Cloud SPE - Observable Network Data

Purpose

What is the specific business problem does this solve? How does this align with an advance the vision? And why should we be working on this now?

Lack of trusted, network-wide performance and demand metrics makes it difficult to assess reliability, surface bottlenecks, or confidently onboard real-time AI workloads. Without clear visibility into latency, success rates, capacity, and workload behavior, Livepeer cannot demonstrate production readiness, establish meaningful Service Level Agreements (SLAs), or give builders confidence to deploy real workloads.

To advance the real-time AI vision, Livepeer must first measure what matters by establishing unified, trustworthy network observability. A shared data foundation enables consistent SLA tracking, informs scaling and incentive decisions, and gives operators, gateways, and developers a clear, objective view of network performance as demand grows.

Prior work: Builds on ecosystem research highlighting fragmented network data and the need for unified, network-wide observability.

Outcome

What does overall success look like in one paragraph? And what are some of the tangible key results that the submissions should focus on?

Overall success is when Livepeer has a unified, trustworthy observability foundation for real-time AI and video workloads—defined by clear metric schemas and open data pipelines that aggregate network-wide performance and demand data into a single, queryable source. Orchestrators, gateways, and the community can access consistent real-time and historical views across key metrics, enabling analysis, insight, and action. This foundation directly enables SLA scoring, informed orchestrator selection, and continuous reliability improvements as demand grows.

Key Metrics To Measure The Outcome Against:

• Unified Metrics Coverage: Number of core performance and demand metrics defined in a standardized schema and made available network-wide.

• Data Source Integration: Number of distinct network data sources integrated into a unified aggregation layer and exposed through documented access paths.

• Observability Completeness & Reliability: Defined indicators showing freshness, completeness, and consistency of network telemetry (e.g. data latency, missing dimensions, ingestion success rates).

• Reproducible Test Load Results: Availability of standardized test load execution producing repeatable, independently verifiable measurements for key SLA metrics.