Chaos Engineering · Method · 360° | Nexonoma

method#Observability#Chaos Engineering#Resilience#Testing

Chaos Engineering

Chaos Engineering is a hands-on method to enhance the resilience of systems through controlled experiments.

Chaos Engineering tests systems by introducing intentional faults and unexpected events.

Maturity

Established

Cognitive loadMedium

Classification

ComplexityMedium
Impact areaTechnical
Decision typeDesign
Organizational maturityAdvanced

Technical context

Integrations

Jira for task management.Prometheus for monitoring purposes.Grafana for reporting.

Principles & goals

Principles

Proactively induce failures.Simulate real conditions.Promote learning systems.

Value stream stage

Iterate

Organizational level

Team, Domain

Use cases & scenarios

Use cases

Scenarios

Compromises

Risks

Unintended data loss.
Negative effects on user experience.
Complex failure scenarios are difficult to simulate.

Best practices

Conduct regular tests.
Emphasize teamwork and communication.
Promote a culture of error.

I/O & resources

Inputs

Comprehensive system documentation.
Testing strategies and plans.
Team resources and skill sets.

Outputs

Reporting on test executions.
Analysis of failure causes.
Recommendations for system improvements.

Resources

Description

Chaos Engineering tests systems by introducing intentional faults and unexpected events. This method helps identify weaknesses and improve overall system stability.

Benefits

Improved system resilience.
Increased visibility of failure sources.
Optimization of recovery processes.

Limitations

Potential disruptions in ongoing operations.
Requires a deep understanding of the system architecture.
Cannot cover all failure scenarios.

Trade-offs

Metrics

Failure Rate
Number of simulated failures in the system.
Recovery Time
Time taken to recover the system after a failure.
System Availability
Percentage of time the system is available.

Examples & implementations

Chaos Monkey

A tool for simulating server failures in AWS environments.

Gremlin

A chaos engineering platform that provides an easy-to-use interface.

Simian Army

A suite of tools to test various scenarios in cloud infrastructures.

Implementation steps

Development of a test plan.

Conduct initial tests.

Analysis and documentation of the results.

Technical debt & bottlenecks

Technical debt

Aged systems without testing.
Insufficient monitoring processes.
Poor documentation of previous tests.

Known bottlenecks

Constraints on system availability.Difficulties in testing in the production environment.High costs for fault simulation.

Misuse examples

Faulty implementation without testing.
Too aggressive fault sampling.
Skipping necessary approvals.

Typical traps

Too long wait times between tests.
Insufficient monitoring during tests.
Lack of assessments of test results.

Required skills

Knowledge of system architecture.Experience in test management.Skills in cloud technologies.

Architectural drivers

Scalability of systems.Flexibility of architecture.Reliability of infrastructure.

Constraints

• Resource limitations.
• Technical dependencies.
• Regulatory requirements.