Jupiter Exchange in Solana, Spain has seen nearly half its transactions fall through during the past month.

Jupiter DEX faces increasing scrutiny after users noticed a near 50% failure rate in transaction, causing concern and raising questions regarding the platform. There are many who are seeking answers and wonder what steps are being taken. The situation is explored in this article. It will look at what factors are contributing to the failure rate, and examine actions taken to improve user experience.

Why high failure rates are so common?

Jupiter’s average failure rate over the past 30 days is 42.89 %, even if you exclude the data missing from August 2 and 3. As a result, an increased number of users are asking what the root causes of the failures are and how they can improve performance.

The fact that users still have to pay fees even for unsuccessful transactions is a source of great frustration. This may seem unjust at first, but it’s a feature of the blockchain. Successful or not, each transaction consumes network resources such as computing power and blocks space. The validator will still process a failed transaction until a problem causes the error. As the network still has to be utilized in order to process the requests, this fee helps compensate for the computing resources.

A solution that increases slippage tolerance can be risky

In order to prevent repeated charges from the network, many users increase their slippage threshold in an effort to complete their transaction. It makes it more likely that the exchange will be successful, as the increased slippage tolerance allows the network to continue the trade even if there is a slight price change from the quote.

The increased slippage can lead to a new risk, namely front-running bots. Bots that detect high-slippage transactions can execute trades before users, buying assets for a lower price than the slippage set by the user and then selling them at a higher price. Users are charged more for their swaps because they receive less advantageous rates.

Front-running on blockchain smart contracts networks

Hacken’s diagram shows front-running on Ethereum. However, the same concept applies to Solana or other blockchains with smart contracts.

• Step 1A smart contract is triggered by the user initiating a network transaction.
• Step 2.The frontrunner monitors and detects users’ transactions.
• Step 3: A new transaction is created by the front-runner with a gas price that’s higher. This higher price of gas encourages the validators to give priority processing the frontrunner’s transaction before that of the original transaction.
• Step 4Since the transaction of the front-runner offers a higher gas price than that of the user, it is processed first. As the transaction from the leader offers a better gas price, it’s processed first.
• Step 5This can lead to financial loss and missed opportunities.

Jupiter own words:

Majority of these failed transactions come from arbitrage bots that route using the program when an arb opportunity is near, hoping to land a transaction when the opportunity takes place — this leads to the higher failure rate. Jupiter UI’s users are experiencing a transaction success rate that is over 90%.

Front-running is heavily dependent on the reliability of RPC (Remote Protocol Call) providers that interact with the blockchain. RPC is a middleman between users and blockchains that transmits data about transactions to the entire network. An RPC service provider that is unreliable could be enabling or participating in front-running, by sharing information with bots and manipulating transaction order. RPC providers who are reputable must adhere to ethical standards, and not allow users to be exploited or to engage in such behaviors.

A high failure rate is also due to the memecoin frenzy. Every day, tens and thousands of tokens get created. There aren’t sufficient tokens in the market for many of these memecoins. Users may fail to complete transactions when they try to sell or buy tokens with low liquidity.

Limitations in the order processing speed

Jupiter’s automatic slippage calculation and gas calculations also contribute to this failure rate. These features work fine in periods of stability but struggle when the market is volatile. The platform has also been struggling with its Free Tier Quote API. This was exploited to allow users to circumvent rate limits through spinning up new machines. It has increased operating costs, and there is a potential for service degradation.

Jupiter is also currently unable to handle the volume of requests, which is causing it to slow its logic for retries to over 25 seconds.

The conclusion of the article is:

Jupiter DEX has some serious challenges to overcome, such as a high number of failed transactions, infrastructure bottlenecks and front-running risk. These aren’t just minor issues—they directly affect user trust and the platform’s ability to perform well. Although the team is hard at work to resolve these issues, a question remains: Will Jupiter be able to not only fix the immediate problems but also meet the increasing demands in the DeFi market?