Automating testing for Time-to-Restore in GitHub Actions is essential for ensuring that your deployment process is efficient and that you can quickly recover from failures. By leveraging GitHub Actions, you can create workflows that measure the time taken to restore your services after an incident.
# .github/workflows/test-time-to-restore.yml
name: Test Time To Restore
on:
push:
branches:
- main
jobs:
restore-test:
runs-on: ubuntu-latest
steps:
- name: Checkout code
uses: actions/checkout@v2
- name: Start the service
run: |
# Start your service here
# Simulating service start with a sleep command
echo "Starting service..."
sleep 10 # Simulating the time taken to start the service
- name: Measure time to restore
run: |
START_TIME=$(date +%s)
# Simulate service failure and restoration
echo "Simulating service failure..."
sleep 5 # Simulating service failure
echo "Restoring service..."
sleep 10 # Simulating time to restore the service
END_TIME=$(date +%s)
RESTORE_TIME=$(( END_TIME - START_TIME ))
echo "Time to restore: $RESTORE_TIME seconds"
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
How do I avoid rehashing overhead with std::set in multithreaded code?
How do I find elements with custom comparators with std::set for embedded targets?
How do I erase elements while iterating with std::set for embedded targets?
How do I provide stable iteration order with std::unordered_map for large datasets?
How do I reserve capacity ahead of time with std::unordered_map for large datasets?
How do I erase elements while iterating with std::unordered_map in multithreaded code?
How do I provide stable iteration order with std::map for embedded targets?
How do I provide stable iteration order with std::map in multithreaded code?
How do I avoid rehashing overhead with std::map in performance-sensitive code?
How do I merge two containers efficiently with std::map for embedded targets?