KubeCon + CloudNativeCon India 2025

In today's complex service mesh environments, ensuring secure and efficient network traffic management is a significant challenge. Many developers struggle with implementing robust, context-aware access control policies without disrupting existing systems. The Kyverno Envoy Plugin offers a solution by integrating with the Envoy proxy and leveraging the Kyverno Authz Server within the cluster, along with a cluster-wide resource called AuthorizationPolicy. This resource utilizes the CEL language to process these requests seamlessly, allowing you to authenticate and enforce policies seamlessly on all traffic.
In this hands-on session, the speakers will leverage this plugin to enhance the security and control of applications, ensuring they are protected from unauthorized access and threats without requiring changes to your microservices. They will also showcase how the plugin seamlessly integrates with various service meshes such as Istio, to extend its functionality across environments.

We spend countless hours making applications resilient and scalable, but often overlook their final moments. While we obsess over startup performance and runtime behavior, the shutdown process remains a mystery. Yet, understanding this crucial phase can mean the difference between clean service transitions and disrupted user experiences.

Join us as we decode Pod termination in Kubernetes, exploring the lifecycle from shutdown signal to final goodbye. We'll examine real-world scenarios through kubectl, kubelet, and API interactions, and share practical strategies for smooth shutdowns. Transform your chaotic Pod terminations into choreographed farewells and enhance your application's reliability.

For: DevOps engineers, SRE teams, and Kubernetes developers.

Providing application teams with a self-service way of deploying applications and their dependencies often means that platform administrators have to hide the implementation details of the platform via simple to consume APIs. In the case of Kubernetes this usually means having to deploy Custom Resource Definition that are either 3rd party or custom built in-house. These CRD’s in addition to allowing Kubernetes users to manage non-Kubernetes objects via the Kubernetes Resources Model (Aka YAML file), they also allow abstracting away the details of how some resources get created and managed.

In this session, you'll learn how KRO allows platform teams to:
- Create high-level APIs that reduce YAML complexity while maintaining flexibility
- Support both native Kubernetes and cloud-specific resources for more efficient orchestration
- Integrate KRO into your Kubernetes workflows for better scalability and simplicity

Building a CNCF community comes with wins and challenges. We launched KCD Sri Lanka in 2022 with a high-grade green screen production, featuring global speakers and over 1K YouTube livestream views. In 2023, our in-person KCD Sri Lanka was an early sold-out, house-full event, drawing speakers from around the world.

From securing sponsorships and growing engagement to handling setbacks, we’ll share key lessons from leading Kubernetes Sri Lanka. Whether you’re starting or scaling a CNCF community, this talk will provide practical takeaways to build a sustainable and impactful cloud native ecosystem.

APIs helped define cloud-native—but agentic systems need more.

In this talk, we introduce MCP (Model, Context, Protocol)—an architectural framework built for adaptive, AI-enhanced, agentic systems. You'll learn how MCP extends API-centric thinking to define not just interfaces, but also capabilities, environment-aware behavior, and reflective discovery.

We’ll explore:

How MCP aligns with Kubernetes' dynamic, declarative model
Why JSON-RPC (not REST/gRPC) is the best fit for dynamic agent tooling
Real-world examples of LLM-driven clients discovering tools, prompts, and commands at runtime
How to structure MCP clients and servers using C# or Go for cloud-native deployment
You'll leave with code samples, a conceptual model, and a UML-driven design for building MCP-based systems—ideal for Kubernetes-based platforms, autonomous agents, and AI-enhanced developer tools.

Kubernetes has become the de facto standard for container orchestration, yet managing complex workloads—particularly stateful applications and large-scale deployments—often requires extensions beyond its native capabilities. OpenKruise, addresses these gaps by introducing powerful and enhancements to streamline application lifecycle management.

This presentation explores how OpenKruise augments Kubernetes with features like in-place pod updates (reducing downtime by updating containers without restarting pods), advanced workload controllers (CloneSet, Advanced StatefulSet). These innovations enable DevOps teams to optimize deployments, minimize operational overhead, and scale stateful applications seamlessly.

We’ll delve into real-world use cases from our experiences, plus, how OpenKruise can be plugged to any complex systems/apps.

Attendees will leave with actionable insights into leveraging OpenKruise to enhance deployment strategies and achieve zero-downtime operations.

In today's fast-paced development landscape, maintaining reliable and up-to-date test environments is crucial yet challenging. Join us as we share our journey of evolving from traditional long-running test environments to testing directly in production, and eventually achieving scalable and ephemeral test environments for platform builders as well as application teams.

- Are you content with the current state of your test environments?
- Do you find yourself relying on outdated, long-running staging and test environments?
- How do you handle the risks of data staleness and unexpected environment corruption?

In this talk, we will go into the strategies and tools that helped us to transition to ephemeral test environments, highlighting the benefits and challenges encountered along the way. We aim to provide you with practical steps to improve the scalability and reliability of your own testing frameworks.

The rise of WebAssembly (WASM) has sparked comparisons with Docker which often leads to questions and confusion: Are WASM and Docker competing technologies?

In this talk, we will see how this is far from the truth. On one side, Docker revolutionised how we bundle and deploy applications, offering unparalleled portability and simplifying workflows across environments. On the other hand, WASM brings speed, security, and efficiency, enabling the execution of code written in languages like C, C++, and Rust almost at native speed, performance, and rapid startup time even in the browser.

We will explore how these two technologies bring the best of both worlds and help developers achieve portability, efficiency, security, and flexibility. We will also look at how Docker is actively working to make WASM mainstream by allowing WASM container images to be hosted on DockerHub and run WASM containers alongside traditional Linux and Windows containers.

This session focuses on enhancing Kubernetes autoscaling by integrating **KEDA** (Kubernetes Event-Driven Autoscaling) with **Prophet**, a time-series forecasting tool. Traditional Kubernetes autoscaling reacts to current resource metrics like CPU and memory, while predictive autoscaling anticipates future workload demands using historical data. By combining Prophet with KEDA, Kubernetes can proactively scale resources before traffic spikes, ensuring better performance and optimized resource usage.

Attendees will learn how to implement predictive autoscaling with KEDA and Prophet to improve efficiency, reduce latency, and manage resources proactively. This approach helps handle fluctuating workloads, enhancing system reliability and providing a seamless user experience.

Ideal for cloud architects, Kubernetes admins, and DevOps professionals, this session provides actionable insights to automate scaling strategies and improve cost efficiency in cloud-native environments.

Imagine presenting to your dream clients when your primary region decides to take a coffee break. That's exactly what happened to us - 25 minutes of unexpected manual failover, and watching hope drain from our team's & audience's faces. Our multi-region setup was more "disaster" than "recovery".

Join this talk as Prerit walk us over how they build an intelligent feature flag orchestration platform using OpenFeature which now processes 1k flag evaluations/second across 3 global regions, reduced infrastructure incident risk by 90% & DR time from 25 minutes to 125 seconds and has successfully handled 15 regional incidents without a single lost transaction.

We will also see they built the "infrastructure gates" to control traffic shifting with millisecond precision, feature state synchronization, and WARM-HOT-COLD DR strategies with just a toggle.

This talk explores how KServe and OPEA are redefining the enterprise AI stack through modular and composable architectures. KServe delivers a scalable, hardware-agnostic Kubernetes native platform for production model deployment. OPEA complements this infrastructure with an open, multi-provider platform that provides optimized GenAI solutions through standardized interfaces. By building on KServe's capabilities, OPEA allows teams to focus on developing innovative applications rather than managing complex infrastructure concerns.
Join us to learn how deconstructing AI systems into specialized Lego blocks leads to more extensible and powerful enterprise AI architectures. We will demonstrate how this separation of concerns speeds up innovation, enabling teams to focus on app development for their app development. We will also discuss practical approaches for implementing this "building block" methodology in your organization's AI strategy.

This session delves into the critical aspects of developing production-ready Large Language Model (LLM) applications using Java. We'll explore how to leverage Java's strengths to build scalable and efficient LLM systems, addressing key challenges such as performance optimization, resource management, and seamless integration with existing infrastructures.

Attendees will gain practical knowledge on handling massive datasets, optimizing model inference, and fine-tuning LLMs for optimal performance. We'll discuss strategies for ensuring the reliability and scalability of your LLM deployments, empowering you to create robust and high-performing AI applications. Whether you're a seasoned Java developer or new to the AI domain, this session will provide valuable insights and guidance for your LLM development journey, equipping you with the tools and knowledge to navigate the complexities of building production-grade LLM systems.

Kubernetes-native development is exhilarating—until complex workflows, slow feedback loops, and steep learning curves slow you down. Teams often spend days or weeks setting up environments, managing dependencies, and debugging microservices. GitLab found that nearly 44% of organizations take over two months to onboard new developers—precious time lost in today’s fast-paced tech world.
This session shows how we cut environment setup from days to minutes, slashed feedback loops by over 90%, and reduced onboarding time by 50%.
The secret? A powerful blend of CNCF tools—Kind and DevSpace—combined with simple lightweight Node.js and Bash/PowerShell scripts, We have automated environment provisioning, code synchronization, and cluster management so that developers can focus on shipping features.
Discover how to integrate Kind and DevSpace for a seamless workflow with real metrics and tips. Developers, architects, and DevOps can streamline Kubernetes, speed onboarding, and boost iterations.

The Tenant Exporter enhances observability in multi-tenant Kubernetes clusters by delivering curated namespace metrics for GPU workloads at Adobe. Built on Prometheus, it exposes metrics like ingress requests, container CPU/memory, GPU utilization, and quotas. Users can select metrics via a ConfigMap, with quotas managing load.

The architecture features a Prometheus instance for metric collection, an Nginx proxy for load balancing, and secure authentication using prom-label-proxy with kube-rbac-proxy. A live demo will showcase configuring self-service metrics for a GPU namespace, integrated with Prometheus.

Attendees will learn to deploy this system, manage quotas, and scale metric delivery across clusters. Drawing from Adobe's experience with thousands of namespaces, this session offers best practices for observability using CNCF tools to reduce overhead and improve insights. Join us to elevate your Kubernetes observability strategy and optimize GPU workload management.