The rise of microservices architecture has sparked significant discussions within the technology industry. Despite the challenges posed by global events like the Russia-Ukraine war and the COVID-19 pandemic, experts project a remarkable growth in the market size of microservices architecture in the coming years. According to the IMARC Group, the market is expected to reach $7.8 billion by 2028. The Business Research Company paints an even brighter picture, predicting a market value of $10.86 billion by 2027. Market Research Future (MRFR) is even more optimistic, forecasting a growth to $21.61 billion by 2030. These projections confirm the widespread adoption of microservices architecture, making it crucial for developers and engineers to enhance their skills in technologies such as Docker, Kubernetes, and REST APIs.
The Complexity Challenge
However, as the adoption of microservices architecture continues to grow, so does the complexity of these systems. Testing these intricated systems made by hundreds of nodes and thousands of microservices is becoming challenging, and predicting failures has become increasingly difficult. Such failures can result in costly outages for companies. According to an International Data Corporation (IDC) report, infrastructure failures can cost large businesses around $100,000 per hour, while critical application failures can range from $500,000 to $1 million per hour. Furthermore, a survey conducted by the Uptime Institute found that nearly one-third of all data centers experienced an outage in 2020.
To proactively address the challenges posed by the complexity of microservices architecture, an increasing number of companies are turning to Chaos Engineering.
Introducing Chaos Engineering
Chaos Engineering is a proactive testing practice designed by Netflix to test its system stability after it was migrated to Amazon Web Services. Its original purpose was to assess how its system responded when critical components of its infrastructure were taken down. By intentionally inducing failures and closely…