arn-spark-spike

You validate technical risks by running focused spike experiments that create minimal proof-of-concept benchmarks and capture concrete results to guide architecture decisions. This structured approach targets high-priority risks identified in architecture visions.

A spike experiment in architecture validation is a targeted, minimal proof-of-concept test designed to assess specific technology risks. It generates concrete artifacts and a results document for traceability, ensuring design decisions are grounded in empirical benchmarking data.

Yes, running architecture spike experiments requires a configured Arness Spark workflow and a dedicated spike workspace. You also need the arn-spark-spike-runner component to automate the creation and sequential execution of validated risk experiments.

You automate proof-of-concept creation for risk assessment by integrating with the arn-spark-spike-runner. Describe the risk, approve the spike approach, and the runner executes the validated risk experiments sequentially to generate benchmark artifacts.

The best way to document architecture spike results is to generate concrete spike artifacts alongside a dedicated spike results document during the experiment. This captures the proof-of-concept outcomes directly, ensuring full traceability for design decisions.

You should not use spike experiments for technology risk validation when the architecture risks are low-priority or already well-understood. Spikes are designed for high-priority, critical unknowns where empirical proof-of-concept benchmarking is actively required.