jonathanhle

import boto3

def get_instance_name(fid):
    """
        When given an instance ID as str e.g. 'i-1234567', return the instance 'Name' from the name tag.
        :param fid:
        :return:
    """
    ec2 = boto3.resource('ec2')
    ec2instance = ec2.Instance(fid)

jonathanhle

•  Releases Managed
    •	You have to have some type of deployable software object before you can do anything.
    •	The object here is the AMI, container, deb, zip, something
•  Deployments are Automated
    •	Now that you have a deployable software object, you have to automate the deployment.
•  APIs for Observability
    •	Both before and after the object is deployed, you're going to have spend some time instrumenting/researching what characteristics need to be exposed for monitoring at runtime.
    •	What should be measured so we can do whatever is needed to ensure the systems keep working optimally
•  Monitoring & Alerting
    •	Using the APIs, logs, whatever from above, implement monitoring and alerting on KPIs

jonathanhle

#!/usr/bin/env bash
#
# gh-dl-release! It works!
# 
# This script downloads an asset from latest or specific Github release of a
# private repo. Feel free to extract more of the variables into command line
# parameters.
#
# PREREQUISITES
#

jonathanhle

import boto3
import csv

# define header row and start a row_list with the header present
header_row = ["account_id", "aws_region", "environment", "instance_id", "instance_name", "security_groups"]
row_list = [header_row]

regions = ["us-east-1", "us-west-2"]

# ---------------------------------------------------------------------------------------------------------------------

jonathanhle

{
  "Comment": "Invoke Lambda every 10 seconds",
  "StartAt": "ConfigureCount",
  "States": {
    "ConfigureCount": {
      "Type": "Pass",
      "Result": {
        "index": 0,
        "count": 6
      },

jonathanhle

# Cancel Pending Runs
export project_env="nonprod"
export project_prefix="project-prefix-yada-foo-bar"
export working_workspaces=$(tfh workspace list | grep ${project_prefix} | grep ${project_env})

for wrkspace in ${working_workspaces}:
  do
    echo $wrkspace
    pending_run=`tfh run list -name ${wrkspace} | grep "pending" | awk '{print $1}' | head -n 1`

jonathanhle

resource "aws_lambda_function" "service" {
  # Your usual aws_lambda_function configuration settings here

  tracing_config {
    mode = "Active"
  }
}

jonathanhle

Keybase proof

I hereby claim:

• I am jonathanhle on github.
• I am jonathanhle (https://keybase.io/jonathanhle) on keybase.
• I have a public key ASBc9Jif9zaS6tJIibA947uteCd8_WfgcY560sBj5XzsBgo

To claim this, I am signing this object:

jonathanhle

import boto3
import hvac
import ssl
#ssl._create_default_https_context = ssl._create_unverified_context

session = boto3.Session()
credentials = session.get_credentials()

client = hvac.Client(verify=False)
client.auth_aws_iam(credentials.access_key, credentials.secret_key, credentials.token, role='example-role', header_value='vault.service.consul')

jonathanhle

vault_aws_auth

These are python 2 and 3 snippets showing how to generate headers to authenticate with HashiCorp's Vault using the AWS authentication method. There's also a Ruby implementation which uses version 3 of the AWS SDK for Ruby.

The python scripts look for credentials in the default boto3 locations; if you need to supply custom credentials (such as from an AssumeRole call), you would use the botocore.session.set_credentials method before calling create_client.