Performance testing with jenkins and JMeter or Gatling¶
Nubenetes V2 Elite Portal
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Architectural Context
Detailed reference for Performance testing with jenkins and JMeter or Gatling in the context of Platform & Site Reliability.
Cloud Native¶
Kubernetes¶
Progressive Delivery¶
- (2024) Iter8 [GO CONTENT] [ADVANCED LEVEL] 🌟🌟🌟🌟 [ENTERPRISE-STABLE] — A Kubernetes-native release validation and progressive delivery tool. Iter8 enables automated canary testing, A/B testing, and SLO evaluation. It coordinates traffic shifting using Service Meshes or Gateways, evaluating metrics from Prometheus and metrics-server to automate rollbacks or promote stable microservice builds.
Infrastructure¶
Testing¶
Load Testing¶
- (2021) Distributed Load Testing on AWS 🌟 [ADVANCED LEVEL] [COMMUNITY-TOOL] [GUIDE] — An AWS Solution blueprint outlining distributed cloud load testing utilizing containerized runners inside AWS Fargate. Simulates high-velocity traffic spikes to assess API gateway throughput bottlenecks and database elasticity limits.
Performance Engineering¶
Load Testing (1)¶
Kubernetes Deployment¶
- (2022) dev.to: The most elegant way to performance test your microservices running on Kubernetes [YAML CONTENT] [ADVANCED LEVEL] 🌟🌟🌟🌟 [ENTERPRISE-STABLE] — Demonstrates running scalable API performance evaluations in target Kubernetes setups. Promotes executing testing runs close to targets using container workloads to limit network noise.
Observability¶
- (2022) linkedin.com: Tuning Grafana - Jmeter Dashboards [N/A CONTENT] 🌟🌟🌟🌟 [ENTERPRISE-STABLE] — Examines methodologies for directing live JMeter thread telemetry to Grafana dashboards via InfluxDB. Gives operational teams real-time visibility into transaction metrics during heavy profiling runs.
Testing (1)¶
Performance Testing¶
Service Level Objectives¶
- (2023) thenewstack.io: Simple HTTP Load Testing with SLOs [N/A CONTENT] [COMMUNITY-TOOL] — A technical exploration of how modern load testing tools are adopting Service Level Objectives (SLOs) as first-class assertions. It contrasts classical metric collections against modern SLO-driven assertions (e.g., verifying 95th percentile latency is under 100ms), showcasing how to integrate these checks directly into automated deployment flows.
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