Workshop Description:
Testing is essential to ensure that your software application performs as expected. No doubt about it. But even if your application runs smoothly in a testing environment, unexpected incidents can occur in production, such as a crashed database or a lost connection to a third-party service.
To ensure your application can handle such incidents and minimize their impact, you need to incorporate chaos testing into your delivery process. In this workshop, we will start with a brief introduction to k6 for backend performance testing and we’ll explore how to implement chaos testing using k6 for two backend services, to help you ensure the resilience of your application.
What will you Learn:
Equip tech leads and engineering managers with the knowledge and skills needed to effectively utilize analysed data extracted from git repositories for optimising software development processes, improving team dynamics, and driving continuous improvement within their teams.
Level: Intermediate
TAGs: #SWCraftsmanship #chaos_testing #chaos_engineering
Target audience: Tech leads, Engineering managers, Developers who want to want to improve their skills in a data-driven way.
Prerequisites on Audience:
- Git installed
- Go installed
- Docker engine in your machine to build the service images
- The kubectl command line tool to interact with the Kubernetes cluster
- Have an account on Docker hub to store the service images
- Minikube installed
Deliverables:
- Software developed during the workshop.
- The presentation presented during the workshop.
Schedule:
Introduction (15 min)
- Brief overview of the workshop and what the audience will cover
- Introduction to chaos engineering and chaos testing principles
Building and Deploying MicroServices (20 min)
- Install a local k8s with minikube
- Build and deploy a provider microservice
- Build and deploy a consumer microservice
Chaos Testing in Practise (20 min)
- Fault injection in the provider microservice with ServiceDisruptor
- Thresholds and SLOs in a chaos testing scenario
- Grafana visualization
- Root cause analysis
- Self healing mechanism
Conclusion (5 min)
- Recap of key elements
- Future insights
Total: 60 min