How do I tie performance to revenue credibly?

Use holdouts or A/B. For the impacted pages or APIs, track both performance (LCP, p95) and business KPIs (conversion, revenue per session). Compare deltas between test/control. Share a single dashboard that shows latency down, conversion up, with confidence intervals.

What if my biggest bottleneck is a third-party API?

Bulkhead it with separate connection pools, strict timeouts, retries with jitter, and a circuit breaker. Cache idempotent responses and design graceful degradation (placeholders, queued actions). Negotiate rate and latency SLOs with the vendor and monitor them as if they were your own service.

We’re already on a service mesh. Isn’t that enough?

Meshes give you the knobs; the playbook tells you where to set them and how to verify the business impact. You still need sane timeouts, retry budgets, SLOs, and canaries wired into rollout policy.

How often should we run load tests?

At minimum, before major launches and monthly thereafter. Automate a short k6 smoke in CI, plus a heavier off-peak run that mimics traffic mix. Re-baseline after big dependency upgrades (framework, runtime, DB).

Can we standardize these across teams without becoming a platform bottleneck?

Yes. Ship opinionated defaults as reusable Terraform/Helm modules and mesh policies, with escape hatches. Guard the SLOs, not the implementation details. Empower teams to deviate only with data.

Performance-optimization · Oct 2, 2025 · 10 minute read

Seven Performance Playbooks That Actually Move the Needle (Core Web Vitals to Token Throughput)

Reusable, testable playbooks that tie p95 latency to revenue — for SPA+BFF, Monolith+DB, Microservices, Kafka, Serverless, and LLM inference.

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Seven Performance Playbooks That Actually Move the Needle (Core Web Vitals to Token Throughput)

Key takeaways

Implementation checklist