As cloud-native services scale, troubleshooting demands also grow exponentially. As service footprints expand, more DevOps cycles are consumed by troubleshooting versus delivering new code, creating barriers to innovation.
This simple model can be customized with company-specific data to illustrate the challenge in numbers. Beyond the cost of human capital, there are a number of other costs that have a direct impact on troubleshooting costs, such as the escalating costs of infrastructure and third-party SaaS services dedicated to the management of observability data.
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This model illustrates the costs and impact of efficiency gains that can be achieved through automated root cause analysis
Related resources
- See Causely in action: request a demo of the causal AI platform.
- Read the blog: Time to Rethink DevOps Economics? The Path to Sustainable Success