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Ensuring resilience in control planes is critical for organizations managing infrastructure and applications across multiple regions with Kubernetes. This talk presents a reference architecture for creating a Crossplane-based Global Control Plane, enhanced with k8gb for DNS-based failover and leveraging an Active/Passive setup. We’ll explore how Crossplane’s declarative infrastructure provisioning integrates with k8gb to build robust, scalable, and resilient multicluster environments. Key takeaways include:
- Architecting resilient multiregion control planes with Active/Passive roles - Demonstrating failover mechanisms where the Passive control plane transitions to Active during failures - Strategies for optimizing failover times while maintaining availability
This session will guide attendees through proven methods and real-world challenges of building resilient Global Control Planes, empowering them to manage critical workloads across geographically distributed regions confidently.
Yury is an experienced software engineer who strongly focuses on open-source, software quality and distributed systems. As the creator of k8gb (https://www.k8gb.io) and active contributor to the Crossplane ecosystem, he frequently speaks at conferences covering topics such as Control... Read More →
Not everything can be thought about while designing or developing the applications, and as such lot of the design decisions are based on estimates and potential usage patterns.
More often that not, these estimates differ from reality and introduce inefficiencies in the system across several fronts - and if at all visible, it always much later in the lifecycle when you already have several customers & high footprint.
And hence, unless there is a clear sign of performance degradation or unjustified costs, there is often no incentive to invest time & effort for some unknown gains.
In this session Yash will outline a real world case study about how they went about building an internal platform for handling several aspects of post deployment challenges like
1. rightsizing opportunities, 2. architecture migrations like moving to serverless, 3. finding right maintenance windows, etc
by using a wide range of metrics, and how impactful these minor optimizations turned out to be.
Yash is working with Google as Software Engineer, and has 9 years of industrial experience with cloud architectures and micro-service development across Google and VMware. He has been a speaker at several international conferences such as KubeCon + CloudNativeCon and Open Source... Read More →
ou might already be using a CI/CD solution, but are you 100% sure things will roll out without a glitch once you go to production? Unfortunately differences between testing/staging and production environments are virtually unavoidable. There’s always a risk for unforeseen issues related to your production environment and/or actual load which can lead to potential disruptions to your users.
Progressive delivery is the next step after Continuous Delivery to roll out your application in a controlled and automated way so you can verify and test your application *in production* before it becomes fully available to all your user bases.
Embrace GitOps and Progressive Delivery with techniques like blue-green, canary release, shadowing traffic, dark launches and automatic metrics-based rollouts to validate the application in production using Kubernetes and tools like Istio, Prometheus, ArgoCD, and Argo Rollouts.
Come to this session to learn about Progressive Delivery in action using Kubernetes.
Kevin is a Java Champion, software engineer, author and international speaker with a passion for Open Source, Java, and Cloud Native Development & Deployment practices. He currently works as developer advocate at Red Hat where he gets to enjoy working with Open Source projects and... Read More →
Do you think platform engineering is too hard? Or is it just a buzzword? Is the CNCF landscape too tricky to visualize? If you’ve been in this industry long enough, you should know that platform engineering has been around for a long time.
Most of us have been trying to build developer platforms for decades, and most of us have failed at that. That begs the questions: “What is different now?” “Why will this time be different?” and “Do we have a chance to succeed?”
We’ll take a look at the past, the present, and the future of platform engineering. We’ll see what we were doing in the past, what we did wrong, and why we failed. Further on, we’ll see what we (the industry as a whole) are doing now and, more importantly, where we might go from here.
Get ready for the hard truths and challenges you will face when trying to build a platform based on Kubernetes. Join us for a pain-infused journey filled with challenges teams will face when building platforms to enable other teams.
Viktor Farcic is a lead rapscallion at Upbound, a member of the CNCF Ambassadors, Google Developer Experts, CDF Ambassadors, and GitHub Stars groups, and a published author. He is a host of the YouTube channel DevOps Toolkit and a co-host of DevOps Paradox.
Mauricio works as an Open Source Software Engineer at @Diagrid, contributing to and driving initiatives for the Dapr OSS project. Mauricio also serves as a Steering Committee member for the Knative Project and Co-Leading the Knative Functions initiative. He published a book titled... Read More →
Constructing and managing platforms for diverse teams and workloads presents a significant challenge in today's cloud-native environment. This session introduces the concept of composable platforms, using modular, reusable components as the foundation for platform engineering. This talk will demonstrate how using Kratix, a workload-centric framework, and Backstage an extensible developer portal enables the creation of self-service platforms that balance standardization with adaptability.
The session will detail platform design for scalability and governance, streamlining developer workflows through Backstage, and using Kratix Promises for varied workload requirements. Attendees will gain practical insights into building scalable and maintainable platforms through real-world examples, architectural patterns, and a live demonstration of a fully integrated Kratix-Backstage deployment.
Hossein is an experienced cloud computing professional with nearly a decade of expertise in distributed systems and cloud technologies. He began as a student specializing in cloud automation and progressed to a full-time role focusing on on-premises cloud infrastructure and containers... Read More →
AI developer in K8S: either in Jupyter notebook or LLM serving: Python Dependency is always a headache : - Prepare a set of base Images? The maintenance amounts & efforts will be a nightmare: Since (1) packages in AI world are rapidly version bumping, (2) diff llm codes require diff packages permutation/combination. - Leave users to `pip install` by themselves ? The resigned waiting blocks productivity and efficiency. You may agree if you did it. - If on a GPU Cloud, the pkg preparation time may even cost a lot: you rent a GPU but wasted in waiting pip downloading... - you may choose to D.I.Y: docker-commit your own base-images, but you have to worry about the Dockerfile, registry and additional cloud cost if you don't have local docker env.
---- So we introduce https://github.com/BaizeAI/dataset.
The solution: 1. A CRD to describe the dependency and env. 2. K8S Job to pre-load the packages. 3. PVC to store and mount 4. `conda` to switch from envs 5. share between namespaces
Cloud native developer, AI researcher, Gopher with 5 years of experience in loads of development fields across AI, data science, backend, frontend. Co-founder of https://github.com/nolebase
