SNMP Trap and M3DB Integration
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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.
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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 stream metrics to M3DB using the Prometheus Remote Write protocol, enabling scalable ingestion through the M3 Coordinator.
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.
M3DB
This configuration uses Telegraf’s HTTP output plugin with prometheusremotewrite
format to send metrics directly to M3DB through the M3 Coordinator. M3DB is a distributed time series database designed for scalable, high-throughput metric storage. It supports ingestion of Prometheus remote write data via its Coordinator component, which manages translation and routing into the M3DB cluster. This approach enables organizations to collect metrics from systems that aren’t natively instrumented for Prometheus (e.g., Windows, SNMP, legacy systems) and ingest them efficiently into M3’s long-term, high-performance storage engine. The setup is ideal for high-scale observability stacks with Prometheus compatibility requirements.
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 = ""
M3DB
# Configuration for sending metrics to M3
[outputs.http]
## URL is the address to send metrics to
url = "https://M3_HOST:M3_PORT/api/v1/prom/remote/write"
## HTTP Basic Auth credentials
username = "admin"
password = "password"
## Data format to output.
data_format = "prometheusremotewrite"
## Outgoing HTTP headers
[outputs.http.headers]
Content-Type = "application/x-protobuf"
Content-Encoding = "snappy"
X-Prometheus-Remote-Write-Version = "0.1.0"
Input and output integration examples
SNMP Trap
-
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.
-
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.
-
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.
-
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.
M3DB
-
Large-Scale Cloud Infrastructure Monitoring: Deploy Telegraf agents across thousands of virtual machines and containers to collect metrics and stream them into M3DB through the M3 Coordinator. This provides reliable, long-term visibility with minimal storage overhead and high availability.
-
Legacy System Metrics Ingestion: Use Telegraf to gather metrics from older systems that lack native Prometheus exporters (e.g., Windows servers, SNMP devices) and forward them to M3DB via remote write. This bridges modern observability workflows with legacy infrastructure.
-
Centralized App Telemetry Aggregation: Collect application-specific telemetry using Telegraf’s plugin ecosystem (e.g.,
exec
,http
,jolokia
) and push it into M3DB for centralized storage and query via PromQL. This enables unified analytics across diverse data sources. -
Hybrid Cloud Observability: Install Telegraf agents on-prem and in the cloud to collect and remote-write metrics into a centralized M3DB cluster. This ensures consistent visibility across environments while avoiding the complexity of running Prometheus federation layers.
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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