Intel PowerStat and Grafana Integration

Input and output integration overview

Monitor power statistics on Intel-based platforms and is compatible with Linux-based operating systems. It helps in understanding and managing power efficiency and CPU performance.

This plugin enables Telegraf to stream metrics directly to Grafana dashboards in real-time, leveraging Grafana Live for instantaneous data visualization and operational insights.

Integration details

Intel PowerStat

The Intel PowerStat plugin is designed to monitor power statistics specifically on Intel-based platforms running a Linux operating system. It offers visibility into critical metrics such as CPU temperature, utilization, and power consumption, making it essential for power saving initiatives and workload migration strategies. By leveraging telemetry frameworks, this plugin enables users to gain insights into platform-level metrics that help with monitoring and analytics systems in the context of Management and Orchestration (MANO). It facilitates the ability to make informed decisions and perform corrective actions based on the state of the platform, ultimately contributing to better system efficiency and reliability.

Grafana

Telegraf can be used to send real-time data to Grafana using the Websocket output plugin. Metrics collected by Telegraf are instantly pushed to Grafana dashboards, enabling real-time visualization and analysis. This plugin is ideal for use cases where low latency, live data visualization is essential, such as operational monitoring, real-time analytics, and immediate incident response scenarios. It supports authentication headers, customizable data serialization formats (like JSON), and secure communication via TLS, offering flexibility and ease of integration in dynamic, interactive dashboard environments.

Configuration

Intel PowerStat

[[inputs.intel_powerstat]]
  # package_metrics = ["current_power_consumption", "current_dram_power_consumption", "thermal_design_power"]
  # cpu_metrics = []
  # included_cpus = []
  # excluded_cpus = []
  # event_definitions = ""
  # msr_read_timeout = "0ms"

Grafana

[[outputs.websocket]]
  ## Grafana Live WebSocket endpoint
  url = "ws://localhost:3000/api/live/push/custom_id"

  ## Optional headers for authentication
  # [outputs.websocket.headers]
  #   Authorization = "Bearer YOUR_GRAFANA_API_TOKEN"

  ## Data format to send metrics
  data_format = "influx"

  ## Timeouts (make sure read_timeout is larger than server ping interval or set to zero).
  # connect_timeout = "30s"
  # write_timeout = "30s"
  # read_timeout = "30s"

  ## Optionally turn on using text data frames (binary by default).
  # use_text_frames = false

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

Input and output integration examples

Intel PowerStat

1. Optimizing Data Center Energy Usage: Monitor power consumption metrics across all CPUs in a data center. By capturing real-time data, administrators can identify which servers consume the most power and implement shutdowns or load balancing strategies during low demand periods, effectively reducing operational costs.

2. Dynamic Workload Migration Based on Power Efficiency: Integrate this plugin with a cloud orchestration tool to enable dynamic migration of workloads based on power usage metrics. If a particular server is recorded as consuming excessive power without corresponding output, the orchestrator can seamlessly migrate workloads to more efficient nodes, ensuring optimal resource utilization and lower energy expenses.

3. Monitoring and Alerting Mechanism for Overheating CPUs: Implement an alerting system using the CPU temperature metrics captured by Intel PowerStat. Setting thresholds for temperature can alert system administrators when a CPU is prone to overheating, allowing proactive measures to be taken before hardware damage occurs, ultimately extending the life of the components.

4. Performance Benchmarking for CPU-intensive Applications: Use the metrics provided to benchmark the performance of CPU-intensive applications. By analyzing the cpu_frequency, cpu_temperature, and power metrics under load, developers can optimize application performance and make informed decisions regarding scaling and resource allocation.

Grafana

1. Real-Time Infrastructure Dashboards: Deploy Telegraf to stream server health metrics directly to Grafana dashboards, enabling IT teams to visualize infrastructure performance in real-time. This setup allows immediate detection and response to critical system events.

2. Interactive IoT Monitoring: Integrate IoT device metrics collected by Telegraf and push live data into Grafana, creating dynamic and interactive dashboards for monitoring smart city projects or manufacturing processes. This real-time visibility significantly enhances responsiveness and operational efficiency.

3. Instantaneous Application Performance Analysis: Stream application metrics in real-time from production environments into Grafana dashboards, enabling development teams to rapidly detect and diagnose performance bottlenecks or anomalies during deployments, minimizing downtime and improving reliability.

4. Live Event Analytics: Utilize Telegraf to capture and stream real-time audience or system metrics during major live events directly into Grafana dashboards. Event organizers can dynamically monitor and react to changing conditions or trends, significantly enhancing audience engagement and operational decision-making.

Feedback

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