Ceph and MariaDB Integration

Input and output integration overview

The Ceph plugin for Telegraf helps in gathering performance metrics from both MON and OSD nodes in a Ceph storage cluster for effective monitoring and management.

This plugin writes metrics from Telegraf directly into MariaDB using parameterized SQL INSERT statements, offering a flexible way to store metrics in structured, relational tables.

Integration details

Ceph

The Ceph Storage Telegraf plugin is designed to collect performance metrics from Monitor (MON) and Object Storage Daemon (OSD) nodes within a Ceph storage cluster. Ceph, a highly scalable storage system, integrates its metrics collection through this plugin, facilitating easy monitoring of its components. With the introduction of this plugin in the 13.x Mimic release, users can effectively gather detailed insights into the performance and health of their Ceph infrastructure. It functions by scanning configured socket directories for specific Ceph service socket files, executing commands via the Ceph administrative interface, and parsing the returned JSON data for metrics. The metrics are organized based on top-level keys, allowing for efficient monitoring and analysis of cluster performance. This plugin provides valuable capabilities for managing and maintaining the performance of a Ceph cluster by allowing administrators to understand system behavior and identify potential issues proactively.

MariaDB

The SQL output plugin in Telegraf enables direct writing of metrics into SQL-compatible databases like MariaDB by executing parameterized SQL statements. With support for the MySQL driver, the plugin seamlessly integrates with MariaDB for reliable, structured metric storage. This setup is ideal for users who prefer SQL-based analytics or want to store metrics alongside business data for unified querying. MariaDB is a community-developed, enterprise-grade fork of MySQL that emphasizes performance, security, and openness. The plugin supports inserting time series metrics into custom schemas, enabling flexible analytics and integrations with BI tools like Metabase or Grafana using SQL connectors.

Configuration

Ceph

[[inputs.ceph]]
  ## This is the recommended interval to poll. Too frequent and you
  ## will lose data points due to timeouts during rebalancing and recovery
  interval = '1m'

  ## All configuration values are optional, defaults are shown below

  ## location of ceph binary
  ceph_binary = "/usr/bin/ceph"

  ## directory in which to look for socket files
  socket_dir = "/var/run/ceph"

  ## prefix of MON and OSD socket files, used to determine socket type
  mon_prefix = "ceph-mon"
  osd_prefix = "ceph-osd"
  mds_prefix = "ceph-mds"
  rgw_prefix = "ceph-client"

  ## suffix used to identify socket files
  socket_suffix = "asok"

  ## Ceph user to authenticate as, ceph will search for the corresponding
  ## keyring e.g. client.admin.keyring in /etc/ceph, or the explicit path
  ## defined in the client section of ceph.conf for example:
  ##
  ##     [client.telegraf]
  ##         keyring = /etc/ceph/client.telegraf.keyring
  ##
  ## Consult the ceph documentation for more detail on keyring generation.
  ceph_user = "client.admin"

  ## Ceph configuration to use to locate the cluster
  ceph_config = "/etc/ceph/ceph.conf"

  ## Whether to gather statistics via the admin socket
  gather_admin_socket_stats = true

  ## Whether to gather statistics via ceph commands, requires ceph_user
  ## and ceph_config to be specified
  gather_cluster_stats = false

MariaDB

[[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})"

  ## SQL INSERT statement with placeholders. Telegraf will substitute values at runtime.
  ## table_template = "INSERT INTO metrics (timestamp, name, value, tags) VALUES (?, ?, ?, ?)"

  ## 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

Ceph

1. Dynamic Monitoring Dashboard: Utilize the Ceph plugin to create a real-time monitoring dashboard that visually represents the performance metrics of your Ceph cluster. By integrating these metrics into a centralized dashboard, system administrators can gain immediate insights into the health of the storage infrastructure, which aids in quickly identifying and addressing potential issues before they escalate.

2. Automated Alerting System: Implement the Ceph plugin in conjunction with an alerting solution to automatically notify administrators of performance degradation or operational issues within the Ceph cluster. By defining thresholds for key metrics, organizations can ensure prompt response actions, thereby improving overall system reliability and performance.

3. Performance Benchmarking: Use the metrics collected by this plugin to conduct performance benchmarking tests across different configurations or hardware setups of your Ceph storage cluster. This process can assist organizations in identifying optimal configurations that enhance performance and resource utilization, promoting a more efficient storage environment.

4. Capacity Planning and Forecasting: Integrate the metrics gathered from the Ceph storage plugin into broader data analytics and reporting tools to facilitate capacity planning. By analyzing historical metrics, organizations can forecast future utilization trends, enabling informed decisions about scaling storage resources effectively.

MariaDB

1. Business Intelligence Integration: Store application performance metrics directly into MariaDB and connect it to BI tools like Metabase or Apache Superset. This setup allows blending of operational data with business KPIs for unified dashboards, enhancing visibility across departments.

2. Compliance Reporting with Historical Metrics: Use this plugin to log metrics into MariaDB for audit and compliance use cases. The relational model enables precise querying of past performance indicators with timestamped entries, supporting regulatory documentation.

3. Custom Alerting Based on SQL Logic: Insert metrics into MariaDB and use custom SQL queries to define alert thresholds or conditions. Combined with cron jobs or scheduled scripts, this enables advanced alerting workflows not possible with traditional metric platforms.

4. IoT Sensor Metrics Storage: Collect sensor data from IoT devices via Telegraf and store it in MariaDB using a normalized schema. This approach is cost-effective and integrates well with existing SQL-based systems for real-time or historical analysis.

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