Kernel and Thanos Integration

Input and output integration overview

The Kernel plugin collects various statistics about the Linux kernel, including context switches, page usage, and entropy availability.

This plugin sends metrics from Telegraf to Thanos using the Prometheus remote write protocol over HTTP, allowing efficient and scalable ingestion into Thanos Receive components.

Integration details

Kernel

The Kernel plugin is designed exclusively for Linux systems and gathers essential kernel statistics that are not covered by other plugins. It primarily focuses on the metrics available in /proc/stat, as well as the entropy available from /proc/sys/kernel/random/entropy_avail. Additional functionalities include the capture of Kernel Samepage Merging (KSM) data and Pressure Stall Information (PSI), requiring Linux kernel version 4.20 or later. This plugin provides a comprehensive look into system behaviors, enabling better understanding and optimization of resource management and usage. The metrics it collects are critical for monitoring system health and performance.

Thanos

Telegraf’s HTTP plugin can send metrics directly to Thanos via its Remote Write-compatible Receive component. By setting the data format to prometheusremotewrite, Telegraf can serialize metrics into the same protobuf-based format used by native Prometheus clients. This setup enables high-throughput, low-latency metric ingestion into Thanos, facilitating centralized observability at scale. It is particularly useful in hybrid environments where Telegraf is collecting metrics from systems outside Prometheus’ native reach, such as SNMP devices, Windows hosts, or custom apps, and streams them directly to Thanos for long-term storage and global querying.

Configuration

Kernel

[[inputs.kernel]]
  ## Additional gather options
  ## Possible options include:
  ## * ksm - kernel same-page merging
  ## * psi - pressure stall information
  # collect = []

Thanos

[[outputs.http]]
  ## Thanos Receive endpoint for remote write
  url = "http://thanos-receive.example.com/api/v1/receive"

  ## HTTP method
  method = "POST"

  ## Data format set to Prometheus remote write
  data_format = "prometheusremotewrite"

  ## Optional headers (authorization, etc.)
  # [outputs.http.headers]
  #   Authorization = "Bearer YOUR_TOKEN"

  ## Optional TLS configuration
  # tls_ca = "/path/to/ca.pem"
  # tls_cert = "/path/to/cert.pem"
  # tls_key = "/path/to/key.pem"
  # insecure_skip_verify = false

  ## Request timeout
  timeout = "10s"

Input and output integration examples

Kernel

1. Memory Optimization through KSM: Utilize the KSM capabilities of this plugin to monitor memory usage patterns in your applications and dynamically adjust the memory allocation strategy based on shared page usage metrics. By analyzing the data collected, you can identify opportunities for consolidating memory and optimizing performance without manual intervention.

2. Real-time System Health Monitoring: Integrate the metrics collected by the Kernel plugin into a real-time dashboard that visualizes key kernel statistics including context switches, interrupts, and entropy availability. This setup allows system administrators to proactively respond to performance issues before they escalate into critical failures, ensuring smooth operation of Linux servers.

3. Enhanced Anomaly Detection: Combine the data from this plugin with machine learning models to predict and detect anomalies in kernel behavior. By continuously monitoring metrics like process forking rates and entropy levels, you can implement an adaptive alerting system that triggers on performance anomalies, allowing for quick responses to potential issues.

4. Resource Usage Patterns Analysis: Use the Pressure Stall Information collected by the plugin to analyze resource usage patterns over time and identify potential bottlenecks under load conditions. By adjusting application performance based on the PSI metrics, you can improve overall resource management and maintain service reliability under varying workloads.

Thanos

1. Agentless Cloud Monitoring: Deploy Telegraf agents across cloud VMs to collect system and application metrics, then stream them directly into Thanos using Remote Write. This provides centralized observability without requiring Prometheus nodes at each location.

2. Scalable Windows Host Monitoring: Use Telegraf on Windows machines to collect OS-level metrics and send them via Remote Write to Thanos Receive. This enables observability across heterogeneous environments with native Prometheus support only on Linux.

3. Cross-Region Metrics Federation: Telegraf agents in multiple geographic regions can push data to region-local Thanos Receivers using this plugin. From there, Thanos can deduplicate and query metrics globally, reducing latency and network egress costs.

4. Integrating Third-Party Data into Thanos: Collect metrics from custom telemetry sources such as REST APIs or proprietary logs using Telegraf inputs and forward them to Thanos via Remote Write. This brings non-native data into a Prometheus-compatible, long-term analytics pipeline.

Feedback

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