Metrics - Data Plane - Batch - REST API (Azure Monitor) (2023)

FAQs

What is metrics in Azure Monitor? ›

Azure Monitor Metrics is a feature of Azure Monitor that collects numeric data from monitored resources into a time-series database. Metrics are numerical values that are collected at regular intervals and describe some aspect of a system at a particular time.

Azure Monitor Metrics can only store numeric data in a particular structure, whereas Azure Monitor Logs can store a variety of data types that have their own structures. You can also perform complex analysis on Azure Monitor Logs data by using log queries, which can't be used for analysis of Azure Monitor Metrics data.

Raw data points (that is, items that you can query in Analytics and inspect in Search) are kept for up to 730 days. You can select a retention duration of 30, 60, 90, 120, 180, 270, 365, 550, or 730 days.

Container - Data about containers, such as Azure Kubernetes Service, Prometheus, and the applications running inside containers. Operating system - Data about the guest operating system on which your application is running.

The 4 key metrics are Deployment Frequency, Lead Time for Changes, Mean Time to Recover and Change Failure Rate.

API monitoring is the process of gathering, visualizing, and alerting on pre-defined metrics in order to ensure that an API is meeting specific expectations. API observability supports API monitoring, but it is much more open-ended.

Metrics can be used to monitor performance, recognize events of importance, and facilitate prediction of future lapses. Logs are usually used for troubleshooting issues, but also for analyzing user behavior, application metrics and a growing variety of additional use cases.

Application Insights is an extension of Azure Monitor and provides application performance monitoring (APM) features. APM tools are useful to monitor applications from development, through test, and into production in the following ways: Proactively understand how an application is performing.

Where does Azure Monitor store even data? ›

Logs in Azure Monitor are stored in a Log Analytics workspace that's based on Azure Data Explorer, which provides a powerful analysis engine and rich query language.

All log data collected by Azure Monitor is stored in a Log Analytics workspace. A workspace is essentially a container where log data is collected from various sources. You might have a single Log Analytics workspace for all your monitoring data, or you might have requirements for multiple workspaces.

Microsoft combined three unique services—Azure Monitor, Log Analytics, and Application Insights—under the umbrella of Azure Monitor to provide powerful end-to-end monitoring of your applications and the components they rely on.

Productivity, profit margin, scope and cost are some examples of performance metrics that a business can track to determine if target objectives and goals are being met.

The three types of metrics you should collect as part of your quality assurance process are: source code metrics, development metrics, and testing metrics.

The answer is with the four Golden Signals: latency, traffic, error rate, and resource saturation. In this blog, we explain what the Golden Signals are, how they work, and how they can make monitoring complex distributed systems easier.

The key classification metrics: Accuracy, Recall, Precision, and F1- Score.

What are the 4 key metrics Agile? ›

The researchers have determined that only four key metrics differentiate between low, medium and high performers: lead time, deployment frequency, mean time to restore (MTTR) and change fail percentage.

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.

In order to figure out how bad your outliers are, you can look at higher percentiles: the 95th, 99th, and 99.9th percentiles are common (abbreviated p95, p99, and p999). They are the response time thresholds at which 95%, 99%, or 99.9% of requests are faster than that particular threshold.

Golden Signals are a reduced set of metrics that offer a wide view of a service from a user or consumer perspective: Latency, Traffic, Errors and Saturation.

Peak visibility is achieved by analyzing the three pillars of observability: Logs, metrics and traces.

Unlike an event log, which records specific events, metrics are a measured value derived from system performance. Metrics are real time-savers because you can easily correlate them across infrastructure components to get a holistic view of system health and performance.

The following metrics can be used for Test Monitoring: Test Coverage Metric. Test Execution Metrics (Number of test cases pass, fail, blocked, on hold) Defect Metrics.

Azure Monitor helps you understand how your applications are performing and proactively identifies issues affecting them and the resources they depend on. Azure Service Health helps you stay informed and take action when Azure service issues like outages and planned maintenance affect you.

What is the difference between Azure function app and Azure Batch? ›

Unlike Azure Functions, Batch does not have an out-of-the-box queue trigger task model. Fortunately, it provides Azure Batch API that allows us to create tasks. Combined with table and queue storage, we can create a program that will monitor the jobs queue and make a batch task for each job, as illustrated in figure 2.

Azure dashboards are useful in providing a "single pane of glass" of your Azure infrastructure and services. While a workbook provides richer functionality, a dashboard can combine Azure Monitor data with data from other Azure services.

Log Analytics and Application Insights are now features of Azure Monitor. The log data engine and query language of Log Analytics is now referred to as Azure Monitor Logs.

Alerts help you detect and address issues before users notice them by proactively notifying you when Azure Monitor data indicates there might be a problem with your infrastructure or application. You can alert on any metric or log data source in the Azure Monitor data platform.

Azure Advisor provides personalized recommendations to optimize Azure resources for performance, security, reliability, and cost-effectiveness. On the other hand, Azur Monitor provides a platform for collecting, analyzing, and acting on telemetry data generated by Azure resources and applications.

Azure Monitor Metrics can only store numeric data in a particular structure, whereas Azure Monitor Logs can store a variety of data types that have their own structures. You can also perform complex analysis on Azure Monitor Logs data by using log queries, which can't be used for analysis of Azure Monitor Metrics data.

Azure Monitor is a powerful reporting and analytics tool. Azure Monitor maximizes the supply and performance of your applications and services by delivering an inclusive solution for collecting, analyzing, and working on telemetry from the user's cloud and on-premises environments.

Activity log events are retained in Azure for 90 days and then deleted. There's no charge for entries during this time regardless of volume.

Azure Storage offers five core services: Blobs, Files, Queues, Tables, and Disks. Let's explore each and establish some common use cases.

Azure Blob Storage is Microsoft's object storage solution for the cloud. Blob Storage is optimized for storing massive amounts of unstructured data, such as text or binary data. Blob Storage is ideal for: Serving images or documents directly to a browser.

What is Azure Monitor metrics? ›

Azure Monitor is a comprehensive monitoring solution for collecting, analyzing, and responding to telemetry from your cloud and on-premises environments. You can use Azure Monitor to maximize the availability and performance of your applications and services.

A batch operation may contain up to 100 individual table operations, with the requirement that each operation entity must have same partition key. A batch with a retrieve operation cannot contain any other operations. Note that the total payload of a batch operation is limited to 4MB.

Metrics are raw data about resource usage or behavior that your monitoring system collects from any of the applications or services on your infrastructure. This is typically done with a monitoring agent, but it can also be done without it for serverless applications.

Metric types in Cloud Monitoring are classified into general groups, based on the type of service that collects the data. This page provides links to reference lists for each of these groups. Metrics from Google Cloud services: Google Cloud metrics, for Google Cloud services such as Compute Engine and BigQuery.

Software metrics measure a software's characteristics in a countable manner. That is why tracking the metrics is a huge part of the development stage. The goal of system metrics monitoring is to determine the quality of the product or process during the development and deployment stages.

Metrics capture a value pertaining to your systems at a specific point in time — for example, the number of users currently logged in to a web application. Therefore, metrics are usually collected once per second, one per minute, or at another regular interval to monitor a system over time.

While metrics represent the data in your system, monitoring is the process of collecting, aggregating, and analyzing those values to improve awareness of your components' characteristics and behavior.

Which two types of data can you view in the monitoring API? ›

The Monitoring API uses filters to select metrics, to fetch time-series data, and to collect monitored resources into groups.

The primary metric determines whether the test "wins" or "loses"—it tracks how your changes affect your visitors' behaviors. Secondary metrics and monitoring goals provide additional information about your visitors' behavior in the vicinity of your change and across your site.

KPI stands for key performance indicator, a quantifiable measure of performance over time for a specific objective. KPIs provide targets for teams to shoot for, milestones to gauge progress, and insights that help people across the organization make better decisions.

There are three categories of metrics: product metrics, process metrics, and project metrics.