# Distributed Analytics Framework ## Pre-requisites | Required | Version | |------------|---------| | Kubernetes | 1.12.3+ | | Docker CE | 18.09+ | | Helm | >=2.12.1 and <=2.13.1 | ## Download Framework ```bash git clone https://github.com/onap/demo.git DA_WORKING_DIR=$PWD/demo/vnfs/DAaaS/deploy ``` ## Install Istio Service Mesh ## Istio is installed in two Steps ```bash 1. Istio-Operator 2. Istio-config ``` ## Download the Istio Installation repo ```bash cd $DA_WORKING_DIR/00-init helm install --name=istio-operator istio-operator --namespace=istio-system cd $DA_WORKING_DIR/00-init/istio helm install --name istio istio-instance --namespace istio-system ``` ## Install Metallb to act as a Loadbalancer ```bash cd $DA_WORKING_DIR/00-init NOTE: Update the IP Address Ranges before you Install Metallb NOTE: If you are using a single IP, use /32 format helm install --name metallb metallb --namespace metallb-system ``` ## Install Rook-Ceph for Persistent Storage Note: This is unusual but Flex volume path can be different than the default value. values.yaml has the most common flexvolume path configured. In case of errors related to flexvolume please refer to the https://rook.io/docs/rook/v0.9/flexvolume.html#configuring-the-flexvolume-path to find the appropriate flexvolume-path and set it in values.yaml ```bash cd $DA_WORKING_DIR/00-init/rook-ceph helm install -n rook . -f values.yaml --namespace=rook-ceph-system ``` Check for the status of the pods in rook-ceph namespace. Once all pods are in Ready state move on to the next section. ```bash $ kubectl get pods -n rook-ceph-system NAME READY STATUS RESTARTS AGE rook-ceph-agent-9wszf 1/1 Running 0 121s rook-ceph-agent-xnbt8 1/1 Running 0 121s rook-ceph-operator-bc77d6d75-ltwww 1/1 Running 0 158s rook-discover-bvj65 1/1 Running 0 133s rook-discover-nbfrp 1/1 Running 0 133s ``` ```bash $ kubectl -n rook-ceph get pod NAME READY STATUS RESTARTS AGE rook-ceph-mgr-a-d9dcf5748-5s9ft 1/1 Running 0 77s rook-ceph-mon-a-7d8f675889-nw5pl 1/1 Running 0 105s rook-ceph-mon-b-856fdd5cb9-5h2qk 1/1 Running 0 94s rook-ceph-mon-c-57545897fc-j576h 1/1 Running 0 85s rook-ceph-osd-0-7cbbbf749f-j8fsd 1/1 Running 0 25s rook-ceph-osd-1-7f67f9646d-44p7v 1/1 Running 0 25s rook-ceph-osd-2-6cd4b776ff-v4d68 1/1 Running 0 25s rook-ceph-osd-prepare-vx2rz 0/2 Completed 0 60s rook-ceph-tools-5bd5cdb949-j68kk 1/1 Running 0 53s ``` #### Troubleshooting Rook-Ceph installation In case your machine had rook previously installed successfully or unsuccessfully and you are attempting a fresh installation of rook operator, you may face some issues. Lets help you with that. * First check if there are some rook CRDs existing : ``` kubectl get crds | grep rook ``` If this return results like : ``` otc@otconap7 /var/lib/rook $ kubectl get crds | grep rook cephblockpools.ceph.rook.io 2019-07-19T18:19:05Z cephclusters.ceph.rook.io 2019-07-19T18:19:05Z cephfilesystems.ceph.rook.io 2019-07-19T18:19:05Z cephobjectstores.ceph.rook.io 2019-07-19T18:19:05Z cephobjectstoreusers.ceph.rook.io 2019-07-19T18:19:05Z volumes.rook.io 2019-07-19T18:19:05Z ``` then you should delete these previously existing rook based CRDs by generating a delete manifest file by these commands and then deleting those files: ``` helm template -n rook . -f values.yaml > ~/delete.yaml kubectl delete -f ~/delete.yaml ``` After this, delete the below directory in all the nodes. ``` sudo rm -rf /var/lib/rook/ ``` Now, again attempt : ``` helm install -n rook . -f values.yaml --namespace=rook-ceph-system ``` ## Install Operator package ### Build docker images #### collectd-operator ```bash cd $DA_WORKING_DIR/../microservices ## Note: The image tag and respository in the Collectd-operator helm charts needs to match the IMAGE_NAME IMAGE_NAME=dcr.cluster.local:32644/collectd-operator:latest ./build_image.sh collectd-operator $IMAGE_NAME ``` #### visualization-operator ```bash cd $DA_WORKING_DIR/../microservices ## Note: The image tag and respository in the Visualization-operator helm charts needs to match the IMAGE_NAME IMAGE_NAME=dcr.cluster.local:32644/visualization-operator:latest ./build_image.sh visualization-operator $IMAGE_NAME ``` ### Install the Operator Package ```bash cd $DA_WORKING_DIR/deploy/operator helm install -n operator . -f values.yaml --namespace=operator ``` Check for the status of the pods in operator namespace. Check if Prometheus operator pods are in Ready state. ```bash kubectl get pods -n operator NAME READY STATUS RESTARTS m3db-operator-0 1/1 Running 0 op-etcd-operator-etcd-backup-operator-6cdc577f7d-ltgsr 1/1 Running 0 op-etcd-operator-etcd-operator-79fd99f8b7-fdc7p 1/1 Running 0 op-etcd-operator-etcd-restore-operator-855f7478bf-r7qxp 1/1 Running 0 op-prometheus-operator-operator-5c9b87965b-wjtw5 1/1 Running 1 op-sparkoperator-6cb4db884c-75rcd 1/1 Running 0 strimzi-cluster-operator-5bffdd7b85-rlrvj 1/1 Running 0 ``` #### Troubleshooting Operator installation Sometimes deleting the previously installed Operator package will fail to remove all operator pods. To troubleshoot this ensure these following steps. 1. Make sure that all the other deployments or helm release is deleted (purged). Operator package is a baseline package for the applications, so if the applications are still running while trying to delete the operator package might result in unwarrented state. 2. Delete all the resources and CRDs associated with operator package. ```bash #NOTE: Use the same release name and namespace as in installation of operator package in the previous section cd $DA_WORKING_DIR/operator helm template -n operator . -f values.yaml --namespace=operator > ../delete_operator.yaml cd ../ kubectl delete -f delete_operator.yaml ``` ## Install Collection package Note: Collectd.conf is avaliable in $DA_WORKING_DIR/collection/charts/collectd/resources/config directory. Any valid collectd.conf can be placed here. ```bash Default (For custom collectd skip this section) ======= cd $DA_WORKING_DIR/deploy/collection helm install -n cp . -f values.yaml --namespace=edge1 Custom Collectd =============== 1. Build the custom collectd image 2. Set COLLECTD_IMAGE_NAME with appropriate image_repository:tag 3. Push the image to docker registry using the command 4. docker push ${COLLECTD_IMAGE_NAME} 5. Edit the values.yaml and change the image repository and tag using COLLECTD_IMAGE_NAME appropriately. 6. Place the collectd.conf in $DA_WORKING_DIR/collection/charts/collectd/resources 7. cd $DA_WORKING_DIR/collection 8. helm install -n cp . -f values.yaml --namespace=edge1 ``` #### Verify Collection package * Check if all pods are up in edge1 namespace * Check the prometheus UI using port-forwarding port 9090 (default for prometheus service) ``` $ kubectl get pods -n edge1 NAME READY STATUS RESTARTS AGE cp-cadvisor-8rk2b 1/1 Running 0 15s cp-cadvisor-nsjr6 1/1 Running 0 15s cp-collectd-h5krd 1/1 Running 0 23s cp-collectd-jc9m2 1/1 Running 0 23s cp-prometheus-node-exporter-blc6p 1/1 Running 0 17s cp-prometheus-node-exporter-qbvdx 1/1 Running 0 17s prometheus-cp-prometheus-prometheus-0 4/4 Running 1 33s $ kubectl get svc -n edge1 NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) cadvisor NodePort 10.43.53.122 80:30091/TCP collectd ClusterIP 10.43.222.34 9103/TCP cp13-prometheus-node-exporter ClusterIP 10.43.17.242 9100/TCP cp13-prometheus-prometheus NodePort 10.43.26.155 9090:30090/TCP prometheus-operated ClusterIP None 9090/TCP ``` #### Configure Collectd Plugins 1. Using the sample [collectdglobal.yaml](microservices/collectd-operator/examples/collectd/collectdglobal.yaml), Configure the CollectdGlobal CR 2. If there are additional Types.db files to update, Copy the additional types.db files to resources folder. 3. Create a ConfigMap to load the types.db and update the configMap with name of the ConfigMap created. 4. Create and configure the required CollectdPlugin CRs. Use these samples as a reference [cpu_collectdplugin_cr.yaml](microservices/collectd-operator/examples/collectd/cpu_collectdplugin_cr.yaml), [prometheus_collectdplugin_cr.yaml](microservices/collectd-operator/examples/collectd/prometheus_collectdplugin_cr.yaml). 4. Use the same namespace where the collection package was installed. 5. Assuming it is edge1, create the config resources that are applicable. Apply the following commands in the same order. ```yaml # Note: ## 1. Create Configmap is optional and required only if additional types.db file needs to be mounted. ## 2. Add/Remove --from-file accordingly. Use the correct file name based on the context. kubectl create configmap typesdb-configmap --from-file ./resource/[FILE_NAME1] --from-file ./resource/[FILE_NAME2] kubectl create -f edge1 collectdglobal.yaml kubectl create -f edge1 [PLUGIN_NAME1]_collectdplugin_cr.yaml kubectl create -f edge1 [PLUGIN_NAME2]_collectdplugin_cr.yaml kubectl create -f edge1 [PLUGIN_NAME3]_collectdplugin_cr.yaml ... ``` #Install visualization package ```bash Default (For custom Grafana dashboards skip this section) ======= cd $DA_WORKING_DIR/visualization helm install -n viz . -f values.yaml -f grafana-values.yaml Custom Grafana dashboards ========================= 1. Place the custom dashboard definition into the folder $DA_WORKING_DIR/visualization/charts/grafana/dashboards Example dashboard definition can be found at $DA_WORKING_DIR/visualization/charts/grafana/dashboards/dashboard1.json 2. Create a configmap.yaml that imports above created dashboard.json file as config and copy that configmap.yaml to $DA_WORKING_DIR/visualization/charts/grafana/templates/ Example configmap can be found at $DA_WORKING_DIR/visualization/charts/grafana/templates/configmap-add-dashboard.yaml 3. Add custom dashboard configuration to values.yaml or an overriding values.yaml. Example configuration can be found in the "dashboardProviders" section of grafana-values.yaml 4. cd $DA_WORKING_DIR/visualization 5. For a fresh install of visualization package, do "helm install" e.g., helm install -n viz . -f values.yaml -f grafana-values.yaml If the custom dashboard is being added to an already running Grafana, do "helm upgrade" e.g., helm upgrade -n viz . -f values.yaml -f grafana-values.yaml -f ...... ``` #### Verify Visualization package Check if the visualization pod is up ``` $ kubectl get pods NAME READY STATUS RESTARTS AGE viz-grafana-78dcffd75-sxnjv 1/1 Running 0 52m ``` ### Login to Grafana ``` 1. Get your 'admin' user password by running: kubectl get secret --namespace default viz-grafana -o jsonpath="{.data.admin-password}" | base64 --decode ; echo 2. Get the Grafana URL to visit by running these commands in the same shell: export POD_NAME=$(kubectl get pods --namespace default -l "app=grafana,release=viz" -o jsonpath="{.items[0].metadata.name}") kubectl --namespace default port-forward $POD_NAME 3000 3. Visit the URL : http://localhost:3000 and login with the password from step 1 and the username: admin ``` #### Configure Grafana Datasources Using the sample [prometheus_grafanadatasource_cr.yaml](microservices/visualization-operator/examples/grafana/prometheus_grafanadatasource_cr.yaml), Configure the GrafanaDataSource CR by running the command below ```yaml kubectl create -f [DATASOURCE_NAME1]_grafanadatasource_cr.yaml kubectl create -f [DATASOURCE_NAME2]_grafanadatasource_cr.yaml ... ``` ## Install Minio Model repository * Prerequisite: Dynamic storage provisioner needs to be enabled. Either rook-ceph ($DA_WORKING_DIR/00-init) or another alternate provisioner needs to be enabled. ```bash cd $DA_WORKING_DIR/minio Edit the values.yaml to set the credentials to access the minio UI. Default values are accessKey: "onapdaas" secretKey: "onapsecretdaas" helm install -n minio . -f values.yaml --namespace=edge1 ``` ## Install Messaging platform We have currently support strimzi based kafka operator. Navigate to ```$DA_WORKING_DIR/deploy/messaging/charts/strimzi-kafka-operator``` directory. Use the below command : ``` helm install . -f values.yaml --name sko --namespace=test ``` NOTE: Make changes in the values.yaml if required. Once the strimzi operator ready, you shall get a pod like : ``` strimzi-cluster-operator-5cf7648b8c-zgxv7 1/1 Running 0 53m ``` Once this done, install the kafka package like any other helm charts you have. Navigate to dir : ```$DA_WORKING_DIRdeploy/messaging``` and use command: ``` helm install --name kafka-cluster charts/kafka/ ``` Once this done, you should have the following pods up and running. ``` kafka-cluster-entity-operator-b6557fc6c-hlnkm 3/3 Running 0 47m kafka-cluster-kafka-0 2/2 Running 0 48m kafka-cluster-kafka-1 2/2 Running 0 48m kafka-cluster-kafka-2 2/2 Running 0 48m kafka-cluster-zookeeper-0 2/2 Running 0 49m kafka-cluster-zookeeper-1 2/2 Running 0 49m kafka-cluster-zookeeper-2 2/2 Running 0 49m ``` You should have the following services when do a ```kubectl get svc``` ``` kafka-cluster-kafka-bootstrap ClusterIP 10.XX.YY.ZZ 9091/TCP,9092/TCP,9093/TCP 53m kafka-cluster-kafka-brokers ClusterIP None 9091/TCP,9092/TCP,9093/TCP 53m kafka-cluster-zookeeper-client ClusterIP 10.XX.YY.ZZ 2181/TCP 55m kafka-cluster-zookeeper-nodes ClusterIP None 2181/TCP,2888/TCP,3888/TCP 55m ``` #### Testing messaging You can test your kafka brokers by creating a simple producer and consumer. Producer : ``` kubectl run kafka-producer -ti --image=strimzi/kafka:0.12.2-kafka-2.2.1 --rm=true --restart=Never -- bin/kafka-console-producer.sh --broker-list kafka-cluster-kafka-bootstrap:9092 --topic my-topic ``` Consumer : ``` kubectl run kafka-consumer -ti --image=strimzi/kafka:0.12.2-kafka-2.2.1 --rm=true --restart=Never -- bin/kafka-console-consumer.sh --bootstrap-server kafka-cluster-kafka-bootstrap:9092 --topic my-topic --from-beginning ``` ## Install Training Package #### Install M3DB (Time series Data lake) ##### Pre-requisites 1. kubernetes cluster with atleast 3 nodes 2. Etcd operator, M3DB operator 3. Node labelled with zone and region. ```bash ## Defult region is us-west1, Default labels are us-west1-a, us-west1-b, us-west1-c ## If this is changed then isolationGroups in training-core/charts/m3db/values.yaml needs to be updated. NODES=($(kubectl get nodes --output=jsonpath={.items..metadata.name})) kubectl label node/${NODES[0]} failure-domain.beta.kubernetes.io/region=us-west1 kubectl label node/${NODES[1]} failure-domain.beta.kubernetes.io/region=us-west1 kubectl label node/${NODES[2]} failure-domain.beta.kubernetes.io/region=us-west1 kubectl label node/${NODES[0]} failure-domain.beta.kubernetes.io/zone=us-west1-a --overwrite=true kubectl label node/${NODES[1]} failure-domain.beta.kubernetes.io/zone=us-west1-b --overwrite=true kubectl label node/${NODES[2]} failure-domain.beta.kubernetes.io/zone=us-west1-c --overwrite=true ``` ```bash cd $DA_WORKING_DIR/training-core/charts/m3db helm install -n m3db . -f values.yaml --namespace training ``` ``` $ kubectl get pods -n training NAME READY STATUS RESTARTS AGE m3db-cluster-rep0-0 1/1 Running 0 103s m3db-cluster-rep1-0 1/1 Running 0 83s m3db-cluster-rep1-0 1/1 Running 0 62s m3db-etcd-sjhgl4xfgc 1/1 Running 0 83s m3db-etcd-lfs96hngz6 1/1 Running 0 67s m3db-etcd-rmgdkkx4bq 1/1 Running 0 51s ``` ##### Configure remote write from Prometheus to M3DB ```bash cd $DA_WORKING_DIR/day2_configs/prometheus/ ``` ```yaml cat << EOF > add_m3db_remote.yaml spec: remoteWrite: - url: "http://m3coordinator-m3db.training.svc.cluster.local:7201/api/v1/prom/remote/write" writeRelabelConfigs: - targetLabel: metrics_storage replacement: m3db_remote EOF ``` ```bash kubectl patch --namespace=edge1 prometheus cp-prometheus-prometheus -p "$(cat add_m3db_remote.yaml)" --type=merge ``` Verify the prometheus GUI to see if the m3db remote write is enabled.