Mesos and Elasticsearch 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 Mesos and InfluxDB.

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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.

See Ways to Get Started

Input and output integration overview

This input plugin gathers metrics from Mesos.

The Telegraf Elasticsearch Plugin seamlessly sends metrics to an Elasticsearch server. The plugin handles template creation and dynamic index management, and supports various Elasticsearch-specific features to ensure data is formatted correctly for storage and retrieval.

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.

Elasticsearch

This plugin writes metrics to Elasticsearch, a distributed, RESTful search and analytics engine capable of storing large amounts of data in near real-time. It is designed to handle Elasticsearch versions 5.x through 7.x and utilizes its dynamic template features to manage data type mapping properly. The plugin supports advanced features such as template management, dynamic index naming, and integration with OpenSearch. It also allows configurations for authentication and health monitoring of the Elasticsearch nodes.

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

Elasticsearch


[[outputs.elasticsearch]]
  ## The full HTTP endpoint URL for your Elasticsearch instance
  ## Multiple urls can be specified as part of the same cluster,
  ## this means that only ONE of the urls will be written to each interval
  urls = [ "http://node1.es.example.com:9200" ] # required.
  ## Elasticsearch client timeout, defaults to "5s" if not set.
  timeout = "5s"
  ## Set to true to ask Elasticsearch a list of all cluster nodes,
  ## thus it is not necessary to list all nodes in the urls config option
  enable_sniffer = false
  ## Set to true to enable gzip compression
  enable_gzip = false
  ## Set the interval to check if the Elasticsearch nodes are available
  ## Setting to "0s" will disable the health check (not recommended in production)
  health_check_interval = "10s"
  ## Set the timeout for periodic health checks.
  # health_check_timeout = "1s"
  ## HTTP basic authentication details.
  ## HTTP basic authentication details
  # username = "telegraf"
  # password = "mypassword"
  ## HTTP bearer token authentication details
  # auth_bearer_token = "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9"

  ## Index Config
  ## The target index for metrics (Elasticsearch will create if it not exists).
  ## You can use the date specifiers below to create indexes per time frame.
  ## The metric timestamp will be used to decide the destination index name
  # %Y - year (2016)
  # %y - last two digits of year (00..99)
  # %m - month (01..12)
  # %d - day of month (e.g., 01)
  # %H - hour (00..23)
  # %V - week of the year (ISO week) (01..53)
  ## Additionally, you can specify a tag name using the notation {{tag_name}}
  ## which will be used as part of the index name. If the tag does not exist,
  ## the default tag value will be used.
  # index_name = "telegraf-{{host}}-%Y.%m.%d"
  # default_tag_value = "none"
  index_name = "telegraf-%Y.%m.%d" # required.

  ## Optional Index Config
  ## Set to true if Telegraf should use the "create" OpType while indexing
  # use_optype_create = false

  ## 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

  ## Template Config
  ## Set to true if you want telegraf to manage its index template.
  ## If enabled it will create a recommended index template for telegraf indexes
  manage_template = true
  ## The template name used for telegraf indexes
  template_name = "telegraf"
  ## Set to true if you want telegraf to overwrite an existing template
  overwrite_template = false
  ## If set to true a unique ID hash will be sent as sha256(concat(timestamp,measurement,series-hash)) string
  ## it will enable data resend and update metric points avoiding duplicated metrics with different id's
  force_document_id = false

  ## Specifies the handling of NaN and Inf values.
  ## This option can have the following values:
  ##    none    -- do not modify field-values (default); will produce an error if NaNs or infs are encountered
  ##    drop    -- drop fields containing NaNs or infs
  ##    replace -- replace with the value in "float_replacement_value" (default: 0.0)
  ##               NaNs and inf will be replaced with the given number, -inf with the negative of that number
  # float_handling = "none"
  # float_replacement_value = 0.0

  ## Pipeline Config
  ## To use a ingest pipeline, set this to the name of the pipeline you want to use.
  # use_pipeline = "my_pipeline"
  ## Additionally, you can specify a tag name using the notation {{tag_name}}
  ## which will be used as part of the pipeline name. If the tag does not exist,
  ## the default pipeline will be used as the pipeline. If no default pipeline is set,
  ## no pipeline is used for the metric.
  # use_pipeline = "{{es_pipeline}}"
  # default_pipeline = "my_pipeline"
  #
  # Custom HTTP headers
  # To pass custom HTTP headers please define it in a given below section
  # [outputs.elasticsearch.headers]
  #    "X-Custom-Header" = "custom-value"

  ## Template Index Settings
  ## Overrides the template settings.index section with any provided options.
  ## Defaults provided here in the config
  # template_index_settings = {
  #   refresh_interval = "10s",
  #   mapping.total_fields.limit = 5000,
  #   auto_expand_replicas = "0-1",
  #   codec = "best_compression"
  # }

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.

Elasticsearch

  1. Time-based Indexing: Use this plugin to store metrics in Elasticsearch to index each metric based on the time collected. For example, CPU metrics can be stored in a daily index namedtelegraf-2023.01.01, allowing easy time-based queries and retention policies.

  2. Dynamic Templates Management: Utilize the template management feature to automatically create a custom template tailored to your metrics. This allows you to define how different fields are indexed and analyzed without manually configuring Elasticsearch, ensuring an optimal data structure for querying.

  3. OpenSearch Compatibility: If you are using AWS OpenSearch, you can configure this plugin to work seamlessly by activating compatibility mode, ensuring your existing Elasticsearch clients remain functional and compatible with newer cluster setups.

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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