Overview

ICN BP 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:

infra-global-controller:  If infrastructure provisioning needs to controlled from a central location, this component is expected to be brought up in one location.  This controller communicates with infra-local-controller (which is kind of agent) that perform the actual software installation/update/patch and provisions the software or BIOS etc...

infra-local-controller:  Typically sits in each site in a bootstrap machine.  Typically provided as bootable USB disk. It works in conjunction with the infra-global-controller.  Note that, if there is no requirement to manage the software provisioning from a central location, then infra-global-controller is brought up along with the infra-local-controller. 

User experience needs to be as simple as possible and even novice user shall be able to set up a site


Akraino's "Integrated Cloud Native NFV & App Stack"  (ICN) Blueprint is a Cloud Native Compute and Network Framework(CN-CNF) to integrated NFV's application to the de-facto standard and setting a framework to address 5G, IOT and various Linux Foundation edge use case in Cloud Native.

ICN has ONAP as the Service Orchestration Engine(SOE) and the Cloud Native(CN) projects such as Kubernetes for Resource Orchestration Engine(ROE), Prometheus as the monitoring and alerting, OVN as the SDN controller, Container Network Interface(CNI) for Orchestration Networking, provides networking between the clusters, Envoy for Service proxy, Helm and Operators for package management and Rook for storage. The framework stack specifics the best configuration methodology, enables development projects, installation scripts, software package to bind CNCF and LF edge use cases together.

This document break downs the hardware requirements, software ingredient, Testing and benchmarking for the R2 and R3 release for and provides overall picture toward blue print effect in Edge use cases.

Goals

Architecture:

Blocks and Modules



All the green items are existing open source projects. If they require any enhancements, it is best done in the upstream community.

All the red items are expected to be part of the Akraino BP.  In some cases, the code in various upstream projects can be leveraged.  But, we made them in red color as we don't know at this time to what extent we can use the upstream ASIS. Some guidance


Since, there are few K8S cluster, let us define them:

Infra-local-controller: 

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

As you see above in the picture, 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 are different K8S clusters. In case of bootstrap machine, it itself is complete K8S cluster with one node that has both master and minion software combined.  All the components of infra-local-controller (such as BPA, Metal3 and Ironic) themselves are containers.  

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

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

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

As indicated above, infra-local-controller is expected to bring K8S cluster on the compute nodes used for workloads.  Bringing up 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 expected to be taken care using Metal3 and Ironic.  Step 3 is expected to be taken care by BPA and Step 4 is expected to be taken care by talking to application-K8S

User experience for infrastructure administrators:

When using USB bootable disk

  1. Select a machine in the location for bootstrapping. 
  2. Boot up a bootstrap machine using USB bootable disk.
  3. Via Kubectl to infra-local-controller via Metal3 CRs, make ironic ready for compute nodes to do PXEBOOT and install Linux.
  4. Upload site specific information via BPA CR - Compute nodes, their roles etc...
  5. Once Linux get installed, Via Kuberctl to BPA (via CR), make BPA install the binary packages (such as Kubelet, docker, kubectl, kubenetes API server for application-K8S)
  6. Via Kuberctl to BPA, get hold of kubeconfig of application-K8S 
  7. Using this kubeconfig, via kubectl to application-K8S, install the packages that can be done via kubectl (such as Multus, OVN Controllers, Virtlet etc...)

As a developer:

  1. Select a machine in the location for bootstrapping.
  2. Install Linux OS
  3. Install Kubernetes on this machine using Kubeadm or any of your favorite tool
  4. Upload all binary packages, Linux OSes to be installed in compute nodes using for applications.
  5. Upload site specific information - Compute nodes, their roles etc...
  6. Once Linux get installed, Via Kuberctl to BPA (via CR), make BPA install the binary packages (such as Kubelet, docker, kubectl, kubenetes API server for application-K8S)
  7. Via Kuberctl to BPA, get hold of kubeconfig of application-K8S 
  8. Using this kubeconfig, via kubectl to application-K8S, install the packages that can be done via kubectl (such as Multus, OVN Controllers, Virtlet etc...)
  9. Make a USB bootable disk for administrators to use in real deployments.
  10. Make a VM image for administrators to use in real deployments.

Binary Provisioning Agent (BPA)

BPA job is to install all packages that can't be installed using kubectl to application-K8S.  Hence, BPA is normally used right after compute nodes get installed with 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 following CRs:

BPA also provides some RESTful API for doing the following:

Since compute nodes may not have Internet connectivity

BPA also takes care of: (After interim release)

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

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 expected to be used not only for storing secrets, but also securely store and perform crypto operations using CSM.

Implementation suggestions:

KuD needs to be broken into pieces

Infra-global-controller: 

There could be multiple edges that need to be brought up.  Administrator going to each location, using infra-local-controller to bring up application-K8S cluster in compute nodes of location is not scalable.  "infra-global-controller" is expected to provide centralized software provisioning and configuration system.  It provides one single-pane-of-glass for administrating the edge locations with respect to infrastructure.   Administration involves

It is expected that infra-local-controller is brought up in each location.  infra-local-controller kubeconfig is something that is expected to be made known to the infra-global-controller. Beyond that everything else is taken care by infra-global-controller. 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.  Following components are part of the infra-global-controller.

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

Admin user experience:

Assuming that infra-global-controller is brought up with all its micro-services, following steps are expected to be taken up to provision sites/edges.

  1. Register infra-local-controllers using infra-local-k8s kubeconfig information and BPA rechability information of each infra-local-controller : This step is required for each infra-local-controller i.e for each location.  This will provide information to infra-global-controller to reach K8S API server of infra-local-controller of each location.
  2. Upload binary packages (which are binary packages installed in compute nodes by infra-local-controller), helm charts and corresponding container images : This step occurs normally once or when the new versions of the packages.
  3. For every site, upload information about compute nodes and their roles.
  4. Trigger installation on each site.
  5. Monitor the progress
  6. Take corrective actions if necessary.
  7. Monitor the status of each site on continuous basis. (Expectation is that all K8S clusters - global, local, application - would be installed with Prometheus, Node-exporter and cAdvisor microservices. It is an assumption is that all logs are generated and put in fluentd)
    1. Monitor the status of infra-local-K8S and its node.
    2. Monitor the status of application-K8S and compute nodes.
    3. Monitor itself 
    4. Log viewer

Infra-global-controller uses Cluster-API to provision OS related installation in the locations via infra-local-controller. 

Following sections describe the components of infra-global-controller.

Provisioning Controller:

It has following functions

Site information : 

Inventory information:  

Application-K8S reachability information:

Software and configuration of site:

Implementation notes:

Binary Provisioning Manager (BPM)

It has following functions

Binary package installation and configuration management :  This functionality via RESTful API is called by PC to trigger the installation.  It then internally calls BPA of infra-local-controller to initiate the installation and configuration process. It triggers BPA via infra-local-K8S BPA CRs.

Binary package distribution :  This functionality via RESTful API is called by PC.  It figures out the differences between the binary packages & container packages it has locally for this location with the packages that are already in the BPA. Any differences are uploaded to BPA via BPA provided RESTful API.

Collection of KubeConfig of application-K8S : This functionality gets the KubeConfig of application-K8S from BPA. This gets stored in the database table that is specific to site.

K8S Provisioning Manager (KPM)

KPM is used to install containerized packages on application-K8S.  KPM looks at all the relevant helm charts and instantiates them by talking to application-K8S.

Implementation details:

Code can be borrowed from the ONAP Multi-Cloud K8S plugin service which does similar functionality.

Design Details(WIP)

Note : ZTP (Zero Touch Provisioning) term is used in the BP presentation.  This represents both infra-local-controller and infra-global-controller.

infra-local-controller

As shown in the above figure, the infra local controller is itself a Bootstrap K8s cluster, that brings up the compute k8s cluster in the edge location.  Infra-local controller has BPA, Metal3, Baremetal operator(Ironic). This section explains the details of it.

Metal3 & Ironic:

This subsection is referred from https://github.com/metal3-io/metal3-docs/blob/master/design/nodes-machines-and-hosts.md

Baremetal operator provides hardware provisioning of compute nodes by using the kubernetes API. The Baremetal operator defines a CRD BaremetalHost Object represents 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. 


BPA (Define CRD, example CRs, RESTful API)

KuD Changes (Describe how KuD works today and what specific changes would be required)

Metal3 & Ironic


Sequence Diagrams involving all of above + CSM + Logging + Monitoring stuff

Infra-global-controller

PC (Define CRD, Restful API and the example CRs and example API requests)

BPM

KPM

Cluster-API

Global ZTP:

Global ZTP system is used for Infrastructure provisioning and configuration in ICN family. It is subdivided into 3 deployments Cluster-API, KuD and ONAP on K8s. 

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 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 deployer(KUD) in ONAP can be 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 Prometheus, Rook, Virlet, OVN, NFD, and Intel device plugins in the edge location(as shown in figure I). In R3 release, KuD will be evolved as "ICN Operator" to install all K8s addons.

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.  

Apps/ Use cases:

ICN Infrastructure layout

Flows & Sequence Diagrams

  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

Installation demonstration

Software components

fComponents

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

Gaps(WIP)

ReleaseBlockComponentsIdentified GapsInitial thought

R2
ZTP Cluster-APIThe cluster upgrade yet to be supportThe definition of "cluster upgrade" and expected behaviour should be documented here. For example cluster upgrade could be kubelet version upgrade. 
No node repair mechanismNode logs such kubelet logs should be enable in the automation script
No Multi-Master supportRequired to confirm from engineers
KuD Virtlet , Multus, NFD & IstioInstallation script are in ansible and static. Required to be in daemonset
Virtlet & Intel Device pluginHave to check with Virtlet support with device plugin framework
ONAPOOM automationPortal chart is deployed with loadbalancer with floating IP address
DashboardMonitoring tool to check the deployment across the multi site and show the metrics/statistics details to the operator
R3APP use casesSDWANOpenWRT is potential candidate to configured SDWAN use case. Required more information on it

Roadmap

August Intermediate release

TimelineReleaserequired state of implementationExpected Result
Aug 2nd ICN-v0.1.0
  • ICN Bootloader
  • Metal3 Baremetal operator
  • KUD provisioning
  • ISO bootloader script
  • Installation script for the bootstrap cluster
  • Installation Script for compute cluster with KuD
  • Will be in dev branch
  • If the deadline is missed,  Aug7th is the extended last deadline
Aug 9th ICN-v0.1.1
  • KUD  addon plugin integration
    • Multus
    • NFD
    • SRIOV
    • Virtlet
    • QAT
    • ROOK
  • Initial integration of BPA controller and BPA RestAPI  
  • Testing and integration of KUD plugins
  • Bug fix from the previous release
  • Will be in dev branch
  • If the deadline is missed,  Aug 14th is the extended last deadline
Aug 16thICN-v0.2.0
  • ICN Bootloader
  • Metal3 Baremetal operator
  • KUD provisioning
  • KUD add-plugins
  • BPA controller
  • BPA RestAPI
  • Merged with Master
  • All Integration must be completed by Aug 16th.

Akraino R2 release

Componentsrequired state of implementationExpected Result
ZTP
  • Cluster-API is integrated with Baremetal operator to instantiate 2 cluster #0, #1, #2 & #3
  • Cluster #0 should have at least 3 machine for ONAP
  • Cluster #1 should have at least 5 machine for Edge location
  • Cluster #2 should have at least 2 machine for Edge location
  • Cluster #3 should have at least 1 machine for Edge location
All-in-one ZTP script with cluster-API and Baremetal operator 
ONAP
  • Consolidated OOM Helm chart and script to install ONAP in the cluster#0
  • With ONAP Dashboard
Should be integrated with the above script
KuD addons
  • Rook, Prometheus, SRIOV, QAT, Collectd, OVN, SFC Manager
Daemonset yaml should be integrated with the above script
Tenant Manager
  • Create Tenant and resource quota
should be deployed as part of KuD addons
Dashboard
  • Akraino Dashboard integrated with ONAP monitoring agent
Dashboard run as deployment in ONAP cluster
App
  • Dummy 3 ubuntu instances to recreate SDWAN use case with Multiple networks, QAT, SRIOV and static SFC
Instantiate 3 workloads from ONAP to show the SFC functionality in Dashboard 
CI
  • Integrated and tested with conformance testing
End-to-End testing script

Akraino R3 release

Componentsrequired state of implementationExpected Result
ZTP
  • Integrated with openNESS components and EdgeXFoundry
All-in-one ZTP script with cluster-API and Baremetal operator 
ONAP
  • Consolidated OOM Helm chart and script to install ONAP in the cluster#0
  • R5/R6 ONAP release will have k8s HPA & Multi-site scheduler
Should be integrated with the above script
KuD addons
  • Kata container, KubeVirt, MetallB
Daemonset yaml should be integrated with the above script
Dashboard
  • Akraino Dashboard integrated with ONAP monitoring agent
Dashboard run as deployment in ONAP cluster
App
  • Run vFW, vIPS, vSDWAN with Multiple networks, QAT, SRIOV, IPsec tunnel and dynamic SFC
  • Run the Distributed Analytics as a Service
Instantiate 3 workloads from ONAP to show the SFC functionality in Dashboard 
CI
  • Integrated and tested with conformance testing
End-to-End testing script

Future releases

Yet to discuss