Mesos and OpenTSDB Integration

Input and output integration overview

This input plugin gathers metrics from Mesos.

The OpenTSDB plugin facilitates the integration of Telegraf with OpenTSDB, allowing users to push time-series metrics to an OpenTSDB backend seamlessly.

Integration details

Mesos

The Mesos plugin for Telegraf is designed to collect and report metrics from Apache Mesos clusters, which is essential for monitoring and observability in container orchestration and resource management. Mesos, known for its scalability and ability to manage diverse workloads, generates various metrics about resource usage, tasks, frameworks, and overall system performance. By utilizing this plugin, users can track the health and efficiency of their Mesos clusters, gather insights into resource distribution, and ensure that applications receive the necessary resources in a timely manner. The configuration allows users to specify the relevant Mesos master’s details, along with the desired metric groups to collect, making it adaptable to different deployments and monitoring needs. Overall, this plugin integrates seamlessly within the Telegraf collection pipeline, supporting detailed observability for cloud-native environments.

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

Mesos

[[inputs.mesos]]
  ## Timeout, in ms.
  timeout = 100

  ## A list of Mesos masters.
  masters = ["http://localhost:5050"]

  ## Master metrics groups to be collected, by default, all enabled.
  master_collections = [
    "resources",
    "master",
    "system",
    "agents",
    "frameworks",
    "framework_offers",
    "tasks",
    "messages",
    "evqueue",
    "registrar",
    "allocator",
  ]

  ## A list of Mesos slaves, default is []
  # slaves = []

  ## Slave metrics groups to be collected, by default, all enabled.
  # slave_collections = [
  #   "resources",
  #   "agent",
  #   "system",
  #   "executors",
  #   "tasks",
  #   "messages",
  # ]

  ## 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 = false

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

Mesos

1. Resource Utilization Monitoring: Use the Mesos plugin to continually monitor CPU, memory, and disk usage across your Mesos cluster. For a rapidly scaling application, tracking these metrics helps ensure that resources are dynamically allocated according to workloads, preventing bottlenecks and optimizing performance.

2. Framework Performance Analysis: Integrate this plugin to measure the performance of different frameworks running on Mesos. By comparing active frameworks and their task success rates, you can identify which frameworks provide the best resource efficiency or may require optimization.

3. Alerts for System Health: Set up alerts based on metrics collected by the Mesos plugin to notify engineering teams when resource utilization exceeds key thresholds or when specific tasks fail. This allows for proactive intervention and maintenance before critical failures occur.

4. Capacity Planning: Utilize gathered metrics to analyze historical resource usage patterns to assist in capacity planning. By understanding peak loads and resource utilization trends, teams can make informed decisions on scaling infrastructure and deploying additional resources as needed.

OpenTSDB

1. 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.

2. 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.

3. 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.

4. 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

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