From: thepipeline_xyz
High transaction volume presents significant challenges for blockchain systems, particularly during high-demand events. The goal for such systems is to avoid making excuses when they fail to stand up under stress [00:00:20].
Scenarios Causing High Volume
One anticipated scenario involves 100,000 concurrent users attempting to send 100 transactions per second [00:00:00]. A prime example of such a stress event is an NFT mint, where a large number of users simultaneously “slam the system” [00:00:04].
Common Failures During High Demand
During periods of high transaction volume, common issues that arise include:
- RPC (Remote Procedure Call) failures [00:00:23]
- Transactions getting reverted [00:00:25]
These types of problems often become public on social media when systems malfunction [00:00:27].
Real-World Examples
A notable example of high transaction volume challenges was the user experience on Solana in the fall of 2021 [00:00:35]. This situation was characterized by people globally “absolutely spam clicking mint buttons” [00:00:45], an event difficult to anticipate in advance [00:00:43].
Future Stress Testing with AI
To further test system resilience, there’s interest in using AI agents on testnets [00:00:50]. The combination of AI and high throughput could yield insightful results [00:00:55]. By incentivizing AI to intentionally crash the testnet, developers can simulate extreme load conditions beyond typical human activity [00:00:58]. This approach aims to optimize systems and ensure they handle such volumes gracefully [00:00:09].