Performance Load Test Simulator
Build a professional load test scenario in under a minute: VUs, ramp-up, plateau, traffic distribution and expert performance & cloud tips.
Quick glossary
VU (Virtual User)
Virtual user simulated in parallel by k6/JMeter/Gatling. Load metric #1.
Ramp-up
Progressive climb from 0 → target load. Gives autoscalers time to react.
Plateau
Load held at target. Where you measure stability and SLOs.
P95 (latency)
95% of requests answer faster than this. Better than average for UX.
P99 (latency)
Catches the slowest requests (cold-starts, GC pauses, locks). Reveals anomalies.
RPM / RPS
Requests per minute (or per second). Effective throughput absorbed by the system.
Throughput
Volume of requests handled over time. Measure on plateau, not peak.
SLO
Service Level Objective. Numeric target to honor (e.g. P95 ≤ 500ms, errors ≤ 1%).
Project context
The more specific the context, the sharper the advice
Everything flows through a single deployable. Typical bottlenecks: shared DB, locks, transactions too wide.
Load parameters
Set the target load and duration
User scenarios
Percentages must sum to 100% (current: 100%)
Estimated total volume
~52 500
over 20 min (ramp-up + plateau)
Target load
500
Throughput
3 000/min
Total duration
20 min
% coherence
100%
Total at 100%
Per-scenario breakdown
Go pro in the Timint app
Analyse results (P95/P99, errors, score), get expert remediation tips, and generate a styled PDF audit report.
✅ Auto-computed performance score
✅ Expert performance & cloud advice
✅ PDF report with charts + profile save
Detailed shot plan
Total and per-scenario load at each ramp-up step, then on plateau
| Phase | Timing | Total VU | Total req/min | search-cart (75%) | checkout (20%) | signup (5%) |
|---|---|---|---|---|---|---|
| Ramp-up step 1/4 (25%) | T+1.3 min | 125 | 750 | 94 ·563 | 25 ·150 | 6 ·38 |
| Ramp-up step 2/4 (50%) | T+2.5 min | 250 | 1 500 | 188 ·1 125 | 50 ·300 | 13 ·75 |
| Ramp-up step 3/4 (75%) | T+3.8 min | 375 | 2 250 | 281 ·1 688 | 75 ·450 | 19 ·113 |
| Ramp-up step 4/4 (100%) | T+5.0 min | 500 | 3 000 | 375 ·2 250 | 100 ·600 | 25 ·150 |
| Sustained plateau | T+5→20 min | 500 | 3 000 | 375 ·2 250 | 100 ·600 | 25 ·150 |
| Estimated volume: ~7 500 actions during ramp-up + ~45 000 actions during plateau = ~52 500 requests total. | ||||||
Risks per critical service
4 service(s) checked — each exposed service has its own risk profile
RiskAuthentication
Auth saturation = session blocks and refresh-token loops. Watch: users-table DB pool, JWT cache, /login throttling.
RiskSearch
Search latency → instant cart abandonment. Bottlenecks: Elasticsearch / Algolia indexes, facet queries, full-text scans.
RiskCheckout
Checkout failure = direct revenue loss. Measure the full funnel (cart → shipping → payment → confirmation).
RiskPayment
PSP error = lost payments or double charges. Idempotency keys are mandatory, PSP A → B failover in < 60s.
Expert recommendations — Monolith
DevOps, SRE and Solution Architect tips tailored to your architecture
🛠️ DevOps & Cloud scale
- •Profile the 10 most expensive endpoints before the test (APM: Datadog, NewRelic, Sentry Performance)
- •Enable DB slow query log and archive it during the test for post-mortem analysis
- •Provision +30% CPU/RAM during the test if stateful — otherwise scale horizontally with round-robin LB
- •Freeze deployments and disable cron jobs during the test window
⚙️ SRE / Platform
- •Define the 4 golden signals BEFORE the test: latency, traffic, errors, saturation
- •Alert on SLOs (P95, error rate), not raw CPU thresholds
- •Prepare a read-only degraded DB mode in case of unexpected saturation
- •Test rollback of the previous deployment in under 5 minutes
🏛️ Solution architect
- •Identify bounded contexts (DDD) to prepare a potential split into modular monolith
- •Progressively move heavy jobs (PDFs, emails, exports) to a queue + worker
- •Externalize sessions to Redis before scaling horizontally (stateless first)
- •Measure operational cost per feature to target the next split
Expert advice tailored to the project — E-commerce
Recommendations specific to the business constraints of your project type
Ready-to-copy k6 code
Script auto-generated with your parameters + scenarios + SLO thresholds
import http from 'k6/http';
import { sleep, group } from 'k6';
export const options = {
stages: [
{ duration: '1.3m', target: 125 },
{ duration: '1.3m', target: 250 },
{ duration: '1.3m', target: 375 },
{ duration: '1.3m', target: 500 },
{ duration: '15m', target: 500 },
],
thresholds: {
http_req_duration: ['p(95)<500', 'p(99)<1500'],
http_req_failed: ['rate<0.01'],
},
};
export default function () {
group('search-cart', () => {
// 75% du trafic — 375 VU cible · 2250 req/min
// TODO: implement requests for the search-cart scenario
});
group('checkout', () => {
// 20% du trafic — 100 VU cible · 600 req/min
// TODO: implement requests for the checkout scenario
});
group('signup', () => {
// 5% du trafic — 25 VU cible · 150 req/min
// TODO: implement requests for the signup scenario
});
sleep(10.0);
}Pre-shot checklist
Tick before launching to avoid false alarms
Share this simulation
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The link will be public. Only the values entered here will be published. No personal data beyond the optional name.
A well-scoped load test costs 10x less than a production outage. Plan it here, run it with your tool (k6, JMeter, Locust), then analyse the results in the Timint app to get a ready-to-share audit report.
Timint Smart Tips
AIPayment service selected: use the PSP sandbox and plan for 3DS retries / idempotency keys.
E-commerce with search: index popular facets and enable a short cache on hot queries.
Download the Timint app to analyse results and generate a styled PDF audit report.
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