SNMP Trap and Snowflake Integration
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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
The SNMP Trap Telegraf plugin enables the receipt of SNMP notifications, facilitating comprehensive network monitoring by capturing important events from network devices.
Telegraf’s SQL plugin allows seamless metric storage in SQL databases. When configured for Snowflake, it employs a specialized DSN format and dynamic table creation to map metrics to the appropriate schema.
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.
Snowflake
Telegraf’s SQL plugin is engineered to dynamically write metrics into an SQL database by creating tables and columns based on the incoming data. When configured for Snowflake, it employs the gosnowflake driver, which uses a DSN that encapsulates credentials, account details, and database configuration in a compact format. This setup allows for the automatic generation of tables where each metric is recorded with precise timestamps, thereby ensuring detailed historical tracking. Although the integration is considered experimental, it leverages Snowflake’s powerful data warehousing capabilities, making it suitable for scalable, cloud-based analytics and reporting solutions.
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 = ""
Snowflake
[[outputs.sql]]
## Database driver
## Valid options: mssql (Microsoft SQL Server), mysql (MySQL), pgx (Postgres),
## sqlite (SQLite3), snowflake (snowflake.com), clickhouse (ClickHouse)
driver = "snowflake"
## Data source name
## For Snowflake, the DSN format typically includes the username, password, account identifier, and optional warehouse, database, and schema.
## Example DSN: "username:password@account/warehouse/db/schema"
data_source_name = "username:password@account/warehouse/db/schema"
## Timestamp column name
timestamp_column = "timestamp"
## Table creation template
## Available template variables:
## {TABLE} - table name as a quoted identifier
## {TABLELITERAL} - table name as a quoted string literal
## {COLUMNS} - column definitions (list of quoted identifiers and types)
table_template = "CREATE TABLE {TABLE} ({COLUMNS})"
## Table existence check template
## Available template variables:
## {TABLE} - table name as a quoted identifier
table_exists_template = "SELECT 1 FROM {TABLE} LIMIT 1"
## Initialization SQL (optional)
init_sql = ""
## Maximum amount of time a connection may be idle. "0s" means connections are never closed due to idle time.
connection_max_idle_time = "0s"
## Maximum amount of time a connection may be reused. "0s" means connections are never closed due to age.
connection_max_lifetime = "0s"
## Maximum number of connections in the idle connection pool. 0 means unlimited.
connection_max_idle = 2
## Maximum number of open connections to the database. 0 means unlimited.
connection_max_open = 0
## Metric type to SQL type conversion
## Defaults to ANSI/ISO SQL types unless overridden. Adjust if needed for Snowflake compatibility.
#[outputs.sql.convert]
# integer = "INT"
# real = "DOUBLE"
# text = "TEXT"
# timestamp = "TIMESTAMP"
# defaultvalue = "TEXT"
# unsigned = "UNSIGNED"
# bool = "BOOL"
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.
Snowflake
-
Cloud-Based Data Lake Integration: Utilize the plugin to stream real-time metrics from various sources into Snowflake, enabling the creation of a centralized data lake. This integration supports complex analytics and machine learning workflows on cloud data.
-
Dynamic Business Intelligence Dashboards: Leverage the plugin to automatically generate tables from incoming metrics and feed them into BI tools. This allows businesses to create dynamic dashboards that visualize performance trends and operational insights without manual schema management.
-
Scalable IoT Analytics: Deploy the plugin to capture high-frequency data from IoT devices into Snowflake. This use case facilitates the aggregation and analysis of sensor data, enabling predictive maintenance and real-time monitoring at scale.
-
Historical Trend Analysis for Compliance: Use the plugin to log and archive detailed metric data in Snowflake, which can then be queried for long-term trend analysis and compliance reporting. This setup ensures that organizations can maintain a robust audit trail and perform forensic analysis if needed.
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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