Here is the article:
** Metamask: Are Metamask gas estimates unreliable on L2 Testnets and bets?
As a developer working with layer 2 tests (L2), such as Arbitrum Sepolia and Unicoin, I noticed that transactions fail in a coherent way. One of the main reasons for this problem is dependence on Metamask gas estimates for the deployment of intelligent contracts. But are these estimates reliable both in the L2 test tests and the Mainnet environments?
** What are the gas estimates?
Gas estimates in blockchain networks like Ethereum, Polkadot or Solana are used to predict the calculation effort required to execute a particular transaction or call. These estimates provide approximate value for the quantity of gas necessary to deploy a function on the network.
The problem with Metamask gas estimates
According to my experience, Metamask gas estimates did not precisely reflect the real gas requirements from various functions. This was particularly problematic when I encountered transactions referred to during the deployment on L2 Testnets and the environments maintained. The differences between estimated and real gas consumption have led to inconsistent behavior, which affected the performance of my project.
L2 Testnets: Gas vs. Actual consumption
On L2 Testnets as Arbitrum Sepolia and Unicoin, I found that Metamask gas estimates were significantly lower than the real gas requirements for deployment functions. This has led to a substantial difference between estimated and real transaction times, resulting in delays or even the full abandonment of my project.
Mainnet environment: gas estimates vs. Actual consumption
In the Mainennet environment like Ethereum or Solana, Metamask gas estimates were generally exact, but not entirely reliable. Network conditions, such as available gas and transaction costs, could always lead to the variability of actual gas consumption compared to the estimated value.
** Why are gas estimates unreliable?
Several factors contribute to the lack of reliability of metamask gas estimates:
- Congestion of the network : high traffic on L2 test tests can lead to the congestion of the network, resulting in an increase in gas prices and reduced precision of gas estimation.
- Volatility of gas prices : Maintenance environments are subject to high fluctuations in gas prices, which can affect the estimated value.
- Complexity of transactions : complex intelligent contracts or function calls can lead to inaccurate gas estimates.
Conclusion
In conclusion, the reliability of metamask gas estimates on L2 fabric tests and the sector environment is an important concern for developers working with these networks. Although gas estimates are essential to plan and optimize the deployment of intelligent contracts, they must be cautious due to the potential inaccuracies associated with network congestion, the volatility of gas prices and the complexity of transactions.
To alleviate this problem, developers must:
- Monitor and analyze the conditions of the network : Regularly check gas prices, network congestion levels and transaction costs both on L2 test tests and main environments.
- Use alternative estimation methods : Use third -party tools or develop personalized estimate algorithms that take into account the use cases and specific networks.
- Validate the values estimated with the actual deployment : Check the precision of gas estimates in deployment of intelligent contracts on L2 tests and the main environment.
By recognizing these limitations and by adopting best practices, developers can be reduced the risks associated with gas estimates and ensure a more reliable intelligent contract deployment on L2 reference tests and the main environment.