AWS Data Firehose and Thanos Integration
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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
This plugin listens for metrics sent via HTTP from AWS Data Firehose in supported data formats, providing real-time data ingestion capabilities.
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
AWS Data Firehose
The AWS Data Firehose Telegraf plugin is designed to receive metrics from AWS Data Firehose via HTTP. This plugin listens for incoming data in various formats and processes it according to the request-response schema outlined in the official AWS documentation. Unlike standard input plugins that operate on a fixed interval, this service plugin initializes a listener that remains active, waiting for incoming metrics. This allows for real-time data ingestion from AWS Data Firehose, making it suitable for scenarios where immediate data processing is required. Key features include the ability to specify service addresses, paths, and support for TLS connections for secure data transmission. Additionally, the plugin accommodates optional authentication keys and custom tags, enhancing its flexibility in various use cases involving data streaming and processing.
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
AWS Data Firehose
[[inputs.firehose]]
## Address and port to host HTTP listener on
service_address = ":8080"
## Paths to listen to.
# paths = ["/telegraf"]
## maximum duration before timing out read of the request
# read_timeout = "5s"
## maximum duration before timing out write of the response
# write_timeout = "5s"
## Set one or more allowed client CA certificate file names to
## enable mutually authenticated TLS connections
# tls_allowed_cacerts = ["/etc/telegraf/clientca.pem"]
## Add service certificate and key
# tls_cert = "/etc/telegraf/cert.pem"
# tls_key = "/etc/telegraf/key.pem"
## Minimal TLS version accepted by the server
# tls_min_version = "TLS12"
## Optional access key to accept for authentication.
## AWS Data Firehose uses "x-amz-firehose-access-key" header to set the access key.
## If no access_key is provided (default), authentication is completely disabled and
## this plugin will accept all request ignoring the provided access-key in the request!
# access_key = "foobar"
## Optional setting to add parameters as tags
## If the http header "x-amz-firehose-common-attributes" is not present on the
## request, no corresponding tag will be added. The header value should be a
## json and should follow the schema as describe in the official documentation:
## https://docs.aws.amazon.com/firehose/latest/dev/httpdeliveryrequestresponse.html#requestformat
# parameter_tags = ["env"]
## Data format to consume.
## Each data format has its own unique set of configuration options, read
## more about them here:
## https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_INPUT.md
# data_format = "influx"
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
AWS Data Firehose
-
Real-Time Data Analytics: Using the AWS Data Firehose plugin, organizations can stream data in real-time from various sources, such as application logs or IoT devices, directly into analytics platforms. This allows data teams to analyze incoming data as it is generated, enabling rapid insights and operational adjustments based on fresh metrics.
-
Profile Access Patterns for Optimization: By collecting data about how clients interact with applications through AWS Data Firehose, businesses can gain valuable insights into user behavior. This can drive content personalization strategies or optimize server architecture for better performance based on traffic patterns.
-
Automated Alerting Mechanism: Integrating AWS Data Firehose with alerting systems via this plugin allows teams to set up automated alerts based on specific metrics collected. For example, if a particular threshold is reached in the input data, alerts can trigger operations teams to investigate potential issues before they escalate.
Thanos
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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
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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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