AWS Data Firehose and Sensu 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 writes metrics events to Sensu via its HTTP events API, enabling seamless integration with the Sensu monitoring platform.
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.
Sensu
This plugin writes metrics events to Sensu via its HTTP events API. Sensu is a monitoring system that enables users to collect, analyze, and manage metrics from various components in their infrastructure. The plugin facilitates the integration of Telegraf, a server agent for collecting and reporting metrics, with the Sensu monitoring platform. Users can configure settings such as backend and agent API URLs, API keys for authentication, and optional TLS settings. The plugin’s core functionality is centered around sending metric events, including check and entity specifications, to Sensu, allowing for comprehensive monitoring and alerting. The API reference provides extensive details about the events and metrics structure, ensuring users can efficiently leverage Sensu’s capabilities for observability and incident response.
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"
Sensu
[[outputs.sensu]]
## BACKEND API URL is the Sensu Backend API root URL to send metrics to
## (protocol, host, and port only). The output plugin will automatically
## append the corresponding backend API path
## /api/core/v2/namespaces/:entity_namespace/events/:entity_name/:check_name).
##
## Backend Events API reference:
## https://docs.sensu.io/sensu-go/latest/api/events/
##
## AGENT API URL is the Sensu Agent API root URL to send metrics to
## (protocol, host, and port only). The output plugin will automatically
## append the correspeonding agent API path (/events).
##
## Agent API Events API reference:
## https://docs.sensu.io/sensu-go/latest/api/events/
##
## NOTE: if backend_api_url and agent_api_url and api_key are set, the output
## plugin will use backend_api_url. If backend_api_url and agent_api_url are
## not provided, the output plugin will default to use an agent_api_url of
## http://127.0.0.1:3031
##
# backend_api_url = "http://127.0.0.1:8080"
# agent_api_url = "http://127.0.0.1:3031"
## API KEY is the Sensu Backend API token
## Generate a new API token via:
##
## $ sensuctl cluster-role create telegraf --verb create --resource events,entities
## $ sensuctl cluster-role-binding create telegraf --cluster-role telegraf --group telegraf
## $ sensuctl user create telegraf --group telegraf --password REDACTED
## $ sensuctl api-key grant telegraf
##
## For more information on Sensu RBAC profiles & API tokens, please visit:
## - https://docs.sensu.io/sensu-go/latest/reference/rbac/
## - https://docs.sensu.io/sensu-go/latest/reference/apikeys/
##
# api_key = "${SENSU_API_KEY}"
## Optional TLS Config
# tls_ca = "/etc/telegraf/ca.pem"
# tls_cert = "/etc/telegraf/cert.pem"
# tls_key = "/etc/telegraf/key.pem"
## Use TLS but skip chain & host verification
# insecure_skip_verify = false
## Timeout for HTTP message
# timeout = "5s"
## HTTP Content-Encoding for write request body, can be set to "gzip" to
## compress body or "identity" to apply no encoding.
# content_encoding = "identity"
## NOTE: Due to the way TOML is parsed, tables must be at the END of the
## plugin definition, otherwise additional config options are read as part of
## the table
## Sensu Event details
##
## Below are the event details to be sent to Sensu. The main portions of the
## event are the check, entity, and metrics specifications. For more information
## on Sensu events and its components, please visit:
## - Events - https://docs.sensu.io/sensu-go/latest/reference/events
## - Checks - https://docs.sensu.io/sensu-go/latest/reference/checks
## - Entities - https://docs.sensu.io/sensu-go/latest/reference/entities
## - Metrics - https://docs.sensu.io/sensu-go/latest/reference/events#metrics
##
## Check specification
## The check name is the name to give the Sensu check associated with the event
## created. This maps to check.metadata.name in the event.
[outputs.sensu.check]
name = "telegraf"
## Entity specification
## Configure the entity name and namespace, if necessary. This will be part of
## the entity.metadata in the event.
##
## NOTE: if the output plugin is configured to send events to a
## backend_api_url and entity_name is not set, the value returned by
## os.Hostname() will be used; if the output plugin is configured to send
## events to an agent_api_url, entity_name and entity_namespace are not used.
# [outputs.sensu.entity]
# name = "server-01"
# namespace = "default"
## Metrics specification
## Configure the tags for the metrics that are sent as part of the Sensu event
# [outputs.sensu.tags]
# source = "telegraf"
## Configure the handler(s) for processing the provided metrics
# [outputs.sensu.metrics]
# handlers = ["influxdb","elasticsearch"]
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.
Sensu
-
Real-Time Infrastructure Monitoring: Utilize the Sensu plugin to send performance metrics from various servers and services directly to Sensu. This real-time data flow enables teams to visualize infrastructure health, track resource usage, and receive immediate alerts for any anomalies detected. By centralizing monitoring through Sensu, organizations can create a holistic view of their systems and respond swiftly to issues.
-
Automated Incident Response Workflows: Leverage the plugin to automatically trigger incident response workflows based on the metrics events sent to Sensu. For example, if CPU usage exceeds a defined threshold, the Sensu system can be configured to alert the operations team, which can then initiate automated remediation processes, reducing downtime and maintaining system reliability. This integration allows for proactive management of system resources.
-
Dynamic Scaling of Resources: Use the Sensu plugin to feed metrics into an auto-scaling system that adjusts resources based on demand. By tracking metrics like request load and resource utilization, organizations can automatically scale their infrastructure up or down, ensuring optimal performance and cost efficiency without manual intervention.
-
Centralized Logging and Monitoring: Combine the Sensu with logging tools to send logs and performance metrics to a centralized monitoring system. This comprehensive approach allows teams to correlate logs with metric events, providing deeper insights into system behavior and performance, which aids in troubleshooting and performance optimization over time.
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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