SNMP and Apache Hudi Integration

Input and output integration overview

The SNMP plugin allows you to collect a variety of metrics from SNMP (Simple Network Management Protocol) agents. It provides flexibility in how data is retrieved, whether collecting single metrics or entire tables.

Writes metrics to Parquet files via Telegraf’s Parquet output plugin, preparing them for ingestion into Apache Hudi’s lakehouse architecture.

Integration details

SNMP

This plugin uses polling to gather metrics from SNMP agents, supporting retrieval of individual OIDs and complete SNMP tables. It can be configured to handle multiple SNMP versions, authentication, and other features.

Apache Hudi

This configuration leverages Telegraf’s Parquet plugin to serialize metrics into columnar Parquet files suitable for downstream ingestion by Apache Hudi. The plugin writes metrics grouped by metric name into files in a specified directory, buffering writes for efficiency and optionally rotating files on timers. It considers schema compatibility—metrics with incompatible schemas are dropped—ensuring consistency. Apache Hudi can then consume these Parquet files via tools like DeltaStreamer or Spark jobs, enabling transactional ingestion, time-travel queries, and upserts on your time series data.

Configuration

SNMP

[[inputs.snmp]]
  agents = ["udp://127.0.0.1:161"]

  [[inputs.snmp.field]]
    oid = "RFC1213-MIB::sysUpTime.0"
    name = "sysUptime"
    conversion = "float(2)"

  [[inputs.snmp.field]]
    oid = "RFC1213-MIB::sysName.0"
    name = "sysName"
    is_tag = true

  [[inputs.snmp.table]]
    oid = "IF-MIB::ifTable"
    name = "interface"
    inherit_tags = ["sysName"]

    [[inputs.snmp.table.field]]
      oid = "IF-MIB::ifDescr"
      name = "ifDescr"
      is_tag = true

Apache Hudi

[[outputs.parquet]]
  ## Directory to write parquet files in. If a file already exists the output
  ## will attempt to continue using the existing file.
  directory = "/var/lib/telegraf/hudi_metrics"

  ## File rotation interval (default is no rotation)
  # rotation_interval = "1h"

  ## Buffer size before writing (default is 1000 metrics)
  # buffer_size = 1000

  ## Optional: compression codec (snappy, gzip, etc.)
  # compression_codec = "snappy"

  ## When grouping metrics, each metric name goes to its own file
  ## If a metric’s schema doesn’t match the existing schema, it will be dropped

Input and output integration examples

SNMP

1. Basic SNMP Configuration: Collect metrics from a local SNMP agent using typical SNMP community string settings. This setup is ideal for local monitoring of device performance.
2. Advanced SNMPv3 Setup: Securely collect metrics using SNMPv3 with authentication and encryption to enhance security. This configuration is recommended for production environments.
3. Collect Interface Metrics: Configure the plugin to collect interface metrics from the device’s SNMP table. Utilize fields to capture specific data points for traffic analysis.
4. Join Two SNMP Tables: By using translation fields, join data from two SNMP tables for a comprehensive view of correlated performance metrics.

Apache Hudi

1. Transactional Lakehouse Metrics: Buffer and write Web service metrics as Parquet files for DeltaStreamer to ingest into Hudi, enabling upserts, ACID compliance, and time-travel on historical performance data.

2. Edge Device Batch Analytics: Telegraf running on IoT gateways writes metrics to Parquet locally, where periodic Spark jobs ingest them into Hudi for long-term analytics and traceability.

3. Schema-Enforced Abnormal Metric Handling: Use Parquet plugin’s strict schema-dropping behavior to prevent malformed or unexpected metric changes. Hudi ingestion then guarantees consistent schema and data quality in downstream datasets.

4. Data Platform Integration: Store Telegraf metrics as Parquet files in an S3/ADLS landing zone. Hudi’s Spark-based ingestion pipeline then loads them into a unified, queryable lakehouse with business events and logs.

Feedback

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