If you're not familiar, AWS Direct Connect lets you hook up your on-prem network directly to AWS.

We had about 85 Direct Connect connections spread out over various AWS regions. Not all of these were active, and manually checking each one wasn't a practical solution. Plus, these connections are managed by different teams and external partners, so just turning one off to see if someone complains wasn't an option—reactivating them can be a real pain.

I went with Python for the script because it's straightforward and widely used. Boto3 is the go-to AWS SDK for Python, letting you directly manage AWS resources. It was the perfect tool for automating checks across our AWS services.

The script does a few simple things:

1. Connects to AWS Direct Connect to get a list of all our connections.
2. Pulls data transfer metrics from CloudWatch for each connection.
3. Calculates the average data transfer rates to figure out if a connection is active or just sitting idle.

Here’s a peek at part of the script:

import boto3
from datetime import datetime, timedelta

# Initialize clients for Direct Connect and CloudWatch
cloudwatch = boto3.client('cloudwatch')
directconnect = boto3.client('directconnect')

# Set up the time period to check for the last 30 days
end_time = datetime.now()
start_time = end_time - timedelta(days=30)

# Fetch all Direct Connect connections
dx_connections = directconnect.describe_connections()['connections']

for connection in dx_connections:
    connection_id = connection['connectionId']
    print(f"Checking metrics for Direct Connect ID: {connection_id}")

    # Check data transfer rates
    for metric_name in ['DataInRate', 'DataOutRate']:
        response = cloudwatch.get_metric_statistics(
            Namespace='AWS/DX',
            MetricName=metric_name,
            Dimensions=[{'Name': 'ConnectionId', 'Value': connection_id}],
            StartTime=start_time,
            EndTime=end_time,
            Period=3600,  # One hour
            Statistics=['Average']
        )

        # Analyze the response
        if response['Datapoints']:
            average = sum(d['Average'] for d in response['Datapoints']) / len(response['Datapoints'])
            print(f" - {metric_name} average: {average} Mbps")
        else:
            print(f" - {metric_name} has no data. This connection might not be in use.")

I’ve put this script on GitHub so anyone can use it, tweak it, or improve it. It’s all there in the README on how to set it up and run it.

Eventually, we found out that none of the Direct Connect connections were being used anymore. We ended up removing all of them. However, automating this check has saved us a lot of time.

That reminded me of my early days. Around the end of the 90s, I was using Linux. I jumped from Slackware to Mandrake, tinkering with some projects. I was amazed by the amount of information available on the internet. Although programming was not my number one passion, it was a way to make things happen. I have been coding since I was a kid. It started with copying code from magazines into my uncle's Commodore 64.

I wasn't so collaborative back then. I was just a consumer of open source. I was surprised to find out I could contribute. However, the groups I found could have been more welcoming. It felt like a closed club. My excitement faded fast. For many, even the purpose of the contribution was to have control over the project, and as an outsider, you don't have a say in it when you don't pay for something. That was the mentality.

It changed a lot when GitHub came along. It became easy to contribute and find projects to contribute to. The community also became more welcoming. Main contributors became more pragmatic rather than protective.

I was on a Discord channel recently, helping people with their questions. Suddenly, it struck me that developers are spending so much effort on things that are not the primary concern of their projects.

There is so much need for practical examples and solutions. I decided to share some of the obstacles I come across and how I solve them.