Cardano Network Close to Reaching Maximum Capacity Amid 94% Congestion

Sebastien Guillemot, the Chief Technology Officer (CTO) of the Paima Ecosystem, recently shared that Cardano, one of the leading blockchain platforms, is operating at an overwhelming 94% of its total potential. In a detailed Twitter thread, Guillemot elucidated the consequences of the increasing transaction load and the potential effects on its user base.

It's crucial to understand, Guillemot emphasized, that Cardano nodes don't prioritize transactions. Instead, they abide by a first-in-first-out rule, contrasting with blockchains such as Bitcoin where users can pay higher fees to expedite their transactions.

Guillemot clarified that if Cardano's operating load hits its maximum capacity of 100%, all transactions, regardless of their characteristics, would join a queue. This situation could lead to one of three possible outcomes.

In the event of network congestion, Guillemot suggested that users might need to endure a considerable wait time for their transactions to be recorded on the blockchain. The more the load exceeds 100%, the longer the delay. Unfortunately, the Cardano protocol doesn't offer alternative mechanisms to accelerate transactions.

Another scenario at peak congestion could mean that some transactions may never make it to the blockchain. Guillemot pointed out that this might occur when light wallet meme pools reach their capacity. However, he reassured users that they would not be charged fees for transactions that fail to reach the blockchain.

When network congestion hits its maximum, Guillemot mentioned, stake pools may sell their priority access. These sales typically go to network users or decentralized applications (DApps). Consequently, he advised users to monitor the effects on the Decentralized Exchanges (DEXs) to discern the most suitable option during these periods.

Looking back at the bull market of 2021, Guillemot recalled that the Cardano network reached peak congestion. He confirmed that all three of the above scenarios occurred during that time. Guillemot believes that it's vital for users to understand these dynamics in preparation for potential similar situations in the future.