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Publish API benchmark

The Publish API is the primary entry point for network participants to publish and update their catalogs across the Fabric network.

The Publish API is the primary entry point for network participants to publish and update their catalogs across the Fabric network. This report presents the measured performance characteristics under realistic catalog workloads.



At a Glance

  • ~1,000 operations/sec — Peak throughput

  • 86–191 ms — P90 latency, 1–4 CPU range

  • 2.52x — throughput gain, 1 CPU → 4 CPU



Methodology

The benchmarks were conducted under controlled conditions on an isolated environment to ensure consistent, repeatable results. The workload uses a standard protocol catalog dataset representative of real-world cross-domain publishing patterns.

150,000 total publish operations were executed across three configurations, based on the following fixed parameters:


Traffic Simulation

Parameter

Value

Concurrent Users

50 virtual users

Total Requests

50,000 payload submissions

Payload Anatomy

Parameter

Value

Payload Size

~52 KB (average)

Catalog Density

2 Catalogs per request

Resources per Catalog

50 Resources & 10 Offers

Total Resources per Request

100


Results

Three service configurations were tested, each with increasing compute (CPU) allocation. Memory was held constant at 1 GB to isolate the effect of compute scaling.

Reading the latency columns. P90 = 90% of requests completed within that time. P95 and P99 capture the 95th and 99th percentiles — the experience of even the slowest requests.

Throughput Overview

Configuration

CPU

Throughput

P90

P95

P99

Standard

1

383 req/s

191 ms

204 ms

285 ms

Enhanced

2

605 req/s

146 ms

171 ms

236 ms

High Performance

4

963 req/s

86 ms

106 ms

150 ms

Comparing the Standard (1 CPU) and High Performance (4 CPU) configurations:

Percentile

Standard

High Performance

Improvement

P90

191 ms

86 ms

55% faster

P95

204 ms

106 ms

48% faster

P99

285 ms

150 ms

47% faster

Latency improved consistently across all percentiles — the gains apply to every request, not just the fastest ones.

From 1 CPU to 4 CPU, throughput increased 2.52x with each doubling of CPU delivering a consistent ~1.6x gain.

Step

Gain

Efficiency

1 CPU → 2 CPU

1.58x

79%

2 CPU → 4 CPU

1.59x

80%

1 CPU → 4 CPU

2.52x

63%


Key Takeaways

  • Highly Scalable: The service scales predictably with compute resources, achieving near-linear throughput gains with ~80% efficiency per CPU doubling.

  • Low Latency: Even at the 99th percentile, the High Performance configuration handles complex catalog payloads in 150 ms.

  • Memory Efficient: All configurations ran with just 1 GB memory — even at 963 req/s, memory was not a limiting factor.

  • High Reliability: Zero errors across 150,000 operations demonstrates robust stability under sustained heavy load.

Benchmarking data collected on the Fabric Catalog Benchmarking environment using standard catalog payloads representative of production traffic patterns.