Autoscaling & performance

429 talks across 33 events, oldest first: 75 case studies where an organization reports its own experience, plus concept talks and tutorials.

Keywords: autoscaling, autoscaler, hpa, vpa, keda, karpenter, cluster autoscaler, scaling, performance, capacity planning, scheduling, scheduler (edit under categories: in wiki.yaml).

Over time

Year	Talks	Case studies
2016	8	0
2017	13	6
2018	44	5
2019	41	7
2020	36	6
2021	27	4
2022	26	2
2023	52	12
2024	68	8
2025	63	6
2026	51	19

Organizations with case studies

Red Hat (2), Bloomberg (2), CERN (2), Huawei, Comcast, WP Engine, Gojek, Lyft, T-Mobile, Onefootball, NVIDIA, JD.com, Baidu, ViaSat, Zalando SE, HashiCorp, Chronosphere, Intuit, Admiralty, Peloton, PingCAP, Spotify, Wolt, Amazon Web Services, ByteDance, Activision, Activision/Blizzard, eBay, Minecraft community, Apple, Hitachi, Uber, Google, J. Giannuzzi, Adobe, PepsiCo, Capital One, Coinbase, Hyundai, China, XL, AWS, Enterprise, Skyscanner, Nutanix, Hyperspeed, Fluent Bit

Talks by event

2016 · KubeCon + CloudNativeCon North America 2016 (Seattle)

• concept · Autoscaling Containers... with Math by Allan Espinosa, Engine Yard, Inc.
• concept · How to Monitor Application Performance in a Container-Based World
• concept · Kubernetes on EGO -- Bringing Enterprise Resource Management and Scheduling to Kubernetes
• concept · Scaling Microservices Beyond a Single Cluster w/ Kubernetes by Dan Wilson, Concur
• concept · Scale and Performance Testing of Kubernetes: Answers for Specific Applications
• concept · Weave Cortex: Horizontally Scalable, Multitenant Prometheus as a Service by Tom Wilkie, Weaveworks. Presents Cortex, a horizontally scalable multitenant Prometheus as a service.
• concept · Everything You Ever Wanted to Know About Resource Scheduling, But Were Afraid to Ask by Tim Hockin
• concept · Performance and Scalability Tuning Kubernetes for OpenShift and Docker by Jeremy Eder, Red Hat

2017 · KubeCon + CloudNativeCon Europe 2017 (Berlin)

• case study · Scale Kubernetes to Support 50,000 Services [I] - Haibin Xie & Quinton Hoole — Huawei. Huawei describes scaling Kubernetes to support 50,000 services and the changes required.
• case study · Scaling Organizations Using Kubernetes [I] - Richard Fliam, Comcast VIPER — Comcast. Comcast VIPER shares lessons and mistakes from scaling its engineering organization and microservices with Kubernetes.
• case study · Kubernetes Scheduling Features or How Can I Make the System Do What I Want? [I] - Marek Grabowski
• concept · Autoscaling a Multi-Platform Kubernetes Cluster Built with kubeadm [I] - Lucas Käldström
• concept · Sched.net: A Network-Aware Kubernetes Scheduler [I] - Akash Gangil & Salvatore Orlando, VMware
• concept · Autoscaling in Kubernetes [I] - Marcin Wielgus, Google
• concept · Configuring Prometheus for High Performance [A] - Björn Rabenstein, SoundCloud Ltd.

2017 · KubeCon + CloudNativeCon North America 2017 (Austin)

• case study · Scaling to 5000+ Unique K8s Deployments, How We Did It [I] - Nicole Hubbard, WP Engine — WP Engine
• case study · Load Testing Kubernetes: How to Optimize Your Cluster Resource Allocation in Production. Shows how load testing Kubernetes can be used to tune cluster resource allocation in production.
• case study · Cost-effective Compute Clusters with Spot and Pre-emptible Instances - Bich Le & Arun Sriraman. Speakers share how they ran cost-effective Kubernetes compute clusters on spot and pre-emptible instances.
• concept · Queueing Theory, In Practice: Performance Modelling in Cloud-Native Territory [I] - Eben Freeman
• concept · Kubernetes Storage Evolution: Enabling High Performance Distributed Datastores. Covers the evolution of Kubernetes storage to support high-performance distributed datastores.
• concept · A Scheduling Simulator for Capacity Estimation of Kubernetes Clusters - Avesh Agarwal

2018 · KubeCon + CloudNativeCon China 2018 (Shanghai)

• case study · From Containerized Application to Secure and Scaling W/ Kubernetes - Shikha Srivastava & Erica Brown
• case study · Kubernetes on Supporting 1 Million Bike-Taxi Drivers in Indonesia - Giri Kuncoro & Iqbal Farabi — Gojek. Gojek describes running Kubernetes to support one million bike-taxi drivers in Indonesia.
• concept · Music Matched to Different Ways to Scale in K8s, What Could Go Wrong? - Ria Bhatia, Microsoft. Uses music analogies to explain the different ways to scale in Kubernetes and pitfalls.
• concept · Intro: SIG Autoscaling - Marcin Wielgus & Maciej Pytel, Google
• concept · Comprehensive Performance Benchmark on Various Well-Known CNI Plugins - Giri Kuncoro & Vijay Dhama. Benchmarks the performance of various well-known CNI plugins.
• concept · Deep Dive: SIG Scheduling - Da Ma, IBM
• concept · Deep Dive: SIG Autoscaling - Marcin Wielgus & Maciej Pytel, Google
• concept · Smart Workload: Automated Routing, Scaling of K8s and Serverless Functions - Enlin Xu, Turbonomic
• concept · Serverless Performance on a Budget - Erwin van Eyk, Platform9
• concept · Apache Spark on Kubernetes: A Technical Deep Dive - Yinan Li, Google. Technical deep dive into running Apache Spark natively on Kubernetes.
• concept · Run Cluster Autoscaler on Your Own Cloud; or, Why Do We Need Cluster API? - Aleksandra Malinowska
• concept · Spark on Kubernetes: Best Practice and Performance - Junjie Chen & Jerry Shao, Tencent
• concept · Intro: SIG Scheduling - Da Ma, IBM

2018 · KubeCon + CloudNativeCon Europe 2018 (Copenhagen)

• concept · Performance and Scale @ Istio Service Mesh - Fawad Khaliq, Laurent Demailly & Surya V Duggirala
• concept · SIG Autoscaling Intro – Marcin Wielgus, Google, & Solly Ross, Red Hat (Any Skill Level)
• concept · SIG Scheduling Deep Dive – Bobby Salamat & Jonathan Basseri, Google
• concept · Horizontal Pod Autoscaler Reloaded - Scale on Custom Metrics - Maciej Pytel & Solly Ross. Explains how the Horizontal Pod Autoscaler can scale workloads on custom metrics via the Kubernetes metrics APIs.
• concept · What’s in the Box? Resource Management in Kubernetes - Louise Daly & Ivan Coughlan, Intel. Intel engineers explain how Kubernetes resource management works for CPU, memory and devices.
• concept · The Path to GPU as a Service in Kubernetes - Renaud Gaubert, NVIDIA (Intermediate Skill Level). Describes the path to offering GPUs as a service in Kubernetes.
• concept · Inside Kubernetes Resource Management (QoS) – Mechanics and Lessons from the Field - Michael Gasch. Explains the mechanics of Kubernetes resource management and QoS classes, with lessons from the field.
• concept · Kubernetes Advanced Scheduling - Robert Carosi, Ad van der Veer & Boris Mattijssen
• concept · SIG Autoscaling Deep Dive – Marcin Wielgus, Google, & Solly Ross, Red Hat (Intermediate Skill Level)
• concept · Lightning Talk: Schedule the Scaling of Your Kubernetes Resources Using kube-start-stop - Lili Cosic
• concept · Lightning Talk: Scaling Distributed Deep Learning with Service Discovery - Yong Tang
• concept · Scaling Non-Traditional Contributor Mentoring Initiatives - Paris Pittman, Google. Google's Paris Pittman describes how the Kubernetes community scales mentoring programs for non-traditional contributors.
• tutorial · Building a Kubernetes Scheduler using Custom Metrics - Mateo Burillo, Sysdig. Walks through building a custom Kubernetes scheduler driven by custom metrics.

2018 · KubeCon + CloudNativeCon North America 2018 (Seattle)

• case study · Instrumenting and Scaling Cloud-Native Databases with Envoy - Daniel Hochman, Lyft — Lyft. Lyft shows how it uses Envoy to instrument and scale its cloud-native databases.
• case study · How T-Mobile Built and Scaled Kubernetes On-Prem for the 2018 Retail Season - James Webb, T-Mobile — T-Mobile. T-Mobile describes building and scaling its own on-prem Kubernetes platform to handle the 2018 retail season.
• case study · Automated Kubernetes Scalability Testing - Sebastian Jug & Naga Ravi Chaitanya Elluri, Red Hat — Red Hat. Red Hat engineers present how they automated Kubernetes scalability testing in their own testing process.
• concept · Lightning Talk: PID Autoscaling Strava's Linkerd Service Mesh Using Prometheus Data - J Evans
• concept · Rightsize Your Pods with Vertical Pod Autoscaling - Beata Skiba, Google
• concept · Peloton - A Unified Scheduler for Web-scale Workloads on Mesos - Min Cai & Nitin Bahadur
• concept · Scale Your Service on What Matters: Autoscaling on Latency - Thomas Rampelberg, Buoyant
• concept · Scaling AI Inference Workloads with GPUs and Kubernetes - Renaud Gaubert & Ryan Olson, NVIDIA. Shows how to scale AI inference workloads using GPUs on Kubernetes.
• concept · Intro: Scheduling SIG – Da Ma, Huawei
• concept · Intro: Autoscaling SIG - Solly Ross, Google & Michael Hausenblas, Red Hat
• concept · Predictive Application Scaling with Prometheus and ML - Chris Dutra, Schireson
• concept · gRPC Performance; Tuning Applications and Libraries - Noah Eisen, Google
• concept · eBPF Powered Distributed Kubernetes Performance Analysis - Lorenzo Fontana, InfluxData
• concept · Performance Testing Ingress for Internet-Scale Workloads - Alexander Brand, Heptio
• concept · Deep Dive: Scheduling SIG - Bobby (Babak) Salamat, Google
• concept · Knative: Scaling From 0 to Infinity - Joseph Burnett & Mark Chmarny, Google
• concept · Deep Dive: Autoscaling SIG - Solly Ross, Google & Michael Hausenblas, Red Hat
• tutorial · Intro to Agones: Scaling Multiplayer Game Servers with Kubernetes - Mark Mandel, Google

2019 · KubeCon + CloudNativeCon China 2019 (Shanghai)

• concept · Cost-Effective Scheduling of a Massive Number of Containers in Kubernetes - Yuan Chen, JD.com
• concept · SPDK Based User Space NVMe Over TCP Transport Solution - Ziye Yang, Intel. Presents an SPDK-based user-space NVMe over TCP transport and its design and performance.
• concept · Extending Kubernetes Scheduler for Multi-Cluster and Multi-Cloud Workloads - Illya Chekrygin
• concept · Istio Performance and Best Practices in Large Scale... Guang Ya Liu & Chun Lin Yang
• concept · Understanding Scalability and Performance in the Kubernetes Master - Xingyu Chen & Fansong Zeng. Explains the scalability and performance characteristics of the Kubernetes master components.
• concept · Inside Knative Serving - Dominik Tornow, SAP & Andrew Chen, Google. An inside look at the design and internals of Knative Serving.

2019 · KubeCon + CloudNativeCon Europe 2019 (Barcelona)

• case study · Scaling Edge Operations at Onefootball with Ambassador: From 0 to 6000 rps - Jonathan Juares Beber — Onefootball. Onefootball scaled its edge operations with Ambassador from zero to 6000 requests per second.
• case study · Scaling and Securing Spark on Kubernetes at Bloomberg - Ilan Filonenko, Bloomberg — Bloomberg
• case study · Production GPU Cluster with K8s for AI and DL Workloads - Madhukar Korupolu, NVIDIA — NVIDIA. NVIDIA describes running production GPU clusters on Kubernetes for AI and deep learning workloads.
• concept · Intro: Autoscaling SIG - Marcin Wielgus, Google
• concept · Benchmarking Cloud Native Storage - Josh Berkus, Red Hat. Discusses approaches and challenges in benchmarking cloud native storage.
• concept · What's the Performance Overhead? Answering the Biggest Question in Tracing - Gabriela Soria. Examines the performance overhead that tracing adds to applications.
• concept · Resize Your Pods w/o Disruptions aka How to Have a Cake and Eat a Cake - Karol Gołąb & Beata Skiba. Explains how to resize pods without disruptions, using vertical autoscaling approaches.
• concept · Benchmarking Cloud Native Databases Performance on Kubernetes - Iqbal Farabi & Tara Baskara, GO-JEK
• concept · Treating Network Assets as Scheduleable Resources - Vinothkumar Siddharth, Amazon. Presents an approach to treating network assets as schedulable resources in Kubernetes.
• concept · Restart-Free Vertical Scaling for Kubernetes Pods - Vinay Kulkarni & Peng Du, Huawei
• concept · Intro: Scheduling SIG - Da Ma & Shivram Srivastava, Huawei
• concept · Kubernetes Scalability Definition Evolution - Wojciech Tyczynski & Andrzej Wasylkowski, Google. Describes how the definition of Kubernetes scalability has evolved.
• concept · High Performance Networking with Kubevirt - Doug Smith, Red Hat & Abdul Halim, Intel
• concept · Deep Dive: Scheduling SIG - Babak Salamat, Google
• concept · Deep Dive: Autoscaling SIG - Aleksandra Malinowska & Slawomir Chylek, Google. Deep dive into the Kubernetes Autoscaling SIG's components and roadmap.
• concept · Autoscaling Multi-Cluster Observability with Thanos and Linkerd - Andrew Seigner & Frederic Branczyk

2019 · KubeCon + CloudNativeCon North America 2019 (San Diego)

• case study · Scaling Resilient Systems: A Journey into Slack's Database Service - Rafael Chacon & Guido Iaquinti
• case study · A Toolkit for Simulating Kubernetes Scheduling at Scale - Yuan Chen, JD.com — JD.com
• case study · Improving Performance of Deep Learning Workloads With Volcano - Ti Zhou, Baidu Inc — Baidu. Baidu shows how Volcano improved performance of its deep learning workloads.
• case study · NHD - A Topology-Aware Scheduler for K8s for Low-Latency & HPC Applications - Cliff Burdick, ViaSat — ViaSat. ViaSat describes NHD, its topology-aware Kubernetes scheduler for low-latency and HPC workloads.
• concept · Scaling Kubernetes to Thousands of Nodes Across Multiple Clusters, Calmly - Ben Hughes, Airbnb
• concept · Fine Grained Mesh Metrics for Better Visibility With Native Performance - Mandar Jog & Kuat Yessenov
• concept · KEDA: Event Driven and Serverless Containers in Kubernetes - Jeff Hollan, Microsoft
• concept · Is There a Place for Performance Sensitive Workloads in Kubernetes?- Gergely Csatari & Levente Kale,
• concept · Deep Dive into Autoscaling - Marcin Wielgus, Google & Vivek Bagade, Google. A deep dive into how Kubernetes autoscaling works across pods and clusters.
• concept · Intro: Scheduling SIG - Wei Huang, IBM & RaviSantosh Gudimetla, Red Hat
• concept · Supercharge Kubeflow Performance on GPU Clusters - Meenakshi Kaushik & Neelima Mukiri, Cisco
• concept · Deep Dive Into the Latest Kubernetes Scheduler Features - Abdullah Gharaibeh, Google Inc.
• concept · RDMA Enabled Kubernetes for High Performance Computing - Jacob Anders, CSIRO & Feng Pan, Red Hat
• concept · Building and Scaling Cloud Native Nordics; Tips, Tricks, and Less... Lucas Käldström & Kasper Nissen
• concept · Scaling Your Cluster (Both Ways) - Scott Coulton & Patrick Chanezon, Microsoft
• concept · How Container Networking Affects Database Performance - Tyler Duzan & Vadim Tkachenko, Percona
• concept · Scaling SPIRE for Performance and Availability - Tyler Julian, Uber
• concept · Throttling: New Developments in Application Performance with CPU Limits - Dave Chiluk, Indeed
• tutorial · Introduction to Autoscaling - Marcin Wielgus, Google & Vivek Bagade, Google

2020 · KubeCon + CloudNativeCon Europe 2020 - Virtual

• case study · Autoscaling at Scale: How We Manage Capacity @ Zalando - Mikkel Larsen, Zalando SE — Zalando SE
• case study · Scaling Prometheus: How We Got Some Thanos Into Cortex - Thor Hansen, HashiCorp & Marco Pracucci — HashiCorp
• case study · Speed Racer: Local Persistent Volumes in Production - Matt Schallert, Chronosphere — Chronosphere. Chronosphere shares its experience running local persistent volumes in production for performance.
• case study · SpoK - Running Big Data Applications @ Scale on K8s - Srivathsan Canchi & Nagaraj Janardhana, Intuit — Intuit. Intuit describes running big data Spark applications at scale on Kubernetes with its SpoK platform.
• concept · Kubernetes as a General Purpose Control Plane: Scaling on Kubernetes - Hasan Turken, Upbound
• concept · Do The Math: Auto-Scaling Applications with Kubernetes - Antoine Hamon, Nephely. Explains the math behind autoscaling applications on Kubernetes.
• concept · eBPF and Kubernetes: Little Helper Minions for Scaling Microservices - Daniel Borkmann, Cilium. Explains how eBPF and Cilium help scale Kubernetes microservices networking.
• concept · Scaling Telepresence Across Your Organization - Abhay Saxena, Datawire. Explains how to scale Telepresence for local development across an organization.
• concept · Predictable Performance Through Prometheus and Topology Aware Schedu... Killian Muldoon & Tom Golway
• concept · What You Didn’t Know About Ingress Controllers’ Performance - Mikko Ylinen & Ismo Puustinen, Intel. Examines the performance characteristics of ingress controllers.
• concept · Performance Optimization – Rook on Kubernetes - Mark Darnell & Ryan Tidwell, SUSE
• concept · Scaling Kubernetes Networking Beyond 100k Endpoints - Rob Scott & Minhan Xia, Google
• concept · Deep Dive into Autoscaling - Maciek Pytel & Joe Burnett, Google
• concept · Autoscaling and Cost Optimization on Kubernetes: From 0 to 100 - Guy Templeton & Jiaxin Shan
• concept · Improving the Performance of Your Kubernetes Cluster - Priya Wadhwa, Google
• concept · SIG Scheduling Deep Dive - Aldo Culquicondor, Google & Mike Dame, Red Hat
• concept · Sponsor Demo: Datadog - Autoscaling Workloads in Kubernetes
• concept · Production Multi-node Jobs with Gang Scheduling, K8s, GPUs... Madhukar Korupolu & Sanjay Chatterjee
• tutorial · BoF: Introduction to Contour, A High Performance Multitenant Ingress... Michael Michael & Nick Young
• tutorial · Introduction to Autoscaling - Marcin Wielgus & Beata Lach, Google

2020 · KubeCon + CloudNativeCon North America 2020 - Virtual

• case study · Building a Global Supercomputer with Virtual Kubelet - Dmitry Mishin & Adrien Trouillaud — Admiralty. Describes building a global supercomputer across clusters using Virtual Kubelet.
• case study · High Performance Networking for Distributed DL Training in Production K8s - Nivedita Viswanath
• concept · Kata Containers Performance Evaluation and Optimization on Arm64 - Jia He, Arm
• concept · SIG Scheduling Deep Dive - Wei Huang, IBM & Abdullah Gharaibeh, Google
• concept · Scaling to Millions of ML Models to Solve the Problems of SRE and Security - Sandeep Pombra. Describes scaling to millions of ML models to address SRE and security problems.
• concept · High Performance KubeVirt in Action - Huamin Chen, Red Hat & Marcin Franczyk, Kubermatic
• concept · Practice of Fine-grained Cgroups Resources Scheduling in Kubernetes - Xianlu Chen & Qingcan Wang
• concept · Optimizing Storage Assignment via Pod Scheduling Under Disturbance Factors - Kenji Morimoto, Cybozu
• concept · Enhancing the Kubernetes Scheduler for Diverse Workloads in Large Clusters - Yuan Chen & Yan Xu. Describes enhancements to the Kubernetes scheduler for diverse workloads in large clusters.
• concept · Prescriptively Benchmarking Kubernetes System and Application Using K-Bench - Yong Li, Facebook. Introduces K-Bench, a framework for prescriptively benchmarking Kubernetes systems and applications.
• concept · Service Mesh Specifications and Why They Matter in Your Deployment - Lee Calcote & Kush Trivedi. Explains service mesh specifications and why they matter for deployments.
• concept · Elastic Scheduling with TiKV - Song Gao & Yutong Liang, PingCAP
• concept · DevOps Performance From a Different Dataset: What 30M Workflows Reveal - Michael Stahnke, CircleCI
• concept · Contour, A High Performance Multitenant Ingress Controller for Kubernetes - Michael Michael. Explains how Contour provides a high-performance multitenant ingress controller for Kubernetes.
• tutorial · Intro to Scaling Prometheus with Cortex - Tom Wilkie, Grafana Labs & Ken Haines, Microsoft
• tutorial · Introduction to Autoscaling - Guy Templeton, Skyscanner & Joe Burnett, Google

2021 · KubeCon + CloudNativeCon + Open Source Summit China 2021

• concept · RDMA Programming Using Rust Async - Pu Wang, China. Shows how to program RDMA using Rust async.
• concept · Improve FUSE Filesystem Performance and Reliability - Tao Peng, Ant Group
• concept · Deep Dive Into Profilers: How CPU Profilers Measure Your Application's Performance - Shuang Chen. Deep dive into how CPU profilers measure application performance.
• concept · Continuous Performance Benchmarking for Vitess - Alkin Tezuysal & Florent Poinsard & Manan Gupta

2021 · KubeCon + CloudNativeCon Europe 2021

• case study · How Cloud Native Tech Helped Peloton Ride to Exponential Growth - Jim Haughwout, VP, Peloton — Peloton. Peloton explains how cloud native technology helped it scale through exponential growth.
• case study · CERN's 1500 Drupal Websites on Kubernetes: Sa... Konstantinos Samaras-Tsakiris & Rajula Vineet Reddy — CERN. CERN describes running its 1500 Drupal websites on Kubernetes and the lessons from doing so.
• concept · Scaling Apache Spark on Kube to Apple Scale - Amanda Moran & Holden Karau, Apple
• concept · Maximizing Workload's Performance With Smarter Runtimes - Krisztian Litkey & Alexander Kanevskiy
• concept · SIG Scheduling Intro and Deep Dive - Mike Dame & Jan Chaloupka, Red Hat
• concept · Automated Machine Learning Performance Evaluation - Alejandro Saucedo
• concept · Discontiguous CIDRs for Dynamic Cluster Scaling - Rahul Joshi & Sudeep Modi, Google
• concept · Power Level 9000! Improving Application Performance with Chaos Engineering - S. Pathak & K. Gaekwad
• concept · Contour, a High Performance Multitenant Ingress Controller for Kubernetes - Steve Sloka, VMware
• concept · Groupless Autoscaling with Karpenter - Ellis Tarn & Prateek Gogia, Amazon. Explains groupless autoscaling with Karpenter.
• concept · Battle of Black Friday: Proactively Autoscaling StockX - Mario Loria, Carta & Kyle Schrade, StockX
• concept · Application Autoscaling Made Easy With Kubernetes Event-Driven Autoscaling - Tom Kerkhove, Codit

2021 · KubeCon + CloudNativeCon North America 2021

• case study · How We Reduced Write Latency in TiKV? - Liqi Geng, PingCAP — PingCAP. PingCAP explains how it reduced write latency in its own TiKV storage engine.
• case study · Scaling Kubeflow for Multi-tenancy at Spotify - Keshi Dai & Jonathan Jin, Spotify — Spotify
• concept · Contour, a High Performance Multitenant Ingress Controller for Kubernetes - Steve Sloka & Alex Xu
• concept · Calico/VPP: Using Calico’s Pluggable Dataplanes for Fun and Fast N... Aloys Augustin & Chris Tomkins. Shows how Calico's pluggable dataplanes, including VPP, deliver faster networking.
• concept · Measuring K8s Network Performance - Kornilios Kourtis, Isovalent
• concept · How Event Driven Autoscaling in Kubernetes Can Combat Climate Change - Annie Talvasto & Adi Polak
• concept · Trimaran: Real Load Aware Scheduling in Kubernetes - Abdul Qadeer, PayPal & Chen Wang, IBM
• concept · Using SLOs for Continuous Performance Optimizations of Your K8s Workloads - Andreas Grabner
• concept · Capacity Scheduling for Elastic Resource Sharing in Kubernetes - Qingcan Wang & Yuan Chen
• concept · SIG-Autoscaling: Introduction + HPA/VPA Updates - Joe Burnett‎ & Marcin Wielgus, Google
• concept · Scaling Machine Learning Workflows to Big Data with Fugue - Kevin Kho, Prefect & Han Wang, Lyft

2022 · KubeCon + CloudNativeCon Europe 2022

• case study · Scaling Open Source ML: How Wolt Uses K8s To Deliver Great Food to Mill... Stephen Batifol & Ed Shee — Wolt. Wolt explains how it uses Kubernetes and open source tools to scale ML for food delivery.
• concept · KubeFlux: An HPC Scheduler Plugin for Kubernetes - Claudia Misale & Daniel Milroy. Presents KubeFlux, a Kubernetes scheduler plugin that brings HPC-style scheduling to Kubernetes.
• concept · Lightning Talk: Scaling Container Builds with Software Supply Chains - Duane DeCapite, VMware
• concept · Scaling K8s Nodes Without Breaking the Bank or Your Sanity - Brandon Wagner & Nick Tran, Amazon
• concept · Autoscaling Elasticsearch for Logs on Kubernetes - Radu Gheorghe & Ciprian Hacman
• concept · Scaling and Orchestrating “Good Bot” With Kubernetes - Aris Cahyadi Risdianto
• concept · SIG Autoscaling Updates and Feature Highlights
• concept · Network-aware Scheduling in Kubernetes - José Santos, Ghent University
• concept · Autoscaling Kubernetes Deployments: A (Mostly) Practical Guide - Natalie Serrino, New Relic
• concept · Working your Cluster: Smarter Scheduling Decisions for Your Work... Madalina Lazar & Denisio Togashi
• concept · How Lombard Odier Deployed VPA to Increase Resource Usage Efficiency - Vincent Sevel
• concept · Kubernetes Event-driven Autoscaling with KEDA - Zbynek Roubalik & Jorge Turrado
• concept · Scaling Databases with Vitess - Harshit Gangal & Manan Gupta, Planetscale

2022 · KubeCon + CloudNativeCon North America 2022

• case study · Building Multi-Tenant Routing And Scaling With Envoy - Yiming Peng, Amazon Web Services, Inc. — Amazon Web Services. AWS describes building multi-tenant routing and scaling with Envoy.
• concept · KEDA - Real Time And Serverless Scaling In Kubernetes - Zbynek Roubalik & Jeff Hollan
• concept · How To Build a Distributed System (And Should You?) - Rebecca Bilbro & Patrick Deziel. Discusses how to build a distributed system and whether you should, weighing the tradeoffs.
• concept · Improving Longhorn Performance With SPDK - Keith Lucas & David Ko, SUSE
• concept · Five Ways With a CNI: Understanding Kubernetes Networking For Performance..-Stig Telfer & Erez Cohen
• concept · Lessons From Scheduling 20 Million Windows Containers a Month - Julian Portillo, Relativity
• concept · Lightning Talk: Back To Basics: How To Measure Etcd Performance And Not To... David Perez Rodriguez
• concept · Stateless Collectors For Stateful Data: Scaling Prometheus As a Node Agent - Danny Clark, Google
• concept · Efficient Scheduling Of High Performance Batch Computing For... Krzysztof Adamski & Tinco Boekestijn
• concept · SIG-Scheduling Deep Dive - Wei Huang, Apple; Qingcan Wang, Alibaba; Kante Yin, Kensei Nakada. SIG-Scheduling deep dive covering recent features and the roadmap for Kubernetes scheduling.
• concept · Beyond Orchestration: The Cloud Native Runtimes Ecosystem for Performance and... - Alexander Jung
• concept · SIG Autoscaling Updates And Feature Highlights - Marcin Wielgus & Jayant Jain, Diego Bonfigli
• tutorial · Tutorial: Unleash the Full Potential Of Kubernetes Scheduler: Configuration, Extension And Operat...

2023 · KubeCon + CloudNativeCon + Open Source Summit China 2023

• case study · How We Scale up to 2k Nodes for Batch Jobs Using Cluster Autoscaler - Lei Qian, ByteDance — ByteDance
• case study · How We Build Production-Grade HPA: From Effective Algorithm to Risk-Free... - Ziqiu Zhu & Yiru Guo. Shares how the speakers built a production-grade HPA, from the scaling algorithm to risk-free rollout.
• concept · CNI-Agnostic Network Performance Accelerator with eBPF - Mengxin Liu, Alauda & Yizhou Xu, Intel
• concept · Build a High Performance Remote Storage for Prometheus with Unlimited Time Series - Yang Xiang. Presents a high performance remote storage design for Prometheus with unlimited time series.
• concept · Advancements in Harbor: Security, OCI Spec v1.1, & Performance Enhancement - Yan Wang & Chenyu Zhang
• concept · What's New on Controller-Runtime of the Day -- Make Your Operator More Efficient - Siyu Wang. Covers new controller-runtime features that make operators more efficient.
• concept · Scaling up and Scaling Out Networking, Observability, and Security... - Bill Mulligan & Jaff Cheng
• concept · Break Through Cluster Boundaries to Autoscale Workloads Across Them on...- Wei Jiang & XingYan Jiang. Explains how to autoscale workloads across cluster boundaries in a multi-cluster setup.
• concept · Towards Optimized Microservices Performance &... - Peng Hui Jiang & Kevin Su & Yingchun Guo
• concept · Multi-Cloud Multi-Cluster HPA Helps Trip.com Group Deal with Business... - Honghui Yue & Jingxue Li
• concept · QuarkContainers: High Performance Secure Container for Serverless - Shaobao Feng, Huawei Cloud
• concept · Sailing with KubeEdge: Driving Multi-Robot Scheduling with Unified Data Interface... - Heng Zhang
• concept · Fill a Gap of Kubernetes: IO Resource Scheduling and Isolation - Theresa Shan & Cathy Zhang, Intel

2023 · KubeCon + CloudNativeCon Europe 2023

• case study · Operating CERN SaaS at Scale with Operators — CERN. CERN describes operating its SaaS offerings at scale using Kubernetes operators.
• case study · Hazardous Defaults: Managing Cardinality and Performance for Your Lo... Derek Cavanaugh & Sara Moore. Discusses managing cardinality and performance pitfalls from hazardous defaults in logging and observability setups.
• case study · Scaling Databases at Activision - Greg Smith & Vladimir Kovacik, Activision/Blizzard — Activision, Activision/Blizzard
• case study · Continuous Profiling Your Production Kubernetes Deployments Running a... Vijay Samuel & Nick Pordash — eBay. Describes how continuous profiling was run on production Kubernetes deployments at scale.
• concept · Sig Scheduling Deep Dive - Aldo Culquicondor, Google & Kante Yin, DaoCloud
• concept · Unlocking the Potential of KEDA: New Features and Best Practices - Jorge Ferrero & Zbynek Roubalik
• concept · Making Legacy Modern: How to Monitor and Fine Tune the Performance of...- Brandon Smith & Howard Hao
• concept · Autoscaling Can Be Reliable: Running Cluster Autoscaler in Prod - Maciej Pytel, Google
• concept · Scheduling Framework: Batch Extensions with Apache YuniKorn - Wilfred Spiegelenburg & Peter Bacsko
• concept · Autoscaling Elastic Kubernetes Infrastructure for Stateful... - Sanjay Pujare & Costin Manolache. Explains how to autoscale elastic Kubernetes infrastructure for stateful workloads.
• concept · Scale Down Your Environmental Impact - Mary Karroqe & Zinnia Gibson, D2iQ. Covers how to reduce the environmental impact of Kubernetes workloads.
• concept · Metrics at Full Throttle: Intro and Deep Dive Into Thanos - Saswata Mukherjee & Filip Petkovski. Introduction to Thanos plus a deep dive into its architecture and recent improvements.
• concept · SIG Autoscaling Updates and Feature Highlights
• concept · Availability and Storage Autoscaling of Stateful Workloads on Kubernetes - Leila Vayghan
• concept · Lightning Talk: Power-Aware Scheduling in Kubernetes - Yuan Chen, Apple Inc.

2023 · KubeCon + CloudNativeCon NA 2023

• case study · 15,000 Minecraft Players Vs One K8s Cluster. Who Wins? - Justin Head & Cornelia Davis — Minecraft community. Tests how a single Kubernetes cluster holds up under 15,000 Minecraft players.
• case study · Building, Scaling, and Growing Internal Developer Platfor... Joshua Bezaleel Abednego & Giri Kuncoro. Speakers describe building, scaling and growing their own internal developer platform.
• case study · Rapidly Scaling for Breaking News with Karpenter and KEDA - Mel Cone & Deepak Goel. Shows how a news organization rapidly scales for breaking-news traffic spikes using Karpenter and KEDA.
• case study · Revolutionizing Kube Scalability Testing with KWOK - Wei Huang & Weiwei Yang, Apple — Apple. Apple describes using KWOK to simulate large clusters and test Kubernetes scalability.
• case study · Real-World Knative: Success Stories from Production Environments.... Four guest speakers describe how their organizations use Knative in production.
• case study · Challenge to Implementing “Scalable” Authorization with Keycloak - Yoshiyuki Tabata, Hitachi, Ltd. — Hitachi. Hitachi describes the challenges it faced implementing scalable authorization with Keycloak.
• concept · High Performance, Low Latency Networking for Edge & Telco
• concept · Break Through Cluster Boundaries to Autoscale Workloads Across Them on... Ying Zhang & XingYan Jiang. Explains how to autoscale workloads across cluster boundaries in a multi-cluster setup.
• concept · A Tale of Two Flamegraphs: Unlocking Performance Insights in a Diverse Application Lan... Ryan Perry
• concept · Sustainable Scaling of Kubernetes Workloads with In-Place Pod Resize... Vinay Kulkarni & Haoran Qiu
• concept · Cluster API Deep Dive: Improving Performance up to 2k Clusters - Fabrizio Pandini & Stefan Büringer
• concept · Exploring KEDA's Graduation and Advancements in Event-Driven Scaling - Zbynek Roubalik, Kedify
• concept · Running Large-Scale Scheduling Simulations with Virtual Kubelet - David Morrison
• concept · Advancing Real-Time Performance at the Edge Cloud: DDS & Real-Time... Kyoungho An & Protima Banerjee
• concept · Turning up Performance to 11: Cilium, NetKit Devices, and Going Big with TCP - Daniel Borkmann. Explains Cilium performance improvements using netkit devices and big TCP.
• concept · Best Practices: Improving Batch Scheduling Performance... Vishakha Ramani & Sara Kokkila-Schumacher
• concept · Kube of Thoughts – Scaling Generative AI Models with Kubernetes and Inference Decisi... Asheesh Goja
• concept · SIG Autoscaling Updates and Feature Highlights - Guy Templeton, Skyscanner & Marcin Wielgus, Google
• concept · SIG Scheduling Updates - Aldo Culquicondor, Google & Kensei Nakada, Mercari
• concept · The Complexity on Scaling ML Pipelines on Kubernetes Using Tekton - Tommy Li, IBM
• concept · Environmentally Sustainable AI via Power-Aware Batch Scheduling - Atanas Atanasov & Daniel Wilson. Presents power-aware batch scheduling as a way to reduce the environmental impact of AI workloads.
• concept · Scaling Kubernetes Networking to 1k, 5k, ... 100k Nodes!? - Marcel Zięba & Dorde Lapcevic
• concept · Building Carbon Awareness with KEDA: Taking the First Step Towards Sustainability - Paul Yu
• tutorial · A Practical Guide to Debugging Browser Performance with OpenTelemetry - Purvi Kanal, Honeycomb. Practical guide to debugging browser performance using OpenTelemetry.

2024 · KubeCon + CloudNativeCon + Open Source Summit + AI_dev China 2024

• concept · How to Increase the Throughput of Kubernetes Scheduler by Tens of Times - Yuquan Ren & Bing Li
• concept · Optimize LLM Workflows with Smart Infrastructure Enhanced by Volcano - Xin Li & Xuzheng Chang. Shows how Volcano helps optimize LLM workflows through smarter scheduling infrastructure.
• concept · Unlocking LLM Performance with EBPF: Optimizing Training and Inference Pipelines - Yang Xiang
• concept · NanoVisor: Revolutionizing FaaS Cold Start Performance with Secure, Lightweight Cont...- Tianyu Zhou
• concept · OpAMP: Scaling OpenTelemetry with Flexibility - Husni Alhamdani & Herbert Sianturi
• concept · Redefining Service Mesh: Leveraging EBPF to Optimize Istio Ambient Architecture and... - Yuxing Zeng. Shows how eBPF can optimize Istio Ambient mesh architecture.
• concept · Leverage Topology Modeling and Topology-Aware Scheduling to Accelerate LLM Training - William Wang
• concept · Boundaryless Computing: Optimizing LLM Performance, Cost, and Efficiency in...- Jian Zhu & Kai Zhang
• concept · AI Inference Performance Acceleration: Methods, Tools, and Deployment Workflows - Yifei Zhang & 磊 钱
• concept · Scaling Kubernetes: Best Practices for Managing Large-Scale Batch Jobs... - Yu Zhuang & Liu Jiaxu
• concept · Implementing Fine-Grained and Pluggable Container Resource Management Leverag...- Qiang Ren & He Cao. Describes a fine-grained, pluggable approach to container resource management in Kubernetes.
• concept · Project Lightning Talk: Xline: Achieving Fast Consensus and High Performance in Wide-Area Networks

2024 · KubeCon + CloudNativeCon Europe 2024

• case study · Precision Matters: Scheduling GPU Workloads on Kubernetes - Amit Kumar & Gaurav Kumar, Uber — Uber. Uber describes how it schedules GPU workloads on Kubernetes with attention to precision and resource fit.
• case study · Fantastic Ordinals and How to Avoid Them: Auto-Scaling Challenges in a Cloud Database. Describes auto-scaling challenges with StatefulSet ordinals when operating a cloud database.
• concept · How KubeVirt Improves Performance with CI-Driven Benchmarking, and You Can Too
• concept · Unikernels in K8s: Performance and Isolation for Serverless Computing with Knative
• concept · CASPIAN: A Carbon-Optimized Multi-Cluster Job Scheduler - Tayebeh Bahreini & Asser Tantawi
• concept · High Performance Multi Regions Messaging with Nats - Cyril Becker & Vincent Bernaud, XBTO
• concept · WG-Batch Updates: What’s New and What Is Next? - Michał Woźniak, Google & Yuki Iwai, CyberAgent, Inc. Project update on the Kubernetes Batch Working Group covering recent features and the roadmap.
• concept · Trimaran: Load-Aware Scheduling for Power Efficiency and Performance Stability
• concept · IoT and WebSockets in K8s: Operating and Scaling an EV Charging Station Network - Saadi Myftija
• concept · Scaling Service Mesh: Self Service Beyond 300 Clusters - Sumit Mathur & Sushanth Kamath A, Intuit
• concept · TikTok’s Edge Symphony: Scaling Beyond Boundaries with Multi-Cluster Controllers - Naveen Mogulla
• concept · Scaling up Without Slowing Down: Accelerating Pod Start Time
• concept · Scaling New Heights with KEDA: Performance, Extensions, and Beyond - Jorge Turrado & Zbynek Roubalik
• concept · To Infinity and Beyond: Seamless Autoscaling with in-Place Resource Resize for Kubernetes Pods. Explains in-place resource resize for Kubernetes pods and how it enables seamless autoscaling.
• concept · Scaling Heights: Mastering Postgres Database Vertical Scalability... Gabriele Bartolini & Gari Singh
• concept · SIG Autoscaling Updates and Feature Highlights - Jonathan Innis, AWS & Maciek Pytel, Google. SIG Autoscaling update highlighting new features and direction for Kubernetes autoscaling.
• concept · Empowering Efficiency: PEAKS - Orchestrating Power-Aware Kubernetes Scheduling
• concept · Is There Room for Improving Kubernetes’ HPA?
• concept · Troubleshooting Hidden Performance and Costs in Network Traffic Across Multiple AZs with eBPF
• concept · Dapr in 2024: Deployments Beyond Sidecars, Distributed Scheduler API and App-Level Zero Trust
• concept · Beyond Default: Harnessing CPU Affinity for Enhanced Performance Across Your Workload Portfolio
• concept · How Many Network Policies Can I Create? - Nadia Pinaeva, Red Hat & Shaun Crampton, Tigera. Examines how many network policies a cluster can handle and how different CNIs scale.
• concept · Cloud-Agnostic Approach to Bin-Packing Pods in Managed Kubernetes in AWS, GCP and Azure. Cloud-agnostic approach to bin-packing pods in managed Kubernetes across AWS, GCP and Azure.
• concept · Advanced Resource Management for Running AI/ML Workloads with Kueue - Michał Woźniak, Yuki Iwai. Covers advanced resource management features in Kueue for running AI/ML workloads.
• concept · How to Save Millions Over Years Using KEDA? - Solene Butruille, BlackRock
• concept · Achieving Balance Between Security and Performance in Falco | Project Lightning Talk
• concept · Advanced Multi Cluster Scheduling with Open Cluster Management | Project Lightning Talk

2024 · KubeCon + CloudNativeCon India 2024

• case study · Scaling Private LLM Model Services with Kserve and Modelcar OCI: A Real-World... - Mayuresh Krishna
• case study · Scaling Beyond Autoscaling: How We Grew Our Kubernetes Clusters - Bhavin Gandhi & Ruturaj Kadikar
• concept · Scalable ML Inferencing Pipeline Using K8s - Smitha Jayaram & Vinod Eswaraprasad, NVIDIA. Presents an architecture for building scalable ML inferencing pipelines on Kubernetes using NVIDIA tooling.

2024 · KubeCon + CloudNativeCon NA 2024 - Salt Lake City

• case study · From Observability to Performance - Nadia Pinaeva, Red Hat & Antonio Ojea, Google — Red Hat, Google
• case study · WASM + KWOK Wizardry: Writing and Testing Scheduler Plugins at Scale - D. Pejchev, J. Giannuzzi — J. Giannuzzi
• case study · The Node Tetris Rabbit Hole: Why Your Binpacking Might Be Underperforming - Hannah Taub, Adobe Inc. — Adobe. Adobe investigates why its node binpacking underperforms and what it learned.
• case study · Dapr's Road Ahead: GenAI APIs, Distributed Scheduling at Scale and What It Means for... Y. Schneider
• concept · Elastic Data Streaming: Autoscaling Apache Kafka - Jakub Scholz, Red Hat
• concept · Cooperative Scheduling for Stateful Systems - Michael Youssef & Zhantong Shang, LinkedIn
• concept · GÖDel Scheduler: A Unified Scheduler for Online and Offline Workloads - B. Li, Y. Yin, L. Jiang
• concept · Scaling and Safeguarding the Heart of Kubernetes: Deep Dive Into etcd - Panel
• concept · SIG Autoscaling Projects Update - Jack Francis, Microsoft. SIG Autoscaling project update covering recent developments and roadmap for Kubernetes autoscaling components.
• concept · SIG Scheduling Intro & Updates - Aldo Culquicondor, Google & Kensei Nakada, Tetrate.io
• concept · Misadventures in Large Scale Cluster Performance - Shane Corbett, AWS & Dima Ilchenko, Lacework
• concept · Does My K8s Application Need CPR? Performance Evaluation of a Multi-Cluster... B. Dumba, E. Silvera
• concept · Optimizing Load Balancing and Autoscaling for Large Language Model (LLM) Inference on Kub... D. Gray
• concept · Platform Performance Optimization for AI - a Resource Management Perspective- A. Kervinen, D. Narang
• concept · Optimizing LLM Performance in Kubernetes with OpenTelemetry - Ashok Chandrasekar & Liudmila Molkova. Shows how to use OpenTelemetry to observe and optimize LLM performance on Kubernetes.
• concept · Scale Job Triggering with a Distributed Scheduler - Cassie Coyle & Artur Souza, Diagrid
• concept · Supercharge Your Kubernetes Autoscaling with Custom Metrics - V. Krishna Samudrala, S. Akinapally
• concept · Better Together! GPU, TPU and NIC Topological Alignment with DRA - John Belamaric & Patrick Ohly. Explains how DRA aligns GPU, TPU and NIC topology for better workload performance.
• concept · Are Your Microservices Truly Scaling? A Framework for Unlocking the Stateful Backend - M. Penaroza
• concept · Service Profiling Based Management and Scheduling in K8- Jia Deng, Cong Xu & Mingmeng Luo, Bytedance
• concept · Open Cluster Management: Scheduling AI Workload Among Multiple Clusters | Project Lightning Talk
• concept · Lightning Talk: Evaluating Scheduler Efficiency for AI/ML Jobs Using Custom Resourc... D. Shmulevich
• concept · Improving Service Availability: Scaling Ahead with Machine Learning for HP... A. Sharma & E. Ramirez
• concept · Behind Schedule: Pod Resource Configuration from Beginning to... Huh? - Joe Thompson. Walks through how pod resource requests and limits are configured and how they affect scheduling, from first setup to troubleshooting.
• concept · Love thy (Noisy) Neighbor: Strategies for Mitigating Performance Interference in Cloud-N... J. Perry
• tutorial · Tutorial: Kubernetes Smart Scaling: Getting Started with Karpenter - Panel. Hands-on tutorial getting started with Karpenter for Kubernetes smart scaling.

2025 · KubeCon + CloudNativeCon China 2025 (Hong Kong)

• concept · Smart GPU Management: Dynamic Pooling, Sharing, and Scheduling for AI Work... Wei Chen & Mengxuan Li
• concept · Unlocking the Power of CEL for Advanced Multi-Cluster Scheduling - Qing Hao & Jian Qiu, Red Hat
• concept · Project Lightning Talk: K8s issue #52757: Sharing GPUs Among Multiple Containers - Xiao Zhang. Lightning talk on Kubernetes issue #52757 and sharing a GPU among multiple containers.
• concept · Lightning Talk: Scaling AI With Wasm and Edge Computing - Miley Fu, WasmEdge. Lightning talk on using WasmEdge and Wasm to scale AI workloads at the edge.

2025 · KubeCon + CloudNativeCon Europe 2025 - London

• case study · From High Performance Computing To AI Workloads on Kubernetes: M... Andrey Velichkevich, & Yuki Iwai
• case study · AI Workload Preemption in a Multi-Cluster Scheduling System at Bloomberg - Leon Zhou & Wei-Cheng Lai — Bloomberg
• concept · SIG Scheduling Intro & Updates - Maciej Skoczeń, Google; Kensei Nakada, Tetrate.io
• concept · Cloud Native AI: Harness the Power of Advanced Scheduling for High-P... William Wang & Xuzheng Chang
• concept · Smooth Scaling With the OpAMP Supervisor: Managing Thousands of OpenTe... Evan Bradley & Andy Keller
• concept · Taming the Beast: Advanced Resource Management With Kubernetes - Lucy Sweet & Dawn Chen. Covers advanced Kubernetes resource management techniques.
• concept · Stateful Connections in Kubernetes: The Scaling Secrets Nobody... André Mocke & Rodrigo Fior Kuntzer
• concept · Get WITty: Evolving Kubernetes Scheduling With the WebAssembly... Dejan Pejchev & Jonathan Giannuzzi
• concept · Beyond the Limits: Scaling Kubernetes Controllers Horizontally - Tim Ebert, STACKIT
• concept · Redefining Access Control: Scaling Policy as Code for Humans and AI Agents - Raz Cohen, Permit.io
• concept · Defusing the Kubernetes API Performance Minefield - Madhav Jivrajani & Marek Siarkowicz
• concept · KEDA: Unlocking Advanced Event-Driven Scaling for Kubernetes - Zbynek Roubalik & Jorge Turrado. KEDA maintainers present advanced event-driven scaling features for Kubernetes.
• concept · Mastering Efficiency in Argo CD: Scaling Smarter, Not Costlier - Alexander Matyushentsev, Akuity
• concept · Optimizing Training Performance for Large Language Model(LLM) in Kubernetes - Klaus Ma & Peng Gu
• concept · Scaling Shopify's Search: Enhancing Elasticsearch Resilience With Kubernetes and KE... Leila Vayghan
• concept · The Next Generation of DaemonSet Autoscaling - Adam Bernot & Bryan Boreham
• concept · Scaling GPU Clusters Without Melting Down! - Alay Patel & Ryan Hallisey, NVIDIA
• concept · Project Lightning Talk: Scheduling AI Workload Among Multiple Clusters - Josh Packer, Supporter. Lightning talk on scheduling AI workloads across multiple Kubernetes clusters.
• concept · Scale Smarter Not Harder: How Extending Cluster Autoscaler Saves Mi... Rahul Rangith & Ben Hinthorne
• concept · Optimizing Metrics Collection & Serving When Autoscaling LLM Workloads - Vincent Hou & Jiří Kremser
• concept · Lightning Talk: Scaling To the Stars: Simulating Massive Clusters With KWOK - Soumya Balakrishnan
• concept · Lightning Talk: Scheduling Success: Precision Updates for Continuous Manufacturing Op... J.C. Orozco
• tutorial · Tutorial: Build, Operate, and Use a Multi-Tenant AI Cluster Base... C. Misale, O. Tardieu & D. Grove. Hands-on tutorial on building, operating and using a multi-tenant AI cluster.
• panel · Starting and Scaling a Platform Engineering Team - Camille Fournier & Ian Nowland. Two engineering leaders discuss how to start and scale a platform engineering team.

2025 · KubeCon + CloudNativeCon India 2025

• case study · Scaling AI Like a Pro-PepsiCo’s LLM Deployment Strategy on K... Praseed Naduvath & Dhanashree Shetty — PepsiCo. PepsiCo describes its strategy for deploying and scaling LLMs on Kubernetes.
• concept · Beyond Productivity: Scaling Cloud Dev Environments for Faster Feedback & Sustaina... Siddhant Khare
• concept · Lightning Talk: Predictive Autoscaling in Kubernetes With KEDA and Prophet - Snigdha Kanchana, IBM
• concept · Scaling Generative AI: Building Production-Ready LLM Applications - Daniel Oh, Red Hat
• concept · Containerized Time Travel: Replicating Production Performance - Sravanthi Naga & Hari Babu Volli
• concept · Auto-instrumentation for GPU Performance Using eBPF - Annanay Agarwal, Grafana Labs
• concept · Handling Node Churn in Karpenter: Efficient Scaling for Large EKS... Shivani Mehrotra & Chetan Saini

2025 · KubeCon + CloudNativeCon Japan 2025 (Tokyo)

• concept · Access AI Models Anywhere: Scaling AI Traffic With Envoy AI Gateway - Dan Sun & Takeshi Yoneda
• concept · Scaling AI Responsibly: Building Et... Amita Sharma, Vincent Caldeira, Mohit Suman & Shamsher Ansari
• concept · Dynamic Provisioning and Capacity-Aware Scheduling for Local Storage - Yuma Ogami, Cybozu, Inc.
• concept · Beyond Stock Outs: Scaling Inference on Mixed GPU Hardware With DRA - John Belamaric & Bo Fu, Google. Shows how DRA can be used to scale inference across mixed GPU hardware and avoid stock-out issues.

2025 · KubeCon + CloudNativeCon North America 2025

• case study · Autoscaling Spring Boot Apps in Kubernetes With KEDA - John Coyne, Capital One — Capital One. Capital One shares how it autoscales Spring Boot applications on Kubernetes with KEDA.
• case study · Rearchitecting Compute at Coinbase: Migrating To Karpenter for Fast, Reliable Scali... Frances Chong — Coinbase. Coinbase rearchitected its compute by migrating to Karpenter for faster, more reliable scaling.
• case study · One Dozen To One Thousand Clusters: How Argo Kept up as We Scaled - Jérémy Albuixech & Kahou Lei. Speakers describe how their Argo CD setup scaled from a dozen to a thousand clusters.
• concept · Scaling and Securing CoreDNS: Performance and Resilience - Yong Tang & John Belamaric
• concept · Optimized Scheduling for Big Data Workloads - The Why, What... Rahul Sharma & Wilfred Spiegelenburg
• concept · Supercharge Cloud Native SQL Database With Object Storage: Scaling TiKV With S3 as... Jinpeng Zhang
• concept · Intelligent Topology for AI Power: Network-Aware Scheduling Optimization With Volcano... Kevin Wang
• concept · Evolving Kubernetes Scheduling - Eric Tune & Wojciech Tyczyński, Google
• concept · Achieving Peak Performance Through Hardware Alignment in DRA - Gaurav Ghildiyal & Byonggon Chun
• concept · Diagnosing Application Performance With EBPF, Pyroscope, and Kubernetes - Liam Mackie
• concept · Under the Hood of Vitess: Database Engineered for Scale and Resilien... Matt Lord & Florent Poinsard. Deep dive into Vitess architecture and how it provides a scalable, resilient database layer on MySQL.
• concept · SIG Autoscaling Projects Update - Jack Francis, Microsoft & Jason Deal, AWS
• concept · Multi-Cluster Wars: The Scheduler Awakens - Dejan Pejchev & Priyanka Ravi, G-Research
• concept · Efficient Kubernetes Autoscaling: News, Challenges, and Best Practi... Zbynek Roubalik & Jan Wozniak. Covers news, challenges and best practices for efficient Kubernetes autoscaling, with a focus on KEDA.
• concept · Beyond the Cloud(s): Falco’s Ascent in Performance and... Leonardo Grasso & Leonardo Di Giovanna. Falco project update on performance improvements and new capabilities.
• concept · Karmada in Action: Scaling AI Workloads Across Multi-Clus... Hongcai Ren, Tessa Pham & Wei-Cheng Lai
• concept · SIG Scheduling Intro & Updates - Kensei Nakada, Independent & Dominik Marciński, Google
• concept · Scaling Generative AI: Building Production-Ready LLM Applications - Daniel Oh & Kevin Dubois, IBM
• concept · State of NATS: Scale, Performance, and Flexibility - Byron Ruth, Synadia
• concept · Slurm Bridge: Slurm Scheduling Superpowers in Kubernetes - Alan Mutschelknaus & Tim Wickberg
• concept · Performance Tuning Java Apps for Kubernetes: From Startup Time To Conta... Ryan Jarvinen & Daniel Oh. Explains how to tune Java applications for Kubernetes, covering startup time and container resource behavior.
• concept · Anatomy of a Kubernetes Scheduler: Narrate Workloads Priority in Sequence - Hoon Jo, Megazone. Walks through the anatomy of the Kubernetes scheduler and how it orders workloads by priority.
• concept · Project Lightning Talk: Making Kubescape Storage Scale From Small and Mid-Size To... Ben Hirschberg. Lightning talk on making Kubescape storage scale from small to large clusters.
• tutorial · Tutorial: Unlock the Future of Kubernetes and Accelerators With Dynamic Resource Alloc... Rey Lejano. A hands-on tutorial on using Dynamic Resource Allocation to manage accelerators in Kubernetes.

2026 · Keynotes - KubeCon + CloudNativeCon Japan 2026

• case study · Out of the Box, at Multi-Region Scale: How Hyundai Scales Its Platform - Jaewoo Choi, Hyundai — Hyundai. Hyundai describes how it scales its platform across multiple regions.
• concept · From 5 to 1,300+ Clusters: Declarative Scaling for Private Kubernetes - Shota Yoshimura

2026 · KubeCon + CloudNativeCon + OpenInfra Summit + PyTorch Conference China 2026

• case study · Kubernetes DRA Architecture: Scheduling, Status, and Topology at Scale - Paco Xu & Kang Zhang
• case study · Scaling Digital Employees at China Merchants Bank in Production: A Controlled AI... Jiahang Xu — China
• case study · 8 Million Tasks Daily: Driving Efficiency in Multi-Tenant Data... JIanxiang Sun & Shuangkun Tian. Reports on running 8 million tasks daily in a multi-tenant data platform and the efficiency gains achieved.
• concept · Tidal Auto-scaling for Training and Inference Based on Kubernetes + KEDA - Jun Zheng & Tan Pei Xiang
• concept · vLLM-Helion: SOTA LLM Performance by advanced autotuning and fine-grained dispatching - Sean Chen. Presents vLLM-Helion, which uses autotuning and fine-grained dispatching to reach state-of-the-art LLM inference performance.
• concept · Beyond Model Sharding: Atomic Scheduling and Disaggregated LLM Serving... Kay Yan & Chen Zicong
• concept · Declarative Underlays: Scaling Purpose-Built Infrastructure(Clusters)... HanSol Park & Kangsub Song
• concept · Volcano: A Unified Scheduling Platform for Cloud Native AI - Chen Zicong, Huawei & DongYang Wang

2026 · KubeCon + CloudNativeCon Europe 2026

• case study · Scaling Valkey the Right Way: Kubernetes at XL Scale - Sarthak Aggarwal & Madelyn Olson, AWS — XL, AWS
• case study · From Idle to Savings: Building a Global Scheduler for Cost‑Efficient Data P... Rainie Li & Ang Zhang. Speakers describe building a global scheduler that cuts idle cost for their data platforms.
• case study · Making Topology-Aware Scheduling Practical for AI Workloads: From Discovery to Simula... Weizhou Lan
• case study · Fusing FinOps, Forecasting, and Kubernetes at Scale - Ankur Singh & Satyam Bhardwaj. Presents how FinOps and forecasting are combined to manage Kubernetes costs at scale; the speakers' organization is not named in the title.
• case study · Scaling Platform Engineering: Lessons From Europe’s Larges... Cat M, Stéphane C, Anna K & Gayathri T. Practitioners from one of Europe's largest organizations share lessons from scaling platform engineering.
• case study · Sponsored Session: Performance at Enterprise Cloud Scale: Coupa’s Ku... Peter Irwin & Carl Baumcratz — Enterprise
• case study · From NLB Sprawl To Mesh Efficiency: How Skyscanner Handles 60M Reque... John Clark & Steven Thwaites — Skyscanner. Skyscanner describes moving from NLB sprawl to a mesh to handle 60M requests efficiently.
• case study · What Survived Production: Operating Game Backends at Million-Player Scale - Berkay Uckac. Reports lessons on what survived in production when operating game backends at million-player scale.
• concept · Unleashing Event Driven Capabilities With KEDA - Jorge Turrado & Zbynek Roubalik
• concept · Cloud Native Theater | Data on Kubernetes Day: KubeVirt Benchmar... Bhumitra Nagar & Dhruv Bhatnagar. Presents KubeVirt benchmarking results and performance findings for running VMs on Kubernetes.
• concept · Project Lightning Talk: Scaling Kubescape to Thousands of Nodes - Matthias Bertschy, Maintainer
• concept · Project Lightning Talk: kcp: Scaling The Kubernetes Control Plane For The Multi-Clust... Jan Willies. Lightning talk introducing kcp, a horizontally scalable lightweight Kubernetes-style control plane that gives isolated API experiences without full clusters.
• concept · Project Lightning Talk: Next-Gen AI Orchestration With Volcano On Kubernetes - Zhonghu Xu. A lightning talk on using Volcano for next-generation AI workload orchestration on Kubernetes.
• concept · Project Lightning Talk: Scheduling at the Edge of Reason: Multi-Cluster AI & OCM - August Simonelli
• concept · Addressing Non-Deterministic Scheduling: Introducing... Ajay K, Sreeram V, Karthik N & Priyanka S
• concept · The Shared Service Blueprint: A Guide to Multi-Tenancy, Illustrated With KEDA - Aya Igarashi
• concept · Scaling the Kubernetes Ecosystem: Uber's Approach to Cluster... Silvio Simunic & Vadim Plakhtinskii
• concept · Cloud Native Theater | KubeVirt Summit: Breaking the Performance Barrier... Jian Li & Yves Weisser
• concept · Beyond Stateless: Distributed Transactions with Autoscaling and Consistency on K... Jumpei Nishitani
• concept · Cloud Native Theater | KubeVirt Summit: Measuring KubeVirt Performance and Scale wi... Sreeja Varnam
• concept · The Future of Kubernetes Node Lifecycle - Lucy Sweet, Uber & Dawn Chen, Google. Looks at the future of Kubernetes node lifecycle management, with Uber and Google speakers.
• concept · SIG Scheduling Update: Transition From Pod To Workload Scheduling - Kensei Nakada & Maciej Skoczeń. SIG Scheduling update on the move from pod-level to workload-level scheduling and recent release changes.
• concept · Automating and Scaling of Threat Modelling for Cloud Native Archit... Hanna Papirna & Emma Yuan Fang
• concept · The Missing Half of Performance Profiling: Understanding Memory in Cloud Native Syste... Dom Delnano
• concept · Instrumenting Kueue Scheduling for ML Training - Amy Chen, CoreWeave & Gabriel Saba, Google
• concept · When DNS Blinks: Scaling and Hardening CoreDNS in Critical Cloud Infra... Yong Tang & John Belamaric. Covers how to scale and harden CoreDNS for critical cloud infrastructure.

2026 · KubeCon + CloudNativeCon India 2026

• case study · Why We Ditched Kube-proxy: Scaling 10M Daily Browser Sessions With Kubernetes Endpoi... Rajat Khanna
• case study · KServe in Production: Scaling Generative Inference the Cloud Native Way - Johnu George, Nutanix — Nutanix
• case study · Sponsored Demo: Scaling EdTech at Hyperspeed: How PhysicsWallah Red... Avinash Gupta & Gaurang Singh — Hyperspeed
• concept · Kubernetes API Server Performance Clinic: Auditing, and Priority... Neel Shah & Suman Chakraborty
• concept · GPU Hunter: Architecting Global GPU Availability With MultiKueue - Kishore Jagannath & Ram J A. Shows an architecture using MultiKueue to improve GPU availability across clusters globally.
• concept · Project Lightning Talk: Vitess in Production: Powering Applications at Massive Sca... Harshit Gangal. Lightning talk on how Vitess powers MySQL-backed applications at massive scale.
• concept · Scaling the Developer Frontier: The TAG DevEx Roadmap for 2026 - Daniel Oh & Kevin Dubois, IBM. Presents the TAG DevEx roadmap for 2026 and its plans for improving developer experience.

2026 · KubeCon + CloudNativeCon Japan 2026

• case study · From Experiment To Enterprise: Scaling an AI Agent for Code Review - Adam Phan. Describes taking an AI code review agent from experiment to enterprise-scale use.
• case study · SIG Scheduling Update: Transition From Pod To Workload Scheduling - Kensei Nakada & Yuki Iwai
• case study · Lessons From Five+ Years of Fluent Bit: Building a Global-Scale Observability Agent - Hiroshi Hatake — Fluent Bit. Hiroshi Hatake shares lessons from more than five years of building and operating Fluent Bit as a global-scale observability agent.
• case study · Don't Start With 500 Clusters: Patterns in Scaling Multi-Cluster Kubernetes… N. Bora & M. Morrison. Speakers share patterns and lessons from scaling multi-cluster Kubernetes with Cluster API, arguing against starting with hundreds of clusters.
• concept · Topology-Aware Scheduling for AI Training & Inference With Kueue - Michał Woźniak & Wei Huang
• concept · Shared GPU Scheduling & Proactive Autoscaling: A Production Blueprint for 1000+… J. Kim & R. Jelveh
• concept · Beyond Single-Cluster Limits: Scaling GPU Workloads Across Kubernetes With… K. Das & E. Bayramova
• concept · Scaling in Kubernetes Safely on On-Prem KaaS Across 1,300+ Clusters and 40,000+ Nodes - S. Yoshimura