Simulatore di Test di Carico
Costruisci uno scenario di load test professionale in meno di un minuto: VU, ramp-up, plateau, distribuzione del traffico e consigli esperti.
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%).
Contesto del progetto
Più preciso il contesto, più affilati i consigli
Everything flows through a single deployable. Typical bottlenecks: shared DB, locks, transactions too wide.
Parametri del test
Imposta il carico target e la durata
Scenari utente
La somma delle percentuali deve essere 100% (attuale: 100%)
Volume totale stimato
~52 500
su 20 min (ramp-up + plateau)
Carico target
500
Throughput
3 000/min
Durata totale
20 min
Coerenza %
100%
Totale al 100%
Ripartizione per scenario
Passa alla versione pro nell'app Timint
Analizza i risultati (P95/P99, errori, score), ricevi consigli esperti di rimedio e genera un report di audit PDF.
✅ Score di performance auto-calcolato
✅ Consigli esperti performance & cloud
✅ Report PDF con grafici + salvataggio profilo
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
RiskAutenticazione
Auth saturation = session blocks and refresh-token loops. Watch: users-table DB pool, JWT cache, /login throttling.
RiskRicerca
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).
RiskPagamento
PSP error = lost payments or double charges. Idempotency keys are mandatory, PSP A → B failover in < 60s.
Expert recommendations — Monolite
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
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Un load test ben progettato costa 10x meno di un'interruzione in produzione. Progetta qui, esegui con il tuo tool (k6, JMeter, Locust), analizza nell'app Timint per un report condivisibile.
Timint Smart Tips
AIServizio pagamento selezionato: usa il sandbox del PSP e prepara retry 3DS / idempotency key.
E-commerce con ricerca: indicizza le facet popolari e attiva una cache breve sulle query frequenti.
Scarica l'app Timint per analizzare i risultati e generare un report PDF.
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