Register external Kubernetes clusters with ACK One for unified hybrid and multi-cloud management.
Registered cluster console
Features
Use ACK One to register Kubernetes clusters from various environments, such as ACK, self-managed, and third-party cloud clusters, for unified management. Consider registered clusters for the following needs:
Hybrid cloud elasticity: Scale self-managed clusters with cloud resources such as Elastic Compute Service (ECS) instances, physical servers, or Elastic Container Instance (ECI). The ack-co-scheduler provides policies to prioritize scale-out, scale in on demand, distribute pod replicas proportionally, and scale GPU-based node pools across data center and cloud.
Consistent operational experience with ACK: Manage all Kubernetes clusters—on Alibaba Cloud or in your data center—from a single console with unified security governance. Centralize cluster and application management, logs, monitoring, alerts, and authorization policies using Alibaba Cloud accounts, RAM users, and RAM roles.
AI and big data capabilities: Improve computing efficiency by 30–40% with topology-aware CPU scheduling and NUMA awareness. Increase GPU utilization by up to 300% through GPU sharing and scheduling. Scale heterogeneous resources across cloud and on-premises environments. Accelerate data access by nearly 10x and reduce bandwidth usage by 90% with Fluid for unified storage access in a hybrid cloud distributed cache.
Backup and disaster recovery: An integrated cloud solution for backup, recovery, and migration provides disaster recovery for data and applications, improving business continuity.
Use cases
Use case 1: Hybrid cloud with registered clusters
Description
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Self-managed clusters in data centers: Connect cluster networks to share resources between your on-premises and cloud environments.
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On-demand scaling of cloud resources and applications: During peak business hours, rapidly scale out resources in the cloud and direct a portion of your traffic to the cloud.
Use case 2: Consistent experience for on-premises clusters
Description
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Consistent operational experience: Extend the unified operational capabilities of ACK to clusters in your data centers and on third-party public clouds.
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Enhanced observability: Gain a cloud-consistent operational experience with support for log, monitoring, and event collection.
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Improved security: Enable auditing, security inspection, node risk detection, and policy governance with a single click.
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Microservice governance: Microservices Engine (MSE) and Service Mesh (ASM) provide microservice governance capabilities.
Use case 3: Data disaster recovery with registered clusters
Description
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Application migration to the cloud: Provides consistent application backups and recovery in seconds across regions and data centers to help you quickly migrate your business applications to the cloud.
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Data disaster recovery: Provides stateful application backups across regions and data centers with support for configurable backup and recovery policies. Continuously back up data to the cloud for disaster recovery to improve protection against ransomware.
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Business disaster recovery: Provides geo-redundant and scheduled backup capabilities for applications and data across regions and data centers.
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Active geo-redundancy: Provides a Kubernetes-compatible solution to quickly build a disaster recovery system with three centers across two regions, which helps you build a high-availability system.
Use case 4: Co-scheduling for AI and big data
Description
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AI algorithm development: Provides comprehensive management of tasks, quotas, and observability.
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AI training: Supports topology-aware scheduling and a rich set of task scheduling policies to improve training efficiency. The compute-storage separation architecture significantly speeds up distributed data training. It also supports cross-cluster job scheduling and provides multi-cluster optimized distribution and scheduling for jobs such as TensorFlow, Spark, and CronJob.
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AI inference: Provides GPU sharing, which can increase resource utilization by approximately 300%. It supports elastic scaling of heterogeneous resources and provides unified elastic scheduling management for both cloud and on-premises environments.
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Intelligent CPU scheduling: Provides intelligent CPU scheduling and NUMA awareness for bare metal servers.