How Limitless Observability Can Help Enable AISecOps-Driven Transformation - AI Summary

The scale and complexity of these data and application environments are increasing relentlessly, and many companies already use five different cloud service platforms on average, according to research conducted by Coleman Parkes and commissioned by Dynatrace. Effective and timely AISecOps processes must draw on converged and contextualized sources of observability, business and security data that can create the precise insights needed to automate, protect and optimize clouds and the digital experiences they power. Even more, maintaining the relationship between each data stream--with continuously updated topology mapping that reveals all the system dependencies across the technology stack--provides the context AI needs to interpret the signals correctly and deliver more precise answers. Combining this storage model with massively parallel processing (MPP) can supercharge AI and analytics capabilities by enabling DevOps teams to query data simultaneously without needing to create an index or use a schema. With an MPP-powered data lakehouse, however, teams can get real-time AI-powered answers and analyze logs and events for deeper pattern searching and troubleshooting, typically saving the organization losses in productivity, revenue and reputation.