SNMP Trap and Apache Druid Integration

Input and output integration overview

The SNMP Trap Telegraf plugin enables the receipt of SNMP notifications, facilitating comprehensive network monitoring by capturing important events from network devices.

This plugin allows Telegraf to send JSON-formatted metrics to Apache Druid over HTTP, enabling real-time ingestion for analytical queries on high-volume time-series data.

Integration details

SNMP Trap

The SNMP Trap plugin serves as a receiving endpoint for SNMP notifications, known as traps and inform requests. Operating over UDP, it listens for incoming notifications, which can be configured to arrive on a specific port. This plugin is integral to network monitoring and management, allowing systems to collect and respond to SNMP traps sent from various devices across the network, including routers, switches, and servers. The plugin supports secure transmission options through SNMPv3, enabling authentication and encryption parameters to protect sensitive data. Additionally, it gives users the flexibility to configure multiple aspects of SNMP like MIB file locations, making it adaptable for various environments and use cases. Transitioning from the deprecated netsnmp backend to the more current gosmi backend is recommended to leverage its enhanced features and support. Users implementing this plugin can effectively monitor network events, automate responses to traps, and maintain a robust network monitoring infrastructure.

Apache Druid

This configuration uses Telegraf’s HTTP output plugin with json data format to send metrics directly to Apache Druid, a real-time analytics database designed for fast, ad hoc queries on high-ingest time-series data. Druid supports ingestion via HTTP POST to various components like the Tranquility service or native ingestion endpoints. The JSON format is ideal for structuring Telegraf metrics into event-style records for Druid’s columnar and time-partitioned storage engine. Druid excels at powering interactive dashboards and exploratory queries across massive datasets, making it an excellent choice for real-time observability and monitoring analytics when integrated with Telegraf.

Configuration

SNMP Trap

[[inputs.snmp_trap]]
  ## Transport, local address, and port to listen on.  Transport must
  ## be "udp://".  Omit local address to listen on all interfaces.
  ##   example: "udp://127.0.0.1:1234"
  ##
  ## Special permissions may be required to listen on a port less than
  ## 1024.  See README.md for details
  ##
  # service_address = "udp://:162"
  ##
  ## Path to mib files
  ## Used by the gosmi translator.
  ## To add paths when translating with netsnmp, use the MIBDIRS environment variable
  # path = ["/usr/share/snmp/mibs"]
  ##
  ## Deprecated in 1.20.0; no longer running snmptranslate
  ## Timeout running snmptranslate command
  # timeout = "5s"
  ## Snmp version; one of "1", "2c" or "3".
  # version = "2c"
  ## SNMPv3 authentication and encryption options.
  ##
  ## Security Name.
  # sec_name = "myuser"
  ## Authentication protocol; one of "MD5", "SHA", "SHA224", "SHA256", "SHA384", "SHA512" or "".
  # auth_protocol = "MD5"
  ## Authentication password.
  # auth_password = "pass"
  ## Security Level; one of "noAuthNoPriv", "authNoPriv", or "authPriv".
  # sec_level = "authNoPriv"
  ## Privacy protocol used for encrypted messages; one of "DES", "AES", "AES192", "AES192C", "AES256", "AES256C" or "".
  # priv_protocol = ""
  ## Privacy password used for encrypted messages.
  # priv_password = ""

Apache Druid

[[outputs.http]]
  ## Druid ingestion endpoint (e.g., Tranquility, HTTP Ingest, or Kafka REST Proxy)
  url = "http://druid-ingest.example.com/v1/post"

  ## Use POST method to send events
  method = "POST"

  ## Data format for Druid ingestion (expects JSON format)
  data_format = "json"

  ## Optional headers (may vary depending on Druid setup)
  # [outputs.http.headers]
  #   Content-Type = "application/json"
  #   Authorization = "Bearer YOUR_API_TOKEN"

  ## Optional timeout and TLS settings
  timeout = "10s"
  # tls_ca = "/path/to/ca.pem"
  # tls_cert = "/path/to/cert.pem"
  # tls_key = "/path/to/key.pem"
  # insecure_skip_verify = false

Input and output integration examples

SNMP Trap

1. Centralized Network Monitoring: Integrate the SNMP Trap plugin into a centralized monitoring solution to receive alerts about network devices in real-time. By configuring the plugin to listen for traps from various routers and switches, network administrators can swiftly react to issues, such as device outages or critical thresholds being surpassed. This setup enables proactive management and quick resolutions to network problems, ensuring minimal downtime.

2. Automated Incident Response: Use the SNMP Trap plugin to trigger automated incident response workflows whenever specific traps are received. For instance, if a trap indicating a hardware failure is detected, an automated script could be initiated to gather diagnostics, notify support personnel, or even attempt a remediation action. This approach enhances the efficiency of IT operations by reducing manual interference and speeding up response times.

3. Network Performance Analytics: Deploy the SNMP Trap plugin to collect performance metrics along with traps for a comprehensive view of network health. By aggregating this data into analytics platforms, network teams can analyze trends, identify bottlenecks, and optimize performance based on historical data. This allows for informed decision-making and strategic planning around network upgrades or changes.

4. Integrating with Alerting Systems: Connect the SNMP Trap plugin to third-party alerting systems like PagerDuty or Slack. Upon receiving predefined traps, the plugin can send alerts to these systems, enabling teams to be instantly notified of important network events. This integration ensures that the right people are informed at the right time, helping maintain high service levels and quick issue resolution.

Apache Druid

1. Real-Time Application Monitoring Dashboard: Use Telegraf to collect metrics from application servers and send them to Druid for immediate analysis and visualization in dashboards. Druid’s low-latency querying allows users to interactively explore system behavior in near real-time.

2. Security Event Aggregation: Aggregate and forward security-related metrics such as failed logins, port scans, or process anomalies to Druid. Analysts can build dashboards to monitor threat patterns and investigate incidents with millisecond-level granularity.

3. IoT Device Analytics: Collect telemetry from edge devices via Telegraf and send it to Druid for fast, scalable processing. Druid’s time-partitioned storage and roll-up capabilities are ideal for handling billions of small JSON events from sensors or gateways.

4. Web Traffic Behavior Exploration: Use Telegraf to capture web server metrics (e.g., requests per second, latency, error rates) and forward them to Druid. This enables teams to drill down into user behavior by region, device, or request type with subsecond query performance.

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