Icinga and Snowflake Integration

Powerful performance with an easy integration, powered by Telegraf, the open source data connector built by InfluxData.

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This is not the recommended configuration for real-time query at scale. For query and compression optimization, high-speed ingest, and high availability, you may want to consider Icinga and InfluxDB.

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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.

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Input and output integration overview

This plugin gathers services & hosts status using Icinga2 Remote API, providing an interface to monitor your infrastructure effectively.

Telegraf’s SQL plugin allows seamless metric storage in SQL databases. When configured for Snowflake, it employs a specialized DSN format and dynamic table creation to map metrics to the appropriate schema.

Integration details

Icinga

The Icinga2 Plugin enables users to gather status information from Icinga2’s Remote API. Icinga2 is a powerful monitoring system that checks the health of hosts and services and provides detailed monitoring capabilities. The plugin facilitates retrieving metrics such as the state of hosts and services, as well as detailed API status metrics. This integration is vital for users looking to keep an eye on their infrastructure’s health and performance metrics automatically, leveraging the Icinga2’s extensive API. By utilizing this plugin, users can easily integrate Icinga2 monitoring data with other systems, providing a comprehensive view of their infrastructure status.

Snowflake

Telegraf’s SQL plugin is engineered to dynamically write metrics into an SQL database by creating tables and columns based on the incoming data. When configured for Snowflake, it employs the gosnowflake driver, which uses a DSN that encapsulates credentials, account details, and database configuration in a compact format. This setup allows for the automatic generation of tables where each metric is recorded with precise timestamps, thereby ensuring detailed historical tracking. Although the integration is considered experimental, it leverages Snowflake’s powerful data warehousing capabilities, making it suitable for scalable, cloud-based analytics and reporting solutions.

Configuration

Icinga

[[inputs.icinga2]]
  ## Required Icinga2 server address
  # server = "https://localhost:5665"

  ## Collected Icinga2 objects ("services", "hosts")
  ## Specify at least one object to collect from /v1/objects endpoint.
  # objects = ["services"]

  ## Collect metrics from /v1/status endpoint
  ## Choose from:
  ##     "ApiListener", "CIB", "IdoMysqlConnection", "IdoPgsqlConnection"
  # status = []

  ## Credentials for basic HTTP authentication
  # username = "admin"
  # password = "admin"

  ## Maximum time to receive response.
  # response_timeout = "5s"

  ## 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 = true

Snowflake

[[outputs.sql]]
  ## Database driver
  ## Valid options: mssql (Microsoft SQL Server), mysql (MySQL), pgx (Postgres),
  ## sqlite (SQLite3), snowflake (snowflake.com), clickhouse (ClickHouse)
  driver = "snowflake"

  ## Data source name
  ## For Snowflake, the DSN format typically includes the username, password, account identifier, and optional warehouse, database, and schema.
  ## Example DSN: "username:password@account/warehouse/db/schema"
  data_source_name = "username:password@account/warehouse/db/schema"

  ## Timestamp column name
  timestamp_column = "timestamp"

  ## Table creation template
  ## Available template variables:
  ##  {TABLE}        - table name as a quoted identifier
  ##  {TABLELITERAL} - table name as a quoted string literal
  ##  {COLUMNS}      - column definitions (list of quoted identifiers and types)
  table_template = "CREATE TABLE {TABLE} ({COLUMNS})"

  ## Table existence check template
  ## Available template variables:
  ##  {TABLE} - table name as a quoted identifier
  table_exists_template = "SELECT 1 FROM {TABLE} LIMIT 1"

  ## Initialization SQL (optional)
  init_sql = ""

  ## Maximum amount of time a connection may be idle. "0s" means connections are never closed due to idle time.
  connection_max_idle_time = "0s"

  ## Maximum amount of time a connection may be reused. "0s" means connections are never closed due to age.
  connection_max_lifetime = "0s"

  ## Maximum number of connections in the idle connection pool. 0 means unlimited.
  connection_max_idle = 2

  ## Maximum number of open connections to the database. 0 means unlimited.
  connection_max_open = 0

  ## Metric type to SQL type conversion
  ## Defaults to ANSI/ISO SQL types unless overridden. Adjust if needed for Snowflake compatibility.
  #[outputs.sql.convert]
  #  integer       = "INT"
  #  real          = "DOUBLE"
  #  text          = "TEXT"
  #  timestamp     = "TIMESTAMP"
  #  defaultvalue  = "TEXT"
  #  unsigned      = "UNSIGNED"
  #  bool          = "BOOL"

Input and output integration examples

Icinga

  1. Centralized Monitoring Dashboard: Integrate the Icinga2 plugin with a visualization tool to create a centralized monitoring dashboard that presents real-time statuses of all monitored services and hosts. This setup allows teams to quickly identify issues and to respond proactively, ensuring minimal downtime.

  2. Automated Incident Response: Use the metrics collected by the plugin to trigger automated incident response workflows. For instance, if a service is reported as critical, an automated system could notify relevant team members and even attempt to restart the service, reducing manual intervention and speeding resolution times.

  3. Service Reliability Reporting: Combine data from the Icinga with business reporting systems to generate insights on service reliability. By analyzing trends in service states over time, organizations can identify weak points in their infrastructure and improve service availability based on factual data.

  4. Cross-System Alerting: Leverage the collected metrics to integrate with various alerting systems. This could route notifications based on specific Icinga2 service states to different departments or teams depending on their roles, enabling tailored and timely responses to potential issues in the infrastructure.

Snowflake

  1. Cloud-Based Data Lake Integration: Utilize the plugin to stream real-time metrics from various sources into Snowflake, enabling the creation of a centralized data lake. This integration supports complex analytics and machine learning workflows on cloud data.

  2. Dynamic Business Intelligence Dashboards: Leverage the plugin to automatically generate tables from incoming metrics and feed them into BI tools. This allows businesses to create dynamic dashboards that visualize performance trends and operational insights without manual schema management.

  3. Scalable IoT Analytics: Deploy the plugin to capture high-frequency data from IoT devices into Snowflake. This use case facilitates the aggregation and analysis of sensor data, enabling predictive maintenance and real-time monitoring at scale.

  4. Historical Trend Analysis for Compliance: Use the plugin to log and archive detailed metric data in Snowflake, which can then be queried for long-term trend analysis and compliance reporting. This setup ensures that organizations can maintain a robust audit trail and perform forensic analysis if needed.

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

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