InfiniBand and MongoDB 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.

The MongoDB Telegraf Plugin enables users to send metrics to a MongoDB database, automatically managing time series collections.

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.

MongoDB

This plugin sends metrics to MongoDB and seamlessly integrates with its time series functionality, allowing for automatic creation of collections as time series when they don’t already exist. It requires MongoDB version 5.0 or higher to utilize the time series collections feature, which is vital for efficiently storing and querying time-based data. This plugin enhances the monitoring capabilities by ensuring that all relevant metrics are stored and organized correctly within MongoDB, providing users the ability to leverage MongoDB’s powerful querying and aggregation features for time series analysis.

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

MongoDB

[[outputs.mongodb]]
              # connection string examples for mongodb
              dsn = "mongodb://localhost:27017"
              # dsn = "mongodb://mongod1:27017,mongod2:27017,mongod3:27017/admin&replicaSet=myReplSet&w=1"

              # overrides serverSelectionTimeoutMS in dsn if set
              # timeout = "30s"

              # default authentication, optional
              # authentication = "NONE"

              # for SCRAM-SHA-256 authentication
              # authentication = "SCRAM"
              # username = "root"
              # password = "***"

              # for x509 certificate authentication
              # authentication = "X509"
              # tls_ca = "ca.pem"
              # tls_key = "client.pem"
              # # tls_key_pwd = "changeme" # required for encrypted tls_key
              # insecure_skip_verify = false

              # database to store measurements and time series collections
              # database = "telegraf"

              # granularity can be seconds, minutes, or hours.
              # configuring this value will be based on your input collection frequency.
              # see https://docs.mongodb.com/manual/core/timeseries-collections/#create-a-time-series-collection
              # granularity = "seconds"

              # optionally set a TTL to automatically expire documents from the measurement collections.
              # ttl = "360h"

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.

MongoDB

1. Dynamic Logging to MongoDB for IoT Devices: Utilize this plugin to collect and store metrics from a fleet of IoT devices in real-time. By sending device logs directly to MongoDB, you can create a centralized database that allows for easy access and querying of health metrics and performance data, enabling proactive maintenance and troubleshooting based on historical trends.

2. Time Series Analysis of Web Traffic: Use the MongoDB Telegraf Plugin to gather and analyze web traffic metrics over time. This application can help you understand peak usage times, user interactions, and behavior patterns, which can guide marketing strategies and infrastructure scaling decisions for improved user experience.

3. Automated Monitoring and Alerting System: Integrate the MongoDB plugin into an automated monitoring system that tracks application performance metrics. With time series collections, you can set up alerts based on specific thresholds, allowing your team to respond to potential issues before they affect users. This proactive management can enhance service reliability and overall performance.

4. Data Retention and TTL Management in Metrics Storage: Leverage the TTL feature for documents within MongoDB collections to auto-expire outdated metrics. This is particularly useful for environments where only recent performance data is relevant, preventing your MongoDB database from becoming cluttered with old metrics and ensuring efficient data management.

Feedback

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