Chaos Engineering as a discipline experiments with the system in production to build confidence in its capability to respond and sustain in turbulent conditions. It helps to identify faults and gaps in the systems. One of the basic principles of chaos engineering is to introduce hypothesis and experiments. The nature and scale of the hypothesis are small while closer to the live systems in terms of functionalities. The primary objective of chaos engineering is to generate new unknown information about a system and its behavior pattern as a whole while reacting to a catastrophe.
Why chaos engineering is important
Ecosystems are becoming more complex and complicated in the digital age. The service outage in current scenarios is costly, and the impact is multi-fold. The traditional ways and means of testing are not enough to guarantee service availability with next-gen systems. Hence, there is a need for an innovative approach to verify and validate availability in an automated manner.
Chaos engineering addresses these requirements. With the approach of identifying the individual component level failures along with ecosystem-level failures, chaos engineering helps to minimize the impact of outages.
Chaos engineering is becoming a norm for disaster recovery testing.
The use cases and benefits
It is recommended to run chaos engineering continuously in the environment. Some of the key benefits of chaos engineering are:
- Ability to simulate unpredictable user behavior intersecting with unforeseeable events to avoid service interruptions
- Ability to manage complex, complicated systems in a structured manner
- Leveraging the benefits of automation
- Building knowledge-based on system failures
Key resiliency areas addressed by chaos engineering
Chaos engineering addresses resiliency of key components in any organization (See Figure 1).