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Simulador de Testes de Carga

Construa um cenário de load test profissional em menos de um minuto: VUs, ramp-up, plateau, distribuição de tráfego e conselhos experts de performance e cloud.

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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%).

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Contexto do projeto

Quanto mais preciso o contexto, mais afiados os conselhos

Everything flows through a single deployable. Typical bottlenecks: shared DB, locks, transactions too wide.

Parâmetros do teste

Defina a carga alvo e a duração

VUs totais500 VU
Duração do ramp-up5 min
Duração do plateau15 min
Ações/min por utilizador6
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Cenários de utilizador

A soma das percentagens deve ser 100% (atual: 100%)

#1
Quota de tráfego: 75%
VUs: 375Ações: 2250/min
#2
Quota de tráfego: 20%
VUs: 100Ações: 600/min
#3
Quota de tráfego: 5%
VUs: 25Ações: 150/min

Volume total estimado

~52 500

em 20 min (ramp-up + plateau)

Carga alvo

500

Throughput

3 000/min

Duração total

20 min

Coerência %

100%

Total a 100%

Divisão por cenário

search-cart375 VU · 2250/min
checkout100 VU · 600/min
signup25 VU · 150/min
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Passe à versão pro na app Timint

Analise os resultados (P95/P99, erros, score), receba conselhos experts de remediação e gere um relatório de auditoria PDF.

✅ Score de performance auto-calculado

✅ Conselhos experts de performance e cloud

✅ Relatório PDF com gráficos + guardar no perfil

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Detailed shot plan

Total and per-scenario load at each ramp-up step, then on plateau

PhaseTimingTotal VUTotal req/minsearch-cart
(75%)
checkout
(20%)
signup
(5%)
Ramp-up step 1/4 (25%)T+1.3 min12575094 ·56325 ·1506 ·38
Ramp-up step 2/4 (50%)T+2.5 min2501 500188 ·1 12550 ·30013 ·75
Ramp-up step 3/4 (75%)T+3.8 min3752 250281 ·1 68875 ·45019 ·113
Ramp-up step 4/4 (100%)T+5.0 min5003 000375 ·2 250100 ·60025 ·150
Sustained plateauT+520 min5003 000375 ·2 250100 ·60025 ·150
Estimated volume: ~7 500 actions during ramp-up + ~45 000 actions during plateau = ~52 500 requests total.
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Risks per critical service

4 service(s) checked — each exposed service has its own risk profile

RiskAutenticação

Auth saturation = session blocks and refresh-token loops. Watch: users-table DB pool, JWT cache, /login throttling.

RiskPesquisa

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.

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Expert recommendationsMonólito

DevOps, SRE and Solution Architect tips tailored to your architecture

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🛠️ 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
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⚙️ 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
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🏛️ 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
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Expert advice tailored to the projectE-commerce

Recommendations specific to the business constraints of your project type

Long cache on product pages (edge + CDN), targeted invalidation from PIM
Short Redis lock on stock decrement to prevent overselling
Move transactional emails out of the sync path (queue + dedicated worker)
Idempotency keys on order creation + payment capture
PSP A → PSP B failover plan in < 60s in case of incident
Prepare for peaks (BF, sales) with a test ≥ 5× average traffic
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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

#1Isolated test accounts (no mix with real users)
#2Representative test catalog / data (size, distribution)
#3Monitoring active: dashboards ready + alerts on key SLOs
#4Structured logs and trace ID propagated across all hit services
#5PSP in sandbox mode + 3DS test mode enabled
#6Freeze deployments and disable crons during the window
#7Hosting / cloud provider notified about the test (capacity + budget alerts)
#8Rollback plan ready and tested: < 5 min to revert to previous state
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Insight Timint

Um load test bem planeado custa 10x menos que uma falha em produção. Planeie aqui, execute com a sua ferramenta (k6, JMeter, Locust), analise na app Timint.

Timint Smart Tips

AI
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Serviço de pagamento marcado: use o sandbox do PSP e prepare retries 3DS / idempotency keys.

🛒

E-commerce com pesquisa: indexe as facets populares e ative uma cache curta nas queries frequentes.

📲

Faça download da app Timint para analisar resultados e gerar um relatório PDF.

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