Today’s applications are becoming more complex, driven by the diverse and demanding needs of various industries. E-commerce sites need to handle a lot of data and provide smooth shopping experiences worldwide. Banks require secure and always-available systems for their customers. Health care apps must protect patient information and be reliable. Gaming platforms need to be fast and responsive for players everywhere. Media companies manage and stream large amounts of content, while telecom providers need to ensure reliable service across networks. IoT applications process data from many devices in various locations.
Kubernetes’ ability to handle large-scale, complex deployments and provide high availability makes it an ideal choice for these modern applications. In this rapidly evolving landscape, managing and scaling applications across multiple Kubernetes clusters has become a more and more common practice for numerous reasons.
- Fault tolerance: Running applications on multiple clusters naturally increases their fault tolerance. In the case that one of the clusters experiences an issue, the rest of the clusters continue to operate, minimizing the application downtime and maintaining service availability. We observe that many organizations have internal policies to run mission critical applications on more than one cluster.
- Performance: For organizations that have a geo-distributed customer base, it is critical to place their applications close to their customers. Therefore, it is natural for the application to run in multiple clusters or regions.
- Scalability: Some applications require vast resources to run (think of ChatGPT) and thus cannot fit into a single cluster.
Multicluster Kubernetes application management involves orchestrating and maintaining applications across multiple clusters to ensure high availability, performance and scalability. This approach allows for seamless updates, efficient resource utilization and robust disaster recovery, making it an appealing strategy for managing complex, distributed applications.
Challenges of Managing Multicluster Applications
However, as organizations increasingly deploy applications across multiple Kubernetes clusters, they also face significant challenges. Managing an application on many clusters naturally increases the operational complexity. Here are a few extra things that an application administrator needs to handle for an application deployed in multiple clusters.
- Continuous deployment: Set up a CD system to upgrade the application in a safe manner.
- Network configuration: Set up network configuration that allows north-south and east-west traffic for the application.
- Resource optimization: Scale an application up and down in each individual cluster according to demand and resource limits on that cluster/region.
- Traffic configuration: Split the traffic into each application according to the scale of the deployment of the application in each cluster.
- Deployment strategies: Move the applications between clusters/regions according to resource utilization or capacity in a risk-mitigated way that does not disrupt live services. This also requires moving the traffic with the application in a seamless way if required.
The complexity of operating applications on multiple clusters requires advanced solutions to ensure fault tolerance, performance, scalability and efficient resource utilization. To address these challenges, a comprehensive framework is needed to streamline multicluster application management. Enter KubeFleet, an open source project that promises to address these challenges by redefining multicluster application management.
What Is KubeFleet?
KubeFleet is a cloud native multicluster/multicloud solution designed to facilitate the deployment, management and scaling of applications across multiple Kubernetes clusters. Using advanced scheduling, resource optimization and policy-based management, KubeFleet aims to provide a seamless and efficient experience for platform operators and application owners alike.
The Problem KubeFleet Solves
- Multicluster deployment: KubeFleet presents the application admin a single control plane to deploy an application across multiple clusters, which includes finding the best suitable cluster to run and controlling the number of replicas on each cluster.
- Rich scheduling capability: KubeFleet supports many Kubernetes scheduling operations, such as Cluster Affinity, Topology Spread, and Preferred vs. Required. It also introduces different multicluster flavored policies, like pick N clusters (Deployment-like) or pick all clusters (DaemonSet-like).
- Metrics-based scheduling: KubeFleet also supports sophisticated metrics-based placement strategies that ensure applications are allocated to the most suitable cluster based on various metrics, including internal metrics (GPU, CPU, memory and node account) and external/custom metrics (cost, IP address availability and network speed).
- Built-in continuous deployment strategies: KubeFleet has a built-in rolling update strategy that is very similar to Kubernetes deployment. We also introduced a cloud native stage-based CD with wait and approval between stages.
Join the KubeFleet Community
KubeFleet represents a significant advancement in fleet application management for the Kubernetes community. However, we are even more excited that it is now part of CNCF. We are looking for more cloud native practitioners to get involved in the community and help shape the future of multicluster application management to ensure that future applications are deployed efficiently and reliably at scale.
To learn more about Kubernetes and the cloud native ecosystem, join us at KubeCon + CloudNativeCon Europe in London on April 1-4.
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