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Azure Monitor and Microsoft SQL Server Integration

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This is not the recommended configuration for real-time query at scale. For query and compression optimization, high-speed ingest, and high availability, you may want to consider <a href="/integrations/azure_monitor-influxdb/">Azure Monitor and InfluxDB</a>.

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Infrastructure Monitoring with Telegraf

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Input and output integration overview

<p>Gather metrics from Azure resources using the Azure Monitor API.</p>

<p>Telegraf’s SQL plugin facilitates the storage of metrics in SQL databases. When configured for Microsoft SQL Server, it supports the specific DSN format and schema requirements, allowing for seamless integration with SQL Server.</p>

Integration details

Azure Monitor

<p>The Azure Monitor Telegraf plugin is specifically designed for gathering metrics from various Azure resources using the Azure Monitor API. Users must provide specific credentials such as <code>client_id</code>, <code>client_secret</code>, <code>tenant_id</code>, and <code>subscription_id</code> to authenticate and gain access to their Azure resources. Additionally, the plugin supports functionality to collect metrics from both individual resources and resource groups or subscriptions, allowing for flexible and scalable metric collection tailored to user needs. This plugin is ideal for organizations leveraging Azure cloud infrastructure, providing crucial insights into resource performance and utilization over time, facilitating proactive management and optimization of cloud resources.</p>

Microsoft SQL Server

<p>Telegraf’s SQL output plugin for Microsoft SQL Server is designed to capture and store metric data by dynamically creating tables and columns that match the structure of incoming data. This integration leverages the go-mssqldb driver, which follows the SQL Server connection protocol through a DSN that includes server, port, and database details. Although the driver is considered experimental due to limited unit tests, it provides robust support for dynamic schema generation and data insertion, enabling detailed time-stamped records of system performance. This flexibility makes it a valuable tool for environments that demand reliable and granular metric logging, despite its experimental status.</p>

Configuration

Azure Monitor

<pre><code class="language-toml"># Gather Azure resources metrics from Azure Monitor API [[inputs.azure_monitor]] # can be found under Overview-&gt;Essentials in the Azure portal for your application/service subscription_id = "&lt;<SUBSCRIPTION_ID>&gt;" # can be obtained by registering an application under Azure Active Directory client_id = "&lt;<CLIENT_ID>&gt;" # can be obtained by registering an application under Azure Active Directory. # If not specified Default Azure Credentials chain will be attempted: # - Environment credentials (AZURE_*) # - Workload Identity in Kubernetes cluster # - Managed Identity # - Azure CLI auth # - Developer Azure CLI auth client_secret = "&lt;<CLIENT_SECRET>&gt;" # can be found under Azure Active Directory-&gt;Properties tenant_id = "&lt;<TENANT_ID>&gt;" # Define the optional Azure cloud option e.g. AzureChina, AzureGovernment or AzurePublic. The default is AzurePublic. # cloud_option = "AzurePublic" # resource target #1 to collect metrics from [[inputs.azure_monitor.resource_target]] # can be found under Overview-&gt;Essentials-&gt;JSON View in the Azure portal for your application/service # must start with 'resourceGroups/...' ('/subscriptions/xxxxxxxx-xxxx-xxxx-xxx-xxxxxxxxxxxx' # must be removed from the beginning of Resource ID property value) resource_id = "&lt;<RESOURCE_ID>&gt;" # the metric names to collect # leave the array empty to use all metrics available to this resource metrics = [ "&lt;<METRIC>&gt;", "&lt;<METRIC>&gt;" ] # metrics aggregation type value to collect # can be 'Total', 'Count', 'Average', 'Minimum', 'Maximum' # leave the array empty to collect all aggregation types values for each metric aggregations = [ "&lt;<AGGREGATION>&gt;", "&lt;<AGGREGATION>&gt;" ] # resource target #2 to collect metrics from [[inputs.azure_monitor.resource_target]] resource_id = "&lt;<RESOURCE_ID>&gt;" metrics = [ "&lt;<METRIC>&gt;", "&lt;<METRIC>&gt;" ] aggregations = [ "&lt;<AGGREGATION>&gt;", "&lt;<AGGREGATION>&gt;" ] # resource group target #1 to collect metrics from resources under it with resource type [[inputs.azure_monitor.resource_group_target]] # the resource group name resource_group = "&lt;<RESOURCE_GROUP_NAME>&gt;" # defines the resources to collect metrics from [[inputs.azure_monitor.resource_group_target.resource]] # the resource type resource_type = "&lt;<RESOURCE_TYPE>&gt;" metrics = [ "&lt;<METRIC>&gt;", "&lt;<METRIC>&gt;" ] aggregations = [ "&lt;<AGGREGATION>&gt;", "&lt;<AGGREGATION>&gt;" ] # defines the resources to collect metrics from [[inputs.azure_monitor.resource_group_target.resource]] resource_type = "&lt;<RESOURCE_TYPE>&gt;" metrics = [ "&lt;<METRIC>&gt;", "&lt;<METRIC>&gt;" ] aggregations = [ "&lt;<AGGREGATION>&gt;", "&lt;<AGGREGATION>&gt;" ] # resource group target #2 to collect metrics from resources under it with resource type [[inputs.azure_monitor.resource_group_target]] resource_group = "&lt;<RESOURCE_GROUP_NAME>&gt;" [[inputs.azure_monitor.resource_group_target.resource]] resource_type = "&lt;<RESOURCE_TYPE>&gt;" metrics = [ "&lt;<METRIC>&gt;", "&lt;<METRIC>&gt;" ] aggregations = [ "&lt;<AGGREGATION>&gt;", "&lt;<AGGREGATION>&gt;" ] # subscription target #1 to collect metrics from resources under it with resource type [[inputs.azure_monitor.subscription_target]] resource_type = "&lt;<RESOURCE_TYPE>&gt;" metrics = [ "&lt;<METRIC>&gt;", "&lt;<METRIC>&gt;" ] aggregations = [ "&lt;<AGGREGATION>&gt;", "&lt;<AGGREGATION>&gt;" ] # subscription target #2 to collect metrics from resources under it with resource type [[inputs.azure_monitor.subscription_target]] resource_type = "&lt;<RESOURCE_TYPE>&gt;" metrics = [ "&lt;<METRIC>&gt;", "&lt;<METRIC>&gt;" ] aggregations = [ "&lt;<AGGREGATION>&gt;", "&lt;<AGGREGATION>&gt;" ] &lt;/code&gt;&lt;/pre&gt; </AGGREGATION></AGGREGATION></METRIC></METRIC></RESOURCE_TYPE></AGGREGATION></AGGREGATION></METRIC></METRIC></RESOURCE_TYPE></AGGREGATION></AGGREGATION></METRIC></METRIC></RESOURCE_TYPE></RESOURCE_GROUP_NAME></AGGREGATION></AGGREGATION></METRIC></METRIC></RESOURCE_TYPE></AGGREGATION></AGGREGATION></METRIC></METRIC></RESOURCE_TYPE></RESOURCE_GROUP_NAME></AGGREGATION></AGGREGATION></METRIC></METRIC></RESOURCE_ID></AGGREGATION></AGGREGATION></METRIC></METRIC></RESOURCE_ID></TENANT_ID></CLIENT_SECRET></CLIENT_ID></SUBSCRIPTION_ID></code></pre>

Microsoft SQL Server

<pre><code class="language-toml">[[outputs.sql]] ## Database driver ## Valid options: mssql (Microsoft SQL Server), mysql (MySQL), pgx (Postgres), ## sqlite (SQLite3), snowflake (snowflake.com), clickhouse (ClickHouse) driver = "mssql" ## Data source name ## For Microsoft SQL Server, the DSN typically includes the server, port, username, password, and database name. ## Example DSN: "sqlserver://username:password@localhost:1433?database=telegraf" data_source_name = "sqlserver://username:password@localhost:1433?database=telegraf" ## Timestamp column name timestamp_column = "timestamp" ## Table creation template ## Available template variables: ## {TABLE} - table name as a quoted identifier ## {TABLELITERAL} - table name as a quoted string literal ## {COLUMNS} - column definitions (list of quoted identifiers and types) table_template = "CREATE TABLE {TABLE} ({COLUMNS})" ## Table existence check template ## Available template variables: ## {TABLE} - table name as a quoted identifier table_exists_template = "SELECT 1 FROM {TABLE} LIMIT 1" ## Initialization SQL (optional) init_sql = "" ## Maximum amount of time a connection may be idle. "0s" means connections are never closed due to idle time. connection_max_idle_time = "0s" ## Maximum amount of time a connection may be reused. "0s" means connections are never closed due to age. connection_max_lifetime = "0s" ## Maximum number of connections in the idle connection pool. 0 means unlimited. connection_max_idle = 2 ## Maximum number of open connections to the database. 0 means unlimited. connection_max_open = 0 ## Metric type to SQL type conversion ## You can customize the mapping if needed. #[outputs.sql.convert] # integer = "INT" # real = "DOUBLE" # text = "TEXT" # timestamp = "TIMESTAMP" # defaultvalue = "TEXT" # unsigned = "UNSIGNED" # bool = "BOOL" </code></pre>

Input and output integration examples

Azure Monitor

<ol> <li> <p><strong>Dynamic Resource Monitoring</strong>: Use the Azure Monitor plugin to dynamically gather metrics from Azure resources based on specific criteria like tags or resource types. Organizations can automate the process of loading and unloading resource metrics, enabling better performance tracking and optimization based on resource utilization patterns.</p> </li> <li> <p><strong>Multi-Cloud Monitoring Integration</strong>: Integrate metrics collected from Azure Monitor with other cloud providers using a centralized monitoring solution. This allows organizations to view and analyze performance data across multiple cloud deployments, providing a holistic overview of resource performance and costs, and streamlining operations.</p> </li> <li> <p><strong>Anomaly Detection and Alerting</strong>: Leverage the metrics gathered via the Azure Monitor plugin in conjunction with machine learning algorithms to detect anomalies in resource utilization. By establishing baseline performance metrics and automatically alerting on deviations, organizations can mitigate risks and address performance issues before they escalate.</p> </li> <li> <p><strong>Historical Performance Analysis</strong>: Use the collected Azure metrics to conduct historical analysis by feeding the data into a data warehousing solution. This enables organizations to track trends over time, allowing for detailed reporting and decision-making based on historical performance data.</p> </li> </ol>

Microsoft SQL Server

<ol> <li> <p><strong>Enterprise Application Monitoring</strong>: Leverage the plugin to capture detailed performance metrics from enterprise applications running on SQL Server. This setup allows IT teams to analyze system performance, track transaction times, and identify bottlenecks across complex, multi-tier environments.</p> </li> <li> <p><strong>Dynamic Infrastructure Auditing</strong>: Deploy the plugin to create a dynamic audit log of infrastructure changes and performance metrics in SQL Server. This use case is ideal for organizations that require real-time monitoring and historical analysis of system performance for compliance and optimization.</p> </li> <li> <p><strong>Automated Performance Benchmarking</strong>: Use the plugin to continuously record and analyze performance metrics of SQL Server databases. This enables automated benchmarking, where historical data is compared against current performance, helping to quickly identify anomalies or degradation in service.</p> </li> <li> <p><strong>Integrated DevOps Dashboards</strong>: Integrate the plugin with DevOps monitoring tools to feed real-time metrics from SQL Server into centralized dashboards. This provides a holistic view of application health, allowing teams to correlate SQL Server performance with application-level events for faster troubleshooting and proactive maintenance.</p> </li> </ol>

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Useful Links

Documentation

Telegraf Quickstart Training

Infrastructure Monitoring with Telegraf

Powerful Performance, Limitless Scale

Collect, organize, and act on massive volumes of high-velocity data. Any data is more valuable when you think of it as time series data. with InfluxDB, the #1 time series platform built to scale with Telegraf.

See Ways to Get Started

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