1 .. This work is licensed under a Creative Commons Attribution 4.0
2 .. International License.
3 .. http://creativecommons.org/licenses/by/4.0
4 .. Copyright 2018-2020 Amdocs, Bell Canada, Orange, Samsung
7 .. _Helm: https://docs.helm.sh/
8 .. _Helm Charts: https://github.com/kubernetes/charts
9 .. _Kubernetes: https://Kubernetes.io/
10 .. _Docker: https://www.docker.com/
11 .. _Nexus: https://nexus.onap.org/
12 .. _AWS Elastic Block Store: https://aws.amazon.com/ebs/
13 .. _Azure File: https://docs.microsoft.com/en-us/azure/storage/files/storage-files-introduction
14 .. _GCE Persistent Disk: https://cloud.google.com/compute/docs/disks/
15 .. _Gluster FS: https://www.gluster.org/
16 .. _Kubernetes Storage Class: https://Kubernetes.io/docs/concepts/storage/storage-classes/
17 .. _Assigning Pods to Nodes: https://Kubernetes.io/docs/concepts/configuration/assign-pod-node/
20 .. _developer-guide-label:
25 .. figure:: oomLogoV2-medium.png
28 ONAP consists of a large number of components, each of which are substantial
29 projects within themselves, which results in a high degree of complexity in
30 deployment and management. To cope with this complexity the ONAP Operations
31 Manager (OOM) uses a Helm_ model of ONAP - Helm being the primary management
32 system for Kubernetes_ container systems - to drive all user driven life-cycle
33 management operations. The Helm model of ONAP is composed of a set of
34 hierarchical Helm charts that define the structure of the ONAP components and
35 the configuration of these components. These charts are fully parameterized
36 such that a single environment file defines all of the parameters needed to
37 deploy ONAP. A user of ONAP may maintain several such environment files to
38 control the deployment of ONAP in multiple environments such as development,
39 pre-production, and production.
41 The following sections describe how the ONAP Helm charts are constructed.
50 Linux containers allow for an application and all of its operating system
51 dependencies to be packaged and deployed as a single unit without including a
52 guest operating system as done with virtual machines. The most popular
53 container solution is Docker_ which provides tools for container management
54 like the Docker Host (dockerd) which can create, run, stop, move, or delete a
55 container. Docker has a very popular registry of containers images that can be
56 used by any Docker system; however, in the ONAP context, Docker images are
57 built by the standard CI/CD flow and stored in Nexus_ repositories. OOM uses
58 the "standard" ONAP docker containers and three new ones specifically created
61 Containers are isolated from each other primarily via name spaces within the
62 Linux kernel without the need for multiple guest operating systems. As such,
63 multiple containers can be deployed with little overhead such as all of ONAP
64 can be deployed on a single host. With some optimization of the ONAP components
65 (e.g. elimination of redundant database instances) it may be possible to deploy
66 ONAP on a single laptop computer.
70 A Helm chart is a collection of files that describe a related set of Kubernetes
71 resources. A simple chart might be used to deploy something simple, like a
72 memcached pod, while a complex chart might contain many micro-service arranged
73 in a hierarchy as found in the `aai` ONAP component.
75 Charts are created as files laid out in a particular directory tree, then they
76 can be packaged into versioned archives to be deployed. There is a public
77 archive of `Helm Charts`_ on GitHub that includes many technologies applicable
78 to ONAP. Some of these charts have been used in ONAP and all of the ONAP charts
79 have been created following the guidelines provided.
81 The top level of the ONAP charts is shown below:
90 │ │ │ └── docker-entrypoint.sh
95 │ │ │ ├── configmap.yaml
96 │ │ │ ├── cronjob.yaml
99 │ │ ├── configmap.yaml
102 │ │ └── statefulset.yaml
107 │ │ ├── _createPassword.tpl
112 │ │ ├── _namespace.tpl
113 │ │ ├── _repository.tpl
114 │ │ ├── _resources.tpl
118 │ │ └── _tplValue.tpl
126 The common section of charts consists of a set of templates that assist with
127 parameter substitution (`_name.tpl`, `_namespace.tpl` and others) and a set of
128 charts for components used throughout ONAP. When the common components are used
129 by other charts they are instantiated each time or we can deploy a shared
130 instances for several components.
132 All of the ONAP components have charts that follow the pattern shown below:
139 │ └── subcomponent-folder
141 │ └── subchart-folder
153 │ ├── deployment.yaml
160 Note that the component charts / components may include a hierarchy of sub
161 components and in themselves can be quite complex.
163 You can use either `charts` or `components` folder for your subcomponents.
164 `charts` folder means that the subcomponent will always been deployed.
166 `components` folders means we can choose if we want to deploy the
169 This choice is done in root `values.yaml`:
182 Then in `Chart.yaml` dependencies section, you'll use these values:
193 repository: 'file://components/component1'
194 condition: component1.enabled
197 repository: 'file://components/component2'
198 condition: component2.enabled
200 Configuration of the components varies somewhat from component to component but
201 generally follows the pattern of one or more `configmap.yaml` files which can
202 directly provide configuration to the containers in addition to processing
203 configuration files stored in the `config` directory. It is the responsibility
204 of each ONAP component team to update these configuration files when changes
205 are made to the project containers that impact configuration.
207 The following section describes how the hierarchical ONAP configuration system
208 is key to management of such a large system.
210 Configuration Management
211 ========================
213 ONAP is a large system composed of many components - each of which are complex
214 systems in themselves - that needs to be deployed in a number of different
215 ways. For example, within a single operator's network there may be R&D
216 deployments under active development, pre-production versions undergoing system
217 testing and production systems that are operating live networks. Each of these
218 deployments will differ in significant ways, such as the version of the
219 software images deployed. In addition, there may be a number of application
220 specific configuration differences, such as operating system environment
221 variables. The following describes how the Helm configuration management
222 system is used within the OOM project to manage both ONAP infrastructure
223 configuration as well as ONAP components configuration.
225 One of the artifacts that OOM/Kubernetes uses to deploy ONAP components is the
226 deployment specification, yet another yaml file. Within these deployment specs
227 are a number of parameters as shown in the following example:
235 app.kubernetes.io/name: zookeeper
236 helm.sh/chart: zookeeper
237 app.kubernetes.io/component: server
238 app.kubernetes.io/managed-by: Tiller
239 app.kubernetes.io/instance: onap-oof
240 name: onap-oof-zookeeper
247 app.kubernetes.io/name: zookeeper
248 app.kubernetes.io/component: server
249 app.kubernetes.io/instance: onap-oof
250 serviceName: onap-oof-zookeeper-headless
254 app.kubernetes.io/name: zookeeper
255 helm.sh/chart: zookeeper
256 app.kubernetes.io/component: server
257 app.kubernetes.io/managed-by: Tiller
258 app.kubernetes.io/instance: onap-oof
265 image: gcr.io/google_samples/k8szk:v3
266 imagePullPolicy: Always
269 - containerPort: 2181
272 - containerPort: 3888
275 - containerPort: 2888
280 Note that within the statefulset specification, one of the container arguments
281 is the key/value pair image: gcr.io/google_samples/k8szk:v3 which
282 specifies the version of the zookeeper software to deploy. Although the
283 statefulset specifications greatly simplify statefulset, maintenance of the
284 statefulset specifications themselves become problematic as software versions
285 change over time or as different versions are required for different
286 statefulsets. For example, if the R&D team needs to deploy a newer version of
287 mariadb than what is currently used in the production environment, they would
288 need to clone the statefulset specification and change this value. Fortunately,
289 this problem has been solved with the templating capabilities of Helm.
291 The following example shows how the statefulset specifications are modified to
292 incorporate Helm templates such that key/value pairs can be defined outside of
293 the statefulset specifications and passed during instantiation of the component.
300 name: {{ include "common.fullname" . }}
301 namespace: {{ include "common.namespace" . }}
302 labels: {{- include "common.labels" . | nindent 4 }}
304 replicas: {{ .Values.replicaCount }}
306 matchLabels: {{- include "common.matchLabels" . | nindent 6 }}
307 # serviceName is only needed for StatefulSet
308 # put the postfix part only if you have add a postfix on the service name
309 serviceName: {{ include "common.servicename" . }}-{{ .Values.service.postfix }}
313 labels: {{- include "common.labels" . | nindent 8 }}
314 annotations: {{- include "common.tplValue" (dict "value" .Values.podAnnotations "context" $) | nindent 8 }}
315 name: {{ include "common.name" . }}
319 - name: {{ include "common.name" . }}
320 image: {{ .Values.image }}
321 imagePullPolicy: {{ .Values.global.pullPolicy | default .Values.pullPolicy }}
323 {{- range $index, $port := .Values.service.ports }}
324 - containerPort: {{ $port.port }}
325 name: {{ $port.name }}
327 {{- range $index, $port := .Values.service.headlessPorts }}
328 - containerPort: {{ $port.port }}
329 name: {{ $port.name }}
333 This version of the statefulset specification has gone through the process of
334 templating values that are likely to change between statefulsets. Note that the
335 image is now specified as: image: {{ .Values.image }} instead of a
336 string used previously. During the statefulset phase, Helm (actually the Helm
337 sub-component Tiller) substitutes the {{ .. }} entries with a variable defined
338 in a values.yaml file. The content of this file is as follows:
343 image: gcr.io/google_samples/k8szk:v3
348 Within the values.yaml file there is an image key with the value
349 `gcr.io/google_samples/k8szk:v3` which is the same value used in
350 the non-templated version. Once all of the substitutions are complete, the
351 resulting statefulset specification ready to be used by Kubernetes.
353 When creating a template consider the use of default values if appropriate.
354 Helm templating has built in support for DEFAULT values, here is
360 - name: "{{ .Values.nsPrefix | default "onap" }}-docker-registry-key"
362 The pipeline operator ("|") used here hints at that power of Helm templates in
363 that much like an operating system command line the pipeline operator allow
364 over 60 Helm functions to be embedded directly into the template (note that the
365 Helm template language is a superset of the Go template language). These
366 functions include simple string operations like upper and more complex flow
367 control operations like if/else.
369 OOM is mainly helm templating. In order to have consistent deployment of the
370 different components of ONAP, some rules must be followed.
372 Templates are provided in order to create Kubernetes resources (Secrets,
373 Ingress, Services, ...) or part of Kubernetes resources (names, labels,
374 resources requests and limits, ...).
376 a full list and simple description is done in
377 `kubernetes/common/common/documentation.rst`.
382 In order to create a Service for a component, you have to create a file (with
383 `service` in the name.
384 For normal service, just put the following line:
388 {{ include "common.service" . }}
390 For headless service, the line to put is the following:
394 {{ include "common.headlessService" . }}
396 The configuration of the service is done in component `values.yaml`:
401 name: NAME-OF-THE-SERVICE
405 someAnnotationsKey: value
417 `annotations` and `postfix` keys are optional.
418 if `service.type` is `NodePort`, then you have to give `nodePort` value for your
419 service ports (which is the end of the computed nodePort, see example).
421 It would render the following Service Resource (for a component named
422 `name-of-my-component`, with version `x.y.z`, helm deployment name
423 `my-deployment` and `global.nodePortPrefix` `302`):
431 someAnnotationsKey: value
432 name: NAME-OF-THE-SERVICE-MY-POSTFIX
434 app.kubernetes.io/name: name-of-my-component
435 helm.sh/chart: name-of-my-component-x.y.z
436 app.kubernetes.io/instance: my-deployment-name-of-my-component
437 app.kubernetes.io/managed-by: Tiller
441 targetPort: tcp-MyPort
447 targetPort: https-api
450 app.kubernetes.io/name: name-of-my-component
451 app.kubernetes.io/instance: my-deployment-name-of-my-component
454 In the deployment or statefulSet file, you needs to set the good labels in
455 order for the service to match the pods.
457 here's an example to be sure it matches (for a statefulSet):
464 name: {{ include "common.fullname" . }}
465 namespace: {{ include "common.namespace" . }}
466 labels: {{- include "common.labels" . | nindent 4 }}
469 matchLabels: {{- include "common.matchLabels" . | nindent 6 }}
470 # serviceName is only needed for StatefulSet
471 # put the postfix part only if you have add a postfix on the service name
472 serviceName: {{ include "common.servicename" . }}-{{ .Values.service.postfix }}
476 labels: {{- include "common.labels" . | nindent 8 }}
477 annotations: {{- include "common.tplValue" (dict "value" .Values.podAnnotations "context" $) | nindent 8 }}
478 name: {{ include "common.name" . }}
482 - name: {{ include "common.name" . }}
484 {{- range $index, $port := .Values.service.ports }}
485 - containerPort: {{ $port.port }}
486 name: {{ $port.name }}
488 {{- range $index, $port := .Values.service.headlessPorts }}
489 - containerPort: {{ $port.port }}
490 name: {{ $port.name }}
494 The configuration of the service is done in component `values.yaml`:
499 name: NAME-OF-THE-SERVICE
503 anotherAnnotationsKey : value
504 publishNotReadyAddresses: true
513 `headless.annotations`, `headless.postfix` and
514 `headless.publishNotReadyAddresses` keys are optional.
516 If `headless.postfix` is not set, then we'll add `-headless` at the end of the
519 If it set to `NONE`, there will be not postfix.
521 And if set to something, it will add `-something` at the end of the service
524 It would render the following Service Resource (for a component named
525 `name-of-my-component`, with version `x.y.z`, helm deployment name
526 `my-deployment` and `global.nodePortPrefix` `302`):
534 anotherAnnotationsKey: value
535 name: NAME-OF-THE-SERVICE
537 app.kubernetes.io/name: name-of-my-component
538 helm.sh/chart: name-of-my-component-x.y.z
539 app.kubernetes.io/instance: my-deployment-name-of-my-component
540 app.kubernetes.io/managed-by: Tiller
545 targetPort: tcp-MyPort
551 targetPort: https-api
553 publishNotReadyAddresses: true
555 app.kubernetes.io/name: name-of-my-component
556 app.kubernetes.io/instance: my-deployment-name-of-my-component
559 Previous example of StatefulSet would also match (except for the `postfix` part
562 Creating Deployment or StatefulSet
563 ----------------------------------
565 Deployment and StatefulSet should use the `apps/v1` (which has appeared in
567 As seen on the service part, the following parts are mandatory:
574 name: {{ include "common.fullname" . }}
575 namespace: {{ include "common.namespace" . }}
576 labels: {{- include "common.labels" . | nindent 4 }}
579 matchLabels: {{- include "common.matchLabels" . | nindent 6 }}
580 # serviceName is only needed for StatefulSet
581 # put the postfix part only if you have add a postfix on the service name
582 serviceName: {{ include "common.servicename" . }}-{{ .Values.service.postfix }}
586 labels: {{- include "common.labels" . | nindent 8 }}
587 annotations: {{- include "common.tplValue" (dict "value" .Values.podAnnotations "context" $) | nindent 8 }}
588 name: {{ include "common.name" . }}
592 - name: {{ include "common.name" . }}
594 ONAP Application Configuration
595 ------------------------------
597 Dependency Management
598 ---------------------
599 These Helm charts describe the desired state
600 of an ONAP deployment and instruct the Kubernetes container manager as to how
601 to maintain the deployment in this state. These dependencies dictate the order
602 in-which the containers are started for the first time such that such
603 dependencies are always met without arbitrary sleep times between container
604 startups. For example, the SDC back-end container requires the Elastic-Search,
605 Cassandra and Kibana containers within SDC to be ready and is also dependent on
606 DMaaP (or the message-router) to be ready - where ready implies the built-in
607 "readiness" probes succeeded - before becoming fully operational. When an
608 initial deployment of ONAP is requested the current state of the system is NULL
609 so ONAP is deployed by the Kubernetes manager as a set of Docker containers on
610 one or more predetermined hosts. The hosts could be physical machines or
611 virtual machines. When deploying on virtual machines the resulting system will
612 be very similar to "Heat" based deployments, i.e. Docker containers running
613 within a set of VMs, the primary difference being that the allocation of
614 containers to VMs is done dynamically with OOM and statically with "Heat".
615 Example SO deployment descriptor file shows SO's dependency on its mariadb
618 SO deployment specification excerpt:
625 name: {{ include "common.fullname" . }}
626 namespace: {{ include "common.namespace" . }}
627 labels: {{- include "common.labels" . | nindent 4 }}
629 replicas: {{ .Values.replicaCount }}
631 matchLabels: {{- include "common.matchLabels" . | nindent 6 }}
635 app: {{ include "common.name" . }}
636 release: {{ .Release.Name }}
647 Kubernetes Container Orchestration
648 ==================================
649 The ONAP components are managed by the Kubernetes_ container management system
650 which maintains the desired state of the container system as described by one
651 or more deployment descriptors - similar in concept to OpenStack HEAT
652 Orchestration Templates. The following sections describe the fundamental
653 objects managed by Kubernetes, the network these components use to communicate
654 with each other and other entities outside of ONAP and the templates that
655 describe the configuration and desired state of the ONAP components.
659 Within the namespaces are Kubernetes services that provide external
660 connectivity to pods that host Docker containers.
662 ONAP Components to Kubernetes Object Relationships
663 --------------------------------------------------
664 Kubernetes deployments consist of multiple objects:
666 - **nodes** - a worker machine - either physical or virtual - that hosts
667 multiple containers managed by Kubernetes.
668 - **services** - an abstraction of a logical set of pods that provide a
670 - **pods** - one or more (but typically one) container(s) that provide specific
671 application functionality.
672 - **persistent volumes** - One or more permanent volumes need to be established
673 to hold non-ephemeral configuration and state data.
675 The relationship between these objects is shown in the following figure:
681 .. component Service {
690 .. figure:: kubernetes_objects.png
692 OOM uses these Kubernetes objects as described in the following sections.
696 OOM works with both physical and virtual worker machines.
698 * Virtual Machine Deployments - If ONAP is to be deployed onto a set of virtual
699 machines, the creation of the VMs is outside of the scope of OOM and could be
700 done in many ways, such as
702 * manually, for example by a user using the OpenStack Horizon dashboard or
704 * automatically, for example with the use of a OpenStack Heat Orchestration
705 Template which builds an ONAP stack, Azure ARM template, AWS CloudFormation
707 * orchestrated, for example with Cloudify creating the VMs from a TOSCA
708 template and controlling their life cycle for the life of the ONAP
711 * Physical Machine Deployments - If ONAP is to be deployed onto physical
712 machines there are several options but the recommendation is to use Rancher
713 along with Helm to associate hosts with a Kubernetes cluster.
717 A group of containers with shared storage and networking can be grouped
718 together into a Kubernetes pod. All of the containers within a pod are
719 co-located and co-scheduled so they operate as a single unit. Within ONAP
720 Amsterdam release, pods are mapped one-to-one to docker containers although
721 this may change in the future. As explained in the Services section below the
722 use of Pods within each ONAP component is abstracted from other ONAP
727 OOM uses the Kubernetes service abstraction to provide a consistent access
728 point for each of the ONAP components independent of the pod or container
729 architecture of that component. For example, the SDNC component may introduce
730 OpenDaylight clustering as some point and change the number of pods in this
731 component to three or more but this change will be isolated from the other ONAP
732 components by the service abstraction. A service can include a load balancer
733 on its ingress to distribute traffic between the pods and even react to dynamic
734 changes in the number of pods if they are part of a replica set.
738 To enable ONAP to be deployed into a wide variety of cloud infrastructures a
739 flexible persistent storage architecture, built on Kubernetes persistent
740 volumes, provides the ability to define the physical storage in a central
741 location and have all ONAP components securely store their data.
743 When deploying ONAP into a public cloud, available storage services such as
744 `AWS Elastic Block Store`_, `Azure File`_, or `GCE Persistent Disk`_ are
745 options. Alternatively, when deploying into a private cloud the storage
746 architecture might consist of Fiber Channel, `Gluster FS`_, or iSCSI. Many
747 other storage options existing, refer to the `Kubernetes Storage Class`_
748 documentation for a full list of the options. The storage architecture may vary
749 from deployment to deployment but in all cases a reliable, redundant storage
750 system must be provided to ONAP with which the state information of all ONAP
751 components will be securely stored. The Storage Class for a given deployment is
752 a single parameter listed in the ONAP values.yaml file and therefore is easily
753 customized. Operation of this storage system is outside the scope of the OOM.
757 Insert values.yaml code block with storage block here
759 Once the storage class is selected and the physical storage is provided, the
760 ONAP deployment step creates a pool of persistent volumes within the given
761 physical storage that is used by all of the ONAP components. ONAP components
762 simply make a claim on these persistent volumes (PV), with a persistent volume
763 claim (PVC), to gain access to their storage.
765 The following figure illustrates the relationships between the persistent
766 volume claims, the persistent volumes, the storage class, and the physical
772 label = "Persistance Volume Claim to Physical Storage Mapping"
774 node [shape=cylinder]
780 node [shape=Mrecord label="StorageClass:ceph"]
788 subgraph clusterSDC {
793 subgraph clusterSDNC {
812 # force all of these nodes to the same line in the given order
814 rank = same; PV0;PV1;PV2;PVn;p0;p1;p2
815 PV0->PV1->PV2->p0->p1->p2->PVn [style=invis]
819 rank = same; D0;D1;Dx;p3;p4;p5
820 D0->D1->p3->p4->p5->Dx [style=invis]
825 In-order for an ONAP component to use a persistent volume it must make a claim
826 against a specific persistent volume defined in the ONAP common charts. Note
827 that there is a one-to-one relationship between a PVC and PV. The following is
828 an excerpt from a component chart that defines a PVC:
832 Insert PVC example here
834 OOM Networking with Kubernetes
835 ------------------------------
838 - Ports - Flattening the containers also expose port conflicts between the
839 containers which need to be resolved.
846 OOM will use the rich set of Kubernetes node and pod affinity /
847 anti-affinity rules to minimize the chance of a single failure resulting in a
848 loss of ONAP service. Node affinity / anti-affinity is used to guide the
849 Kubernetes orchestrator in the placement of pods on nodes (physical or virtual
850 machines). For example:
852 - if a container used Intel DPDK technology the pod may state that it as
853 affinity to an Intel processor based node, or
854 - geographical based node labels (such as the Kubernetes standard zone or
855 region labels) may be used to ensure placement of a DCAE complex close to the
856 VNFs generating high volumes of traffic thus minimizing networking cost.
857 Specifically, if nodes were pre-assigned labels East and West, the pod
858 deployment spec to distribute pods to these nodes would be:
863 failure-domain.beta.Kubernetes.io/region: {{ .Values.location }}
865 - "location: West" is specified in the `values.yaml` file used to deploy
866 one DCAE cluster and "location: East" is specified in a second `values.yaml`
867 file (see OOM Configuration Management for more information about
868 configuration files like the `values.yaml` file).
870 Node affinity can also be used to achieve geographic redundancy if pods are
871 assigned to multiple failure domains. For more information refer to `Assigning
875 One could use Pod to Node assignment to totally constrain Kubernetes when
876 doing initial container assignment to replicate the Amsterdam release
877 OpenStack Heat based deployment. Should one wish to do this, each VM would
878 need a unique node name which would be used to specify a node constaint
879 for every component. These assignment could be specified in an environment
880 specific values.yaml file. Constraining Kubernetes in this way is not
883 Kubernetes has a comprehensive system called Taints and Tolerations that can be
884 used to force the container orchestrator to repel pods from nodes based on
885 static events (an administrator assigning a taint to a node) or dynamic events
886 (such as a node becoming unreachable or running out of disk space). There are
887 no plans to use taints or tolerations in the ONAP Beijing release. Pod
888 affinity / anti-affinity is the concept of creating a spacial relationship
889 between pods when the Kubernetes orchestrator does assignment (both initially
890 an in operation) to nodes as explained in Inter-pod affinity and anti-affinity.
891 For example, one might choose to co-located all of the ONAP SDC containers on a
892 single node as they are not critical runtime components and co-location
893 minimizes overhead. On the other hand, one might choose to ensure that all of
894 the containers in an ODL cluster (SDNC and APPC) are placed on separate nodes
895 such that a node failure has minimal impact to the operation of the cluster.
896 An example of how pod affinity / anti-affinity is shown below:
898 Pod Affinity / Anti-Affinity
905 name: with-pod-affinity
909 requiredDuringSchedulingIgnoredDuringExecution:
916 topologyKey: failure-domain.beta.Kubernetes.io/zone
918 preferredDuringSchedulingIgnoredDuringExecution:
927 topologyKey: Kubernetes.io/hostname
929 - name: with-pod-affinity
930 image: gcr.io/google_containers/pause:2.0
932 This example contains both podAffinity and podAntiAffinity rules, the first
933 rule is is a must (requiredDuringSchedulingIgnoredDuringExecution) while the
934 second will be met pending other considerations
935 (preferredDuringSchedulingIgnoredDuringExecution). Preemption Another feature
936 that may assist in achieving a repeatable deployment in the presence of faults
937 that may have reduced the capacity of the cloud is assigning priority to the
938 containers such that mission critical components have the ability to evict less
939 critical components. Kubernetes provides this capability with Pod Priority and
940 Preemption. Prior to having more advanced production grade features available,
941 the ability to at least be able to re-deploy ONAP (or a subset of) reliably
942 provides a level of confidence that should an outage occur the system can be
943 brought back on-line predictably.
948 Monitoring of ONAP components is configured in the agents within JSON files and
949 stored in gerrit under the consul-agent-config, here is an example from the AAI
950 model loader (aai-model-loader-health.json):
956 "name": "A&AI Model Loader",
959 "id": "model-loader-process",
960 "name": "Model Loader Presence",
961 "script": "/consul/config/scripts/model-loader-script.sh",
972 These liveness probes can simply check that a port is available, that a
973 built-in health check is reporting good health, or that the Consul health check
974 is positive. For example, to monitor the SDNC component has following liveness
975 probe can be found in the SDNC DB deployment specification:
979 sdnc db liveness probe
983 command: ["mysqladmin", "ping"]
984 initialDelaySeconds: 30 periodSeconds: 10
987 The 'initialDelaySeconds' control the period of time between the readiness
988 probe succeeding and the liveness probe starting. 'periodSeconds' and
989 'timeoutSeconds' control the actual operation of the probe. Note that
990 containers are inherently ephemeral so the healing action destroys failed
991 containers and any state information within it. To avoid a loss of state, a
992 persistent volume should be used to store all data that needs to be persisted
993 over the re-creation of a container. Persistent volumes have been created for
994 the database components of each of the projects and the same technique can be
995 used for all persistent state information.
1005 The \ `Microservices Bus
1006 Project <https://wiki.onap.org/pages/viewpage.action?pageId=3246982>`__ provides
1007 facilities to integrate micro-services into ONAP and therefore needs to
1008 integrate into OOM - primarily through Consul which is the backend of
1009 MSB service discovery. The following is a brief description of how this
1010 integration will be done:
1012 A registrator to push the service endpoint info to MSB service
1015 - The needed service endpoint info is put into the kubernetes yaml file
1016 as annotation, including service name, Protocol,version, visual
1017 range,LB method, IP, Port,etc.
1019 - OOM deploy/start/restart/scale in/scale out/upgrade ONAP components
1021 - Registrator watch the kubernetes event
1023 - When an ONAP component instance has been started/destroyed by OOM,
1024 Registrator get the notification from kubernetes
1026 - Registrator parse the service endpoint info from annotation and
1027 register/update/unregister it to MSB service discovery
1029 - MSB API Gateway uses the service endpoint info for service routing
1032 Details of the registration service API can be found at \ `Microservice
1034 Documentation <https://wiki.onap.org/display/DW/Microservice+Bus+API+Documentation>`__.
1036 ONAP Component Registration to MSB
1037 ----------------------------------
1038 The charts of all ONAP components intending to register against MSB must have
1039 an annotation in their service(s) template. A `sdc` example follows:
1041 .. code-block:: yaml
1049 namespace: "{{ .Values.nsPrefix }}"
1051 msb.onap.org/service-info: '[
1053 "serviceName": "sdc",
1061 "serviceName": "sdc-deprecated",
1073 MSB Integration with OOM
1074 ------------------------
1075 A preliminary view of the OOM-MSB integration is as follows:
1077 .. figure:: MSB-OOM-Diagram.png
1079 A message sequence chart of the registration process:
1083 participant "OOM" as oom
1084 participant "ONAP Component" as onap
1085 participant "Service Discovery" as sd
1086 participant "External API Gateway" as eagw
1087 participant "Router (Internal API Gateway)" as iagw
1089 box "MSB" #LightBlue
1095 == Deploy Servcie ==
1098 oom -> sd: Register service endpoints
1099 sd -> eagw: Services exposed to external system
1100 sd -> iagw: Services for internal use
1102 == Component Life-cycle Management ==
1104 oom -> onap: Start/Stop/Scale/Migrate/Upgrade
1105 oom -> sd: Update service info
1106 sd -> eagw: Update service info
1107 sd -> iagw: Update service info
1109 == Service Health Check ==
1111 sd -> onap: Check the health of service
1112 sd -> eagw: Update service status
1113 sd -> iagw: Update service status
1116 MSB Deployment Instructions
1117 ---------------------------
1118 MSB is helm installable ONAP component which is often automatically deployed.
1119 To install it individually enter::
1121 > helm install <repo-name>/msb
1124 TBD: Vaidate if the following procedure is still required.
1126 Please note that Kubernetes authentication token must be set at
1127 *kubernetes/kube2msb/values.yaml* so the kube2msb registrator can get the
1128 access to watch the kubernetes events and get service annotation by
1129 Kubernetes APIs. The token can be found in the kubectl configuration file
1132 More details can be found here `MSB installation <https://docs.onap.org/projects/onap-msb-apigateway/en/latest/platform/installation.html>`_.
1136 .. Note that although OOM uses Kubernetes facilities to minimize the effort
1137 .. required of the ONAP component owners to implement a successful rolling
1138 .. upgrade strategy there are other considerations that must be taken into
1140 .. For example, external APIs - both internal and external to ONAP - should be
1141 .. designed to gracefully accept transactions from a peer at a different
1142 .. software version to avoid deadlock situations. Embedded version codes in
1143 .. messages may facilitate such capabilities.
1145 .. Within each of the projects a new configuration repository contains all of
1146 .. the project specific configuration artifacts. As changes are made within
1147 .. the project, it's the responsibility of the project team to make appropriate
1148 .. changes to the configuration data.