Managed Kubernetes Service
Managed Kubernetes in Cozystack
Whenever you want to deploy a custom containerized application in Cozystack, it’s best to deploy it to a managed Kubernetes cluster.
Cozystack deploys and manages Kubernetes-as-a-service as standalone applications within each tenant’s isolated environment. In Cozystack, such clusters are named tenant Kubernetes clusters, while the base Cozystack cluster is called a management or root cluster. Tenant clusters are fully separated from the management cluster and are intended for deploying tenant-specific or customer-developed applications.
Within a tenant cluster, users can take advantage of LoadBalancer services and easily provision physical volumes as needed.
The control-plane operates within containers, while the worker nodes are deployed as virtual machines, all seamlessly managed by the application.
Why Use a Managed Kubernetes Cluster?
Kubernetes has emerged as the industry standard, providing a unified and accessible API, primarily utilizing YAML for configuration. This means that teams can easily understand and work with Kubernetes, streamlining infrastructure management.
Kubernetes leverages robust software design patterns, enabling continuous recovery in any scenario through the reconciliation method. Additionally, it ensures seamless scaling across a multitude of servers, addressing the challenges posed by complex and outdated APIs found in traditional virtualization platforms. This managed service eliminates the need for developing custom solutions or modifying source code, saving valuable time and effort.
The Managed Kubernetes Service in Cozystack offers a streamlined solution for efficiently managing server workloads.
Starting Work
Once the tenant Kubernetes cluster is ready, you can get a kubeconfig file to work with it.
It can be done via UI or a kubectl request:
Open the Cozystack dashboard, switch to your tenant, find and open the application page. Copy one of the config files from the Secrets section.
Run the following command (using the management cluster kubeconfig):
kubectl get secret -n tenant-<name> kubernetes-<clusterName>-admin-kubeconfig -o go-template='{{ printf "%s\n" (index .data "admin.conf" | base64decode) }}' > admin.conf
There are several kubeconfig options available:
admin.conf— The standard kubeconfig for accessing your new cluster. You can create additional Kubernetes users using this configuration.admin.svc— Same token asadmin.conf, but with the API server address set to the internal service name. Use it for applications running inside the cluster that need API access.super-admin.conf— Similar toadmin.conf, but with extended administrative permissions. Intended for troubleshooting and cluster maintenance tasks.super-admin.svc— Same assuper-admin.conf, but pointing to the internal API server address.
Implementation Details
A tenant Kubernetes cluster in Cozystack is essentially Kubernetes-in-Kubernetes. Deploying it involves the following components:
Kamaji Control Plane: Kamaji is an open-source project that facilitates the deployment of Kubernetes control planes as pods within a root cluster. Each control plane pod includes essential components like
kube-apiserver,controller-manager, andscheduler, allowing for efficient multi-tenancy and resource utilization.Etcd Cluster: A dedicated etcd cluster is deployed using Ænix’s etcd-operator. It provides reliable and scalable key-value storage for the Kubernetes control plane.
Worker Nodes: Virtual Machines are provisioned to serve as worker nodes using KubeVirt. These nodes are configured to join the tenant Kubernetes cluster, enabling the deployment and management of workloads.
Cluster API: Cozystack is using the Kubernetes Cluster API to provision the components of a cluster.
This architecture ensures isolated, scalable, and efficient tenant Kubernetes environments.
See the reference for components utilized in this service:
- Kamaji Control Plane
- Kamaji — Cluster API
- github.com/clastix/kamaji
- KubeVirt
- github.com/kubevirt/kubevirt
- github.com/aenix-io/etcd-operator
- Kubernetes Cluster API
- github.com/kubernetes-sigs/cluster-api-provider-kubevirt
- github.com/kubevirt/csi-driver
Parameters
Common Parameters
| Name | Description | Value |
|---|---|---|
host | The hostname used to access the Kubernetes cluster externally. Defaults to using the cluster name as a subdomain for the tenant host. | "" |
controlPlane.replicas | Number of replicas for Kubernetes control-plane components. | 2 |
storageClass | StorageClass used to store user data. | replicated |
nodeGroups | nodeGroups configuration | {} |
Cluster Addons
| Name | Description | Value |
|---|---|---|
addons.certManager.enabled | Enable the Cert-manager: automatically creates and manages SSL/TLS certificates. | false |
addons.certManager.valuesOverride | Custom values to override | {} |
addons.cilium.valuesOverride | Custom values to override | {} |
addons.gatewayAPI.enabled | Enable the Gateway API | false |
addons.ingressNginx.enabled | Enable the Ingress-NGINX controller (expect nodes with ‘ingress-nginx’ role). | false |
addons.ingressNginx.valuesOverride | Custom values to override | {} |
addons.ingressNginx.hosts | List of domain names that should be passed through to the cluster by the upper cluster. | [] |
addons.gpuOperator.enabled | Enable the GPU-operator | false |
addons.gpuOperator.valuesOverride | Custom values to override | {} |
addons.fluxcd.enabled | Enable FluxCD | false |
addons.fluxcd.valuesOverride | Custom values to override | {} |
addons.monitoringAgents.enabled | Enable Monitoring Agents (fluentbit, vmagents for sending logs and metrics to storage) if tenant monitoring enabled, send to tenant storage, else to root storage. | false |
addons.monitoringAgents.valuesOverride | Custom values to override | {} |
addons.verticalPodAutoscaler.valuesOverride | Custom values to override | {} |
Kubernetes Control Plane Configuration
| Name | Description | Value |
|---|---|---|
controlPlane.apiServer.resources | Resources, explicit value | {} |
controlPlane.apiServer.resourcesPreset | Use a common resources preset when resources is not set explicitly. | small |
controlPlane.controllerManager.resources | Resources, explicit value | {} |
controlPlane.controllerManager.resourcesPreset | Use a common resources preset when resources is not set explicitly. | micro |
controlPlane.scheduler.resources | Resources, explicit value | {} |
controlPlane.scheduler.resourcesPreset | Use a common resources preset when resources is not set explicitly. | micro |
controlPlane.konnectivity.server.resources | Resources, explicit value | {} |
controlPlane.konnectivity.server.resourcesPreset | SUse a common resources preset when resources is not set explicitly. | micro |
For each controlPlane.*.resourcesPreset parameter:
- Allowed values are
none,nano,micro,small,medium,large,xlarge,2xlarge. - This value is ignored if the corresponding
resourcesvalue is set. In production environments, it’s recommended to setresourcesexplicitly.
Resources Reference
instanceType Resources
The following instanceType resources are provided by Cozystack:
| Name | vCPUs | Memory |
|---|---|---|
cx1.2xlarge | 8 | 16Gi |
cx1.4xlarge | 16 | 32Gi |
cx1.8xlarge | 32 | 64Gi |
cx1.large | 2 | 4Gi |
cx1.medium | 1 | 2Gi |
cx1.xlarge | 4 | 8Gi |
gn1.2xlarge | 8 | 32Gi |
gn1.4xlarge | 16 | 64Gi |
gn1.8xlarge | 32 | 128Gi |
gn1.xlarge | 4 | 16Gi |
m1.2xlarge | 8 | 64Gi |
m1.4xlarge | 16 | 128Gi |
m1.8xlarge | 32 | 256Gi |
m1.large | 2 | 16Gi |
m1.xlarge | 4 | 32Gi |
n1.2xlarge | 16 | 32Gi |
n1.4xlarge | 32 | 64Gi |
n1.8xlarge | 64 | 128Gi |
n1.large | 4 | 8Gi |
n1.medium | 4 | 4Gi |
n1.xlarge | 8 | 16Gi |
o1.2xlarge | 8 | 32Gi |
o1.4xlarge | 16 | 64Gi |
o1.8xlarge | 32 | 128Gi |
o1.large | 2 | 8Gi |
o1.medium | 1 | 4Gi |
o1.micro | 1 | 1Gi |
o1.nano | 1 | 512Mi |
o1.small | 1 | 2Gi |
o1.xlarge | 4 | 16Gi |
rt1.2xlarge | 8 | 32Gi |
rt1.4xlarge | 16 | 64Gi |
rt1.8xlarge | 32 | 128Gi |
rt1.large | 2 | 8Gi |
rt1.medium | 1 | 4Gi |
rt1.micro | 1 | 1Gi |
rt1.small | 1 | 2Gi |
rt1.xlarge | 4 | 16Gi |
u1.2xlarge | 8 | 32Gi |
u1.2xmedium | 2 | 4Gi |
u1.4xlarge | 16 | 64Gi |
u1.8xlarge | 32 | 128Gi |
u1.large | 2 | 8Gi |
u1.medium | 1 | 4Gi |
u1.micro | 1 | 1Gi |
u1.nano | 1 | 512Mi |
u1.small | 1 | 2Gi |
u1.xlarge | 4 | 16Gi |
U Series: Universal
The U Series is quite neutral and provides resources for general purpose applications.
U is the abbreviation for “Universal”, hinting at the universal attitude towards workloads.
VMs of instance types will share physical CPU cores on a time-slice basis with other VMs.
U Series Characteristics
Specific characteristics of this series are:
- Burstable CPU performance - The workload has a baseline compute performance but is permitted to burst beyond this baseline, if excess compute resources are available.
- vCPU-To-Memory Ratio (1:4) - A vCPU-to-Memory ratio of 1:4, for less noise per node.
O Series: Overcommitted
The O Series is based on the U Series, with the only difference being that memory is overcommitted.
O is the abbreviation for “Overcommitted”.
O Series Characteristics
Specific characteristics of this series are:
- Burstable CPU performance - The workload has a baseline compute performance but is permitted to burst beyond this baseline, if excess compute resources are available.
- Overcommitted Memory - Memory is over-committed in order to achieve a higher workload density.
- vCPU-To-Memory Ratio (1:4) - A vCPU-to-Memory ratio of 1:4, for less noise per node.
CX Series: Compute Exclusive
The CX Series provides exclusive compute resources for compute intensive applications.
CX is the abbreviation of “Compute Exclusive”.
The exclusive resources are given to the compute threads of the VM. In order to ensure this, some additional cores (depending on the number of disks and NICs) will be requested to offload the IO threading from cores dedicated to the workload. In addition, in this series, the NUMA topology of the used cores is provided to the VM.
CX Series Characteristics
Specific characteristics of this series are:
- Hugepages - Hugepages are used in order to improve memory performance.
- Dedicated CPU - Physical cores are exclusively assigned to every vCPU in order to provide fixed and high compute guarantees to the workload.
- Isolated emulator threads - Hypervisor emulator threads are isolated from the vCPUs in order to reduce emaulation related impact on the workload.
- vNUMA - Physical NUMA topology is reflected in the guest in order to optimize guest sided cache utilization.
- vCPU-To-Memory Ratio (1:2) - A vCPU-to-Memory ratio of 1:2.
M Series: Memory
The M Series provides resources for memory intensive applications.
M is the abbreviation of “Memory”.
M Series Characteristics
Specific characteristics of this series are:
- Hugepages - Hugepages are used in order to improve memory performance.
- Burstable CPU performance - The workload has a baseline compute performance but is permitted to burst beyond this baseline, if excess compute resources are available.
- vCPU-To-Memory Ratio (1:8) - A vCPU-to-Memory ratio of 1:8, for much less noise per node.
RT Series: RealTime
The RT Series provides resources for realtime applications, like Oslat.
RT is the abbreviation for “realtime”.
This series of instance types requires nodes capable of running realtime applications.
RT Series Characteristics
Specific characteristics of this series are:
- Hugepages - Hugepages are used in order to improve memory performance.
- Dedicated CPU - Physical cores are exclusively assigned to every vCPU in order to provide fixed and high compute guarantees to the workload.
- Isolated emulator threads - Hypervisor emulator threads are isolated from the vCPUs in order to reduce emaulation related impact on the workload.
- vCPU-To-Memory Ratio (1:4) - A vCPU-to-Memory ratio of 1:4 starting from the medium size.