With the evolution of observability, DevOps and beyond, driven by data, AI and computation, we will see new observability pillars driving DevOps practices. Predictive visibility will allow deep and broad forecasts of cloud and business systems. Workload data and telemetry allow for model creation, validation and tuning. Autonomous remediation for rapid, targeted response to cloud and business issues will be automatic, even when teams are not available.
Alignment of cloud and business metrics spanning across the production floor and virtual cloud will merge to expose valuable insights. These new pillars will improve observability ROI by forcing a shift from consumption-based pricing models allocating funding for DevOps 2.0.
Key learnings:
– Why the new ways to observe, identify and repair infrastructure are different from the old technology will change DevOps practices.
– Why accessibility, low cost of quality, organized and large quantities of data is essential for DevOps 2.0.
– Why these change will allow the redistribution of resources to more higher value activities.