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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. The CCE manages clusters, images, templates and compatible applications, as well as the operation of these applications.

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Reasons for CCE in the Open Telekom Cloud

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Ease of use

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.

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Compatibility and portability

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.

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Security

The CCE service follows the CIS benchmark guidelines and continuously analyses the latest releases. Regardless of the community release cycle, each CCE Kubernetes version maintenance is supported for approximately two years and is fully GDPR-compliant.


Key Features of CCE

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Managed 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.
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Flexible operation and maintenance

There are many ways to run the CCE clusters and store the images in our Software Repository for Containers service:

  • Visual console
  • Kubectl
  • Helm command-line interface
  • APIs
  • Terraform
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High availability

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
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Adaptive

The Kubernetes cluster can be customised and extended with predefined add-ons or your own Helm charts.

  • CoreDNS: DNS-based service discovery and domain name resolution services for Kubernetes clusters
  • Everest: Storage driver for data persistent on OBS, EVS, SFS, and SFS Turbo
  • Autoscaler: For horizontal POD autoscaling
  • Metrics-server: An aggregator for monitoring data of core cluster resources
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Dynamic persistent Storage Solutions 

Cloud Container Engine can be used with SFS Turbo, Elastic Volume Service (EVS) and Object Storage Service (OBS). It's possible to encrypt all the Storage solutions for CCE via the KMS.

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Cost-effective

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.

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Monitoring and troubleshooting

CCE can be easily monitored with the data provided in the console and connects to cloud services such as Application Operations Management (AOM) and Cloud Eye (CES).


Use Cases

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.


Advantages

  • 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.

Example Scenarios

Website | Online Shop
 

Example scenario for Auto Cluster Scaling: Website, Online Shop


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.


Advantages

  • 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.  

Example Scenarios

Financial systems | Medical/health applications | Database applications
 

Example scenario for High Availability Cluster: Financial systems, medical/health application, database application

GPU Containers

Running containers on high-performance GPU-accelerated cloud servers significantly improves AI computing performance, and GPU sharing among containers greatly reduces AI computing costs.


Advantages

  • 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

Example Scenarios

Training of machine learning applications | CEA applications | Scientific computing

Example scenario for GPU Containers: training of machine learning applications, CEA applications, scientific computing

Getting Started with Cloud Container Engine

Getting Started with Cloud Container Engine in the Open Telekom Cloud

Step 1: Authorize an IAM user to use CCE

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.

Step 2: Create a cluster

For details on how to create a regular Kubernetes cluster, see Creating a Hybrid Cluster.

Step 3: Create a workload from images or a chart

For details on how to create a workload from images, see Workloads.
For details on how to create a workload from a chart, see Charts.

Step 4: View workload status and logs. Upgrade, scale, and monitor the workload

For details, see Managing a Deployment.

New Features

CCE - New release with Kubernetes 1.19 and other functions released
View details
CCE - Kubernetes 1.19.10, new Everest and CoreDNS version
View details
CCE Turbo cluster Beta Launch in Germany
View details
CCE – New release with Kubernetes 1.21
View details

Find out more

Book now and claim starting credit of EUR 250* (code: 4UOTC250)

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+800 33 04 47 70 from abroad

* Voucher can be redeemed until December 31, 2022. Please contact us when using the voucher for booking. The discount is only valid for customers with a billing address in Germany and expires two months after conclusion of the contract. The credit is deducted according to the valid list prices as per the service description. Payment of the credit in cash is excluded.

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