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AWS Neptune demo application

How to deploy this demo app

prerequisites:
deployment steps:
  • create an AWS Neptune instance:
    • go to AWS Neptune home
    • click "Launch Amazon Neptune"
    • select DB engine version and DB instance class
    • enable or disable high availability (Multi-AZ)
    • enter a DB instance identifier in the "Settings" section
    • click "Next"
    • select VPC, subnet group and availability zone
    • leave "Create new VPC security group" checked
    • leave other parameters as default and click "Create Database" below
    • it will take some time (ca. 7 min) for the instance to start and become available
  • adjust the created Neptune's security group:
    • go to the security groups
    • find the newly created security group. it should have the name "rds-launch-wizard" or similar.
    • write down the security group ID
    • add a new inbound rule allowing all incoming TCP connections from inside the security group:
      • Type = Custom TCP
      • Protocol = TCP
      • Port Range = 0 - 65535
      • Source = < ID of the security group >
  • create an S3 bucket. AWS SAM will use it for storing lambdas (ZIP archives).
  • create an IAM role for lambdas. The role should have the following (predefined by AWS) policies:
  • build and deploy lambdas:
    • cd cloudformation
    • cp vars.template.sh vars.sh
    • vi vars.sh
    • adjust the variables:
      • S3_BUCKET -- name of the created S3 bucket where lambdas will be stored.
      • STACK_NAME -- name that will be used for the CloudFormation stack with lambdas.
      • ROLE_ARN -- ARN of the created IAM role for lambdas.
      • SECURITY_GROUP_IDS -- the ID of the security group created for Neptune.
      • SUBNET_IDS -- IDs of the subnets of the VPC where the Neptune instance has been deployed.
      • NEPTUNE_ENDPOINT -- Neptune's endpoint. It can be found in the Neptune clusters. Click on the created cluster and find the "Cluster endpoint" DNS name in the "Details" section.
      • NEPTUNE_PORT -- Neptune's port (8182 by default).
      • TAG_USER -- user name for marking AWS resources with tag user.
    • build and deploy lambdas: . build.sh && . package.sh && . deploy.sh
  • go to the CloudFormation home and observe that a new stack with lambdas appeared
  • wait for the stack to be ready
  • go to the AWS Lambda Functions and observe 2 AWS functions

Loading test data

  • go to the AWS Lambda Functions
  • find the LoadTestDataFunction function and click on it
  • run test with any payload e.g. with the empty one: {}
  • the lambda should then load test data into Neptune

Executing test query

  • go to the AWS Lambda Functions
  • find the RunAdHocQueryFunction function and click on it
  • call lambda (via "Test") with the following payload:
{
  "skill1": "Java EE 8",
  "skill2": "PostgreSQL",
  "skill3": "TDD",
  "certificate": "OCP Java SE 8",
  "customer": "Big Brother Corporation",
  "availableFrom": 1516492800000,
  "availableTo": 1516665600000
}
  • the response should be:
[
  {
    "firstName": [
      "Bob"
    ],
    "lastName": [
      "Smith"
    ],
    "id": [
      10
    ],
    "position": [
      "software engineer"
    ]
  }
]
  • call lambda with another payload:
{
  "skill1": "Java EE 8",
  "skill2": "PostgreSQL",
  "skill3": "TDD",
  "certificate": "OCP Java SE 8",
  "customer": "Space Logistics AG",
  "availableFrom": 1514764800000,
  "availableTo": 1517443200000
}
  • the response should be:
[
  {
    "firstName": [
      "Alice"
    ],
    "lastName": [
      "Brown"
    ],
    "id": [
      20
    ],
    "position": [
      "senior software engineer"
    ]
  },
  {
    "firstName": [
      "Bob"
    ],
    "lastName": [
      "Smith"
    ],
    "id": [
      10
    ],
    "position": [
      "software engineer"
    ]
  }
]

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