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• Gateway API represents a cloud load balancer for routing configuration
• Multi-Cluster Services enable connecting clusters together for improved availability and reduced latency
• Combining Gateway API and Multi-Cluster Services creates Multi-Cluster Gateways for advanced routing across clusters
• Multi-Cluster routing can improve application availability and demonstrate failover capabilities
• APIs can provide portable multi-cluster routing configuration even when mapped to different underlying cloud infrastructure

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• Policies are important in protecting against disruption and cluster maintenance in a NoSQL database deployment
• Without policies, evicting or draining nodes during maintenance can result in lost parts and production outrage
• Creating policies per replica ring can help protect against disruptions
• Distributed policies can provide protection for complex NoSQL database deployments
• Multi-cluster mode requires separate service accounts, service, and RBAC to extract tokens to allow controllers to talk to other clusters
• Building a fully compatible controller to the built-in type is a formidable challenge
• Democratizing extensibility for building types is desirable

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• Cardinality and data retention are important aspects to consider in multi-cluster observability
• Metrics can be fetched from running services like Prometheus, but data retention costs can add up quickly
• Differentiating between clusters and applications is important for effective dashboarding
• The presentation focuses on Istio, Prometheus, and Thanos as key projects for multi-cluster observability
• The demo showcases the installation process for Istio and the creation of certificates for secure communication between clusters

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• The AWS cloud map MCS controller for Kubernetes is demonstrated in a demo using two EKS clusters.
• Both clusters have the about API CRD and MCS API installed.
• Service exports and imports are created to showcase the integration with the about API and MCS API.
• The speaker highlights the importance of community input and invites participation in bi-weekly meetings.

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• Chaos Mesh is an open-source tool for chaos engineering in large-scale distributed systems
• The project aims to increase the probability of reproducing bugs by injecting failures into the system
• Features of the project include Azure chaos, multi-Kubernetes support, and improved usability
• Azure chaos allows users to run chaos workloads on top of the Azure cloud
• Multi-Kubernetes support enables users to run chaos experiments across multiple Kubernetes clusters using one central controller
• Improved usability includes a drag and drop feature for defining workflows

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• Policy-based governance is crucial in protecting the integrity of Ansible playbooks and ensuring a consistent approach to managing clusters
• Best practices can be represented as policies, managed like source code, and deployed using GitHub's methodology
• Benefits include reduced operational costs, continuous security and audit readiness, and efficient day-to-day collaboration among various personas
• The Kubernetes Policy Workgroup's white paper on policy management and the Open Cluster Management CNCF Sandbox project enable the policy-based governance approach

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• Deploying a database on a single Kubernetes cluster is easy, but deploying it on multiple clusters in different regions requires careful planning and consideration of network design, security, and failure handling.
• Multi-cluster deployment can provide high availability, better performance, and geolocality.
• Common pitfalls include issues with networking, automation, and communication between clusters.
• Planning and collaboration between different teams is crucial for successful multi-cluster deployment.
• References to helpful technologies and projects are provided.

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• Multi-cluster support in Kubernetes is important for application efficiency, better resource utilization, and breaking geographic boundaries.
• Existing open source projects have addressed challenges in multi-cluster management but either introduce new APIs/workflows or have scalability limitations.
• Clusterless abstracts multiple clusters as Pod resource providers, connecting to a management cluster exposed to users, without introducing new APIs and preserving consistent user experiences.
• Pod dispatching is done by a highly efficient two-level scheduling algorithm achieving O(n) scheduling throughput, where n is the number of managed clusters.
• Clusterless is great for running more of what you already have in a single cluster, but not for redundancy or availability of workloads or heterogeneous hardware.

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• SIG-Multicluster is focused on solving common challenges related to the management of many Kubernetes clusters
• The SIG is working to identify the best, most durable primitives that will help achieve all these multi-cluster use cases
• The cluster set represents a pattern of use from the field
• The SIG is collaborating with many other SIGs
• The SIG is seeking input from users to expand the multi-cluster Kubernetes landscape

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• Cloud deployments have become increasingly geographically distributed, leading to challenges in managing resources and deploying applications
• Mck8s addresses these challenges by providing automated ways of deploying applications and managing resources, including solving problems related to resilience, scaling, user traffic routing, and load balancing
• Mck8s is built on top of Kubernetes and offers a more integrated and autonomous approach for managing geo-distributed Kubernetes clusters at scale
• Mck8s emphasizes usability and easy adoption by using manifest files similar to vanilla Kubernetes