AWS Data Firehose and OSI PI Integration

Input and output integration overview

<p>This plugin listens for metrics sent via HTTP from AWS Data Firehose in supported data formats, providing real-time data ingestion capabilities.</p>

<p>This setup converts Telegraf into a lightweight PI Web API publisher, letting you push any Telegraf metric into the OSI PI System with a simple HTTP POST.</p>

Integration details

AWS Data Firehose

<p>The AWS Data Firehose Telegraf plugin is designed to receive metrics from AWS Data Firehose via HTTP. This plugin listens for incoming data in various formats and processes it according to the request-response schema outlined in the official AWS documentation. Unlike standard input plugins that operate on a fixed interval, this service plugin initializes a listener that remains active, waiting for incoming metrics. This allows for real-time data ingestion from AWS Data Firehose, making it suitable for scenarios where immediate data processing is required. Key features include the ability to specify service addresses, paths, and support for TLS connections for secure data transmission. Additionally, the plugin accommodates optional authentication keys and custom tags, enhancing its flexibility in various use cases involving data streaming and processing.</p>

OSI PI

<p>OSI PI is an data management and analytics platform used in energy, manufacturing, and critical infrastructure. The PI Web API is its REST interface, exposing endpoints such as <strong>/piwebapi/streams/{WebId}/value</strong> that accept JSON payloads containing a <code>Timestamp</code> and <code>Value</code>. By pairing Telegraf’s flexible HTTP output with this endpoint, any metric Telegraf collects—SNMP counters, Modbus readings, Kubernetes stats—can be written directly into PI without installing proprietary interfaces. The configuration above authenticates with Basic or Kerberos, serializes each batch to JSON, and renders a minimal body template that aligns with PI Web API’s single-value write contract. Because Telegraf already supports batching, TLS, proxies, and custom headers, this approach scales from edge gateways to cloud VMs, allowing organizations to back-fill historical data, stream live telemetry, or mirror non-PI sources (e.g., Prometheus) into the PI data archive. It also sidesteps older SDK dependencies and enables hybrid architectures where PI remains on-prem while Telegraf agents run in containers or IIoT devices.</p>

Configuration

AWS Data Firehose

OSI PI

Input and output integration examples

AWS Data Firehose

<ol> <li> <p><strong>Real-Time Data Analytics</strong>: Using the AWS Data Firehose plugin, organizations can stream data in real-time from various sources, such as application logs or IoT devices, directly into analytics platforms. This allows data teams to analyze incoming data as it is generated, enabling rapid insights and operational adjustments based on fresh metrics.</p> </li> <li> <p><strong>Profile Access Patterns for Optimization</strong>: By collecting data about how clients interact with applications through AWS Data Firehose, businesses can gain valuable insights into user behavior. This can drive content personalization strategies or optimize server architecture for better performance based on traffic patterns.</p> </li> <li> <p><strong>Automated Alerting Mechanism</strong>: Integrating AWS Data Firehose with alerting systems via this plugin allows teams to set up automated alerts based on specific metrics collected. For example, if a particular threshold is reached in the input data, alerts can trigger operations teams to investigate potential issues before they escalate.</p> </li> </ol>

OSI PI

<ol> <li> <p><strong>Remote Pump Stations Telemetry Bridge</strong>: Install Telegraf on edge gateways at oil-field pump stations, gather flow-meter and vibration readings over Modbus, and POST them to the PI Web API. Operations teams view real-time data in PI Vision without deploying heavyweight PI interfaces, while bandwidth-friendly batching keeps satellite links economical.</p> </li> <li> <p><strong>Green-Energy Micro-Grid Dashboard</strong>: Export inverter, battery, and weather metrics from MQTT into Telegraf, which relays them to PI. PI AF analytics can calculate real-time power balance and feed a campus dashboard; historical deltas inform sustainability reports.</p> </li> <li> <p><strong>Brownfield SCADA Modernization</strong>: Legacy PLCs logged to CSV are ingested by Telegraf’s <code>tail</code> input; each row is parsed and immediately sent to PI via HTTP, creating a live data stream that co-exists with archival files while the SCADA upgrade proceeds incrementally.</p> </li> <li> <p><strong>Synthetic Data Generator for Training</strong>: Telegraf’s <code>exec</code> input can run a script that emits simulated sensor patterns. Posting those metrics to a non-production PI server through the Web API supplies realistic datasets for PI Vision training sessions without risking production tags.</p> </li> </ol>

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