InfiniBand and Cortex Integration

Input and output integration overview

The InfiniBand Telegraf plugin collects performance metrics from all InfiniBand devices installed on a Linux system, providing essential insights for monitoring network performance and reliability.

This plugin enables Telegraf to send metrics to Cortex using the Prometheus remote write protocol, allowing seamless ingestion into Cortex’s scalable, multi-tenant time series storage.

Integration details

InfiniBand

This plugin gathers statistics for all InfiniBand devices and ports on the system. InfiniBand is a high-speed networking technology commonly used in high-performance computing and enterprise data centers. The plugin retrieves various performance counters from the system’s InfiniBand devices located in /sys/class/infiniband/<dev>/port/<port>/counters/. The metrics depend on the specific InfiniBand hardware and include various packet and error statistics that are essential for monitoring network health and performance. By utilizing this plugin, users can gain insights into the operational status of their InfiniBand networks, helping to identify potential issues and optimize performance.

Cortex

With Telegraf’s HTTP output plugin and the prometheusremotewrite data format you can send metrics directly to Cortex, a horizontally scalable, long-term storage backend for Prometheus. Cortex supports multi-tenancy and accepts remote write requests using the Prometheus protobuf format. By using Telegraf as the collection agent and Remote Write as the transport mechanism, organizations can extend observability into sources not natively supported by Prometheus—such as Windows hosts, SNMP-enabled devices, or custom application metrics—while leveraging Cortex’s high-availability and long-retention capabilities.

Configuration

InfiniBand

# Gets counters from all InfiniBand cards and ports installed
# This plugin ONLY supports Linux
[[inputs.infiniband]]
  # no configuration

  ## Collect RDMA counters
  # gather_rdma = false

Cortex

[[outputs.http]]
  ## Cortex Remote Write endpoint
  url = "http://cortex.example.com/api/v1/push"

  ## Use POST to send data
  method = "POST"

  ## Send metrics using Prometheus remote write format
  data_format = "prometheusremotewrite"

  ## Optional HTTP headers for authentication
  # [outputs.http.headers]
  #   X-Scope-OrgID = "your-tenant-id"
  #   Authorization = "Bearer YOUR_API_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

InfiniBand

1. Performance Monitoring in High-Performance Computing (HPC): Monitor the performance metrics of InfiniBand interconnects in a high-performance computing cluster. By analyzing metrics such as packet errors and throughput, system administrators can ensure optimal operation and quickly identify any performance degradation. This setup enhances the reliability of computational tasks by allowing timely interventions based on accurate monitoring data.

2. Network Health Audits: Perform routine health checks of InfiniBand networks. The detailed metrics gathered, such as excessive buffer overruns and link integrity errors, provide valuable insights for network audits. By establishing baseline performance and watching for anomalies, IT professionals can ensure the stability and performance of critical infrastructures.

3. Integration with Alerting Systems: Set up the InfiniBand plugin to work in conjunction with alerting systems to trigger notifications based on performance thresholds. For instance, if the number of link errors exceeds a predefined limit, an alert can be sent to the network operations team. This proactive approach ensures that potential issues are addressed before they impact business operations.

4. Data Visualization Dashboards: Feed InfiniBand metrics to a visualization tool to create dashboards that display the real-time performance of the network. This can help stakeholders visualize critical data such as packet transmission rates and errors, facilitating better decision-making regarding network management and capacity planning.

Cortex

1. Unified Multi-Tenant Monitoring: Use Telegraf to collect metrics from different teams or environments and push them to Cortex with separate X-Scope-OrgID headers. This enables isolated data ingestion and querying per tenant, ideal for managed services and platform teams.

2. Extending Prometheus Coverage to Edge Devices: Deploy Telegraf on edge or IoT devices to collect system metrics and send them to a centralized Cortex cluster. This approach ensures consistent observability even for environments without local Prometheus scrapers.

3. Global Service Observability with Federated Tenants: Aggregate metrics from global infrastructure by configuring Telegraf agents to push data into regional Cortex clusters, each tagged with tenant identifiers. Cortex handles deduplication and centralized access across regions.

4. Custom App Telemetry Pipeline: Collect app-specific telemetry via Telegraf’s exec or http input plugins and forward it to Cortex. This allows DevOps teams to monitor app-specific KPIs in a scalable, query-efficient format while keeping metrics logically grouped by tenant or service.

Feedback

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