HTTP and OpenTSDB Integration
Powerful performance with an easy integration, powered by Telegraf, the open source data connector built by InfluxData.
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Time series database
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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
The HTTP plugin allows for the collection of metrics from specified HTTP endpoints, handling various data formats and authentication methods.
The OpenTSDB plugin facilitates the integration of Telegraf with OpenTSDB, allowing users to push time-series metrics to an OpenTSDB backend seamlessly.
Integration details
HTTP
The HTTP plugin collects metrics from one or more HTTP(S) endpoints, which should have metrics formatted in one of the supported input data formats. It also supports secrets from secret-stores for various authentication options and includes globally supported configuration settings.
OpenTSDB
The OpenTSDB plugin is designed to send metrics to an OpenTSDB instance using either the telnet or HTTP mode. With the introduction of OpenTSDB 2.0, the recommended method for sending metrics is via the HTTP API, which allows for batch processing of metrics by configuring the ‘http_batch_size’. The plugin supports several configuration options including metrics prefixing, server host and port specification, URI path customization for reverse proxies, and debug options for diagnosing communication issues with OpenTSDB. This plugin is particularly useful in scenarios where time series data is generated and needs to be efficiently stored in a scalable time series database like OpenTSDB, making it suitable for a wide range of monitoring and analytics applications.
Configuration
HTTP
[[inputs.http]]
## One or more URLs from which to read formatted metrics.
urls = [
"http://localhost/metrics",
"http+unix:///run/user/420/podman/podman.sock:/d/v4.0.0/libpod/pods/json"
]
## HTTP method
# method = "GET"
## Optional HTTP headers
# headers = {"X-Special-Header" = "Special-Value"}
## HTTP entity-body to send with POST/PUT requests.
# body = ""
## HTTP Content-Encoding for write request body, can be set to "gzip" to
## compress body or "identity" to apply no encoding.
# content_encoding = "identity"
## Optional Bearer token settings to use for the API calls.
## Use either the token itself or the token file if you need a token.
# token = "eyJhbGc...Qssw5c"
# token_file = "/path/to/file"
## Optional HTTP Basic Auth Credentials
# username = "username"
# password = "pa$$word"
## OAuth2 Client Credentials. The options 'client_id', 'client_secret', and 'token_url' are required to use OAuth2.
# client_id = "clientid"
# client_secret = "secret"
# token_url = "https://indentityprovider/oauth2/v1/token"
# scopes = ["urn:opc:idm:__myscopes__"]
## HTTP Proxy support
# use_system_proxy = false
# http_proxy_url = ""
## Optional TLS Config
## Set to true/false to enforce TLS being enabled/disabled. If not set,
## enable TLS only if any of the other options are specified.
# tls_enable =
## Trusted root certificates for server
# tls_ca = "/path/to/cafile"
## Used for TLS client certificate authentication
# tls_cert = "/path/to/certfile"
## Used for TLS client certificate authentication
# tls_key = "/path/to/keyfile"
## Password for the key file if it is encrypted
# tls_key_pwd = ""
## Send the specified TLS server name via SNI
# tls_server_name = "kubernetes.example.com"
## Minimal TLS version to accept by the client
# tls_min_version = "TLS12"
## List of ciphers to accept, by default all secure ciphers will be accepted
## See https://pkg.go.dev/crypto/tls#pkg-constants for supported values.
## Use "all", "secure" and "insecure" to add all support ciphers, secure
## suites or insecure suites respectively.
# tls_cipher_suites = ["secure"]
## Renegotiation method, "never", "once" or "freely"
# tls_renegotiation_method = "never"
## Use TLS but skip chain & host verification
# insecure_skip_verify = false
## Optional Cookie authentication
# cookie_auth_url = "https://localhost/authMe"
# cookie_auth_method = "POST"
# cookie_auth_username = "username"
# cookie_auth_password = "pa$$word"
# cookie_auth_headers = { Content-Type = "application/json", X-MY-HEADER = "hello" }
# cookie_auth_body = '{"username": "user", "password": "pa$$word", "authenticate": "me"}'
## cookie_auth_renewal not set or set to "0" will auth once and never renew the cookie
# cookie_auth_renewal = "5m"
## Amount of time allowed to complete the HTTP request
# timeout = "5s"
## List of success status codes
# success_status_codes = [200]
## 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"
OpenTSDB
[[outputs.opentsdb]]
## prefix for metrics keys
prefix = "my.specific.prefix."
## DNS name of the OpenTSDB server
## Using "opentsdb.example.com" or "tcp://opentsdb.example.com" will use the
## telnet API. "http://opentsdb.example.com" will use the Http API.
host = "opentsdb.example.com"
## Port of the OpenTSDB server
port = 4242
## Number of data points to send to OpenTSDB in Http requests.
## Not used with telnet API.
http_batch_size = 50
## URI Path for Http requests to OpenTSDB.
## Used in cases where OpenTSDB is located behind a reverse proxy.
http_path = "/api/put"
## Debug true - Prints OpenTSDB communication
debug = false
## Separator separates measurement name from field
separator = "_"
Input and output integration examples
HTTP
- Collecting Metrics from Localhost: The plugin can fetch metrics from an HTTP endpoint like
http://localhost/metrics
, allowing for easy local monitoring. - Using Unix Domain Sockets: You can specify metrics collection from services over Unix domain sockets by using the http+unix scheme, for example,
http+unix:///path/to/service.sock:/api/endpoint
.
OpenTSDB
-
Real-time Infrastructure Monitoring: Utilize the OpenTSDB plugin to collect and store metrics from various infrastructure components. By configuring the plugin to push metrics to OpenTSDB, organizations can have a centralized view of their infrastructure health and performance over time.
-
Custom Application Metrics Tracking: Integrate the OpenTSDB plugin into custom applications to track key performance indicators (KPIs) such as response times, error rates, and user interactions. This setup allows developers and product teams to visualize application performance trends and make data-driven decisions.
-
Automated Anomaly Detection: Leverage the plugin in conjunction with machine learning algorithms to automatically detect anomalies in time-series data sent to OpenTSDB. By continuously monitoring the incoming metrics, the system can train models that alert users to potential issues before they affect application performance.
-
Historical Data Analysis: Use the OpenTSDB plugin to store and analyze historical performance data for capacity planning and trend analysis. This provides valuable insights into system behavior over time, helping teams to understand usage patterns and prepare for future growth.
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
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