a workaround. Create an ADX cluster and go to the Query tab.
In the Azure portal, navigate to your API Management instance.On the Overview page, on the Monitor tab, review key metrics for your APIs. To investigate metrics in detail, select Metrics from the left menu. From the drop-down, select metrics you're interested in.
To check the API response time, simulate the load and capture the speed using your preferred tool. It is always a good idea to gather the API response time measurement from different tools because the architecture of the two tools can be different, resulting in different API response times.
API logs monitoring involves tracking and analyzing log data generated by API endpoints, services, and applications. It's essential for gaining insights into API activity, troubleshooting issues, detecting anomalies, and ensuring the reliability and security of API-based systems.
An API Response is the data or information that is returned from a server when an API (Application Programming Interface) request is sent. It is typically in the form of a JSON or XML document and contains either a status (“o*k”, “error”, etc.) or data (e.g. a list of items).
Log analytics involves searching, analyzing, and visualizing machine data generated by your IT systems and technology infrastructure to gain operational insights.
The definition of API Logging encompasses the collection, storage, and analysis of data generated during the interaction with APIs to ensure performance optimization, security compliance, and troubleshooting of issues.
Maximum of 30 MB per post to Log Analytics Data Collector API. This is a size limit for a single post. If the data from a single post that exceeds 30 MB, you should split the data up to smaller sized chunks and send them concurrently. Maximum of 32 KB limit for field values.
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