Datadog agent changelog : https://github.com/DataDog/datadog-agent/blob/main/CHANGELOG.rst
Datadog helm chart changelog : https://github.com/DataDog/helm-charts/blob/main/charts/datadog/CHANGELOG.md
Datadog helm chart readme : https://github.com/DataDog/helm-charts/tree/main/charts/datadog

It's worth to think about your rollup/aggregation strategy

For metrics-like errors, its better to show the worst case scenario with max/max

You want to really understand decorators? Watch this video!

boilerplate:

import functools

def decorator(func):
    @functools.wraps(func)
    def wrapper_decorator(*args, **kwargs):
        # Do something before
        value = func(*args, **kwargs)
        # Do something after
        return value
    return wrapper_decorator

• https://realpython.com/primer-on-python-decorators/

• https://kubernetes.io/docs/concepts/storage/dynamic-provisioning/

• https://www.youtube.com/watch?v=hTjHuoWxsks
• https://timber.io/blog/promql-for-humans/
• https://promlabs.com/promql-cheat-sheet/
• https://prometheus.io/docs/prometheus/latest/querying/basics/

def bubbleSort(arr):
n = len(arr)

# Traverse through all array elements
for i in range(n):

    # Last i elements are already in place
    for j in range(0, n-i-1):

        # traverse the array from 0 to n-i-1
        # Swap if the element found is greater
        # than the next element
        if arr[j] > arr[j+1] :
            arr[j], arr[j+1] = arr[j+1], arr[j

• https://docs.aws.amazon.com/AmazonCloudFront/latest/DeveloperGuide/ServingCompressedFiles.html