Phillips Hue Bridge and Mimir Integration

Powerful performance with an easy integration, powered by Telegraf, the open source data connector built by InfluxData.

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This is not the recommended configuration for real-time query at scale. For query and compression optimization, high-speed ingest, and high availability, you may want to consider Phillips Hue Bridge and InfluxDB.

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Powerful Performance, Limitless Scale

Collect, organize, and act on massive volumes of high-velocity data. Any data is more valuable when you think of it as time series data. with InfluxDB, the #1 time series platform built to scale with Telegraf.

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Input and output integration overview

This plugin gathers status from Hue Bridge devices using the CLIP API interface.

This plugin sends Telegraf metrics directly to Grafana’s Mimir database using HTTP, providing scalable and efficient long-term storage and analysis for Prometheus-compatible metrics.

Integration details

Phillips Hue Bridge

The Hue Bridge plugin allows users to gather real-time status from Philips Hue Bridge devices utilizing the CLIP API interface. By communicating with Hue Bridges, this plugin is capable of retrieving various metrics related to home lighting and environmental conditions. It offers multiple schemes for accessing the bridges, such as local LAN, cloud, and mDNS, ensuring flexibility in deployment scenarios. The plugin can handle diverse configurations such as room assignments for devices, which optimizes the evaluation of statuses, especially in environments with many devices. Furthermore, it provides various monitoring metrics applicable to lights, temperature sensors, motion sensors, and device power status, thereby enabling comprehensive insights into a smart home setup. The configuration options allow users to tailor their connections to optimize performance and security, including optional TLS configurations for secure communication.

Mimir

Grafana Mimir supports the Prometheus Remote Write protocol, enabling Telegraf collected metrics to be efficiently ingested into Mimir clusters for large-scale, long-term storage. This integration leverages Prometheus’s well-established standards, allowing users to combine Telegraf’s extensive data collection capabilities with Mimir’s advanced features, such as query federation, multi-tenancy, high availability, and cost-efficient storage. Grafana Mimir’s architecture is optimized for handling high volumes of metric data and delivering fast query responses, making it ideal for complex monitoring environments and distributed systems.

Configuration

Phillips Hue Bridge

[[inputs.huebridge]]
  ## URL of bridges to query in the form ://:@
/ ## See documentation for available schemes. bridges = [ "address://:@/" ] ## Manual device to room assignments to apply during status evaluation. ## E.g. for motion sensors which are reported without a room assignment. # room_assignments = { "Motion sensor 1" = "Living room", "Motion sensor 2" = "Corridor" } ## Timeout for gathering information # timeout = "10s" ## Optional TLS Config # tls_ca = "/etc/telegraf/ca.pem" # tls_cert = "/etc/telegraf/cert.pem" # tls_key = "/etc/telegraf/key.pem" # tls_key_pwd = "secret" ## Use TLS but skip chain & host verification # insecure_skip_verify = false </code></pre>

Mimir

[[outputs.http]]
  url = "http://data-load-balancer-backend-1:9009/api/v1/push"
  data_format = "prometheusremotewrite"
  username = "*****"
  password = "******"
  [outputs.http.headers]
     Content-Type = "application/x-protobuf"
     Content-Encoding = "snappy"
     X-Scope-OrgID = "****"

Input and output integration examples

Phillips Hue Bridge

  1. Automated Lighting Control Based on Room Occupancy: Utilize the Hue Bridge plugin to monitor motion sensors within various rooms of a home. When motion is detected, the system can automatically trigger the lights to turn on, providing convenience and energy efficiency. This integration could significantly enhance user experience and preferences, adapting the lighting to occupancy levels without manual intervention.

  2. Environmental Monitoring in Smart Homes: Implement the Hue Bridge plugin to track temperature and light levels within the house. By continuously monitoring these metrics, users can create a comfortable indoor climate, adjusting heating and cooling systems based on temperature trends or activating lights based on light levels detected. This data-driven approach leads to smart home automation that responds to actual environmental conditions.

  3. Integration with Home Automation Systems: Leverage this plugin to integrate Philips Hue Bridge statistics into broader home automation frameworks. For example, collecting light and temperature data can feed into a centralized dashboard that provides homeowners with insights about their energy usage patterns. Environments can be programmed to respond proactively to user habits, promoting efficiency and energy conservation.

  4. Battery Monitoring for Smart Devices: Use the Hue Bridge plugin to monitor battery levels across various connected smart devices. By being alerted about low battery states, homeowners can take timely actions to replace or recharge devices, preventing outages and ensuring smooth operation of their smart home systems.

Mimir

  1. Enterprise-Scale Kubernetes Monitoring: Integrate Telegraf with Grafana Mimir to stream metrics from Kubernetes clusters at enterprise scale. This enables comprehensive visibility, improved resource allocation, and proactive troubleshooting across hundreds of clusters, leveraging Mimir’s horizontal scalability and high availability.

  2. Multi-tenant SaaS Application Observability: Use this plugin to centralize metrics from diverse SaaS tenants into Grafana Mimir, enabling tenant isolation and accurate billing based on resource usage. This approach provides reliable observability, efficient cost management, and secure multi-tenancy support.

  3. Global Edge Network Performance Tracking: Stream latency and availability metrics from globally distributed edge servers into Grafana Mimir. Organizations can quickly identify performance degradation or outages, leveraging Mimir’s fast querying capabilities to ensure optimal service reliability and user experience.

  4. Real-Time Analytics for High-Volume Microservices: Implement Telegraf metrics collection in high-volume microservices architectures, feeding data into Grafana Mimir for real-time analytics and anomaly detection. Mimir’s powerful querying enables teams to detect anomalies and quickly respond, maintaining high service availability and performance.

Feedback

Thank you for being part of our community! If you have any general feedback or found any bugs on these pages, we welcome and encourage your input. Please submit your feedback in the InfluxDB community Slack.

Powerful Performance, Limitless Scale

Collect, organize, and act on massive volumes of high-velocity data. Any data is more valuable when you think of it as time series data. with InfluxDB, the #1 time series platform built to scale with Telegraf.

See Ways to Get Started

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