HTTP and PostgreSQL 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

The HTTP plugin allows for the collection of metrics from specified HTTP endpoints, handling various data formats and authentication methods.

The Telegraf PostgreSQL plugin allows you to efficiently write metrics to a PostgreSQL database while automatically managing the database schema.

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.

PostgreSQL

This plugin writes metrics to PostgreSQL (or acompatible database) and manages the schema, automatically updating missing columns.

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"

PostgreSQL

# Publishes metrics to a postgresql database
[[outputs.postgresql]]
  ## Specify connection address via the standard libpq connection string:
  ##   host=... user=... password=... sslmode=... dbname=...
  ## Or a URL:
  ##   postgres://[user[:password]]@localhost[/dbname]?sslmode=[disable|verify-ca|verify-full]
  ## See https://www.postgresql.org/docs/current/libpq-connect.html#LIBPQ-CONNSTRING
  ##
  ## All connection parameters are optional. Environment vars are also supported.
  ## e.g. PGPASSWORD, PGHOST, PGUSER, PGDATABASE
  ## All supported vars can be found here:
  ##  https://www.postgresql.org/docs/current/libpq-envars.html
  ##
  ## Non-standard parameters:
  ##   pool_max_conns (default: 1) - Maximum size of connection pool for parallel (per-batch per-table) inserts.
  ##   pool_min_conns (default: 0) - Minimum size of connection pool.
  ##   pool_max_conn_lifetime (default: 0s) - Maximum age of a connection before closing.
  ##   pool_max_conn_idle_time (default: 0s) - Maximum idle time of a connection before closing.
  ##   pool_health_check_period (default: 0s) - Duration between health checks on idle connections.
  # connection = ""

  ## Postgres schema to use.
  # schema = "public"

  ## Store tags as foreign keys in the metrics table. Default is false.
  # tags_as_foreign_keys = false

  ## Suffix to append to table name (measurement name) for the foreign tag table.
  # tag_table_suffix = "_tag"

  ## Deny inserting metrics if the foreign tag can't be inserted.
  # foreign_tag_constraint = false

  ## Store all tags as a JSONB object in a single 'tags' column.
  # tags_as_jsonb = false

  ## Store all fields as a JSONB object in a single 'fields' column.
  # fields_as_jsonb = false

  ## Name of the timestamp column
  ## NOTE: Some tools (e.g. Grafana) require the default name so be careful!
  # timestamp_column_name = "time"

  ## Type of the timestamp column
  ## Currently, "timestamp without time zone" and "timestamp with time zone"
  ## are supported
  # timestamp_column_type = "timestamp without time zone"

  ## Templated statements to execute when creating a new table.
  # create_templates = [
  #   '''CREATE TABLE {{ .table }} ({{ .columns }})''',
  # ]

  ## Templated statements to execute when adding columns to a table.
  ## Set to an empty list to disable. Points containing tags for which there is no column will be skipped. Points
  ## containing fields for which there is no column will have the field omitted.
  # add_column_templates = [
  #   '''ALTER TABLE {{ .table }} ADD COLUMN IF NOT EXISTS {{ .columns|join ", ADD COLUMN IF NOT EXISTS " }}''',
  # ]

  ## Templated statements to execute when creating a new tag table.
  # tag_table_create_templates = [
  #   '''CREATE TABLE {{ .table }} ({{ .columns }}, PRIMARY KEY (tag_id))''',
  # ]

  ## Templated statements to execute when adding columns to a tag table.
  ## Set to an empty list to disable. Points containing tags for which there is no column will be skipped.
  # tag_table_add_column_templates = [
  #   '''ALTER TABLE {{ .table }} ADD COLUMN IF NOT EXISTS {{ .columns|join ", ADD COLUMN IF NOT EXISTS " }}''',
  # ]

  ## The postgres data type to use for storing unsigned 64-bit integer values (Postgres does not have a native
  ## unsigned 64-bit integer type).
  ## The value can be one of:
  ##   numeric - Uses the PostgreSQL "numeric" data type.
  ##   uint8 - Requires pguint extension (https://github.com/petere/pguint)
  # uint64_type = "numeric"

  ## When using pool_max_conns>1, and a temporary error occurs, the query is retried with an incremental backoff. This
  ## controls the maximum backoff duration.
  # retry_max_backoff = "15s"

  ## Approximate number of tag IDs to store in in-memory cache (when using tags_as_foreign_keys).
  ## This is an optimization to skip inserting known tag IDs.
  ## Each entry consumes approximately 34 bytes of memory.
  # tag_cache_size = 100000

  ## Enable & set the log level for the Postgres driver.
  # log_level = "warn" # trace, debug, info, warn, error, none

Input and output integration examples

HTTP

  1. Collecting Metrics from Localhost: The plugin can fetch metrics from an HTTP endpoint like http://localhost/metrics, allowing for easy local monitoring.
  2. 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.

PostgreSQL

  1. Monitoring Database Performance: You can use this plugin to regularly send metrics on PostgreSQL performance such as active connections, query performance, and resource usage, allowing for better monitoring and optimization of your database.

  2. Integrating with TimescaleDB: If you’re using TimescaleDB for time-series data storage, this plugin can help you write metrics directly into a hypertable. This allows you to benefit from TimescaleDB’s advanced time-series capabilities while leveraging standard PostgreSQL features.

  3. Data Archiving: Create a long-term data archiving solution where you can push metrics into PostgreSQL for historical analysis. The plugin’s support for JSONB allows you to store complex data structures directly into a single column, making retrieval efficient.

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

Kafka 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 Integration

Kinesis 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

MQTT and InfluxDB Integration

The MQTT plugin is a service input for reading metrics from specified MQTT topics. It supports various data formats and configuration options for reliable message consumption.

View Integration