Senior Performance Test Engineer k6 Azure

Sunovaa Tech; Bengaluru; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Sunovaa Tech in Bengaluru, India is seeking a performance testing expert to design and execute k6-based tests for cloud-native microservices. You will build realistic workload models and run comprehensive tests across REST, gRPC, WebSocket, and GraphQL APIs.

The role requires strong scripting in JavaScript, experience with CI/CD integrations (Azure DevOps or GitHub Actions), and proficiency with monitoring tools like Azure Monitor, Grafana and Prometheus.

Qualifications

• Experience designing and executing performance tests for cloud-native microservices.
• Expertise with k6 scripting, scenarios, executors, thresholds, and think-time modelling.
• Strong knowledge of workload modelling, capacity planning, and percentile metrics.
• Familiarity with telemetry, distributed tracing, and performance analysis tools.
• Bachelor's or Master's degree in CS/Engineering or related discipline.

Responsibilities

• Design, develop and execute performance tests using k6 for cloud-native microservices.
• Create realistic workload models for end-to-end user journeys and run load, stress, spike, soak tests.
• Develop k6 scripts using JavaScript, scenarios, executors, thresholds, checks, and parameterization.
• Test REST, gRPC, WebSocket, and GraphQL APIs for performance.
• Integrate performance tests into Azure DevOps/GitHub Actions CI/CD pipelines with quality gates.
• Monitor and analyze app performance with Azure Monitor, Log Analytics, Grafana and Prometheus.
• Validate autoscaling on AKS with HPA and Cluster Autoscaler; troubleshoot bottlenecks.

Skills

Performance testing

Load testing

Analytical thinking

Stakeholder management

SLA/SLO analysis

Education

Bachelor's or Master's in Computer Science/Engineering

Tools

k6

Azure DevOps

GitHub Actions

Azure

AKS/Kubernetes

Docker

Helm

kubectl

Grafana

Prometheus

Job description

Role & Responsibilities

• Design, develop, and execute performance tests using k6 for cloud-native, microservices-based applications.
• Create realistic workload models for end-to-end user journeys and execute load, stress, spike, soak, scalability, and failover testing.
• Develop k6 scripts using JavaScript, scenarios, executors, thresholds, checks, correlation, parameterization, and think-time modelling.
• Perform performance testing of REST, gRPC, WebSocket, and GraphQL APIs.
• Integrate k6 performance tests into Azure DevOps/GitHub Actions CI/CD pipelines with automated quality gates.
• Monitor and analyze application performance using Azure Application Insights, Azure Monitor, Log Analytics, KQL, Grafana, and Prometheus.
• Validate performance and autoscaling of applications running on Azure Kubernetes Service (AKS), including HPA and Cluster Autoscaler.
• Identify and troubleshoot bottlenecks across application, microservices, containers, databases, Redis cache, storage, and network layers.
• Perform root-cause analysis using telemetry, distributed tracing, execution plans, wait statistics, Query Store, and other performance metrics.
• Prepare technical and executive-level performance reports highlighting findings, risks, capacity limitations, and recommendations.

Preferred Candidate Profile

• 58 years of experience in Performance Testing/Performance Engineering.
• Strong hands-on experience with k6 is mandatory, including scripting, scenarios, executors, thresholds, checks, correlation, and parameterization.
• 3+ years of experience in performance testing of cloud-based microservices, preferably on Microsoft Azure.
• Strong hands-on knowledge of Azure, AKS/Kubernetes, Docker, Helm, kubectl, and CI/CD.
• Experience with Azure Application Insights, Azure Monitor, Log Analytics, and KQL.
• Strong understanding of REST APIs; experience with gRPC, WebSocket, SignalR, or GraphQL is an advantage.
• Experience with Azure DevOps/GitHub Actions and integrating performance tests into CI/CD pipelines.
• Good knowledge of SQL/database performance, Redis, Grafana, and Prometheus.
• Strong understanding of workload modelling, capacity planning, SLA/SLO analysis, and percentile-based performance metrics.
• Excellent analytical, problem-solving, communication, and stakeholder management skills.
• Bachelor's or Master's degree in Computer Science, Engineering, or a related discipline.