IPVS and Elasticsearch Integration
Powerful performance with an easy integration, powered by Telegraf, the open source data connector built by InfluxData.
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Table of Contents
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
The IPVS plugin is designed to collect metrics related to IPVS virtual and real servers on Linux systems.
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
IPVS
The IPVS plugin gathers metrics about IPVS virtual and real servers using the Linux kernel netlink socket interface. As a component specifically designed for Linux, it tracks performance related to IP virtual servers, allowing users to monitor various attributes such as active connections, packet statistics, and byte counts. Key metrics include those for both virtual and real servers, facilitating a comprehensive view of server performance. The plugin also requires the Telegraf process to run with appropriate permissions, typically as root or a user with specific capabilities for proper operation.
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
IPVS
[[inputs.ipvs]]
# no configuration
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
IPVS
-
Load Balancing Performance Monitoring: Use the IPVS plugin to monitor the performance of a load balancing setup in a Linux environment where IPVS is implemented. By collecting metrics such as byte counts, packet rates, and active connections, administrators can gain real-time insights into server performance, allowing for proactive adjustments to load distribution strategies and ensuring that no individual server becomes a bottleneck.
-
Automated Alerting for Connection Thresholds: Integrate the metrics collected by the IPVS plugin with an alerting system to automatically notify administrators when active connections exceed or fall below specified thresholds. This use case enables dynamic scaling of backend resources, optimizing application performance and resource utilization, while minimizing the risk of sudden service disruptions.
-
Historical Performance Trend Analysis: Store the metrics gathered by the IPVS plugin in a time-series database for historical analysis. By analyzing trends over time, organizations can identify patterns in server performance, correlate them with application usage spikes, and make informed decisions regarding infrastructure upgrades or maintenance schedules to better handle peak loads.
Elasticsearch
-
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 named
telegraf-2023.01.01
, allowing easy time-based queries and retention policies. -
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.
-
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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