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Refactoring Monoliths with Microservices and Serverless

This document outlines a demo of gloo composing ('glooing') an application from a monolith, a microservice and AWS Lambda.

Prerequisites

In this demo, we will use the following command line tools:

  • minikube to create a kubernetes test environment.
  • kubectl to interact with kubernetes.
  • glooctl to interact with gloo.
  • aws (the aws cli) to create resources on aws.
  • jq to parse the aws output to retrieve the ARN of created resources.

You will need an AWS account. this is used to extend the application to the cloud. In this demo we will create real resources on the cloud, which may result in small charges to your account.

Additionally, some of the demo commands reference files, so first cd to the folder that contains this readme (usually this is cd $GOPATH/src/github.com/solo-io/gloo/example/demo).

Setup the environment

Install Kubernetes

minikube start --extra-config=apiserver.Authorization.Mode=RBAC --cpus 4 --memory 4096
kubectl create clusterrolebinding permissive-binding \
         --clusterrole=cluster-admin \
         --user=admin \
         --user=kubelet \
         --group=system:serviceaccounts

Install Gloo

glooctl install kube

Wait \ Verify that all the pods are in Running status:

kubectl get pods --all-namespaces

Get the url of the ingress

If you installed kubernetes using minikube as mentioned above, you can use this command:

export GATEWAY_URL=http://$(minikube ip):$(kubectl get svc ingress -n gloo-system -o 'jsonpath={.spec.ports[?(@.name=="http")].nodePort}')

Deploy

Deploy the pet store monolith

Note - source code for this demo is here: https://github.com/solo-io/spring-petclinic, https://github.com/solo-io/petclinic-vet.

kubectl apply -f https://raw.githubusercontent.com/solo-io/gloo/master/example/demo/yamls/pet-clinic.yaml

Verify it is available as an upstream:

glooctl upstream get

you should see default-petclinic-80 in the list.

Add a route to it!

glooctl route create --path-prefix / --upstream default-petclinic-80

Now you should see pet clinict in your browser if you open the $GATEWAY_URL.

Notice that the vets page is missing the city column. To fix the bug, we will deploy a microservice that replaces the vets page in the monolith.

Deploy the microservice:

kubectl apply -f https://raw.githubusercontent.com/solo-io/gloo/master/example/demo/yamls/vets.yaml

Add a route to the new microservice from gloo:

glooctl route create --sort --path-exact /vets.html --upstream default-petclinic-vets-80

Now the vets page will contain a city column!

Add some Cloud™

Let's expand the app functionality by displaying a contact form and saving the contact response to an AWS S3 bucket.

Note: The current Gloo-AWS integration sends the aws keys unencrypted from gloo to envoy. This means that they may be sent in the clear over the local network, and appear in the envoy debug logs (which are off by default). we plan to fix that very soon.

In this section, we will:

  1. Create an S3 bucket to receive form responses
  2. Create a policy and a role to allow a lambda function to put objects in the bucket.
  3. Create a lambda functions to display and process the form.
  4. Configure gloo to route requests to the lambda function.

Configure AWS

Create an S3 bucket, set the BUCKET variable to a new name.

BUCKET=name-of-bucket-to-add
aws s3api  create-bucket  --acl private --bucket $BUCKET

Create a policy to match your bucket:

curl -L https://raw.githubusercontent.com/solo-io/gloo/master/example/demo/aws/policy-document_template.json \
    | sed s/io.solo.petclinic/$BUCKET/ > policy-document.json

Create the needed policy and role that allows the lambda function to access the bucket:

aws iam create-policy --policy-name gloo-contact-lambda-policy --policy-document file://policy-document.json
POLICY_ARN=$(aws iam list-policies | jq -r '.Policies[] | select(.PolicyName == "gloo-contact-lambda-policy") | .Arn')

aws iam create-role --role-name gloo-contact-lambda-role \
    --assume-role-policy-document https://raw.githubusercontent.com/solo-io/gloo/master/example/demo/aws/assume-role-policy-document.json
aws iam attach-role-policy --role-name gloo-contact-lambda-role --policy-arn $POLICY_ARN
ROLE_ARN=$(aws iam list-roles | jq -r '.Roles[] | select(.RoleName == "gloo-contact-lambda-role") | .Arn')

Create the lambda function:

# download the lambda function zip:
wget https://github.com/solo-io/gloo/raw/master/example/demo/aws/contact.zip

aws lambda create-function \
--region us-east-1 \
--function-name processContact \
--zip-file fileb://contact.zip \
--handler index.handler \
--runtime nodejs6.10 \
--role $ROLE_ARN \
--environment "Variables={BUCKET=$BUCKET}"

Route to AWS Lambda from gloo

Upload the aws secret to gloo, so that gloo can call your function. This command will upload the aws credentials ot kubernetes as a secret. by default it takes the credentials from ~/.aws/credentials. Run with glooctl secret create aws --help to see other ways to provide the credentials.

glooctl secret create aws --name aws-lambda-us-east-1

Create the aws upstream in gloo:

glooctl upstream create -f \
    https://raw.githubusercontent.com/solo-io/gloo/master/example/demo/yamls/aws-upstream.yaml

Verify that the upstream was created and the functions were auto discovered:

glooctl upstream get aws-lambda-us-east-1 -o yaml

Route the contact paths to the function:

glooctl route create --sort --path-exact /contact --upstream aws-lambda-us-east-1 --function 'processContact:$LATEST'
glooctl route create --sort --path-exact /contact.html --upstream aws-lambda-us-east-1 --function 'processContact:$LATEST'

Go to the contact page. Notice that you see json in stead of HTML. To fix that, we will attach a transformation to the route:

glooctl route update --old-path-exact /contact.html --old-upstream aws-lambda-us-east-1 --old-function 'processContact:$LATEST' --path-exact /contact.html --upstream aws-lambda-us-east-1 --function 'processContact:$LATEST' --extensions ./yamls/transformation.yaml

Now the contact form will be presented! Post some messages through the contact form.

To view the sent messages, have a look at the S3 bucket:

aws s3 ls $BUCKET

Cleanup

Cloud resources

aws lambda delete-function --function-name processContact
aws iam detach-role-policy --role-name gloo-contact-lambda-role --policy-arn $POLICY_ARN
aws iam    delete-role --role-name gloo-contact-lambda-role
aws iam    delete-policy --policy-arn "$POLICY_ARN"

Delete all the objects in the bucket. and then:

aws s3api  delete-bucket --bucket $BUCKET

Minikube

minikube delete