Resiliency testing and Chaos Engineering

Today let’s discuss about one of the fast-growing topics, resiliency testing and chaos engineering. With the phenomenal growth ‘digital’ in the current era, where the Internet is turning into the backbone of any major business. This has not only increased the need for high-capacity servers, but also how resilient is your application. Let’s start with basic definitions:

What is Resiliency Testing

Resiliency testing is a type of testing performed to assess the ability of a system or application to recover from various types of failures and continue to operate in a degraded state without completely shutting down or losing data. The purpose of resiliency testing is to identify potential weaknesses or vulnerabilities in a system and to test how well it can recover from various types of failures, such as hardware failures, network failures, software failures, cyberattacks, and other types of disruptions.

Resiliency testing can involve simulating various types of failures or disruptions and observing how the system responds. The testing may include conducting controlled experiments in a test environment or conducting real-world simulations to assess the system’s resilience under actual operating conditions.

The goal of resiliency testing is to ensure that a system can continue to operate with minimal interruption or downtime, even in the face of unexpected events or disruptions.

What is Chaos Engineering

Chaos engineering is a software testing methodology that involves intentionally introducing controlled and carefully designed disruptions or failures into a system to observe how it responds and to identify potential weaknesses or vulnerabilities. The goal of chaos engineering is to improve the resilience and reliability of complex systems, such as distributed computing systems, cloud-based systems, and microservices architectures.

Chaos engineering typically involves the following steps:

• Identify the components of the system to be tested and the potential failure scenarios.
• Create experiments that introduce controlled disruptions, such as killing a server or disconnecting a network connection.
• Run the experiments and observe how the system responds.
• Analyse the results and identify areas where the system can be improved to better handle failures.
• Chaos engineering is based on the idea that failures and disruptions are inevitable in complex systems and that by deliberately introducing controlled failures, system designers can learn how to design more resilient and reliable systems. By identifying and addressing weaknesses before they lead to real-world failures or outages, chaos engineering can help to prevent costly downtime, data loss, and other negative impacts.

Both resilience testing and chaos engineering are important tools for improving the reliability and resilience of complex systems. By identifying and addressing weaknesses in a system, organizations can reduce the risk of downtime, data loss, and other negative impacts, and ensure that their systems can continue to operate even in the face of unexpected disruptions.

Key Benefits:

• Aid us to quickly spot, isolate & fix single point of failures in the application
• Meets Quality of Service (QoS) to higher standards
• Application Down time cost is considerably minimized. Reduce MTTD & MTTR
• Helps to enable strong resilient features with auto-healing capabilities.

Focus Areas:

• CPU, Memory, Disk, I/O attacks
• Restart/shutdown
• Network Latency Delay/Packet Loss
• Process Crash
• Black Hole/App Delays

Tool Set:

Chaos Engg:

Mangle, Simian Army (includes Chaos monkey), Gremlin, Chaos Blade, Nagarro’s Chaos framework Cloud: Fault Injection Simulator (FIS) – AWS; Chaos Data Studio Service – Azure; Gremlin from Marketplace – GCP

Also read: The Role of Digital Assurance in Accessibility and Inclusion

In the future, we can expect that chaos engineering will continue to grow in importance as more and more critical systems become increasingly complex and interconnected. As systems become more complex, they become harder to predict and harder to control, and so the risks associated with system failures increase. Chaos engineering will play a key role in helping organizations identify and mitigate these risks by allowing them to test their systems in a controlled environment and identify potential weaknesses before they become real-world problems.

Additionally, we will see a continued evolution of chaos engineering techniques and tools, including the development of new approaches to chaos engineering that consider the unique characteristics of specific systems and environments. We will also see continued integration of chaos engineering into DevOps and agile development methodologies, allowing organizations to build resilience and reliability into their systems from the ground up.

Overall, I believe that chaos engineering will continue to play an increasingly important role in ensuring the reliability and resilience of complex systems in the years to come.