1 .. This work is licensed under a Creative Commons Attribution 4.0 International License.
2 .. http://creativecommons.org/licenses/by/4.0
3 .. Copyright 2018 Amdocs, Bell Canada
6 .. _Helm: https://docs.helm.sh/
7 .. _Helm Charts: https://github.com/kubernetes/charts
8 .. _Kubernetes: https://Kubernetes.io/
9 .. _Docker: https://www.docker.com/
10 .. _Nexus: https://nexus.onap.org/#welcome
11 .. _AWS Elastic Block Store: https://aws.amazon.com/ebs/
12 .. _Azure File: https://docs.microsoft.com/en-us/azure/storage/files/storage-files-introduction
13 .. _GCE Persistent Disk: https://cloud.google.com/compute/docs/disks/
14 .. _Gluster FS: https://www.gluster.org/
15 .. _Kubernetes Storage Class: https://Kubernetes.io/docs/concepts/storage/storage-classes/
16 .. _Assigning Pods to Nodes: https://Kubernetes.io/docs/concepts/configuration/assign-pod-node/
19 .. _developer-guide-label:
24 .. figure:: oomLogoV2-medium.png
27 ONAP consists of a large number of components, each of which are substantial
28 projects within themselves, which results in a high degree of complexity in
29 deployment and management. To cope with this complexity the ONAP Operations
30 Manager (OOM) uses a Helm_ model of ONAP - Helm being the primary management
31 system for Kubernetes_ container systems - to drive all user driven life-cycle
32 management operations. The Helm model of ONAP is composed of a set of
33 hierarchical Helm charts that define the structure of the ONAP components and
34 the configuration of these components. These charts are fully parameterized
35 such that a single environment file defines all of the parameters needed to
36 deploy ONAP. A user of ONAP may maintain several such environment files to
37 control the deployment of ONAP in multiple environments such as development,
38 pre-production, and production.
40 The following sections describe how the ONAP Helm charts are constructed.
49 Linux containers allow for an application and all of its operating system
50 dependencies to be packaged and deployed as a single unit without including a
51 guest operating system as done with virtual machines. The most popular
52 container solution is Docker_ which provides tools for container management
53 like the Docker Host (dockerd) which can create, run, stop, move, or delete a
54 container. Docker has a very popular registry of containers images that can be
55 used by any Docker system; however, in the ONAP context, Docker images are
56 built by the standard CI/CD flow and stored in Nexus_ repositories. OOM uses
57 the "standard" ONAP docker containers and three new ones specifically created
60 Containers are isolated from each other primarily via name spaces within the
61 Linux kernel without the need for multiple guest operating systems. As such,
62 multiple containers can be deployed with little overhead such as all of ONAP
63 can be deployed on a single host. With some optimization of the ONAP components
64 (e.g. elimination of redundant database instances) it may be possible to deploy
65 ONAP on a single laptop computer.
69 A Helm chart is a collection of files that describe a related set of Kubernetes
70 resources. A simple chart might be used to deploy something simple, like a
71 memcached pod, while a complex chart might contain many micro-service arranged
72 in a hierarchy as found in the `aai` ONAP component.
74 Charts are created as files laid out in a particular directory tree, then they
75 can be packaged into versioned archives to be deployed. There is a public
76 archive of `Helm Charts`_ on GitHub that includes many technologies applicable
77 to ONAP. Some of these charts have been used in ONAP and all of the ONAP charts
78 have been created following the guidelines provided.
80 The top level of the ONAP charts is shown below:
84 digraph onap_top_chart {
88 oValues [label="values.yaml"]
89 oChart [label="Chart.yaml"]
90 dev [label="dev.yaml"]
91 prod [label="prod.yaml"]
92 crb [label="clusterrolebindings.yaml"]
93 secrets [label="secrets.yaml"]
97 vCom [label="component"]
105 resources -> environments
112 Within the `values.yaml` file at the `onap` level, one will find a set of
113 boolean values that control which of the ONAP components get deployed as shown
118 aaf: # Application Authorization Framework
121 so: # Service Orchestrator
124 By setting these flags a custom deployment can be created and used during
125 deployment by using the `-f` Helm option as follows::
127 > helm install local/onap -name development -f dev.yaml
129 Note that there are one or more example deployment files in the
130 `onap/resources/environments/` directory. It is best practice to create a unique
131 deployment file for each environment used to ensure consistent behaviour.
133 To aid in the long term supportability of ONAP, a set of common charts have
134 been created (and will be expanded in subsequent releases of ONAP) that can be
135 used by any of the ONAP components by including the common component in its
136 `requirements.yaml` file. The common components are arranged as follows:
140 digraph onap_common_chart {
144 mValues [label="values.yaml"]
145 ccValues [label="values.yaml"]
146 comValues [label="values.yaml"]
147 comChart [label="Chart.yaml"]
148 ccChart [label="Chart.yaml"]
149 mChart [label="Chart.yaml"]
151 mReq [label="requirements.yaml"]
152 mService [label="service.yaml"]
153 mMap [label="configmap.yaml"]
154 ccName [label="_name.tpl"]
155 ccNS [label="_namespace.tpl"]
158 cCom [label="common"]
159 mTemp [label="templates"]
160 ccTemp [label="templates"]
163 more [label="...",style=dashed]
186 The common section of charts consists of a set of templates that assist with
187 parameter substitution (`_name.tpl` and `_namespace.tpl`) and a set of charts
188 for components used throughout ONAP. Initially `mysql` is in the common area but
189 this will expand to include other databases like `mariadb-galera`, `postgres`,
190 and `cassandra`. Other candidates for common components include `redis` and
191 `kafka`. When the common components are used by other charts they are
192 instantiated each time. In subsequent ONAP releases some of the common
193 components could be a setup as services that are used by multiple ONAP
194 components thus minimizing the deployment and operational costs.
196 All of the ONAP components have charts that follow the pattern shown below:
200 digraph onap_component_chart {
204 cValues [label="values.yaml"]
205 cChart [label="Chart.yaml"]
206 cService [label="service.yaml"]
207 cMap [label="configmap.yaml"]
208 cFiles [label="config file(s)"]
211 cCharts [label="charts"]
212 cTemp [label="templates"]
213 cRes [label="resources"]
217 sCom [label="component",style=dashed]
232 Note that the component charts may include a hierarchy of components and in
233 themselves can be quite complex.
235 Configuration of the components varies somewhat from component to component but
236 generally follows the pattern of one or more `configmap.yaml` files which can
237 directly provide configuration to the containers in addition to processing
238 configuration files stored in the `config` directory. It is the responsibility
239 of each ONAP component team to update these configuration files when changes
240 are made to the project containers that impact configuration.
242 The following section describes how the hierarchical ONAP configuration system is
243 key to management of such a large system.
245 Configuration Management
246 ========================
248 ONAP is a large system composed of many components - each of which are complex
249 systems in themselves - that needs to be deployed in a number of different
250 ways. For example, within a single operator's network there may be R&D
251 deployments under active development, pre-production versions undergoing system
252 testing and production systems that are operating live networks. Each of these
253 deployments will differ in significant ways, such as the version of the
254 software images deployed. In addition, there may be a number of application
255 specific configuration differences, such as operating system environment
256 variables. The following describes how the Helm configuration management
257 system is used within the OOM project to manage both ONAP infrastructure
258 configuration as well as ONAP components configuration.
260 One of the artifacts that OOM/Kubernetes uses to deploy ONAP components is the
261 deployment specification, yet another yaml file. Within these deployment specs
262 are a number of parameters as shown in the following mariadb example:
266 apiVersion: extensions/v1beta1
278 image: nexus3.onap.org:10001/mariadb:10.1.11
281 - name: MYSQL_ROOT_PASSWORD
283 - name: MARIADB_MAJOR
287 - name: onap-docker-registry-key
289 Note that within the deployment specification, one of the container arguments
290 is the key/value pair image: nexus3.onap.org:10001/mariadb:10.1.11 which
291 specifies the version of the mariadb software to deploy. Although the
292 deployment specifications greatly simplify deployment, maintenance of the
293 deployment specifications themselves become problematic as software versions
294 change over time or as different versions are required for different
295 deployments. For example, if the R&D team needs to deploy a newer version of
296 mariadb than what is currently used in the production environment, they would
297 need to clone the deployment specification and change this value. Fortunately,
298 this problem has been solved with the templating capabilities of Helm.
300 The following example shows how the deployment specifications are modified to
301 incorporate Helm templates such that key/value pairs can be defined outside of
302 the deployment specifications and passed during instantiation of the component.
306 apiVersion: extensions/v1beta1
310 namespace: "{{ .Values.nsPrefix }}-mso"
319 image: {{ .Values.image.mariadb }}
320 imagePullPolicy: {{ .Values.pullPolicy }}
323 - name: MYSQL_ROOT_PASSWORD
325 - name: MARIADB_MAJOR
329 - name: "{{ .Values.nsPrefix }}-docker-registry-key"apiVersion: extensions/v1beta1
333 namespace: "{{ .Values.nsPrefix }}-mso"
342 image: {{ .Values.image.mariadb }}
343 imagePullPolicy: {{ .Values.pullPolicy }}
346 - name: MYSQL_ROOT_PASSWORD
348 - name: MARIADB_MAJOR
352 - name: "{{ .Values.nsPrefix }}-docker-registry-key"
354 This version of the deployment specification has gone through the process of
355 templating values that are likely to change between deployments. Note that the
356 image is now specified as: image: {{ .Values.image.mariadb }} instead of a
357 string used previously. During the deployment phase, Helm (actually the Helm
358 sub-component Tiller) substitutes the {{ .. }} entries with a variable defined
359 in a values.yaml file. The content of this file is as follows:
364 pullPolicy: IfNotPresent
366 readiness: oomk8s/readiness-check:1.0.0
367 mso: nexus3.onap.org:10001/openecomp/mso:1.0-STAGING-latest
368 mariadb: nexus3.onap.org:10001/mariadb:10.1.11
370 Within the values.yaml file there is an image section with the key/value pair
371 mariadb: nexus3.onap.org:10001/mariadb:10.1.11 which is the same value used in
372 the non-templated version. Once all of the substitutions are complete, the
373 resulting deployment specification ready to be used by Kubernetes.
375 Also note that in this example, the namespace key/value pair is specified in
376 the values.yaml file. This key/value pair will be global across the entire
377 ONAP deployment and is therefore a prime example of where configuration
378 hierarchy can be very useful.
380 When creating a deployment template consider the use of default values if
381 appropriate. Helm templating has built in support for DEFAULT values, here is
387 - name: "{{ .Values.nsPrefix | default "onap" }}-docker-registry-key"
389 The pipeline operator ("|") used here hints at that power of Helm templates in
390 that much like an operating system command line the pipeline operator allow
391 over 60 Helm functions to be embedded directly into the template (note that the
392 Helm template language is a superset of the Go template language). These
393 functions include simple string operations like upper and more complex flow
394 control operations like if/else.
397 ONAP Application Configuration
398 ------------------------------
400 Dependency Management
401 ---------------------
402 These Helm charts describe the desired state
403 of an ONAP deployment and instruct the Kubernetes container manager as to how
404 to maintain the deployment in this state. These dependencies dictate the order
405 in-which the containers are started for the first time such that such
406 dependencies are always met without arbitrary sleep times between container
407 startups. For example, the SDC back-end container requires the Elastic-Search,
408 Cassandra and Kibana containers within SDC to be ready and is also dependent on
409 DMaaP (or the message-router) to be ready - where ready implies the built-in
410 "readiness" probes succeeded - before becoming fully operational. When an
411 initial deployment of ONAP is requested the current state of the system is NULL
412 so ONAP is deployed by the Kubernetes manager as a set of Docker containers on
413 one or more predetermined hosts. The hosts could be physical machines or
414 virtual machines. When deploying on virtual machines the resulting system will
415 be very similar to "Heat" based deployments, i.e. Docker containers running
416 within a set of VMs, the primary difference being that the allocation of
417 containers to VMs is done dynamically with OOM and statically with "Heat".
418 Example SO deployment descriptor file shows SO's dependency on its mariadb
421 SO deployment specification excerpt:
425 apiVersion: extensions/v1beta1
428 name: {{ include "common.name" . }}
429 namespace: {{ include "common.namespace" . }}
431 app: {{ include "common.name" . }}
432 chart: {{ .Chart.Name }}-{{ .Chart.Version | replace "+" "_" }}
433 release: {{ .Release.Name }}
434 heritage: {{ .Release.Service }}
436 replicas: {{ .Values.replicaCount }}
440 app: {{ include "common.name" . }}
441 release: {{ .Release.Name }}
452 Kubernetes Container Orchestration
453 ==================================
454 The ONAP components are managed by the Kubernetes_ container management system
455 which maintains the desired state of the container system as described by one
456 or more deployment descriptors - similar in concept to OpenStack HEAT
457 Orchestration Templates. The following sections describe the fundamental
458 objects managed by Kubernetes, the network these components use to communicate
459 with each other and other entities outside of ONAP and the templates that
460 describe the configuration and desired state of the ONAP components.
464 Within the namespaces are Kubernetes services that provide external connectivity to pods that host Docker containers.
466 ONAP Components to Kubernetes Object Relationships
467 --------------------------------------------------
468 Kubernetes deployments consist of multiple objects:
470 - **nodes** - a worker machine - either physical or virtual - that hosts
471 multiple containers managed by Kubernetes.
472 - **services** - an abstraction of a logical set of pods that provide a
474 - **pods** - one or more (but typically one) container(s) that provide specific
475 application functionality.
476 - **persistent volumes** - One or more permanent volumes need to be established
477 to hold non-ephemeral configuration and state data.
479 The relationship between these objects is shown in the following figure:
485 .. component Service {
494 .. figure:: kubernetes_objects.png
496 OOM uses these Kubernetes objects as described in the following sections.
500 OOM works with both physical and virtual worker machines.
502 * Virtual Machine Deployments - If ONAP is to be deployed onto a set of virtual
503 machines, the creation of the VMs is outside of the scope of OOM and could be
504 done in many ways, such as
506 * manually, for example by a user using the OpenStack Horizon dashboard or
508 * automatically, for example with the use of a OpenStack Heat Orchestration
509 Template which builds an ONAP stack, Azure ARM template, AWS CloudFormation
511 * orchestrated, for example with Cloudify creating the VMs from a TOSCA
512 template and controlling their life cycle for the life of the ONAP
515 * Physical Machine Deployments - If ONAP is to be deployed onto physical
516 machines there are several options but the recommendation is to use Rancher
517 along with Helm to associate hosts with a Kubernetes cluster.
521 A group of containers with shared storage and networking can be grouped
522 together into a Kubernetes pod. All of the containers within a pod are
523 co-located and co-scheduled so they operate as a single unit. Within ONAP
524 Amsterdam release, pods are mapped one-to-one to docker containers although
525 this may change in the future. As explained in the Services section below the
526 use of Pods within each ONAP component is abstracted from other ONAP
531 OOM uses the Kubernetes service abstraction to provide a consistent access
532 point for each of the ONAP components independent of the pod or container
533 architecture of that component. For example, the SDNC component may introduce
534 OpenDaylight clustering as some point and change the number of pods in this
535 component to three or more but this change will be isolated from the other ONAP
536 components by the service abstraction. A service can include a load balancer
537 on its ingress to distribute traffic between the pods and even react to dynamic
538 changes in the number of pods if they are part of a replica set.
542 To enable ONAP to be deployed into a wide variety of cloud infrastructures a
543 flexible persistent storage architecture, built on Kubernetes persistent
544 volumes, provides the ability to define the physical storage in a central
545 location and have all ONAP components securely store their data.
547 When deploying ONAP into a public cloud, available storage services such as
548 `AWS Elastic Block Store`_, `Azure File`_, or `GCE Persistent Disk`_ are
549 options. Alternatively, when deploying into a private cloud the storage
550 architecture might consist of Fiber Channel, `Gluster FS`_, or iSCSI. Many
551 other storage options existing, refer to the `Kubernetes Storage Class`_
552 documentation for a full list of the options. The storage architecture may vary
553 from deployment to deployment but in all cases a reliable, redundant storage
554 system must be provided to ONAP with which the state information of all ONAP
555 components will be securely stored. The Storage Class for a given deployment is
556 a single parameter listed in the ONAP values.yaml file and therefore is easily
557 customized. Operation of this storage system is outside the scope of the OOM.
561 Insert values.yaml code block with storage block here
563 Once the storage class is selected and the physical storage is provided, the
564 ONAP deployment step creates a pool of persistent volumes within the given
565 physical storage that is used by all of the ONAP components. ONAP components
566 simply make a claim on these persistent volumes (PV), with a persistent volume
567 claim (PVC), to gain access to their storage.
569 The following figure illustrates the relationships between the persistent
570 volume claims, the persistent volumes, the storage class, and the physical
576 label = "Persistance Volume Claim to Physical Storage Mapping"
578 node [shape=cylinder]
584 node [shape=Mrecord label="StorageClass:ceph"]
592 subgraph clusterSDC {
597 subgraph clusterSDNC {
616 # force all of these nodes to the same line in the given order
618 rank = same; PV0;PV1;PV2;PVn;p0;p1;p2
619 PV0->PV1->PV2->p0->p1->p2->PVn [style=invis]
623 rank = same; D0;D1;Dx;p3;p4;p5
624 D0->D1->p3->p4->p5->Dx [style=invis]
629 In-order for an ONAP component to use a persistent volume it must make a claim
630 against a specific persistent volume defined in the ONAP common charts. Note
631 that there is a one-to-one relationship between a PVC and PV. The following is
632 an excerpt from a component chart that defines a PVC:
636 Insert PVC example here
638 OOM Networking with Kubernetes
639 ------------------------------
642 - Ports - Flattening the containers also expose port conflicts between the containers which need to be resolved.
649 OOM will use the rich set of Kubernetes node and pod affinity /
650 anti-affinity rules to minimize the chance of a single failure resulting in a
651 loss of ONAP service. Node affinity / anti-affinity is used to guide the
652 Kubernetes orchestrator in the placement of pods on nodes (physical or virtual
653 machines). For example:
655 - if a container used Intel DPDK technology the pod may state that it as
656 affinity to an Intel processor based node, or
657 - geographical based node labels (such as the Kubernetes standard zone or
658 region labels) may be used to ensure placement of a DCAE complex close to the
659 VNFs generating high volumes of traffic thus minimizing networking cost.
660 Specifically, if nodes were pre-assigned labels East and West, the pod
661 deployment spec to distribute pods to these nodes would be:
666 failure-domain.beta.Kubernetes.io/region: {{ .Values.location }}
668 - "location: West" is specified in the `values.yaml` file used to deploy
669 one DCAE cluster and "location: East" is specified in a second `values.yaml`
670 file (see OOM Configuration Management for more information about
671 configuration files like the `values.yaml` file).
673 Node affinity can also be used to achieve geographic redundancy if pods are
674 assigned to multiple failure domains. For more information refer to `Assigning
678 One could use Pod to Node assignment to totally constrain Kubernetes when
679 doing initial container assignment to replicate the Amsterdam release
680 OpenStack Heat based deployment. Should one wish to do this, each VM would
681 need a unique node name which would be used to specify a node constaint
682 for every component. These assignment could be specified in an environment
683 specific values.yaml file. Constraining Kubernetes in this way is not
686 Kubernetes has a comprehensive system called Taints and Tolerations that can be
687 used to force the container orchestrator to repel pods from nodes based on
688 static events (an administrator assigning a taint to a node) or dynamic events
689 (such as a node becoming unreachable or running out of disk space). There are
690 no plans to use taints or tolerations in the ONAP Beijing release. Pod
691 affinity / anti-affinity is the concept of creating a spacial relationship
692 between pods when the Kubernetes orchestrator does assignment (both initially
693 an in operation) to nodes as explained in Inter-pod affinity and anti-affinity.
694 For example, one might choose to co-located all of the ONAP SDC containers on a
695 single node as they are not critical runtime components and co-location
696 minimizes overhead. On the other hand, one might choose to ensure that all of
697 the containers in an ODL cluster (SDNC and APPC) are placed on separate nodes
698 such that a node failure has minimal impact to the operation of the cluster.
699 An example of how pod affinity / anti-affinity is shown below:
701 Pod Affinity / Anti-Affinity
708 name: with-pod-affinity
712 requiredDuringSchedulingIgnoredDuringExecution:
719 topologyKey: failure-domain.beta.Kubernetes.io/zone
721 preferredDuringSchedulingIgnoredDuringExecution:
730 topologyKey: Kubernetes.io/hostname
732 - name: with-pod-affinity
733 image: gcr.io/google_containers/pause:2.0
735 This example contains both podAffinity and podAntiAffinity rules, the first
736 rule is is a must (requiredDuringSchedulingIgnoredDuringExecution) while the
737 second will be met pending other considerations
738 (preferredDuringSchedulingIgnoredDuringExecution). Preemption Another feature
739 that may assist in achieving a repeatable deployment in the presence of faults
740 that may have reduced the capacity of the cloud is assigning priority to the
741 containers such that mission critical components have the ability to evict less
742 critical components. Kubernetes provides this capability with Pod Priority and
743 Preemption. Prior to having more advanced production grade features available,
744 the ability to at least be able to re-deploy ONAP (or a subset of) reliably
745 provides a level of confidence that should an outage occur the system can be
746 brought back on-line predictably.
751 Monitoring of ONAP components is configured in the agents within JSON files and
752 stored in gerrit under the consul-agent-config, here is an example from the AAI
753 model loader (aai-model-loader-health.json):
759 "name": "A&AI Model Loader",
762 "id": "model-loader-process",
763 "name": "Model Loader Presence",
764 "script": "/consul/config/scripts/model-loader-script.sh",
775 These liveness probes can simply check that a port is available, that a
776 built-in health check is reporting good health, or that the Consul health check
777 is positive. For example, to monitor the SDNC component has following liveness
778 probe can be found in the SDNC DB deployment specification:
782 sdnc db liveness probe
786 command: ["mysqladmin", "ping"]
787 initialDelaySeconds: 30 periodSeconds: 10
790 The 'initialDelaySeconds' control the period of time between the readiness
791 probe succeeding and the liveness probe starting. 'periodSeconds' and
792 'timeoutSeconds' control the actual operation of the probe. Note that
793 containers are inherently ephemeral so the healing action destroys failed
794 containers and any state information within it. To avoid a loss of state, a
795 persistent volume should be used to store all data that needs to be persisted
796 over the re-creation of a container. Persistent volumes have been created for
797 the database components of each of the projects and the same technique can be
798 used for all persistent state information.
808 The \ `Microservices Bus
809 Project <https://wiki.onap.org/pages/viewpage.action?pageId=3246982>`__ provides
810 facilities to integrate micro-services into ONAP and therefore needs to
811 integrate into OOM - primarily through Consul which is the backend of
812 MSB service discovery. The following is a brief description of how this
813 integration will be done:
815 A registrator to push the service endpoint info to MSB service
818 - The needed service endpoint info is put into the kubernetes yaml file
819 as annotation, including service name, Protocol,version, visual
820 range,LB method, IP, Port,etc.
822 - OOM deploy/start/restart/scale in/scale out/upgrade ONAP components
824 - Registrator watch the kubernetes event
826 - When an ONAP component instance has been started/destroyed by OOM,
827 Registrator get the notification from kubernetes
829 - Registrator parse the service endpoint info from annotation and
830 register/update/unregister it to MSB service discovery
832 - MSB API Gateway uses the service endpoint info for service routing
835 Details of the registration service API can be found at \ `Microservice
837 Documentation <https://wiki.onap.org/display/DW/Microservice+Bus+API+Documentation>`__.
839 ONAP Component Registration to MSB
840 ----------------------------------
841 The charts of all ONAP components intending to register against MSB must have
842 an annotation in their service(s) template. A `sdc` example follows:
852 namespace: "{{ .Values.nsPrefix }}"
854 msb.onap.org/service-info: '[
856 "serviceName": "sdc",
864 "serviceName": "sdc-deprecated",
876 MSB Integration with OOM
877 ------------------------
878 A preliminary view of the OOM-MSB integration is as follows:
880 .. figure:: MSB-OOM-Diagram.png
882 A message sequence chart of the registration process:
886 participant "OOM" as oom
887 participant "ONAP Component" as onap
888 participant "Service Discovery" as sd
889 participant "External API Gateway" as eagw
890 participant "Router (Internal API Gateway)" as iagw
901 oom -> sd: Register service endpoints
902 sd -> eagw: Services exposed to external system
903 sd -> iagw: Services for internal use
905 == Component Life-cycle Management ==
907 oom -> onap: Start/Stop/Scale/Migrate/Upgrade
908 oom -> sd: Update service info
909 sd -> eagw: Update service info
910 sd -> iagw: Update service info
912 == Service Health Check ==
914 sd -> onap: Check the health of service
915 sd -> eagw: Update service status
916 sd -> iagw: Update service status
919 MSB Deployment Instructions
920 ---------------------------
921 MSB is helm installable ONAP component which is often automatically deployed.
922 To install it individually enter::
924 > helm install <repo-name>/msb
927 TBD: Vaidate if the following procedure is still required.
929 Please note that Kubernetes authentication token must be set at
930 *kubernetes/kube2msb/values.yaml* so the kube2msb registrator can get the
931 access to watch the kubernetes events and get service annotation by
932 Kubernetes APIs. The token can be found in the kubectl configuration file
935 More details can be found here `MSB installation <http://onap.readthedocs.io/en/latest/submodules/msb/apigateway.git/docs/platform/installation.html>`__.
939 .. Note that although OOM uses Kubernetes facilities to minimize the effort
940 .. required of the ONAP component owners to implement a successful rolling upgrade
941 .. strategy there are other considerations that must be taken into consideration.
942 .. For example, external APIs - both internal and external to ONAP - should be
943 .. designed to gracefully accept transactions from a peer at a different software
944 .. version to avoid deadlock situations. Embedded version codes in messages may
945 .. facilitate such capabilities.
947 .. Within each of the projects a new configuration repository contains all of the
948 .. project specific configuration artifacts. As changes are made within the
949 .. project, it's the responsibility of the project team to make appropriate
950 .. changes to the configuration data.