Azure Monitor and Thanos Integration
Powerful performance with an easy integration, powered by Telegraf, the open source data connector built by InfluxData.
5B+
Telegraf downloads
#1
Time series database
Source: DB Engines
1B+
Downloads of InfluxDB
2,800+
Contributors
Table of Contents
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
Input and output integration overview
Gather metrics from Azure resources using the Azure Monitor API.
This plugin sends metrics from Telegraf to Thanos using the Prometheus remote write protocol over HTTP, allowing efficient and scalable ingestion into Thanos Receive components.
Integration details
Azure Monitor
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 client_id
, client_secret
, tenant_id
, and subscription_id
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.
Thanos
Telegraf’s HTTP plugin can send metrics directly to Thanos via its Remote Write-compatible Receive component. By setting the data format to prometheusremotewrite
, Telegraf can serialize metrics into the same protobuf-based format used by native Prometheus clients. This setup enables high-throughput, low-latency metric ingestion into Thanos, facilitating centralized observability at scale. It is particularly useful in hybrid environments where Telegraf is collecting metrics from systems outside Prometheus’ native reach, such as SNMP devices, Windows hosts, or custom apps, and streams them directly to Thanos for long-term storage and global querying.
Configuration
Azure Monitor
# Gather Azure resources metrics from Azure Monitor API
[[inputs.azure_monitor]]
# can be found under Overview->Essentials in the Azure portal for your application/service
subscription_id = "<>"
# can be obtained by registering an application under Azure Active Directory
client_id = "<>"
# 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 = "<>"
# can be found under Azure Active Directory->Properties
tenant_id = "<>"
# 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->Essentials->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 = "<>"
# the metric names to collect
# leave the array empty to use all metrics available to this resource
metrics = [ "<>", "<>" ]
# 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 = [ "<>", "<>" ]
# resource target #2 to collect metrics from
[[inputs.azure_monitor.resource_target]]
resource_id = "<>"
metrics = [ "<>", "<>" ]
aggregations = [ "<>", "<>" ]
# 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 = "<>"
# defines the resources to collect metrics from
[[inputs.azure_monitor.resource_group_target.resource]]
# the resource type
resource_type = "<>"
metrics = [ "<>", "<>" ]
aggregations = [ "<>", "<>" ]
# defines the resources to collect metrics from
[[inputs.azure_monitor.resource_group_target.resource]]
resource_type = "<>"
metrics = [ "<>", "<>" ]
aggregations = [ "<>", "<>" ]
# resource group target #2 to collect metrics from resources under it with resource type
[[inputs.azure_monitor.resource_group_target]]
resource_group = "<>"
[[inputs.azure_monitor.resource_group_target.resource]]
resource_type = "<>"
metrics = [ "<>", "<>" ]
aggregations = [ "<>", "<>" ]
# subscription target #1 to collect metrics from resources under it with resource type
[[inputs.azure_monitor.subscription_target]]
resource_type = "<>"
metrics = [ "<>", "<>" ]
aggregations = [ "<>", "<>" ]
# subscription target #2 to collect metrics from resources under it with resource type
[[inputs.azure_monitor.subscription_target]]
resource_type = "<>"
metrics = [ "<>", "<>" ]
aggregations = [ "<>", "<>" ]
</code></pre>
Thanos
[[outputs.http]]
## Thanos Receive endpoint for remote write
url = "http://thanos-receive.example.com/api/v1/receive"
## HTTP method
method = "POST"
## Data format set to Prometheus remote write
data_format = "prometheusremotewrite"
## Optional headers (authorization, etc.)
# [outputs.http.headers]
# Authorization = "Bearer YOUR_TOKEN"
## Optional TLS configuration
# tls_ca = "/path/to/ca.pem"
# tls_cert = "/path/to/cert.pem"
# tls_key = "/path/to/key.pem"
# insecure_skip_verify = false
## Request timeout
timeout = "10s"
Input and output integration examples
Azure Monitor
-
Dynamic Resource Monitoring: 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.
-
Multi-Cloud Monitoring Integration: 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.
-
Anomaly Detection and Alerting: 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.
-
Historical Performance Analysis: 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.
Thanos
-
Agentless Cloud Monitoring: Deploy Telegraf agents across cloud VMs to collect system and application metrics, then stream them directly into Thanos using Remote Write. This provides centralized observability without requiring Prometheus nodes at each location.
-
Scalable Windows Host Monitoring: Use Telegraf on Windows machines to collect OS-level metrics and send them via Remote Write to Thanos Receive. This enables observability across heterogeneous environments with native Prometheus support only on Linux.
-
Cross-Region Metrics Federation: Telegraf agents in multiple geographic regions can push data to region-local Thanos Receivers using this plugin. From there, Thanos can deduplicate and query metrics globally, reducing latency and network egress costs.
-
Integrating Third-Party Data into Thanos: Collect metrics from custom telemetry sources such as REST APIs or proprietary logs using Telegraf inputs and forward them to Thanos via Remote Write. This brings non-native data into a Prometheus-compatible, long-term analytics pipeline.
Feedback
Thank you for being part of our community! If you have any general feedback or found any bugs on these pages, we welcome and encourage your input. Please submit your feedback in the InfluxDB community Slack.
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
Related Integrations
Related Integrations
HTTP and InfluxDB Integration
The HTTP plugin collects metrics from one or more HTTP(S) endpoints. It supports various authentication methods and configuration options for data formats.
View IntegrationKafka and InfluxDB Integration
This plugin reads messages from Kafka and allows the creation of metrics based on those messages. It supports various configurations including different Kafka settings and message processing options.
View IntegrationKinesis and InfluxDB Integration
The Kinesis plugin allows for reading metrics from AWS Kinesis streams. It supports multiple input data formats and offers checkpointing features with DynamoDB for reliable message processing.
View Integration