Building an OTEL Collector for Rivian Vehicles
Webinar Replay
If your team is thinking about moving from Splunk to Oracle Cloud Logging Analytics (OCLA), this session will walk through everything you need to evaluate, plan, and execute a successful migration. This is a practical session focused on real-world considerations, technical trade-offs, and cost optimization. We’ll also include a live demo comparing the two tools side by side.
Modern telemetry isn’t just for cloud services anymore.
In this live webinar, we’ll walk through how to build a custom OpenTelemetry (OTEL) metrics collector in Python using real-world vehicle data from the Rivian API. This session is designed for engineers, DevOps practitioners, and observability teams who want to understand how OpenTelemetry works beyond the basics — by wiring it up to a non-traditional data source and exporting meaningful metrics.
Using Rivian vehicle telemetry as our case study, we’ll show how to:
- Authenticate and interact with a real external API
- Transform domain-specific data into OTEL metrics
- Export metrics on a fixed cadence
- Integrate with downstream observability tooling
What You’ll Learn:
- OpenTelemetry SDK fundamentals in Python
- How the OTEL Python SDK generates, processes, and exports metrics
- Key components like the MeterProvider, Metric Readers, and Exporters
- Working with OTLP metrics
- Using the OTLP Metric Exporter
- Configuring periodic metric export intervals
- Metric instrument selection
- When to use Counters, Histograms, and Gauges
- Why Gauges are ideal for sampled telemetry data
- Integrating external APIs into OTEL pipelines
- Pulling live and historical vehicle data from the Rivian API
- Handling authentication, sessions, and rate-limit considerations
- Design considerations for real-world collectors
Who Should Attend
- DevOps and Platform Engineers
- Site Reliability Engineers (SREs)
- Observability and Telemetry Architects
- Developers working with OpenTelemetry
- Anyone exploring custom metrics pipelines beyond traditional services
- A basic familiarity with Python and observability concepts is helpful, but not required.