Cost & Evaluation
How can I measure the cost of deterministic replay without deploying a full production workload?
Build a representative benchmark that exercises replay of agent histories with varying state sizes. Measure CPU, I/O, and memory overhead for replay versus forward execution, then extrapolate based on expected replay frequency. Caveat: synthetic workloads may underrepresent cache effects and interleaving, so combine with small-scale production sampling and factor the storage cost of replay logs. To refine the model, run isolated replay tests on a subset of production traffic.
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- Cost & Evaluation
How should I scope a proof of concept for a durable agent execution platform?
Focus a proof of concept on resilience over scale to reveal true platform fit for agentic workflows.
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What key metrics should I track during a durable execution proof of concept?
Measure recovery correctness and operational overhead reductions, not agent logic accuracy, when evaluating durable execution.
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What cost categories do teams often overlook when planning to run a durable execution platform in production?
Engineering for state design, upgrade testing, and on-call triage often outweigh infrastructure costs in durable systems.