From: thepipeline_xyz
Blockchain systems, particularly those aiming for high throughput, require robust stress testing to ensure stability under extreme loads [00:00:18]. The goal is to simulate scenarios such as 100,000 concurrent users attempting to send 100 transactions per second or a massive NFT mint where “everyone slams an NFT at the same time” [00:00:00].
Current Stress Testing Challenges
Past experiences highlight the unpredictability of user behavior during high-demand events. For instance, the Solana network in fall 2021 experienced issues due to “people from across the globe absolutely spam clicking mint buttons” [00:00:45], a scenario that was difficult to anticipate [00:00:43]. Common problems that emerge under stress, often reported on Twitter, include:
- RPC failures [00:00:23]
- Transaction getting reverted [00:00:25]
The objective for new systems is to avoid making excuses when performance issues arise during high-stress situations [00:00:30]. Addressing these challenges is part of dealing with blockchain system failures.
Potential Role of AI Agents in Stress Testing
There is a growing interest in leveraging AI agents for stress testing on blockchain testnets [00:00:50]. The combination of AI and high throughput could yield “interesting results” [00:00:54].
Instead of human users, “robots clicking” could be utilized [00:01:02]. One proposed approach involves incentivizing these AI agents to intentionally try and crash the testnet [00:00:58], thereby pushing the system to its limits in ways human-driven tests might not achieve. This proactive approach aims to identify weaknesses and optimize the system for unforeseen loads [00:00:11].