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Introduction

The ICN blueprint family intends to address deployment of workloads in a large number of edges and also in public clouds using K8S as resource orchestrator in each site and ONAP-K8S as service level orchestrator (across sites).  ICN also intends to integrate infrastructure orchestration which is needed to bring up a site using bare-metal servers. Infrastructure orchestration, which is the focus of this page, needs to ensure that the infrastructure software required on edge servers is installed on per-site basis, but controlled from a central dashboard.  Infrastructure orchestration is expected to do the following:

  • Installation : First-time installation of all infrastructure software.
    • Keep monitoring for new servers and install the software based on the role of the server machine.
  • Patching:  Continue to install the patches (mainly security related) if new patch release is made in any one of the infrastructure software packages.
    • May need to work with resource and service orchestrators to ensure that workload functionality does not get impacted.
  • Software updates:  Updating software due to new releases.

The user experience needs to be as simple as possible and even a novice user should be able to set up a site.

Use Cases

  1. SDWAN,  Customer Edge,  Edge Clouds – deploy VNFs/CNFs and applications as micro-services (Completed in R2 release using OpenWRT SDWAN Containerized)
  2. DAaaS - Distributed Ana

Where on the Edge

Kuralamudhan Ramakrishnan (Deactivated)  - what are the drivers?

Business Drivers


Overall Architecture

On an edge deployment, there may be multiple edges that need to be brought up.  The Administrator going to each location, using the infra-local-controller to bring up application-K8S clusters in compute nodes of each location, is not scalable.  Therefore, we have an "infra-global-controller" to control multiple "infra-local-controllers" which are controlling the worker nodes. The "infra-global-controller" is expected to provide a centralized software provisioning and configuration system.  It provides one single-pane-of-glass for administrating the edge locations with respect to infrastructure. The worker nodes may be baremetal servers, or they may be virtual machines resident on the infra-local-controller. So the minimum platform configuration is one global controller and one local controller (although the local controller can be run without a global controller).

Since, there are a few K8S clusters, let us define them:

  • infra-global-controller-K8S :  This is the K8S cluster where infra-global-controller related containers are run.
  • infra-local-controller-K8S:  This is the K8S cluster where the infra-local-controller related containers are run, which bring up compute nodes.
  • application-K8S :  These are K8S clusters on compute nodes, where application workloads are run.

Flows & Sequence Diagrams

@Kural - I think this is the closest to a general architectural view, but the steps in the sequence (1-6 below the diagram) you might say belong in the Software Architecture diagram.



  1. Use Clusterctl command to create the cluster for the cluster-api-provider-baremetal provider. For this step, we required KuD to provide a cluster and run the machine controller and cluster controller
  2. Users Machine CRD and Cluster CRD in configured to instated 4 clusters as #0, #1, #2, #3
  3. Automation script for OOM deployment is trigged to deploy ONAP on cluster #0
  4. KuD addons script in trigger in all edge location to deploy K8s App components, NFV Specific and NFVi SDN controller
  5. Subscriber or Operator requires to deploy the VNF workload such as SDWAN in Service Orchestration
  6. ONAP should place the workload in the edge location based on Multi-site scheduling and K8s HPA



Platform Architecture


@Kural - I have explanations of software components in both Platform Architecture and Software Platform Architecture. Maybe it would be better to rewrite the PA to have a more general explanation of the arch, and move details into SPA? Also, maybe the locations of the elements (global, local) is not clear.


Infra-global-controller: 

   Administration involves

  • First time bring up.
  • Addition of new compute nodes in locations.
  • Removal of compute nodes from locations
  • Software patching
  • Software upgrading

The infra-local-controller will be brought up in each location.  The infra-local-controller kubeconfig will be made known to the infra-global-controller. Beyond that, everything else is taken care by the infra-global-controller. The infra-global-controller communicates with various infra-local-controllers to do the job of software installation and provisioning.

Infra-global-controller runs in its own K8S cluster. All the components of infra-global-controllers are containers.  The following components are part of the infra-global-controller.

  • Provisioning controller  (PC) Micro Services
  • Binary Provisioning Manager (BPM) Micro services
  • K8S Provisioning Manager (KPM) Micro-services
  • CSM: Certificate and Secret management related Micro-services
  • Cluster-API related Micro-services
  • MongoDB for storing packages and OS images.
  • Prometheus: Monitoring and alerting

Since we expect the infra-global-controller to be reachable from the Internet, we should be secured using

  • ISTIO and Envoy (for internal communication as well as for external communication) 
  • Store Citadel private keys using CSM.
  • Store secrets using SMS of CSM.

Infra-local-controller: 

The "infra-local-controller" runs on the bootstrap machine in each location.  The Bootstrap is the one which installs the required software in compute nodes used for future workloads.  For example, say a location has 10 servers. 1 server can be used as the bootstrap machine and all other 9 servers can be used as compute nodes for running workloads.  The Bootstrap machine not only installs all required software in the compute nodes, but is also expected to patch and update compute nodes with newer patched versions of the software.

As you see above in the picture, the bootstrap machine itself is based on K8S.  Note that this K8S is different from the K8S that gets installed in compute nodes.  That is, these are two different K8S clusters. In case of bootstrap machine, it itself is a complete K8S cluster with one node that has both master and minion software combined.  All the components of the infra-local-controller (such as BPA, Metal3 and Ironic) are containers.  

Since we expect infra-local-controller is reachable from outside we expect it to be secured using

  • ISTIO and Envoy (for internal communication as well as for external communication) 

Infra-local-controller is expected to be brought up in two ways:

  • As a USB bootable disk:   One should be able to get any bare-metal server machine, insert USB and restart the server. This means that the USB bootable disk shall have basic Linux, K8S and all containers coming up without any user actions.  It must also have packages and OS images that are required to provision actual compute nodes.  As in above example, these binary, OS and packages are installed on 9 compute nodes.
  • As individual entities:  As developers, one shall be able to use any machine without inserting a USB disk.  In this case, the developer can choose a machine as a bootstrap machine, install Linux OS, Install K8S using Kubeadm and then bring up BPA, Metal3 and Ironic. Then upload packages via RESTAPIs provided by BPA to the system.
  • As a KVM/QMEU Virtual machine image:   One shall be able to use any VM as a bootstrap machine using this image.

Note that the infra-local-controller can be run without the infra-global-controller. In the interim release, we expect that only the infra-local-controller is supported.  The infra-global-controller is targeted for the final Akraino R2 release. It is the goal that any operations done in the interim release on infra-local-controller manually are automated by infra-global-controller. And hence the interface provided by infra-local-controller is flexible enough to support both manual actions as well as automated actions. 

As indicated above, infra-local-controller will bring up K8S clusters on the compute nodes used for workloads.  Bringing up a workload K8S cluster normally requires the following steps

  1. Bring up Linux operating system.
  2. Provision the software with right configuration
  3. Bring up basic Kubernetes components (such as Kubelet, Docker, kubectl, kubeadm etc..
  4. Bring up components that can be installed using kubectl.

Step 1 and 2 are performed by Metal3 and Ironic.  Step 3 is performed by BPA and Step 4 is done by talking to application-K8S

Metal3 Baremetal Operator & Ironic

The Baremetal Operator provides provisioning of compute nodes (either baremetal or VM) by using the kubernetes API. The Baremetal Operator defines a CRD BaremetalHost Object representing a physical server; it represents several hardware inventories. Ironic is responsible for provisioning the physical servers, and the Baremetal Operator is for responsible for wrapping the Ironic and represents them as CRD object. 

Binary Provisioning Agent (BPA)

The job of the BPA is to install all packages to the application-K8S that can't be installed using kubectl.  Hence, the BPA is used right after the compute nodes get installed with the Linux operating system, before installing kubernetes-based packages.  BPA is also an implementation of CRD controller of infra-local-controller-k8s.  We expect to have the following CRs:

  • To upload site specific information - compute nodes and their roles
  • To instantiate the binary package installation.
  • To get hold of application-K8S kubeconfig file.
  • Get status of the installation

The BPA also provides some RESTful APIs for doing the following:

  • To upload binary images that are used to install the stuff in compute nodes.
  • To upload Linux Operating system that are needed in compute nodes.
  • Get status of installation of all packages as prescribed before.

Since compute nodes may not have Internet connectivity

  • The BPA also acts as a local Docker Hub repository and ensures that all K8S container packages (that need to be installed on the application-K8S) are served locally here.
  • The BPA also configures docker to access packages from this local repository.

BPA also takes care of: (After interim release)

  • When a new compute node is added, once the administrator adds the new compute node in the site list, it shall take care of installing the packages.
  • If a new binary package version is uploaded, it shall take care of figuring out the compute nodes that require this new version and update that compute node with the new version.

BPA is expected to store any private key and secret information in CSM.

  • SSH passwords used to authenticate with the compute nodes is expected to be stored in SMS of CSM
  • Kuberconfig used to authenticate with application-K8S.

BPA and Ironic related integration:

Ironic is expected to bring up Linux on compute nodes. It is also expected to create SSH keys automatically for each compute node. In addition, it is also expected to create SSH user for each compute node. Usernames and password are expected to be stored in SMS for security reasons in infra-local-controller.  BPA is expected to leverage these authentication credentials when it installs the software packages.

CSM is used for storing secrets and performing crypto operations using CSM.

  • Use PKCS11
  • If TPM is present, Citadel keys are expected to be distributed to TPM and also use TPM for signing operations.

Software Platform Architecture

@Kural - see comments under platform arch

Local Controller: kubeadm, Metal3, Baremetal Operator, Ironic, Prometheus, CSM, ONAP

Global Controller: kubeadm, KuD, K8S Provisioning Manager, Binary Provisioning Manager, Prometheus, CSM

Cluster-API & Baremetal Operator

One of the major challenges to cloud admin managing multiple clusters in different edge location is coordinate control plane of each cluster configuration remotely, managing patches and updates/upgrades across multiple machines. Cluster-API provides declarative APIs to represent clusters and machines inside a cluster.  Cluster-API provides the abstraction for various common logic that can be seen in various cluster provider such as GKE, AWS, Vsphere. Cluster-API consolidated all those logic provide abstractions for all those logic functions such as grouping machines for the upgrade, autoscaling mechanism.

In ICN family stack, Cluster-API Baremetal provider is the Metal3 Baremetal Operator. It is used as a machine actuator that uses Ironic to provide k8s API to manage the physical servers that also run Kubernetes clusters on bare metal host. Cluster-API manages the kubernetes control plane through cluster CRD, and Kubernetes node(host machine) through machine CRDs, Machineset CRDs and MachineDeployment CRDS. It also has an autoscaler mechanism that checks the Machineset CRD that is similar to the analogy of K8s replica set and MachineDeployment CRD similar to the analogy of K8s Deployment. MachineDeployment CRDs are used to update/upgrade of software drivers in 

Cluster-API provider with Baremetal operator is used to provision physical server, and initiate the Kubernetes cluster with user configuration 

KuD

Kubernetes deployment (KUD) is a project that uses Kubespray to bring up a Kubernetes deployment and some addons on a provisioned machine. As it already part of ONAP it can be effectively reused to deploy the K8s App components(as shown in fig. II), NFV Specific components and NFVi SDN controller in the edge cluster. In R2 release KuD will be used to deploy the K8s addon such as  Virlet, OVN, NFD, and Intel device plugins such as SRIOV and QAT in the edge location(as shown in figure I). In R3 release, KuD will be evolved as "ICN Operator" to install all K8s addons. For more information on the architecture of KuD please find the information here

ONAP on K8s

One of the Kubernetes clusters with high availability, which is provisioned and configured by Cluster-API will be used to deploy ONAP on K8s. ICN family uses ONAP Operations Manager(OOM) to deploy ONAP installation. OOM provides a set of helm chart to be used to install ONAP on a K8s cluster. ICN family will create OOM installation and automate the ONAP installation once a Kubernetes cluster is configured by cluster-API

ONAP Block and Modules:

ONAP will be the Service Orchestration Engine in ICN family and is responsible for the VNF life cycle management, tenant management and Tenant resource quota allocation and managing Resource Orchestration engine(ROE) to schedule VNF workloads with Multi-site scheduler awareness and Hardware Platform abstraction(HPA). Required an Akraino dashboard that sits on the top of ONAP to deploy the VNFs

Kubernetes  Block and Modules:

Kubernetes will be the Resource Orchestration Engine in ICN family to manage Network, Storage and Compute resource for the VNF application. ICN family will be using multiple container runtimes as Virtlet, Kata container, Kubevirt and gVisor. Each release supports different container runtimes that are focused on use cases. 

Kubernetes module is divided into 3 groups - K8s App components, NFV specific components and NFVi SDN controller components, all these components will be installed using KuD addons

K8s App components: This block has k8s storage plugins, container runtime, OVN for networking, Service proxy and Prometheus for monitoring, and responsible application management

NFV Specific components: This block is responsible for k8s compute management to support both software and hardware acceleration(include network acceleration) with CPU pinning and Device plugins such as QAT, FPGA, SRIOV & GPU.

SDN Controller components: This block is responsible for managing SDN controller and to provide additional features such as Service Function chaining(SFC) and Network Route manager.  

Modules Design & Architecture:

Please explain each component & their design/architecture, Please keep maximum 2 paragraph, if possible link your project wiki link for more information

Metal3: Kuralamudhan Ramakrishnan (Deactivated)

BPA Operator: Itohan Ukponmwan (Deactivated) Ramamani Yeleswarapu (Deactivated)

BPA Rest Agent: Enyinna Ochulor Tingjie Chen (Deactivated)

KUD: Akhila Kishore (Deactivated) Kuralamudhan Ramakrishnan (Deactivated)

ONAP4K8s: Kuralamudhan Ramakrishnan (Deactivated)

SDWAN: SDWAN module is worked as software defined router which can be used to defined the rules when connect to external internet. It is implemented as CNF instead of VNF for better performance and effective deployment, and leverage OpenWRT (an open source project based on Linux, and used on embedded devices to route network traffic) and mwan3 package (for wan interfaces management) to implement its functionalities, detail information can be found at: SDWAN Module Design


Components

Link

Akraino Release target

Cluster-API

https://github.com/kubernetes-sigs/cluster-api - 0.1.0

R2

Cluster-API-Provider-bare metal

https://github.com/metal3-io/cluster-api-provider-baremetal

R2

Provision stack - Metal3

https://github.com/metal3-io/baremetal-operator/

R2

Host Operating system

Ubuntu 18.04

R2

Quick Access Technology(QAT) drivers

Intel® C627 Chipset - https://ark.intel.com/content/www/us/en/ark/products/97343/intel-c627-chipset.html

R2

NIC drivers

XL710 - https://www.intel.com/content/dam/www/public/us/en/documents/datasheets/xl710-10-40-controller-datasheet.pdf

R2

ONAP

Latest release 3.0.1-ONAP - https://github.com/onap/integration/

R2

Workloads

  • OpenWRT SDWAN - https://openwrt.org/
  • Distributed Analytics as a Service
  • EdgeXFoundry use case
  • VR 360 streaming

R3

KUD

https://git.onap.org/multicloud/k8s/ 

R2

Kubespray

https://github.com/kubernetes-sigs/kubespray

R2

K8s

https://github.com/kubernetes/kubeadm - v1.15

R2

Docker

https://github.com/docker - 18.09

R2

Virtlet

https://github.com/Mirantis/virtlet -1.4.4

R2

SDN - OVN

https://github.com/ovn-org/ovn-kubernetes - 0.3.0

R2

OpenvSwitch

https://github.com/openvswitch/ovs - 2.10.1

R2

Ansible

https://github.com/ansible/ansible - 2.7.10

R2

Helm

https://github.com/helm/helm - 2.9.1

R2

Istio

https://github.com/istio/istio - 1.0.3

R2

Kata container

https://github.com/kata-containers/runtime/releases - 1.4.0

R3

Kubevirt

https://github.com/kubevirt/kubevirt/ - v0.18.0

R3

Collectd

https://github.com/collectd/collectd

R2

Rook/Ceph

https://rook.io/docs/rook/v1.0/helm-operator.html v1.0

R2

MetalLB

https://github.com/danderson/metallb/releases - v0.7.3

R3

Kube - Prometheus

https://github.com/coreos/kube-prometheus - v0.1.0

R2

OpenNESS

Will be updated soon

R3

Multi-tenancy

https://github.com/kubernetes-sigs/multi-tenancy 

R2

Knative

https://github.com/knative

R3

Device Plugins

https://github.com/intel/intel-device-plugins-for-kubernetes - QAT, SRIOV

R2

https://github.com/intel/intel-device-plugins-for-kubernetes - FPGA, GPUR3

Node Feature Discovery

https://github.com/kubernetes-sigs/node-feature-discovery -

R2

CNI

https://github.com/coreos/flannel/ - release tag v0.11.0

https://github.com/containernetworking/cni - release tag v0.7.0

https://github.com/containernetworking/plugins - release tag v0.8.1

https://github.com/containernetworking/cni#3rd-party-plugins - Multus v3.3tp, SRIOV CNI v2.0( withSRIOV Network Device plugin)

R2

Conformance Test for K8s

https://github.com/heptio/sonobuoy

R2

Kuralamudhan Ramakrishnan (Deactivated)  - Edit it for R2 release

APIs

Kuralamudhan Ramakrishnan (Deactivated) kuralamudhan- what to do here?

APIs with reference to Architecture and Modules

High Level definition of APIs are stated here, assuming Full definition APIs are in the API documentation

Hardware and Software Management

@Kural - what to do here? software management is covered under Platform Architecture

Licensing

  • GNU/common license


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