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bhoobalan-bhoo/hyperswitch-aws-toolkit

Analysis updated 2026-05-18

3PythonAudience · ops devopsComplexity · 4/5LicenseSetup · moderate

TLDR

A Python toolkit that adds security, monitoring, alerting, and incident response for running Hyperswitch payments on AWS.

Mindmap

mindmap
  root((repo))
    What it does
      Security audits
      Monitoring dashboards
      Incident response flow
    Tech stack
      Python
      AWS
      Grafana
      CloudWatch
    Use cases
      Harden Hyperswitch security
      Track payment costs
      Respond to production incidents
    Audience
      DevOps engineers
      Fintech operators
    Setup
      pip install deps
      Needs AWS CLI and kubectl
    Notes
      MIT licensed
      PCI-DSS checks included

Code map

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filefunction / class

What do people build with it?

USE CASE 1

Audit IAM, VPC, and secrets exposure for a Hyperswitch deployment on AWS.

USE CASE 2

Set up CloudWatch alarms and Grafana dashboards for payment traffic.

USE CASE 3

Follow a defined incident response flow when a payment connector fails.

USE CASE 4

Estimate and track AWS costs for a Hyperswitch deployment by transaction volume.

What is it built with?

PythonAWSGrafanaCloudWatchboto3

How does it compare?

bhoobalan-bhoo/hyperswitch-aws-toolkit0marildo/imagoagentlexi/agent-lexi
Stars333
LanguagePythonPythonPython
Setup difficultymoderateeasymoderate
Complexity4/52/54/5
Audienceops devopsgeneralvibe coder

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · moderate Time to first run · 1h+

Requires an existing Hyperswitch deployment on AWS plus AWS CLI, kubectl, and Helm access.

Use freely for any purpose, including commercial use, as long as you keep the copyright notice.

In plain English

hyperswitch-aws-toolkit is a Python-based collection of scripts for running Hyperswitch, an open source payment orchestration platform, safely in production on AWS. Hyperswitch itself already has a deployment guide, but the author found nothing to help watch over it once it was running: no runbooks, no alerts, no defined way to respond when something broke. This toolkit fills that gap, covering security hardening, observability, alerting, incident response, cost tracking, and chaos testing after the initial deploy is done. The toolkit is organized into folders by purpose. A security folder audits IAM permissions, VPC network exposure, and secrets stored in plaintext. A compliance folder checks PCI-DSS v4.0 controls and CloudTrail logging. An observability folder sets up CloudWatch alarms and Grafana dashboards, and can route alerts to Slack or email. An operations folder streams live logs and detects anomalies. A runbooks folder holds step by step guides for specific problems like connector failures, high latency, database issues, or crashed pods. A resilience folder handles chaos and load testing, and a cost folder estimates AWS spending based on transaction volume or pulls real numbers from AWS Cost Explorer. Getting started means installing a handful of Python packages such as boto3, pyyaml, and requests, or simply running a bash script that sets up a virtual environment and drops the user into an interactive menu covering all the checks, alarms, and dashboards. Before configuring anything, a user edits a YAML config file with their AWS region, cluster and database names, alert thresholds, and a Slack webhook URL. The incident response flow described in the README runs through several of these scripts in sequence: an anomaly detector flags a problem, a classifier assigns it a priority level, an escalation script creates the incident and sends a notification, and the responder follows the matching runbook before marking it acknowledged or resolved. The toolkit also includes a connector capability matrix comparing which payment methods providers like Stripe, Adyen, Razorpay, PayPal, and Klarna support, and rough monthly cost tiers ranging from about 120 dollars for small setups to over 2,000 dollars for large ones. It requires Python 3.9 or newer, the AWS CLI, kubectl, and Helm, and is released under the MIT License.

Copy-paste prompts

Prompt 1
Help me run start.sh and walk through the interactive menu for hyperswitch-aws-toolkit.
Prompt 2
Explain what security/iam_hardening.py checks and how to fix a failing finding.
Prompt 3
Show me how to import the Grafana dashboards from grafana_setup.py into my Grafana instance.
Prompt 4
Walk me through the incident flow from anomaly detection to escalation in this toolkit.

Frequently asked questions

What is hyperswitch-aws-toolkit?

A Python toolkit that adds security, monitoring, alerting, and incident response for running Hyperswitch payments on AWS.

What language is hyperswitch-aws-toolkit written in?

Mainly Python. The stack also includes Python, AWS, Grafana.

What license does hyperswitch-aws-toolkit use?

Use freely for any purpose, including commercial use, as long as you keep the copyright notice.

How hard is hyperswitch-aws-toolkit to set up?

Setup difficulty is rated moderate, with roughly 1h+ to a first successful run.

Who is hyperswitch-aws-toolkit for?

Mainly ops devops.

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