Apache and Apache Hudi Integration

Input and output integration overview

This plugin interfaces with the Apache HTTP Server’s mod_status to gather and report performance metrics from the server.

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

Integration details

Apache

The Apache plugin collects server performance information using the mod_status module of the Apache HTTP Server. It relies on the mod_status feature, which must be explicitly enabled in the Apache configuration to access a machine-readable status page. This plugin allows users to fetch several metrics related to Apache’s operational performance, including worker status, connection statistics, and server load, thereby facilitating effective monitoring and troubleshooting of web server performance in real-time.

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

Apache

[[inputs.apache]]
  ## An array of URLs to gather from, must be directed at the machine
  ## readable version of the mod_status page including the auto query string.
  ## Default is "http://localhost/server-status?auto".
  urls = ["http://localhost/server-status?auto"]

  ## Credentials for basic HTTP authentication.
  # username = "myuser"
  # password = "mypassword"

  ## Maximum time to receive response.
  # response_timeout = "5s"

  ## Optional TLS Config
  # tls_ca = "/etc/telegraf/ca.pem"
  # tls_cert = "/etc/telegraf/cert.pem"
  # tls_key = "/etc/telegraf/key.pem"
  ## Use TLS but skip chain & host verification
  # insecure_skip_verify = false

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

Apache

1. Real-Time Performance Monitoring: Use the Apache input plugin to set up a real-time dashboard displaying critical performance metrics of your Apache server. By visualizing metrics such as BusyWorkers, and Load averages, you can quickly identify performance bottlenecks and server health issues, aiding in proactive management of web traffic loads.

2. Automated Alerting for Server Issues: Implement alerts based on metrics collected by this plugin to notify administrators in case of performance degradation. For instance, if the BusyWorkers metric exceeds a certain threshold, automatic alerts can be triggered, ensuring prompt incident response to maintain uptime and service reliability.

3. Historical Performance Analysis: Combine data collected by the Apache plugin with long-term storage solutions to track performance trends over time. This accumulated data helps in understanding usage patterns, forecasting resource needs, and making informed decisions regarding server scaling or optimization.

4. Cross-System Monitoring: Integrate metrics gathered from Apache alongside metrics from other components of your web stack using Telegraf’s capabilities to send data to a centralized monitoring solution. This holistic view can simplify troubleshooting and coordination between different technologies, ensuring optimal system performance across the board.

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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