AWS Data Firehose and OpenObserve 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 configuration pairs Telegraf’s HTTP output with OpenObserve’s native JSON ingestion API, turning any Telegraf agent into a first-class OpenObserve collector.</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>

OpenObserve

<p>OpenObserve is an open source observability platform written in Rust that stores data cost-effectively on object storage or local disk. It exposes REST endpoints such as <code>/api/{org}/ingest/metrics/_json</code> that accept batched metric documents conforming to a concise JSON schema, making it an attractive drop-in replacement for Loki or Elasticsearch stacks. The Telegraf HTTP output plugin streams metrics to arbitrary HTTP targets; when the "data_format = "json"" serializer is selected, Telegraf batches its metric objects into a payload that matches OpenObserve’s ingestion contract. The plugin supports configurable batch size, custom headers, TLS, and compression, allowing operators to authenticate with Basic or Bearer tokens and to enforce back-pressure without additional collectors. By reusing existing Telegraf agents already collecting system, application, or SNMP data, organizations can funnel rich telemetry into OpenObserve dashboards and SQL-like analytics with minimal overhead, enabling unified observability, long-term retention, and real-time alerting without vendor lock-in.</p>

Configuration

AWS Data Firehose

OpenObserve

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>

OpenObserve

<ol> <li> <p><strong>Edge Device Health Mirror</strong>: Deploy Telegraf on thousands of industrial IoT devices to capture temperature, vibration, and power metrics, then use this output to push JSON batches to OpenObserve. Plant operators gain a real-time overview of machine health and can trigger maintenance based on anomalies without relying on heavyweight collectors.</p> </li> <li> <p><strong>Blue-Green Deployment Canary</strong>: Attach a lightweight Telegraf sidecar to each Kubernetes release-candidate pod that scrapes /metrics and forwards container stats to a dedicated “canary” stream in OpenObserve. Continuous comparison of error rates between blue and green versions empowers the CI pipeline to auto-roll back poor performers within seconds.</p> </li> <li> <p><strong>Multi-Tenant SaaS Billing Pipeline</strong>: Emit per-customer usage counters via Telegraf and tag them with <code>tenant_id</code>; the HTTP plugin posts them to OpenObserve where SQL reports aggregate usage into invoices, eliminating separate metering services and simplifying compliance audits.</p> </li> <li> <p><strong>Security Threat Scoring</strong>: Fuse Suricata events and host resource metrics in Telegraf, deliver them to OpenObserve’s analytics engine, and run stream-processing rules that correlate spikes in suspicious traffic with CPU saturation to produce an actionable threat score and automatically open tickets in a SOAR platform.</p> </li> </ol>

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