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Azure Monitor and SQLite 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 output plugin stores metrics in an SQL database by creating tables dynamically for each metric type. When configured for SQLite, it utilizes a file-based DSN and a minimal SQL schema tailored for lightweight, embedded database usage.</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>

SQLite

<p>The SQL output plugin writes Telegraf metrics to an SQL database using a dynamic schema where each metric type corresponds to a table. For SQLite, the plugin uses the modernc.org/sqlite driver and requires a DSN in the format of a file URI (e.g., ‘file:/path/to/telegraf.db?cache=shared’). This configuration leverages standard ANSI SQL for table creation and data insertion, ensuring compatibility with SQLite’s capabilities.</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>

SQLite

<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 = "sqlite" ## Data source name ## For SQLite, the DSN is a filename or URL with the scheme "file:". ## Example: "file:/path/to/telegraf.db?cache=shared" data_source_name = "file:/path/to/telegraf.db?cache=shared" ## 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 ## The values on the left are the data types Telegraf has and the values on the right are the SQL types used when writing to SQLite. #[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>

SQLite

<ol> <li><strong>Local Monitoring Storage</strong>: Configure the plugin to write metrics to a local SQLite database file. This is ideal for lightweight deployments where setting up a full-scale database server is not required.</li> <li><strong>Embedded Applications</strong>: Use SQLite as the backend for applications embedded in edge devices, benefiting from its file-based architecture and minimal resource requirements.</li> <li><strong>Quick Setup for Testing</strong>: Leverage SQLite’s ease of use to quickly set up a testing environment for Telegraf metrics collection without the need for external database services.</li> <li><strong>Custom Schema Management</strong>: Adjust the table creation templates to predefine your schema if you require specific column types or indexes, ensuring compatibility with your application’s needs.</li> </ol>

Feedback

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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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