Edge Intelligence: Real-Time Analytics at the Source
summary
Claims specific impact numbers and concrete tools: 37% downtime reduction from on-device predictive models, 23% defect cut and ~80% lower cloud transfer cost in one manufacturing rollout, and a case where edge control survives a 3-day cloud outage avoiding >$1M/day loss. Describes lightweight container work (Alpine-based images, distro containers), progressive rollouts with resumable CI/CD, local anomaly detection and summarized observability, mesh networking, smart replication, and IaC plus policy-as-code with Git-based reconciliation for large-scale device fleets.
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chapters (12)
- 0:00Introduction and Overview
- 1:23The Shift to Edge Computing
- 2:43Applying SRE Principles to Edge Environments
- 4:29DevOps and Containerization at the Edge
- 6:12Observability and Automation at the Edge
- 7:48Intelligence and Predictive Maintenance at the Edge
- 9:19Real-World Use Cases of Edge Intelligence
- 11:06Designing Resilient Edge Systems
- 12:39Managing Edge Systems at Scale
- 14:08Balancing Local and Cloud Workloads
- 15:46Key Takeaways and Next Steps
- 17:23Conclusion and Final Thoughts
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