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(IT-NEWSWIRE.COM, December 12, 2023 ) The global Chaos Engineering Tools Market size is expected to grow from USD 1.9 billion in 2023 to USD 2.9 billion by 2028 at a Compound Annual Growth Rate (CAGR) of 8.8% during the forecast period. Modern IT systems have become highly complex, often involving microservices, containers, and cloud-based infrastructure. Chaos engineering tools are essential for testing and improving the resilience of these systems, which is expected to create demand during the forecasted period.
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Chaos Engineering Tools Market Dynamics:
Drivers:
Need for observability tools for managing distributed systems.
Gain real-time insights into system behaviour.
Measure the effects of injected failures with unprecedented accuracy.
Restraints:
Privacy and security concerns.
Raise valid apprehensions about data privacy and system security.
Opportunities:
Integration with monitoring and observability tools.
Enables quicker detection and response to issues.
List of Key Players in Chaos Engineering Tools Market:
Microsoft (US)
AWS (US)
OpenText (US)
Virtusa (US)
Tricentis (US)
Harness (US)
Nagarro (Germany)
PagerDuty (US)
Cavission Systems (US)
Gremlin (US)
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By component, the services segment is expected to grow at the highest CAGR during the forecast period.
Chaos engineering is a relatively new discipline, and many organizations are still in the early stages of adopting it. As a result, there is a strong demand for professional services in the chaos engineering tools market. As organizations adopt chaos engineering practices, they often encounter hurdles related to strategy development, tool selection, implementation, and result interpretation. Professional services in this context offer invaluable guidance and expertise to help businesses tailor chaos engineering to their specific needs and goals. These services can assist in designing controlled experiments, identifying potential points of failure, and providing a structured framework for assessing and improving system resilience.
By deployment mode, the public cloud segment holds a larger market size during the forecast period.
The adoption of chaos engineering tools on public cloud platforms has seen remarkable growth, driven by cloud providers' scalability, flexibility, and cost-efficiency. For instance, Netflix, a pioneer in chaos engineering, utilizes Amazon Web Services (AWS) for its experiments, taking advantage of AWS's extensive global infrastructure to test system resilience. By leveraging the scalability and ease of deployment that public clouds offer, organizations can proactively identify vulnerabilities, improve incident response strategies, and ensure their services remain robust despite unexpected disruptions. This adoption trend aligns with the growing significance of public cloud environments in the chaos engineering environment, facilitating the continued evolution of these crucial practices.
By Region, Asia Pacific is expected to grow at the highest CAGR during the forecast period.
Asia Pacific is home to some of the world's leading ICT companies, such as Alibaba, Tencent, and Baidu. These companies are investing heavily in chaos engineering tools to improve the reliability and resilience of their systems. The Asia Pacific governments are increasingly recognizing the importance of digital transformation. For instance, Singapore’s “Smart Nation” and South Korea's “Digital New Deal” emphasize digital transformation, providing fertile ground for chaos engineering adoption. Technological trends, such as microservices, AI, ML, and DevOps, are also driving the adoption of chaos engineering tools in the Asia Pacific region. Chaos engineering tools can be used to test microservices-based applications and ensure they are reliable and resilient. AI and ML can be used to develop more sophisticated chaos engineering tools.
Some of the key players operating in the chaos engineering tools market are – Microsoft (US), AWS (US), OpenText (US), Virtusa (US), Tricentis (US), Harness (US), Nagarro (Germany), PagerDuty (US), Cavission Systems (US), and Gremlin (US).
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