Top performers had 99.99%+ availability and an MTTR of under one hour (highlighted above). In order to achieve these impressive numbers, we looked into what tooling teams used. Notably, autoscaling, load balancers, backups, select rollouts of deployments, and monitoring with health checks were all more common in the top availability group. Some of these, such as multi-zone, are expensive, while others, such as circuit breakers and select rollouts, are a time and engineering expertise issue.

Teams who consistently run chaos experiments have higher levels of availability than those who have never performed an experiment, or do so ad-hoc. But ad-hoc experiments are an important part of the practice, and teams with >99.9% availability are performing more ad-hoc experiments.

The biggest inhibitors to adopting Chaos Engineering are a lack of awareness and experience. These are followed closely by ‘other priorities’ but interestingly more than 10% mentioned the fear that something might go wrong was also a prohibitor. It’s true that in practicing Chaos Engineering we are injecting failure into systems, but using modern methods that follow scientific principles, and methodically isolating experiments to a single service, we can be intentional about the practice and not disrupt customer experiences.

We believe the next stage of Chaos Engineering involves opening up this important testing process to a broader audience and to making it easier to safely experiment in more environments. As the practice matures and tooling evolves, we expect it to be more accessible and faster for engineers and operators to design and run experiments to improve the reliability of their systems across environments - today, 30% of respondents are running chaos experiments in production. We believe that chaos experiments will become more targeted and automated, while also becoming more commonplace and frequent.

The data sources for this report include a comprehensive survey with 400+ responses and Gremlin’s product data. Survey respondents are from a range of company sizes and industries, primarily in Software and Services. Adoption of Chaos Engineering has hit the enterprise, with nearly 50% of respondents working for companies with more than 1,000 employees, and nearly 20% working for companies with more than 10,000 employees.

The survey highlighted a tipping point in cloud computing, where nearly 60% of respondents ran a majority of their workloads in the cloud, and used a CI/CD pipeline. Containers and Kubernetes are reaching a similar level of maturity, but the survey confirmed that service meshes are still in their early days. The most common cloud platform is AWS at nearly 40%, with GCP, Azure, and on-premises following around 11-12%.