AI Inference at Scale: Reliability, Observability, Cost & Sustainability
AI inference is no longer a simple model call—it is a multi-hop DAG of planners, retrievers, vector searches, large models, tools, and agent loops. With this complexity comes new failure modes: tail-latency blowups, silent retry storms, vector store cold partitions, GPU queue saturation, exponential cost curves, and unmeasured carbon impact.
In this talk, we unveil ROCS-Loop, a practical architecture designed to close the four critical loops of enterprise AI:
•Reliability (Predictable latency, controlled queues, resilient routing)
•Observability (Full DAG tracing, prompt spans, vector metrics, GPU queue depth)
•Cost-Awareness (Token budgets, model tiering, cost attribution, spot/preemptible strategies)
•Sustainability (SCI metrics, carbon-aware routing, efficient hardware, eliminating unnecessary work)
KEY TAKEAWAYS
•Understand the four forces behind AI outages (latency, visibility, cost, carbon).
•Learn the ROCS-Loop framework for enterprise-grade AI reliability.
•Apply 19 practical patterns to reduce P99, prevent retry storms, and control GPU spend.
•Gain a clear view of vector store + agent observability and GPU queue metrics.
•Learn how ROCS-Loop maps to GCP, Azure, Databricks, FinOps & SCI.
•Leave with a 30-day action plan to stabilize your AI workloads.
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AGENDA
1.The Quiet Outage: Why AI inference fails
2.X-Ray of the inference pipeline (RAG, agents, vector, GPUs)
3.Introducing the ROCS-Loop framework
4.19 patterns for Reliability, Observability, FinOps & GreenOps
5.Cross-cloud mapping (GCP, Azure, Databricks)
6.Hands-on: Diagnose an outage with ROCS
7.Your 30-day ROCS stabilization plan
8.Closing: Becoming a ROCS AI Architect
About Rohit Bhardwaj
Rohit Bhardwaj is a Director of AI & Data Architecture at Salesforce, where he focuses on enterprise AI, agentic systems, cloud-native architecture, distributed systems, data platforms, security, and large-scale transformation.
Over his career, Rohit has designed and led complex enterprise platforms across AWS, Google Cloud, microservices, real-time data, API ecosystems, resilient distributed systems, and AI-enabled architectures. His work increasingly focuses on the challenges enterprises face as software evolves from deterministic services to AI-native and agentic systems—particularly around reliability, governance, evidence, security, observability, cost, and safe autonomy.
Rohit is the author of System Design with AI Interview Guide: Designing Scalable, Agentic, and Defensible Systems, published by Apress. The book presents a modern approach to system design covering scalability, distributed systems, AI architecture primitives, security, reliability, economics, agentic systems, and real-world architectures including e-commerce, ride sharing, payments, fraud detection, messaging, video streaming, file storage, and search. (Springer Link)
Book:
Amazon: https://a.co/d/09Zs1twa
Publisher / Springer Nature: https://link.springer.com/book/10.1007/979-8-8688-2782-2
O'Reilly: https://learning.oreilly.com/library/view/system-design-with/9798868827822/
Rohit is also an O’Reilly instructor and a frequent speaker at technology conferences including No Fluff Just Stuff, UberConf, GIDS, and other international events. His talks focus on practical architecture lessons from building and operating complex systems, including AI control planes, trusted agents, inference at scale, evidence-first RAG, AI security, distributed-system failure, and AI-era software architecture.
As a trusted advisor and architecture leader, Rohit works at the intersection of business strategy and deep technical architecture—helping teams translate complex business problems into scalable, resilient, secure, and economically sustainable systems.
Rohit holds an MBA in Corporate Entrepreneurship from Babson College and graduate-level education in Computer Science from Boston University and Harvard University.
Connect with Rohit:
LinkedIn: http://linkedin.com/in/rohit-bhardwaj-cloud
X / Twitter: @rbhardwaj1