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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.
Poznámka
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. You can analyze that data by using a rich query language.
There are multiple types of metrics supported by Azure Monitor Metrics:
The differences between each of the metrics are summarized in the following table.
Category | Native platform metrics | Native custom metrics | Prometheus metrics |
---|---|---|---|
Sources | Azure resources | Azure Monitor agent Application insights REST API |
Azure Kubernetes service (AKS) cluster Any Kubernetes cluster through remote-write |
Configuration | None | Varies by source | Enable Azure Monitor managed service for Prometheus |
Stored | Subscription | Subscription | Azure Monitor workspace |
Cost | No | Yes (free during preview) | Yes (free during preview) |
Aggregation | preaggregated | preaggregated | raw data |
Analyze | Metrics Explorer | Metrics Explorer | PromQL Grafana dashboards |
Alert | metrics alert rule | metrics alert rule | Prometheus alert rule |
Visualize | Workbooks Azure dashboards Grafana |
Workbooks Azure dashboards Grafana |
Grafana |
Retrieve | Azure CLI Azure PowerShell cmdlets REST API or client library .NET Go Java JavaScript Python |
Azure CLI Azure PowerShell cmdlets REST API or client library .NET Go Java JavaScript Python |
Grafana |
Azure Monitor collects metrics from the following sources. After these metrics are collected in the Azure Monitor metric database, they can be evaluated together regardless of their source:
Poznámka
Metrics collected from different sources and by different methods may be aggregated differently. For example, platform metrics are preaggregated and stored in a time-series database, while Prometheus metrics are stored as raw data.Resource metrics may also have a different latency than other metrics. This can lead to differences in metric values for a specific sample time. Over time when latency ceases to be an issue, and when analyzing the metrics at the same time granularity, these differences disappear.
Azure Monitor provides REST APIs that allow you to get data in and out of Azure Monitor Metrics.
All communication between connected systems and the Azure Monitor service is encrypted using the TLS 1.2 (HTTPS) protocol. The Microsoft SDL process is followed to ensure all Azure services are up-to-date with the most recent advances in cryptographic protocols.
Secure connection is established between the agent and the Azure Monitor service using certificate-based authentication and TLS with port 443. Azure Monitor uses a secret store to generate and maintain keys. Private keys are rotated every 90 days and are stored in Azure and are managed by the Azure operations who follow strict regulatory and compliance practices. For more information on security, see Encryption of data in transit, Encryption of data at rest, and Azure Monitor security overview and guidelines.
Use Metrics Explorer to interactively analyze the data in your metric database and chart the values of multiple metrics over time. You can pin the charts to a dashboard to view them with other visualizations. You can also retrieve metrics by using the Azure monitoring REST API.
For more information, see Analyze metrics with Azure Monitor metrics explorer.
Data that Azure Monitor Metrics collects, is stored in a time-series database that's optimized for analyzing time-stamped data. Each set of metric values is a time series with the following properties:
One of the challenges to metric data is that it often has limited information to provide context for collected values. Azure Monitor addresses this challenge with multi-dimensional metrics.
Metric dimensions are name/value pairs that carry more data to describe the metric value. For example, a metric called Available disk space might have a dimension called Drive with values C: and D:. That dimension would allow viewing available disk space across all drives or for each drive individually.
See Apply dimension filters and splitting for details on viewing metric dimensions in metrics explorer.
The following table shows sample data from a nondimensional metric, network throughput. It can only answer a basic question like "What was my network throughput at a given time?"
Timestamp | Metric value |
---|---|
8/9/2017 8:14 | 1,331.8 Kbps |
8/9/2017 8:15 | 1,141.4 Kbps |
8/9/2017 8:16 | 1,110.2 Kbps |
The following table shows sample data from a multidimensional metric, network throughput with two dimensions called IP and Direction. It can answer questions such as "What was the network throughput for each IP address?" and "How much data was sent versus received?"
Timestamp | Dimension "IP" | Dimension "Direction" | Metric value |
---|---|---|---|
8/9/2017 8:14 | IP="192.168.5.2" | Direction="Send" | 646.5 Kbps |
8/9/2017 8:14 | IP="192.168.5.2" | Direction="Receive" | 420.1 Kbps |
8/9/2017 8:14 | IP="10.24.2.15" | Direction="Send" | 150.0 Kbps |
8/9/2017 8:14 | IP="10.24.2.15" | Direction="Receive" | 115.2 Kbps |
8/9/2017 8:15 | IP="192.168.5.2" | Direction="Send" | 515.2 Kbps |
8/9/2017 8:15 | IP="192.168.5.2" | Direction="Receive" | 371.1 Kbps |
8/9/2017 8:15 | IP="10.24.2.15" | Direction="Send" | 155.0 Kbps |
8/9/2017 8:15 | IP="10.24.2.15" | Direction="Receive" | 100.1 Kbps |
Poznámka
Dimension names and dimension values are case-insenstive.
Platform and custom metrics are stored for 93 days with the following exceptions:
Classic guest OS metrics: These performance counters are collected by the Windows diagnostic extension or the Linux diagnostic extension and routed to an Azure Storage account. Retention for these metrics is guaranteed to be at least 14 days, although no expiration date is written to the storage account.
For performance reasons, the portal limits how much data it displays based on volume. So, the actual number of days that the portal retrieves can be longer than 14 days if the volume of data being written isn't large.
Guest OS metrics sent to Azure Monitor Metrics: These performance counters are collected by the Windows diagnostic extension and sent to the Azure Monitor data sink, or the InfluxData Telegraf agent on Linux machines, or the newer Azure Monitor agent via data-collection rules. Retention for these metrics is 93 days.
Guest OS metrics collected by the Log Analytics agent: These performance counters are collected by the Log Analytics agent and sent to a Log Analytics workspace. Retention for these metrics is 31 days and can be extended up to 2 years.
Application Insights log-based metrics: Behind the scenes, log-based metrics translate into log queries. Their retention is variable and matches the retention of events in underlying logs, which is 31 days to 2 years. For Application Insights resources, logs are stored for 90 days.
Poznámka
You can send platform metrics for Azure Monitor resources to a Log Analytics workspace for long-term trending.
While platform and custom metrics are stored for 93 days, you can only query (in the Metrics tile) for a maximum of 30 days' worth of data on any single chart. This limitation doesn't apply to log-based metrics. If you see a blank chart or your chart displays only part of metric data, verify that the difference between start and end dates in the time picker doesn't exceed the 30-day interval. After you've selected a 30-day interval, you can pan the chart to view the full retention window.
Poznámka
Moving or renaming an Azure Resource may result in a lost of metric history for that resource.
Prometheus metrics are stored for 18 months, but a PromQL query can only span a maximum of 32 days.
Udalosti
Vytváranie inteligentných aplikácií
17. 3., 21 - 21. 3., 10
Pripojte sa k sérii meetup a vytvorte škálovateľné riešenia AI na základe prípadov reálneho používania so spolupracovníkmi a odborníkmi.
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