Gateway Header Injection for Chaos Resilience Testing
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Solution Overview
Problem
Current chaos engineering platforms inefficiently inject chaos into systems, often affecting idle components and failing to measure system resiliency due to lack of network traffic during testing.
Innovation Solution
A system and method where a gateway inserts headers into application requests to determine whether to inject chaos, with a proxy agent acting as a middleman to receive chaos instructions from an orchestrator, allowing controlled chaos injection based on network traffic and configuration settings, and a monitoring agent to assess system behavior.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If chaos is randomly injected into the system, then system components can be tested for resiliency, but the testing becomes inefficient and ineffective when no network traffic is present
Solution Approach 1:
The system performs preliminary actions by checking for the presence of network traffic before injecting chaos. The gateway monitors incoming requests and only triggers chaos injection when it detects active traffic, ensuring that chaos is injected at appropriate moments when the system is actually under load and needs to be tested for resiliency.
Solution Approach 2:
The system implements feedback mechanisms where the gateway continuously monitors network traffic conditions and adjusts chaos injection decisions based on this feedback. When traffic is detected, chaos injection is activated; when traffic is absent, injection is suppressed. This feedback loop ensures efficient and effective testing of system resiliency.
2Reliability
If chaos is injected into idle components, then system resiliency can be tested, but the impact on production environment is minimized and testing accuracy is reduced
Solution Approach 1:
Before injecting chaos, the system performs a preliminary check to verify that network traffic is currently flowing through the target component. This preliminary action ensures that chaos is only injected when the component is actively handling requests, thereby maintaining test accuracy while limiting impact during low-traffic periods.
Solution Approach 2:
The system changes the parameter of traffic presence as a gatekeeper condition for chaos injection. By monitoring traffic parameters (such as request rate, response time, or connection status) and using this information to control when chaos injection occurs, the system ensures that testing accurately reflects real-world resiliency conditions.
3Productivity
If chaos injection rate is increased to improve testing coverage, then more system components can be tested, but the impact on user experience and system stability increases
Solution Approach 1:
The gateway uses feedback from monitoring network traffic conditions to dynamically control chaos injection rate. When traffic volume is high, chaos injection is suppressed or reduced to minimize user impact. When traffic is low or absent, injection rate can be increased to improve testing coverage. This feedback-based rate control balances testing effectiveness with user experience protection.
Solution Approach 2:
The system makes the chaos injection rate dynamic rather than static. The injection rate adapts in real-time based on monitored traffic conditions, allowing the system to optimize between testing coverage and user impact protection. This dynamic adjustment enables the system to achieve high testing coverage during appropriate windows while protecting users during critical periods.
Data Source
AI summary
Systems and methods are described for injecting chaos into an application based on a determination that network traffic will be at the application when the chaos is injected. In an example, a gateway can receive requests for applications in a system. The gateway can be configured to periodically insert a header into an application request that causes a proxy agent associated with the requested application to request chaos instructions from a server. When chaos instructions are requested, the server can determine whether and what kind of chaos to inject into the application. The server can send instructions to the proxy agent, which can inject chaos according to the instructions. A monitoring agent can then monitor traffic around the application to determine whether other applications and system components behave appropriately in response to the injected chaos.