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refactor terraform modules, add clustering lambda (#4)
This commit is contained in:
Will Freeman
1
.gitignore
vendored
1
.gitignore
vendored
@@ -44,6 +44,7 @@ terraform.tfstate*
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serverless/*/lambda.zip
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serverless/*/src/*
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!serverless/*/src/alpr_counts.py
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!serverless/*/src/alpr_clusters.py
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!serverless/*/src/requirements.txt
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# TODO: need a better way to handle python packages
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@@ -1,974 +0,0 @@
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{
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]
|
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}
|
||||
@@ -1,62 +0,0 @@
|
||||
import requests
|
||||
import json
|
||||
from sklearn.cluster import DBSCAN
|
||||
from geopy.distance import great_circle
|
||||
from geopy.point import Point
|
||||
import numpy as np
|
||||
|
||||
# Set up the Overpass API query
|
||||
# TODO: remove the bbox
|
||||
query = """
|
||||
[out:json];
|
||||
node["man_made"="surveillance"]["surveillance:type"="ALPR"];
|
||||
out body;
|
||||
"""
|
||||
|
||||
# Request data from Overpass API
|
||||
print("Requesting data from Overpass API...")
|
||||
url = "http://overpass-api.de/api/interpreter"
|
||||
response = requests.get(url, params={'data': query}, headers={'User-Agent': 'DeFlock/1.0'})
|
||||
data = response.json()
|
||||
print("Data received. Parsing nodes...")
|
||||
|
||||
# Parse nodes and extract lat/lon for clustering
|
||||
coordinates = []
|
||||
node_ids = []
|
||||
for element in data['elements']:
|
||||
if element['type'] == 'node':
|
||||
coordinates.append([element['lat'], element['lon']])
|
||||
node_ids.append(element['id'])
|
||||
|
||||
# Convert coordinates to NumPy array for DBSCAN
|
||||
coordinates = np.array(coordinates)
|
||||
|
||||
# Define the clustering radius (10 miles in meters)
|
||||
radius_miles = 50
|
||||
radius_km = radius_miles * 1.60934 # 1 mile = 1.60934 km
|
||||
radius_in_radians = radius_km / 6371.0 # Earth's radius in km
|
||||
|
||||
# Perform DBSCAN clustering
|
||||
db = DBSCAN(eps=radius_in_radians, min_samples=1, algorithm='ball_tree', metric='haversine').fit(np.radians(coordinates))
|
||||
labels = db.labels_
|
||||
|
||||
# Prepare clusters and calculate centroids
|
||||
clusters = {}
|
||||
for label in set(labels):
|
||||
cluster_points = coordinates[labels == label]
|
||||
centroid = np.mean(cluster_points, axis=0)
|
||||
first_node_id = node_ids[labels.tolist().index(label)]
|
||||
|
||||
# Store in clusters dict with centroid and first node ID
|
||||
clusters[label] = {
|
||||
"lat": centroid[0],
|
||||
"lon": centroid[1],
|
||||
"id": first_node_id
|
||||
}
|
||||
|
||||
# Save clusters to JSON
|
||||
output = {"clusters": list(clusters.values())}
|
||||
with open("alpr_clusters.json", "w") as outfile:
|
||||
json.dump(output, outfile, indent=2)
|
||||
|
||||
print("Clustering complete. Results saved to alpr_clusters.json.")
|
||||
31
serverless/alpr_clusters/deploy.sh
Executable file
31
serverless/alpr_clusters/deploy.sh
Executable file
@@ -0,0 +1,31 @@
|
||||
#!/bin/bash
|
||||
|
||||
ECR_REPO_URL=912821578123.dkr.ecr.us-east-1.amazonaws.com/alpr_clusters-lambda
|
||||
|
||||
set -e
|
||||
|
||||
# check if AWS role is assumed
|
||||
if ! aws sts get-caller-identity &> /dev/null; then
|
||||
echo "Error: AWS role is not assumed. Please assume the necessary role and try again."
|
||||
exit 1
|
||||
fi
|
||||
|
||||
cd src
|
||||
|
||||
# build Docker image
|
||||
docker build -t alpr_clusters .
|
||||
|
||||
# tag docker image with ECR repo
|
||||
docker tag alpr_clusters:latest $ECR_REPO_URL:latest
|
||||
|
||||
# login to ECR
|
||||
aws ecr get-login-password --region us-east-1 | docker login --username AWS --password-stdin $ECR_REPO_URL
|
||||
|
||||
# push Docker image to ECR
|
||||
docker push $ECR_REPO_URL:latest
|
||||
|
||||
# update lambda function
|
||||
export AWS_PAGER=""
|
||||
aws lambda update-function-code --function-name alpr_clusters --image-uri $ECR_REPO_URL:latest
|
||||
|
||||
echo "Deployed!"
|
||||
78
serverless/alpr_clusters/src/alpr_clusters.py
Normal file
78
serverless/alpr_clusters/src/alpr_clusters.py
Normal file
@@ -0,0 +1,78 @@
|
||||
import boto3
|
||||
import requests
|
||||
import json
|
||||
from sklearn.cluster import DBSCAN
|
||||
import numpy as np
|
||||
|
||||
def get_clusters():
|
||||
# Set up the Overpass API query
|
||||
query = """
|
||||
[out:json];
|
||||
node["man_made"="surveillance"]["surveillance:type"="ALPR"];
|
||||
out body;
|
||||
"""
|
||||
|
||||
# Request data from Overpass API
|
||||
print("Requesting data from Overpass API.")
|
||||
url = "http://overpass-api.de/api/interpreter"
|
||||
response = requests.get(url, params={'data': query}, headers={'User-Agent': 'DeFlock/1.0'})
|
||||
data = response.json()
|
||||
print("Data received. Parsing nodes...")
|
||||
|
||||
# Parse nodes and extract lat/lon for clustering
|
||||
coordinates = []
|
||||
node_ids = []
|
||||
for element in data['elements']:
|
||||
if element['type'] == 'node':
|
||||
coordinates.append([element['lat'], element['lon']])
|
||||
node_ids.append(element['id'])
|
||||
|
||||
# Convert coordinates to NumPy array for DBSCAN
|
||||
coordinates = np.array(coordinates)
|
||||
|
||||
# Define the clustering radius (10 miles in meters)
|
||||
radius_miles = 50
|
||||
radius_km = radius_miles * 1.60934 # 1 mile = 1.60934 km
|
||||
radius_in_radians = radius_km / 6371.0 # Earth's radius in km
|
||||
|
||||
# Perform DBSCAN clustering
|
||||
db = DBSCAN(eps=radius_in_radians, min_samples=1, algorithm='ball_tree', metric='haversine').fit(np.radians(coordinates))
|
||||
labels = db.labels_
|
||||
|
||||
# Prepare clusters and calculate centroids
|
||||
clusters = {}
|
||||
for label in set(labels):
|
||||
cluster_points = coordinates[labels == label]
|
||||
centroid = np.mean(cluster_points, axis=0)
|
||||
first_node_id = node_ids[labels.tolist().index(label)]
|
||||
|
||||
# Store in clusters dict with centroid and first node ID
|
||||
clusters[label] = {
|
||||
"lat": centroid[0],
|
||||
"lon": centroid[1],
|
||||
"id": first_node_id
|
||||
}
|
||||
|
||||
output = {"clusters": list(clusters.values())}
|
||||
print("Clustering complete.")
|
||||
return output
|
||||
|
||||
|
||||
def lambda_handler(event, context):
|
||||
alpr_clusters = get_clusters()
|
||||
|
||||
s3 = boto3.client('s3')
|
||||
bucket = 'deflock-clusters'
|
||||
key = 'alpr_clusters.json'
|
||||
|
||||
s3.put_object(
|
||||
Bucket=bucket,
|
||||
Key=key,
|
||||
Body=json.dumps(alpr_clusters),
|
||||
ContentType='application/json'
|
||||
)
|
||||
|
||||
return {
|
||||
'statusCode': 200,
|
||||
'body': 'Successfully fetched ALPR counts.',
|
||||
}
|
||||
4
serverless/alpr_clusters/src/requirements.txt
Normal file
4
serverless/alpr_clusters/src/requirements.txt
Normal file
@@ -0,0 +1,4 @@
|
||||
boto3
|
||||
requests
|
||||
scikit-learn
|
||||
numpy
|
||||
17
terraform/main.tf
Normal file
17
terraform/main.tf
Normal file
@@ -0,0 +1,17 @@
|
||||
provider "aws" {
|
||||
region = "us-east-1"
|
||||
}
|
||||
|
||||
module "alpr_counts" {
|
||||
module_name = "alpr_counts"
|
||||
source = "./modules/alpr_counts"
|
||||
deflock_stats_bucket = var.deflock_stats_bucket
|
||||
rate = "rate(60 minutes)"
|
||||
}
|
||||
|
||||
module "alpr_clusters" {
|
||||
module_name = "alpr_clusters"
|
||||
source = "./modules/alpr_clusters"
|
||||
deflock_stats_bucket = var.deflock_stats_bucket
|
||||
rate = "rate(1 day)"
|
||||
}
|
||||
72
terraform/modules/alpr_clusters/main.tf
Normal file
72
terraform/modules/alpr_clusters/main.tf
Normal file
@@ -0,0 +1,72 @@
|
||||
resource "aws_iam_role" "lambda_role" {
|
||||
name = "${var.module_name}_lambda_s3_write_role"
|
||||
|
||||
assume_role_policy = jsonencode({
|
||||
Version = "2012-10-17"
|
||||
Statement = [
|
||||
{
|
||||
Action = "sts:AssumeRole"
|
||||
Effect = "Allow"
|
||||
Principal = {
|
||||
Service = "lambda.amazonaws.com"
|
||||
}
|
||||
}
|
||||
]
|
||||
})
|
||||
}
|
||||
|
||||
resource "aws_iam_policy" "lambda_s3_write_policy" {
|
||||
name = "${var.module_name}_lambda_s3_write_policy"
|
||||
description = "Policy for Lambda to write to S3 bucket ${var.deflock_stats_bucket}"
|
||||
|
||||
policy = jsonencode({
|
||||
Version = "2012-10-17"
|
||||
Statement = [
|
||||
{
|
||||
Action = [
|
||||
"s3:PutObject",
|
||||
"s3:PutObjectAcl"
|
||||
]
|
||||
Effect = "Allow"
|
||||
Resource = "arn:aws:s3:::${var.deflock_stats_bucket}/${var.output_filename}"
|
||||
}
|
||||
]
|
||||
})
|
||||
}
|
||||
|
||||
resource "aws_iam_role_policy_attachment" "lambda_s3_write_attachment" {
|
||||
role = aws_iam_role.lambda_role.name
|
||||
policy_arn = aws_iam_policy.lambda_s3_write_policy.arn
|
||||
}
|
||||
|
||||
resource "aws_lambda_function" "overpass_lambda" {
|
||||
function_name = var.module_name
|
||||
role = aws_iam_role.lambda_role.arn
|
||||
package_type = "Image"
|
||||
image_uri = "${aws_ecr_repository.lambda_repository.repository_url}:latest"
|
||||
timeout = 90
|
||||
}
|
||||
|
||||
resource "aws_cloudwatch_event_rule" "lambda_rule" {
|
||||
name = "${var.module_name}_rule"
|
||||
description = "Rule to trigger ${var.module_name} lambda"
|
||||
schedule_expression = var.rate
|
||||
}
|
||||
|
||||
resource "aws_cloudwatch_event_target" "lambda_target" {
|
||||
target_id = "${var.module_name}_target"
|
||||
rule = aws_cloudwatch_event_rule.lambda_rule.name
|
||||
arn = aws_lambda_function.overpass_lambda.arn
|
||||
}
|
||||
|
||||
resource "aws_lambda_permission" "allow_cloudwatch_to_call_lambda" {
|
||||
statement_id = "AllowExecutionFromCloudWatch"
|
||||
action = "lambda:InvokeFunction"
|
||||
function_name = aws_lambda_function.overpass_lambda.function_name
|
||||
principal = "events.amazonaws.com"
|
||||
source_arn = aws_cloudwatch_event_rule.lambda_rule.arn
|
||||
}
|
||||
|
||||
resource "aws_ecr_repository" "lambda_repository" {
|
||||
name = "${var.module_name}-lambda"
|
||||
}
|
||||
3
terraform/modules/alpr_clusters/outputs.tf
Normal file
3
terraform/modules/alpr_clusters/outputs.tf
Normal file
@@ -0,0 +1,3 @@
|
||||
output "ecr_repository_url" {
|
||||
value = aws_ecr_repository.lambda_repository.repository_url
|
||||
}
|
||||
16
terraform/modules/alpr_clusters/variables.tf
Normal file
16
terraform/modules/alpr_clusters/variables.tf
Normal file
@@ -0,0 +1,16 @@
|
||||
variable "module_name" {
|
||||
description = "Name of the module"
|
||||
}
|
||||
|
||||
variable "output_filename" {
|
||||
description = "Filename for the ALPR clusters JSON file"
|
||||
default = "alpr_clusters.json"
|
||||
}
|
||||
|
||||
variable "deflock_stats_bucket" {
|
||||
description = "S3 bucket for the ALPR clusters JSON file"
|
||||
}
|
||||
|
||||
variable "rate" {
|
||||
description = "Rate at which to run the Lambda function"
|
||||
}
|
||||
@@ -1,12 +1,3 @@
|
||||
locals {
|
||||
alpr_counts_filename = "alpr-counts.json"
|
||||
}
|
||||
|
||||
|
||||
provider "aws" {
|
||||
region = "us-east-1"
|
||||
}
|
||||
|
||||
resource "aws_iam_role" "lambda_role" {
|
||||
name = "lambda_s3_write_role"
|
||||
|
||||
@@ -26,7 +17,7 @@ resource "aws_iam_role" "lambda_role" {
|
||||
|
||||
resource "aws_iam_policy" "lambda_s3_write_policy" {
|
||||
name = "lambda_s3_write_policy"
|
||||
description = "Policy for Lambda to write to S3 bucket deflock-clusters"
|
||||
description = "Policy for Lambda to write to S3 bucket ${var.deflock_stats_bucket}"
|
||||
|
||||
policy = jsonencode({
|
||||
Version = "2012-10-17"
|
||||
@@ -37,7 +28,7 @@ resource "aws_iam_policy" "lambda_s3_write_policy" {
|
||||
"s3:PutObjectAcl"
|
||||
]
|
||||
Effect = "Allow"
|
||||
Resource = "arn:aws:s3:::deflock-clusters/${local.alpr_counts_filename}"
|
||||
Resource = "arn:aws:s3:::${var.deflock_stats_bucket}/${var.output_filename}"
|
||||
}
|
||||
]
|
||||
})
|
||||
@@ -51,43 +42,43 @@ resource "aws_iam_role_policy_attachment" "lambda_s3_write_attachment" {
|
||||
resource "null_resource" "pip_install" {
|
||||
provisioner "local-exec" {
|
||||
command = <<EOT
|
||||
cd ${path.module}/../serverless/alpr-counts/src
|
||||
cd ${path.root}/../serverless/${var.module_name}/src
|
||||
pip3 install -r requirements.txt -t .
|
||||
EOT
|
||||
}
|
||||
|
||||
triggers = {
|
||||
# Re-run the provisioner if the file changes
|
||||
file_hash = "${filemd5("${path.module}/../serverless/alpr-counts/src/alpr_counts.py")}"
|
||||
file_hash = "${filemd5("${path.root}/../serverless/${var.module_name}/src/${var.module_name}.py")}"
|
||||
}
|
||||
}
|
||||
|
||||
data "archive_file" "python_lambda_package" {
|
||||
type = "zip"
|
||||
source_dir = "${path.module}/../serverless/alpr-counts/src"
|
||||
output_path = "${path.module}/../serverless/alpr-counts/lambda.zip"
|
||||
source_dir = "${path.root}/../serverless/${var.module_name}/src"
|
||||
output_path = "${path.root}/../serverless/${var.module_name}/lambda.zip"
|
||||
|
||||
depends_on = [ null_resource.pip_install ]
|
||||
}
|
||||
|
||||
resource "aws_lambda_function" "overpass_lambda" {
|
||||
filename = data.archive_file.python_lambda_package.output_path
|
||||
function_name = "alpr_counts"
|
||||
function_name = var.module_name
|
||||
role = aws_iam_role.lambda_role.arn
|
||||
handler = "alpr_counts.lambda_handler"
|
||||
handler = "${var.module_name}.lambda_handler"
|
||||
runtime = "python3.9"
|
||||
source_code_hash = data.archive_file.python_lambda_package.output_base64sha256
|
||||
timeout = 30
|
||||
}
|
||||
|
||||
resource "aws_cloudwatch_event_rule" "lambda_rule" {
|
||||
name = "alpr_counts_rule"
|
||||
description = "Rule to trigger alpr_counts lambda"
|
||||
schedule_expression = "rate(60 minutes)"
|
||||
name = "${var.module_name}_rule"
|
||||
description = "Rule to trigger ${var.module_name} lambda"
|
||||
schedule_expression = var.rate
|
||||
}
|
||||
|
||||
resource "aws_cloudwatch_event_target" "lambda_target" {
|
||||
target_id = "alpr_counts_target"
|
||||
target_id = "${var.module_name}_target"
|
||||
rule = aws_cloudwatch_event_rule.lambda_rule.name
|
||||
arn = aws_lambda_function.overpass_lambda.arn
|
||||
}
|
||||
16
terraform/modules/alpr_counts/variables.tf
Normal file
16
terraform/modules/alpr_counts/variables.tf
Normal file
@@ -0,0 +1,16 @@
|
||||
variable "module_name" {
|
||||
description = "Name of the module"
|
||||
}
|
||||
|
||||
variable "output_filename" {
|
||||
description = "Filename for the ALPR counts JSON file"
|
||||
default = "alpr-counts.json"
|
||||
}
|
||||
|
||||
variable "deflock_stats_bucket" {
|
||||
description = "S3 bucket for the ALPR counts JSON file"
|
||||
}
|
||||
|
||||
variable "rate" {
|
||||
description = "Rate at which to run the Lambda function"
|
||||
}
|
||||
39
terraform/remote-backend.tf
Normal file
39
terraform/remote-backend.tf
Normal file
@@ -0,0 +1,39 @@
|
||||
resource "aws_s3_bucket" "terraform_state" {
|
||||
bucket = "deflock-terraform-state"
|
||||
|
||||
tags = {
|
||||
Name = "Terraform State Bucket"
|
||||
}
|
||||
}
|
||||
|
||||
resource "aws_s3_bucket_versioning" "enable_versioning" {
|
||||
bucket = aws_s3_bucket.terraform_state.id
|
||||
versioning_configuration {
|
||||
status = "Enabled"
|
||||
}
|
||||
}
|
||||
|
||||
resource "aws_dynamodb_table" "terraform_locks" {
|
||||
name = "deflock-terraform-state-locks"
|
||||
billing_mode = "PAY_PER_REQUEST"
|
||||
hash_key = "LockID"
|
||||
|
||||
attribute {
|
||||
name = "LockID"
|
||||
type = "S"
|
||||
}
|
||||
|
||||
tags = {
|
||||
Name = "Terraform State Lock Table"
|
||||
}
|
||||
}
|
||||
|
||||
terraform {
|
||||
backend "s3" {
|
||||
bucket = "deflock-terraform-state"
|
||||
key = "global/s3/terraform.tfstate"
|
||||
region = "us-east-1"
|
||||
dynamodb_table = "terraform-state-locks"
|
||||
encrypt = true
|
||||
}
|
||||
}
|
||||
4
terraform/variables.tf
Normal file
4
terraform/variables.tf
Normal file
@@ -0,0 +1,4 @@
|
||||
variable "deflock_stats_bucket" {
|
||||
description = "S3 bucket for the ALPR counts JSON file"
|
||||
default = "deflock-clusters"
|
||||
}
|
||||
Reference in New Issue
Block a user