How to know when you need more concurrency.

Inngest concurrency measures the number of code-executing steps running simultaneously, rather than total workflows in progress, and account-level limits are shared across functions and environments. The article explains that capacity can be estimated with Little’s Law by multiplying steps started per second by average step duration, meaning increased latency from services such as LLM providers can raise concurrency needs even without more traffic. Key indicators that a workload needs more capacity include a backlog that never returns to zero, throughput that plateaus while queued work grows, recurring or exhausted burst-concurrency budgets, and typical weekly peaks approaching within roughly 25% of the account limit. Bursty concurrency can absorb occasional spikes and reveal actual peak demand, but persistent growth requires raising limits based on observed peak usage. The article also cautions that more account capacity will not resolve function-specific limits, uneven customer workloads, downstream API rate limits, inefficient in-code waiting, or prioritization needs, which may instead require concurrency keys, throttling, durable waiting steps, or priority settings.

Use this post, company, and trend context to find content marketing opportunities, perform competitive analysis, or address product feature gaps via the Plushcap MCP server or the Plushcap API.