See how much more you can get out of GitHub Codespaces by taking advantage of the improved processing power and increased headroom in the next generation of virtual machines.
Overview
The article discusses how GitHub has optimized its Codespaces costs by upgrading to new virtual machines that offer improved performance at reduced costs. By leveraging AMD-based hosts, GitHub has doubled RAM and enhanced CPU performance, resulting in significant cost savings for developers.
What You'll Learn
1
How to optimize GitHub Codespaces costs by upgrading virtual machines
2
Why using AMD-based hosts can improve developer experience and reduce costs
3
How to test smaller virtual machines in your development environment
Key Questions Answered
How does upgrading to new virtual machines affect GitHub Codespaces costs?
Upgrading to new virtual machines has allowed GitHub to provide users with double the RAM and 10-30% improved CPU performance, enabling the same or better machine performance for half the cost of the previous generation. This change results in approximately 50% savings for GitHub.
What impact did the new virtual machines have on developer experience?
The new virtual machines improved developer experience by eliminating the need to overprovision CPUs for memory-intensive workloads. Developers can now achieve high performance without sacrificing productivity or incurring additional costs.
What steps did GitHub take to test the new virtual machines?
GitHub's internal developer experience team tested the new machines by moving teams with RAM-hungry workflows to machines with half the CPU count but the same RAM. The tests showed no negative impacts and confirmed that developers were just as successful on the smaller machines.
How can organizations implement similar cost-saving measures with GitHub Codespaces?
Organizations can implement similar cost-saving measures by encouraging development teams to test smaller virtual machines in their existing environments. Most configurations remain unchanged, making it easy to find the optimal machine type for performance and cost.
Key Statistics & Figures
Cost savings from new virtual machines
50%
Achieved by GitHub after transitioning to AMD-based hosts.
Improved CPU performance
10-30%
Realized by adopting new virtual machines.
RAM increase
Twice the RAM
Provided to all users with the new virtual machines.
Technologies & Tools
Development Environment
Github Codespaces
Used for building and testing applications in a cloud-based environment.
Hardware
Amd
Used as the basis for new virtual machines that enhance performance.
Key Actionable Insights
1Consider transitioning to AMD-based virtual machines to reduce development costs while maintaining performance.This transition can lead to significant savings, as demonstrated by GitHub's experience of achieving approximately 50% cost reductions.
2Encourage your development teams to experiment with smaller virtual machines to optimize resource usage.Testing smaller machines can help identify the best balance between performance and cost, allowing teams to work efficiently without unnecessary expenses.
3Implement policies to restrict machine types based on performance needs and cost considerations.By setting such policies, organizations can ensure that developers have the necessary resources while controlling costs effectively.
Common Pitfalls
1
Overprovisioning CPUs for memory-intensive workloads can lead to unnecessary costs and complexity.
This often occurs when developers are forced to choose between performance and cost, leading to frustration and inefficiencies.