For identification of weak areas and increasing resiliency.
Though this be madness, yet there is a method in it
No application in this world is entirely secure. There is a constant want to test and analyze applications deployed by an organization, even with the security of the cloud platform. It prevents the crashing of applications under various adverse conditions.
Chaos Engineering can be defined as the discipline of experimenting on software systems in production at scale to build confidence that the software systems can withstand turbulent and adverse conditions in production. Netflix- the popular video streaming platform devised this concept with its Chaos Monkey approach. Failures can happen anytime. Therefore, knowing failure stimulations serve to learn how to protect the system when actually under attack. This process makes sure there is thoroughly comprehensive and effective vulnerability testing, which would ultimately benefit the end-user.
Why Chaos Engineering?
Chaos Engineering helps you with:
Earlier forms of disaster recovery were custom, fragile, and expensive. Chaos Engineering makes use of APIs and automation in cloud computing to make recovery low cost and robust, which can be regularly exercised.
Chaos Engineering runs the test on real-time in-production systems rather than hypothetical situations, which provides a clearer picture of how the error would look and how the solution would work on it.
In cloud architecture, several vulnerabilities are difficult to detect with traditional DevOps and quality engineering. Chaos Engineering makes it easier to find these hidden problems.
MozoCloud's Phases of Chaos Engineering
Proper phases are prepared and implemented to achieve maximum results from this process:
A steady-state which resembles normal circumstances is used as a baseline, and a hypothesis is developed that this state will remain constant in normalcy and abnormality.
A series of possible real-world attack events are created. Random actions such as creation, deletion, modification of respective cloud APIs are orchestrated.
Attacks are launched on the software systems with varying magnitudes such as LOW, MEDIUM, and HIGH, and acquisition of detailed information on the composition and deployment of the software is stored.
Experiments are automated in the systems which allow security measures to initiate for either malicious or benign reasons and thereby gain insights into efﬁcient ways for designing and implementing secure cloud systems.