IPVS and Graphite Integration

Input and output integration overview

The IPVS plugin is designed to collect metrics related to IPVS virtual and real servers on Linux systems.

The Graphite plugin enables users to send metrics collected by Telegraf into Graphite via TCP. This integration allows for efficient storage and visualization of time-series data using Graphite’s powerful capabilities.

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.

Graphite

This plugin writes metrics to Graphite via raw TCP, allowing for seamless integration of Telegraf collected metrics into the Graphite ecosystem. With this plugin, users can configure multiple TCP endpoints for load balancing, ensuring high availability and reliability in metric transmission. The ability to customize metric naming with prefixes and utilize various templating options enhances flexibility in how data is represented within Graphite. Additionally, support for Graphite tags and options for strict sanitization of metric names allow for robust data management, catering to the varying needs of users. This capability is essential for organizations looking to leverage Graphite’s powerful metrics storage and visualization while maintaining control over data representation.

Configuration

IPVS

[[inputs.ipvs]]
  # no configuration

Graphite

# Configuration for Graphite server to send metrics to
[[outputs.graphite]]
  ## TCP endpoint for your graphite instance.
  ## If multiple endpoints are configured, the output will be load balanced.
  ## Only one of the endpoints will be written to with each iteration.
  servers = ["localhost:2003"]

  ## Local address to bind when connecting to the server
  ## If empty or not set, the local address is automatically chosen.
  # local_address = ""

  ## Prefix metrics name
  prefix = ""

  ## Graphite output template
  ## see https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_OUTPUT.md
  template = "host.tags.measurement.field"

  ## Strict sanitization regex
  ## This is the default sanitization regex that is used on data passed to the
  ## graphite serializer. Users can add additional characters here if required.
  ## Be aware that the characters, '/' '@' '*' are always replaced with '_',
  ## '..' is replaced with '.', and '\' is removed even if added to the
  ## following regex.
  # graphite_strict_sanitize_regex = '[^a-zA-Z0-9-:._=\p{L}]'

  ## Enable Graphite tags support
  # graphite_tag_support = false

  ## Applied sanitization mode when graphite tag support is enabled.
  ## * strict - uses the regex specified above
  ## * compatible - allows for greater number of characters
  # graphite_tag_sanitize_mode = "strict"

  ## Character for separating metric name and field for Graphite tags
  # graphite_separator = "."

  ## Graphite templates patterns
  ## 1. Template for cpu
  ## 2. Template for disk*
  ## 3. Default template
  # templates = [
  #  "cpu tags.measurement.host.field",
  #  "disk* measurement.field",
  #  "host.measurement.tags.field"
  #]

  ## timeout in seconds for the write connection to graphite
  # timeout = "2s"

  ## 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

Input and output integration examples

IPVS

1. 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.

2. 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.

3. 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.

Graphite

1. Dynamic Metric Visualization: The Graphite plugin can be utilized to feed real-time metrics from various sources, such as application performance data or server health metrics, into Graphite. This dynamic integration allows teams to create interactive dashboards that visualize key performance indicators, track trends over time, and make data-driven decisions to enhance system performance.

2. Load Balanced Metrics Collection: By configuring multiple TCP endpoints within the plugin, organizations can implement load balancing for metric transmission. This use case ensures that metric delivery is both resilient and efficient, reducing the risk of data loss during high-traffic periods and maintaining a reliable flow of information to Graphite.

3. Customized Metrics Tagging: With support for Graphite tags, users can employ the Graphite plugin to enhance the granularity of their metrics. Tagging metrics with relevant information, such as application environment or service type, allows for more refined queries and analytics, enabling teams to drill down into specific areas of interest for better operational insights.

4. Enhanced Data Sanitization: Leveraging the plugin’s strict sanitization options, users can ensure that their metric names comply with Graphite’s requirements. This proactive measure eliminates potential issues arising from invalid characters in metric names, allowing for cleaner data management and more accurate visualizations.

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.