Get My IP and patch AWS Security Group

My particular use case was that In my own AWS Account where I do most of the R&D I had one security group which was only for me doing SSH into EC2 instances. Way back in 2020 during pandemic season, had to go freelance for sometime while in notice period with one company and in negotiation with another one. Well this time I was mostly connected from mobile hotspot switching from JIO on Galaxy M14 to Airtel on Galaxy A54 and BSNL on second sim of M14 and this was causing my security group update a real pain.

Basically being lazy and having devops and automation since long back. Started working on an idea an the outcome was an AWS Serverless clone of what is my ip service which is named echo my ip. Check it out on github. The nodejs code and aws sam template to deploy is given over there.

Next using the standard Ubuntu terminal text editor added the following to the .bash_aliases file.

sgupdate()
{
  currentip=$(curl --silent https://{api gateway url}/Prod/ip/)
  /usr/local/bin/aws ec2 describe-security-groups --group-id $AWS_SECURITY_GROUP > /dev/shm/permissions.json
  grep CidrIp /dev/shm/permissions.json | grep -v '/0' | awk -F'"' '{print $4}' | while read cidr;
   do
     /usr/local/bin/aws ec2 revoke-security-group-ingress --group-id $AWS_SECURITY_GROUP --ip-permissions "FromPort=-1,IpProtocol=-1,IpRanges=[{CidrIp=$cidr}]"
   done   
  /usr/local/bin/aws ec2 authorize-security-group-ingress --group-id $AWS_SECURITY_GROUP --protocol "-1" --cidr "$currentip/32"
}

alias aws-permit-me='sgupdate'

I already have a .env file for every project I am handling and a cd command will check for existance of .env and source it in case it exists.

cwd(){
  cd $1
  if [ -f .env ] ; then
    . .env
  fi
}

alias cd='cwd'

The env file is of structure as follows with coresponding values after the ‘=’ ofcourse.

export AWS_DEFAULT_REGION=
export AWS_ACCESS_KEY_ID=
export AWS_SECRET_ACCESS_KEY=
export AWS_SECURITY_GROUP=
export AWS_SSH_ID=
export AWS_ACCOUNT=

It’s a common problem for people working from home with dynamic IPs to manage firewall rules. Automating the process with a serverless function and a shell alias is a great way to simplify things. Sharing on github is to help others and provide back to the community.

This method provides some advantages

  • Automation: Eliminates the tedious manual process of updating security group rules.
  • Serverless: Cost-effective, as you only pay for the compute time used.
  • Shell Alias: Provides a convenient and easy-to-remember way to trigger the update.
  • GitHub Sharing: Makes the solution accessible to others.
  • Secure: Security Group Modification uses aws cli and credentials in terminal environment

Publish Lambda Layers across Regions

This could even be classified as re:Inventing the wheel but was a quick hack workaround that I found at the early stages where we required a set of node.js libraries and custom modules across multiple regions, in fact, I needed this in only 5 regions. Since these libraries and modules could have frequent updates, I wanted the latest package to be updated and published as a new layer version to each region and concerned developers be notified about the new layer version as well as the changelog. Well, to make the long story short, I was at that time familiar with subversion, and the project code was committed to an svn repository. This could have biased me to use the following solution at that time period, rather now my preference would be either “Multi-Region Deployment” using cloud formation or “CodeCommit and CodePipeline with SNS” instead of S3 triggers.

The architecture is simple and was deployed manually at that time. Sorry to say that I no longer have any access to the aws account, as it is a discarded community project and the account is closed at this time. Thought about posting the idea over here since there was a discussion or rather query about this in a community forum.

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Refactored a Complicated Lambda to use Layers and split it up

Till recently, in fact, till last week, was not too worried about writing all code into single code folder, and mapping multiple AWS::Serverless::Function into individual named handlers. Till I stumbled on this article, where I started wondering how my folder structure and sam templates were going into the stack. A detailed inspection was not required, though this was the time when I used the GUI ( after a long time ). But the outcome showed how pathetic the condition was.

The lambda console with the filter “aws:cloudformation:stack-name: <stack>”

Well, it is clear that the whole mess is being uploaded into all the function code. What does this mean – holy grail, any one small change here or there, would update all the functions – last modified is the same, all functions will have the node_modules and other artifacts like templates and custom modules.

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Export Cloudwatch Logs to AWS S3 – Deploy using SAM

With due reference to the blog which helped me in the right direction, the Tensult blogs article Exporting of AWS CloudWatch logs to S3 using Automation, though at some points I have deviated from the original author’s suggestion.

Some points are blindly my preference and some other due to the suggested best practices. I do agree that starters, would be better off with setting IAM policies with ‘*’ in the resource field. But when you move things into production it is recommended to use least required permissions. Also, some critical policies were missing from the assume role policy. Another unnecessary activity was the checking of the existence of s3 bucket and attempt to create if not exists, at each repeated execution. Again for this purpose the lambda role needed create bucket permission. All these were over my head, and the outcome is this article.

Well if you need CloudWatch logs to be exported to S3 for whatever reason, this could save your time a lot, though this needs to be run in every different region where you need to deploy the stack. Please excuse me as the whole article expects to have aws-cli and sam-cli pre-installed.

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