Hashicorp Nomad and MySQL 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 Nomad 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 allows users to collect metrics from Hashicorp Nomad agents in distributed environments.

The Telegraf SQL plugin allows you to store metrics from Telegraf directly into a MySQL database, making it easier to analyze and visualize the collected metrics.

Integration details

Hashicorp Nomad

The Hashicorp Nomad input plugin is designed to gather metrics from every Nomad agent within a cluster. By deploying Telegraf on each node, it can connect to the local Nomad agent, typically available at ‘http://127.0.0.1:4646’. With this setup, users can systematically collect and monitor metrics related to the performance and status of their Nomad environment, ensuring they maintain a healthy and efficient cluster operational state. This plugin enables visibility into the operational aspects of Nomad, which is essential for maintaining reliable cloud infrastructure.

MySQL

Telegraf’s SQL output plugin is designed to seamlessly write metric data to a SQL database by dynamically creating tables and columns based on the incoming metrics. When configured for MySQL, the plugin leverages the go-sql-driver/mysql, which requires enabling the ANSI_QUOTES SQL mode to ensure proper handling of quoted identifiers. This dynamic schema creation approach ensures that each metric is stored in its own table with a structure derived from its fields and tags, providing a detailed, timestamped record of system performance. The flexibility of the plugin allows it to handle high-throughput environments, making it ideal for scenarios that demand robust, granular metric logging and historical data analysis.

Configuration

Hashicorp Nomad

[[inputs.nomad]]
  ## URL for the Nomad agent
  # url = "http://127.0.0.1:4646"

  ## Set response_timeout (default 5 seconds)
  # response_timeout = "5s"

  ## Optional TLS Config
  # tls_ca = /path/to/cafile
  # tls_cert = /path/to/certfile
  # tls_key = /path/to/keyfile

MySQL

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

  ## Data source name
  ## The format of the data source name is different for each database driver.
  ## See the plugin readme for details.
  data_source_name = "username:password@tcp(host:port)/dbname"

  ## 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} - tablename as a quoted identifier
  table_exists_template = "SELECT 1 FROM {TABLE} LIMIT 1"

  ## Initialization SQL
  init_sql = "SET sql_mode='ANSI_QUOTES';"

  ## 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

  ## 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

  ## Metric type to SQL type conversion
  ## The values on the left are the data types Telegraf has and the values on
  ## the right are the data types Telegraf will use when sending to a database.
  ##
  ## The database values used must be data types the destination database
  ## understands. It is up to the user to ensure that the selected data type is
  ## available in the database they are using. Refer to your database
  ## documentation for what data types are available and supported.
  #[outputs.sql.convert]
  #  integer              = "INT"
  #  real                 = "DOUBLE"
  #  text                 = "TEXT"
  #  timestamp            = "TIMESTAMP"
  #  defaultvalue         = "TEXT"
  #  unsigned             = "UNSIGNED"
  #  bool                 = "BOOL"
  #  ## This setting controls the behavior of the unsigned value. By default the
  #  ## setting will take the integer value and append the unsigned value to it. The other
  #  ## option is "literal", which will use the actual value the user provides to
  #  ## the unsigned option. This is useful for a database like ClickHouse where
  #  ## the unsigned value should use a value like "uint64".
  #  # conversion_style = "unsigned_suffix"

Input and output integration examples

Hashicorp Nomad

  1. Cluster Health Monitoring: Use the Hashicorp Nomad plugin to aggregate metrics across all nodes in a Nomad deployment. By monitoring health metrics such as allocation status, job performance, and resource utilization, operations teams can gain insights into the overall health of their deployment, quickly identify and resolve issues, and optimize resource allocation based on real-time data.

  2. Performance Analytics for Job Execution: Leverage the metrics provided by Nomad to analyze job execution times and resource consumption. This use case enables developers to adjust job parameters effectively, optimize task performance, and illustrate trends over time, ultimately leading to increased efficiency and reduced costs in resource allocation.

  3. Alerting on Critical Conditions: Implement alerting mechanisms based on metrics scraped from Nomad agents. By setting thresholds for critical metrics like CPU usage or failed job allocations, teams can proactively respond to potential issues before they escalate, ensuring higher uptime and reliability for applications running on the Nomad platform.

  4. Integration with Visualization Tools: Use the data collected by the Hashicorp Nomad plugin to feed into visualization tools for real-time dashboards. This setup allows teams to monitor cluster workloads, job states, and system performance at a glance, facilitating better decision-making and strategic planning based on visual insights into the Nomad environment.

MySQL

  1. Real-Time Web Analytics Storage: Leverage the plugin to capture website performance metrics and store them in MySQL. This setup enables teams to monitor user interactions, analyze traffic patterns, and dynamically adjust site features based on real-time data insights.

  2. IoT Device Monitoring: Utilize the plugin to collect metrics from a network of IoT sensors and log them into a MySQL database. This use case supports continuous monitoring of device health and performance, allowing for predictive maintenance and immediate response to anomalies.

  3. Financial Transaction Logging: Record high-frequency financial transaction data with precise timestamps. This approach supports robust audit trails, real-time fraud detection, and comprehensive historical analysis for compliance and reporting purposes.

  4. Application Performance Benchmarking: Integrate the plugin with application performance monitoring systems to log metrics into MySQL. This facilitates detailed benchmarking and trend analysis over time, enabling organizations to identify performance bottlenecks and optimize resource allocation effectively.

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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