Installing and Running Mashery Local for Docker on GCP

To install and run Mashery Local for Docker on GCP (Google Cloud Platform), follow the steps below.

Note: This section assumes that you have already done the following:

Installed and configured Google Cloud SDK.
Created and configured your Kubernetes cluster.

Procedure

Download and extract Mashery Local Docker edition. Load the following images in local Docker host, if it is not loaded:
```
docker load -i ml-core.tar.gz

docker load -i ml-db.tar.gz

docker load -i ml-mem.tar.gz
```
Upload the Docker Images to the GCP Container Registry.
1. In order to deploy Mashery Local to your Kubernetes cluster on GCP, you will need to upload the images to your GCP Container Registry. The registry console is available at https://cloud.google.com/container-registry. The ML Docker images need to be tagged first before they can be uploaded to the registry.
  Use the following command to tag them:
```
docker tag [IMAGE] [HOSTNAME]/[PROJECT-ID]/[IMAGE]
```
  For example:
```
docker tag ml-core:v4.1.1.0 us.gcr.io/[PROJECT-ID]/ml-core:v4.1.1.0
docker tag ml-mem:v4.1.1.0 us.gcr.io/[PROJECT-ID]/ml-mem:v4.1.1.0
docker tag ml-db:v4.1.1.0 us.gcr.io/[PROJECT-ID]/ml-db:v4.1.1.0
```
  Upload the images using the gcloud docker push command:
```
gcloud docker -- push us.gcr.io/[PROJECT-ID]/ml-core
gcloud docker -- push us.gcr.io/[PROJECT-ID]/ml-mem
gcloud docker -- push us.gcr.io/[PROJECT-ID]/ml-db
```
2. Once the push commands complete, the new images should be listed in the Container Registry console.
  You can also verify the pushed images using the gcloud container images command, for example:
```
gcloud container images list-tags us.gcr.io/[PROJECT-ID]/ml-core
DIGEST        TAGS      TIMESTAMP
b20b0700bf3a  v4.1.1.0  2017-08-03T22:33:02
```
3. With the Docker images in the container registry, you can inspect the images in the Container Registry console.

Go to the folder <Absolute path>/TIB_mash-local_<ML-version>_docker/examples/googleCloudPlatform/kubernetes in the extracted directory and perform the following steps:

Modify the gcp-env.sh as per requirement and environment. This is the place to customize your deployment such as image version, docker image registry, persistent volume size, etc. All the scripts afterwards should be executed from the same terminal.
```
source gcp-env.sh
```
Execute the following script to store the Docker registry key as Kubernetes "Secret":
```
./set-registry-key.sh
 
 
Sample o/p:
secret "mlregistrykey" created
```

Execute the following script to store MOM host and key as Kubernetes "Secret":

set-mom-secret.sh create <MOM key> <MOM secret> <MOM Host>

For example:

./set-mom-secret.sh create 7uy26rr6z936hfnsw3jes8ap cu4ChaHt2h mom.api.mca-mom.mashspud.com
 
 
Sample o/p:
secret "mlmomsecret" created

Create storage classes for Mashery Local for Docker persistent stores:

./set-storage-classes.sh
 
 
Sample o/p:
storageclass "mldb-storage" created
storageclass "mldata-storage" created

Create Mashery Local Traffic Manager service and Mashery Local Master service:

./set-ml-services.sh
 
 
Sample o/p:
service "ml-traffic-manager" created
service "ml-master" created

Check the services with the following commands:

kubectl describe service ml-traffic-manager

kubectl describe service ml-master

Deploy Mashery Local Master instance:

./deploy-master.sh
Sample o/p:
persistentvolumeclaim "mldb-master-pvc" created
persistentvolumeclaim "mldata-master-pvc" created
deployment "ml-master" created

You can check the ML instance pods with the command:

kubectl get pods

For example:

kubectl get pods
NAME                         READY     STATUS    RESTARTS   AGE
ml-master-2132837488-vrx1n   4/4       Running   0          3m

To find the ML master instance node public IP with the following command:

kubectl describe node `kubectl get pods -o wide |grep ml-master |awk -F' ' '{print $7}'` |grep ExternalIP |cut -d "," -f 3

Deploy slaves using the following command:

deploy-slaves.sh

For example:

./deploy-slaves.sh
 
service "ml-slave" created
 
statefulset "ml-slave" created

Check Master and Slave status:

kubectl get pods
 
Sample o/p:
NAME                         READY     STATUS    RESTARTS   AGE
ml-master-2132837488-vrx1n   4/4       Running   0          11m
ml-slave-0                   4/4       Running   0          7m
ml-slave-1                   4/4       Running   0          4m

If everything works properly, you should have a fully deployed cluster with one Master and two Slaves.

Access the Mashery Local UI. To access the Mashery Local UI, open the port 5480 on nodes in GCP. Navigate to the Firewall rules section in the Google Cloud Platform and add an entry as below. This will enable UI on all nodes. You can also create a specific rule node.

The Mashery Local Cluster Manager console should look like this:

To find the LB IP address:

export LB=`kubectl describe service ml-traffic-manager|grep Ingress|awk -F' ' '{print $3}'` && echo $LB
35.230.36.250

To make a traffic call through the LB:

curl -v -H 'Host:chainsproxy.api.mca.mashspud.com'  'http://35.230.36.250/v1/api/patient/1234/qatest/testRequestInfo.php?api_key=3bvu8u3p8k5vjxmhrs6tnd6e'
 
*   Trying 35.230.36.250...
 
* TCP_NODELAY set
 
* Connected to 35.230.36.250 (35.230.36.250) port 80 (#0)
 
> GET /v1/api/patient/1234/qatest/testRequestInfo.php?api_key=3bvu8u3p8k5vjxmhrs6tnd6e HTTP/1.1
 
> Host:chainsproxy.api.mca.mashspud.com
 
> User-Agent: curl/7.54.0
 
> Accept: */*
 
>
 
< HTTP/1.1 200 OK
 
< X-Mashery-Responder: ml-slave-0
 
< Content-Type: text/plain; charset=UTF-8
 
< Date: Thu, 22 Feb 2018 16:11:56 GMT
 
< X-Powered-By: PHP/5.3.3
 
< Content-Length: 642
 
<
 
TIME NOW: 2018-02-22 08:11:56
 
================================
 
 
 
 
Server Script: /internal/patients/1234/info/qatest/testRequestInfo.php
 
Query params: api_key=3bvu8u3p8k5vjxmhrs6tnd6e
 
Request Method: GET
 
Request Protocol: HTTP/1.1
 
Requested URI: /internal/patients/1234/info/qatest/testRequestInfo.php?api_key=3bvu8u3p8k5vjxmhrs6tnd6e
 
REQUEST HEADERS:
 
Array
 
(
 
    [host] => content.mock.mashery.com
 
    [Accept] => */*
 
    [User-Agent] => Mashery Proxy
 
    [X-Original-User-Agent] => curl/7.54.0
 
    [X-Forwarded-For] => 10.138.0.2, 35.230.118.130
 
    [X-Forwarded-Port] => 80
 
    [X-Forwarded-Proto] => http
 
    [Connection] => keep-alive
 
)
 
 
 
 
* Connection #0 to host 35.230.36.250 left intact

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Installing and Running Mashery Local for Docker on GCP

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