Cloud Container Engine (CCE)
Containers take working with clouds to the next level: transport only the essential parts of applications and let the platform provide things such as the operating system and libraries.
The Cloud Container Engine (CCE) in the Open Telekom Cloud allows containers to be configured using virtual machines (ECS). Based on Kubernetes, CCE is compatible with Docker and offers the option of accessing the public resources of the Docker hub or the Software Repository for Containers service zuzugreifen. Das CCE verwaltet Cluster, Images, Templates und kompatible Anwendungen sowie den Betrieb dieser Anwendungen.
CCE allows you to create Managed Kubernetes in only a few clicks and just a few minutes. Manual installation, management and maintenance of Kubernetes are a thing of the past. Additionally, a visual console helps users who are unfamiliar with Kubernetes.
Users benefit from the fact that Cloud Container Engine uses open-source technology. The compatibility with Docker grants access to the public, to open-source image repositories from Docker Hub, and enables the portability of the Kubernetes environment.
- Business acceleration: CCE helps you focus on your business and save time in operating a Kubernetes environment. Get started with pre-configured clusters in just a few minutes instead of a few months.
- Cloud integration: The high Open Telekom Cloud integration enables usage of scaled services, including, but not limited to,Elastic Load Balancer (ELB), Object Storage Services (OBS) and Key Management Services (KMS). For example, there is an integrated ingress controller with a functional ELB at the application layer to start without any configuration.
- Scalability: From small, single-az-mode clusters with 50x nodes, to highly available clusters with up to 2000x nodes possible in the enterprise environment.
- Variability and efficiency: Availability of standard, memory, compute, storage, or AI-optimised resources depending on the use case.
- Shared responsibility: The master node will be managed by Open Telekom Cloud and the worker nodes are accessible for the customers.
CCE is designed for enterprise environments to meet the requirements of productive applications:
- Up to three master nodes to increase fault tolerance
- Node pools across multiple AZs
- Ready for disaster recovery
- Integrated health inspection of containers
The Kubernetes cluster can be customised and extended with predefined add-ons or your own Helm charts.
The costs are based on the use of the cloud resources such as Elastic Cloud Server (ECS), etc. The smallest cluster without HA is free of charge for the CCE service self and can be used for smaller workloads.
Auto Cluster Scaling
Computing resources can be adjusted based on service requirements and preset strategies. The number of cloud servers or containers increases or decreases with service traffic changes, ensuring service stability.
- Flexibility: Offer multiple scaling policies and scale containers within seconds when specified conditions are met.
- High availability: Automatically detect the statuses of pods in auto-scaling groups and replace unhealthy pods with new ones.
- Low cost: You only pay for the cloud servers that you use.
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High Availability Cluster
High availability and functionality of an application can be ensured with multiple master nodes distributed over different availability zones. Even if a master node fails, the application will not be affected.
- High availability: Increased reliability/fail-safety due to multiple master nodes across different availability zones.
- Simple setup: Set up native Kubernetes with just one click.
- Easy integration: The high availability functionality can be added to every other CCE use case.
Financial systems | Medical/health applications | Database applications
Running containers on high-performance GPU-accelerated cloud servers significantly improves AI computing performance, and GPU sharing among containers greatly reduces AI computing costs.
- Efficient computing: GPUs are shared and scheduled among multiple containers, greatly reducing computing costs.
- Interoperability with ModelArts: Move data from machine learning applications between CCE clusters and ModelArts.
Training of machine learning applications | CEA applications | Scientific computing
The accounts have the permission to use CCE. However, IAM users created by the accounts do not have the permission. You need to manually assign the permission to IAM users
For details on how to create a regular Kubernetes cluster, see Creating a Hybrid Cluster.
For details, see Managing a Deployment.
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