Suricata and Librato Integration
Powerful performance with an easy integration, powered by Telegraf, the open source data connector built by InfluxData.
5B+
Telegraf downloads
#1
Time series database
Source: DB Engines
1B+
Downloads of InfluxDB
2,800+
Contributors
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
This plugin reports internal performance counters of the Suricata IDS/IPS engine and processes the incoming data to fit Telegraf’s format.
The Librato plugin for Telegraf is designed to facilitate seamless integration with the Librato Metrics API, allowing for efficient metric reporting and monitoring.
Integration details
Suricata
The Suricata plugin captures and reports internal performance metrics from the Suricata IDS/IPS engine, which includes a wide range of statistics such as traffic volume, memory usage, uptime, and counters for flows and alerts. This plugin listens for JSON-formatted log outputs from Suricata, allowing it to parse and format the data for integration with Telegraf. It operates as a service input plugin, meaning it actively waits for metrics or events from Suricata rather than collecting metrics at predefined intervals. The plugin supports configurations for different metrics versions allowing for enhanced flexibility and detailed data gathering.
Librato
The Librato plugin enables Telegraf to send metrics to the Librato Metrics API. To authenticate, users must provide an api_user
and api_token
, which can be acquired from the Librato account settings. This integration allows for efficient monitoring and reporting of custom metrics within the Librato platform. The plugin also utilizes a source_tag
option that can enrich the metrics with contextual information from Point Tags; however, it does not currently support sending associated Point Tags. It is essential to note that any point value sent that cannot be converted to a float64 type will be skipped, ensuring that only valid metrics are processed and sent to Librato. The plugin also supports secret-store options for managing sensitive authentication credentials securely, facilitating best practices in credential management.
Configuration
Suricata
[[inputs.suricata]]
## Source
## Data sink for Suricata stats log. This is expected to be a filename of a
## unix socket to be created for listening.
# source = "/var/run/suricata-stats.sock"
## Delimiter
## Used for flattening field keys, e.g. subitem "alert" of "detect" becomes
## "detect_alert" when delimiter is "_".
# delimiter = "_"
## Metric version
## Version 1 only collects stats and optionally will look for alerts if
## the configuration setting alerts is set to true.
## Version 2 parses any event type message by default and produced metrics
## under a single metric name using a tag to differentiate between event
## types. The timestamp for the message is applied to the generated metric.
## Additional tags and fields are included as well.
# version = "1"
## Alerts
## In metric version 1, only status is captured by default, alerts must be
## turned on with this configuration option. This option does not apply for
## metric version 2.
# alerts = false
Librato
[[outputs.librato]]
## Librato API Docs
## http://dev.librato.com/v1/metrics-authentication
## Librato API user
api_user = "[email protected]" # required.
## Librato API token
api_token = "my-secret-token" # required.
## Debug
# debug = false
## Connection timeout.
# timeout = "5s"
## Output source Template (same as graphite buckets)
## see https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_OUTPUT.md#graphite
## This template is used in librato's source (not metric's name)
template = "host"
Input and output integration examples
Suricata
-
Network Traffic Analysis: Utilize the Suricata plugin to track detailed metrics about network intrusion attempts and performance, aiding in real-time threat detection and response. By visualizing captured alerts and flow statistics, security teams can quickly pinpoint vulnerabilities and mitigate risks.
-
Performance Monitoring Dashboard: Create a dashboard using the Suricata Telegraf plugin metrics to monitor the health and performance of the IDS/IPS engine. This use case provides an overview of memory usage, captured packets, and alert statistics, allowing teams to maintain optimal operating conditions.
-
Automated Security Reporting: Leverage the plugin to generate regular reports on alert statistics and traffic patterns, helping security analysts to identify long-term trends and prepare strategic defense initiatives. Automated reports also ensure that the security posture of the network is continually assessed.
-
Real-time Alert Handling: Integrate Suricata’s alert metrics within a broader incident response automation framework. By incorporating the inputs from the Suricata plugin, organizations can develop smart triggers for alerting and automated response workflows that enhance reaction times to potential threats.
Librato
-
Real-time Application Monitoring: Utilize Librato to collect performance metrics from a web application in real-time. This setup involves sending response times, error rates, and user interactions to Librato, allowing developers to monitor the application’s health and performance metrics closely. By analyzing these metrics, teams can quickly identify and address performance bottlenecks or application failures before they impact end users.
-
Infrastructure Metrics Aggregation: Leverage this plugin to gather and send metrics from various infrastructure components, such as servers or containers, to Librato for centralized monitoring. Configuring the plugin to send CPU, memory usage, and disk I/O metrics enables system administrators to have a comprehensive view of infrastructure performance, assisting in capacity planning and resource optimization strategies.
-
Custom Metrics for Business Operations: Feed business-specific metrics, such as sales transactions or user sign-ups, to the Librato service using this plugin. By tracking these custom metrics, businesses can gain insights into their operational performance and make data-driven decisions to enhance their strategies, marketing efforts, or product development initiatives.
-
Anomaly Detection in Metrics: Implement monitoring tools that utilize machine learning for anomaly detection. By continuously sending real-time metrics to Librato, teams can analyze trends and automatically flag unusual behavior, such as sudden spikes in latency or unusual traffic patterns, enabling timely intervention and troubleshooting.
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
Related Integrations
Related Integrations
HTTP and InfluxDB Integration
The HTTP plugin collects metrics from one or more HTTP(S) endpoints. It supports various authentication methods and configuration options for data formats.
View IntegrationKafka and InfluxDB Integration
This plugin reads messages from Kafka and allows the creation of metrics based on those messages. It supports various configurations including different Kafka settings and message processing options.
View IntegrationKinesis and InfluxDB Integration
The Kinesis plugin allows for reading metrics from AWS Kinesis streams. It supports multiple input data formats and offers checkpointing features with DynamoDB for reliable message processing.
View Integration