Asmita Khuspe
Empowering Developers with Expertise in Cloud, AI, and Platform Engineering.
Pune, India
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Asmita Khuspe is a Platform Engineer at NCS with expertise in Google Cloud, AWS, AI/ML, and Platform Engineering. She brings complex cloud and AI concepts to life through real-life analogue storytelling. Asmita holds the AWS Solutions Architect – Associate and Google Associate Cloud Engineer certifications, and has presented at numerous tech events across India, including DevFest, Cloud Community Day, AWS Community Day, CNCF, and Build with AI. Her sessions focus on practical insights, innovative cloud solutions, and making emerging technologies relatable for everyone.
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Beyond kubectl: Reimagining Platform Engineering with AI on GKE
What if troubleshooting a GKE workload was as simple as having a conversation?
Platform engineering has traditionally relied on commands, dashboards, YAML, runbooks, and deep Kubernetes expertise. But with AI entering the developer workflow, we're moving toward a new model where engineers can interact with infrastructure using natural language while still working within the guardrails of the platform.
In this practical, demo-driven session, we'll explore how Gemini can become a powerful copilot for platform engineers on Google Kubernetes Engine (GKE). Starting with a real-world broken workload, we'll move beyond traditional `kubectl`-based troubleshooting and progressively give AI the context it needs to understand code, Kubernetes configurations, and the live GKE environment.
Through a hands-on Codelab-style demonstration, you'll see Gemini CLI, the GKE Model Context Protocol (MCP), and AI-powered workflows in action from diagnosing failures and understanding cluster state to generating configurations and turning repetitive operational knowledge into reusable workflows.
You'll leave with a practical understanding of how AI can augment not replace platform engineers, and how teams can begin building smarter, more contextual, and developer-friendly cloud platforms on GKE.
Platform Engineering in the AI Era: Guardrails, Scale, and Security
Platform engineering in 2025 is no longer just about Kubernetes clusters or CI/CD pipelines — it’s about building resilient platforms that are secure, scalable, and ready for AI-driven workloads. In this session, we’ll dive into how AI-first development is reshaping platform design. We’ll explore the shift from static “golden paths” to dynamic guardrails that give developers freedom while ensuring cost efficiency, compliance, and security at scale. Through real-world cloud-native examples and Google Cloud’s AI Development Kit (ADK), we’ll unpack the architectural patterns, tooling, and principles that make platforms AI-ready. Rather than focusing on fundamentals, this talk will highlight concrete practices engineers can apply to build modern platforms — from integrating AI workloads safely to designing systems that scale intelligently with demand. Learning Outcomes / Takeaways: 1. Learn how AI adoption is transforming the architecture of modern platforms. 2. Discover guardrail-driven design patterns for security, compliance, and efficiency. 3. Explore how tools like Google Cloud’s ADK enable secure, scalable, AI-first platforms.
Security Beyond Pods: Hidden Threats in Kubernetes IAM Configurations
Kubernetes security often focuses on pods, network policies, and runtime protection, but one of the biggest attack vectors is IAM (Identity and Access Management) misconfigurations—a silent threat that can lead to full cluster compromise.
In this lightning talk, I will demystify Kubernetes IAM across AWS, GCP, and Azure, highlighting common security pitfalls that engineers unknowingly introduce. Through real-world misconfigurations and attack scenarios, attendees will learn:
1- How Kubernetes IAM differs across cloud platforms and why it matters.
2- Common IAM mistakes—overly permissive roles, insecure service accounts, and default credentials.
3- How attackers exploit weak IAM settings to escalate privileges and access clusters.
4- Quick security fixes—implementing least privilege, external identity providers, and secure RBAC.
This session is ideal for cloud engineers, security professionals, and Kubernetes beginners who want to improve their Kubernetes security posture with practical, easy-to-implement IAM best practices.
Pune Made Me a Platform Engineer!
Every techie in Pune has a story that starts on FC Road — mine just happened to end in the cloud.
In this talk, I’ll share how the streets, cafés, and community of Pune made me the engineer I am today — from attending my first DevFest with a pocket full of stickers to speaking at one, and now building platforms that power real-world applications. Through funny and heartfelt analogies inspired by Vaishali’s queues, Roopali’s self-service efficiency, and FC Road’s beautiful chaos, we’ll uncover what Platform Engineering truly means beyond YAML files and CI/CD pipelines.
You’ll also see a short live demo where I blend Google Cloud + AI/ML — showcasing how today’s platform engineers can infuse intelligence into deployments using Cloud Deploy, Vertex AI, and Cloud Workstations.
Because in Pune, whether you’re serving Poha or deploying pipelines — it’s all about consistency, scalability, and the joy of building something that lasts.
On-Call Nightmare of Non-Deterministic Stacks: Managing Cascading Failures in Agentic K8s Clusters
Moving autonomous AI agents from a local IDE demo to a high-scale production Kubernetes environment introduces an entirely new class of infrastructure volatility. Unlike traditional deterministic microservices, agentic workloads exhibit unpredictable runtime behaviors, spontaneous burst capacity demands, and non-deterministic memory footprints that easily bypass classic horizontal pod autoscaling.
This session steps away from the AI hype to address the raw infrastructure reality that engineering leaders and platform teams face when agents go rogue. We will explore real-world patterns for isolating probabilistic AI workloads from core business logic using advanced Kubernetes scheduling, custom metric-driven autoscaling, and intelligent resource quotas. Attendees will analyze a blueprint for building resilient platform guardrails that prevent cascading cluster failures, manage vector database state sync issues during outages, and maintain systemic stability when AI logic behaves unpredictably.
Devfest Abuja 2026 Sessionize Event Upcoming
Devfest Hubli 2026 Sessionize Event
Devfest Pune 2025 Sessionize Event
DevFest Raipur 2025 Sessionize Event
KCD Bengaluru 2025 Sessionize Event
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