SNMP Trap and MongoDB 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.
The MongoDB Telegraf Plugin enables users to send metrics to a MongoDB database, automatically managing time series collections.
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.
MongoDB
This plugin sends metrics to MongoDB and seamlessly integrates with its time series functionality, allowing for automatic creation of collections as time series when they don’t already exist. It requires MongoDB version 5.0 or higher to utilize the time series collections feature, which is vital for efficiently storing and querying time-based data. This plugin enhances the monitoring capabilities by ensuring that all relevant metrics are stored and organized correctly within MongoDB, providing users the ability to leverage MongoDB’s powerful querying and aggregation features for time series analysis.
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 = ""
MongoDB
[[outputs.mongodb]]
# connection string examples for mongodb
dsn = "mongodb://localhost:27017"
# dsn = "mongodb://mongod1:27017,mongod2:27017,mongod3:27017/admin&replicaSet=myReplSet&w=1"
# overrides serverSelectionTimeoutMS in dsn if set
# timeout = "30s"
# default authentication, optional
# authentication = "NONE"
# for SCRAM-SHA-256 authentication
# authentication = "SCRAM"
# username = "root"
# password = "***"
# for x509 certificate authentication
# authentication = "X509"
# tls_ca = "ca.pem"
# tls_key = "client.pem"
# # tls_key_pwd = "changeme" # required for encrypted tls_key
# insecure_skip_verify = false
# database to store measurements and time series collections
# database = "telegraf"
# granularity can be seconds, minutes, or hours.
# configuring this value will be based on your input collection frequency.
# see https://docs.mongodb.com/manual/core/timeseries-collections/#create-a-time-series-collection
# granularity = "seconds"
# optionally set a TTL to automatically expire documents from the measurement collections.
# ttl = "360h"
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.
MongoDB
-
Dynamic Logging to MongoDB for IoT Devices: Utilize this plugin to collect and store metrics from a fleet of IoT devices in real-time. By sending device logs directly to MongoDB, you can create a centralized database that allows for easy access and querying of health metrics and performance data, enabling proactive maintenance and troubleshooting based on historical trends.
-
Time Series Analysis of Web Traffic: Use the MongoDB Telegraf Plugin to gather and analyze web traffic metrics over time. This application can help you understand peak usage times, user interactions, and behavior patterns, which can guide marketing strategies and infrastructure scaling decisions for improved user experience.
-
Automated Monitoring and Alerting System: Integrate the MongoDB plugin into an automated monitoring system that tracks application performance metrics. With time series collections, you can set up alerts based on specific thresholds, allowing your team to respond to potential issues before they affect users. This proactive management can enhance service reliability and overall performance.
-
Data Retention and TTL Management in Metrics Storage: Leverage the TTL feature for documents within MongoDB collections to auto-expire outdated metrics. This is particularly useful for environments where only recent performance data is relevant, preventing your MongoDB database from becoming cluttered with old metrics and ensuring efficient data management.
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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