Suricata and Loki 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 Suricata 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 plugin reports internal performance counters of the Suricata IDS/IPS engine and processes the incoming data to fit Telegraf’s format.

The Loki plugin allows users to send logs to Loki for aggregation and querying, leveraging Loki’s efficient storage capabilities.

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.

Loki

This Loki plugin integrates with Grafana Loki, a powerful log aggregation system. By sending logs in a format compatible with Loki, this plugin allows for efficient storage and querying of logs. Each log entry is structured in a key-value format where keys represent the field names and values represent the corresponding log information. The sorting of logs by timestamp ensures that the log streams maintain chronological order when queried through Loki. This plugin’s support for secrets makes it easier to manage authentication parameters securely, while options for HTTP headers, gzip encoding, and TLS configuration enhance the adaptability and security of log transmission, fitting various deployment needs.

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

Loki

[[outputs.loki]]
  ## The domain of Loki
  domain = "https://loki.domain.tld"

  ## Endpoint to write api
  # endpoint = "/loki/api/v1/push"

  ## Connection timeout, defaults to "5s" if not set.
  # timeout = "5s"

  ## Basic auth credential
  # username = "loki"
  # password = "pass"

  ## Additional HTTP headers
  # http_headers = {"X-Scope-OrgID" = "1"}

  ## If the request must be gzip encoded
  # gzip_request = false

  ## Optional TLS Config
  # tls_ca = "/etc/telegraf/ca.pem"
  # tls_cert = "/etc/telegraf/cert.pem"
  # tls_key = "/etc/telegraf/key.pem"

  ## Sanitize Tag Names
  ## If true, all tag names will have invalid characters replaced with
  ## underscores that do not match the regex: ^[a-zA-Z_:][a-zA-Z0-9_:]*.
  # sanitize_label_names = false

  ## Metric Name Label
  ## Label to use for the metric name to when sending metrics. If set to an
  ## empty string, this will not add the label. This is NOT suggested as there
  ## is no way to differentiate between multiple metrics.
  # metric_name_label = "__name"

Input and output integration examples

Suricata

  1. 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.

  2. 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.

  3. 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.

  4. 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.

Loki

  1. Centralized Logging for Microservices: Utilize the Loki plugin to gather logs from multiple microservices running in a Kubernetes cluster. By directing logs to a centralized Loki instance, developers can monitor, search, and analyze logs from all services in one place, facilitating easier troubleshooting and performance monitoring. This setup streamlines operations and supports rapid response to issues across distributed applications.

  2. Real-Time Log Anomaly Detection: Combine Loki with monitoring tools to analyze log outputs in real-time for unusual patterns that could indicate system errors or security threats. Implementing anomaly detection on log streams enables teams to proactively identify and respond to incidents, thereby improving system reliability and enhancing security postures.

  3. Enhanced Log Processing with Gzip Compression: Configure the Loki plugin to utilize gzip compression for log transmission. This approach can reduce bandwidth usage and improve transmission speeds, especially beneficial in environments where network bandwidth may be a constraint. It’s particularly useful for high-volume logging applications where every byte counts and performance is critical.

  4. Multi-Tenancy Support with Custom Headers: Leverage the ability to add custom HTTP headers to segregate logs from different tenants in a multi-tenant application environment. By using the Loki plugin to send different headers for each tenant, operators can ensure proper log management and compliance with data isolation requirements, making it a versatile solution for SaaS applications.

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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