Building hybrid blockchain/cloud applications with Ethereum and Google Cloud

With the help of the public cloud and internet resources, the usage of blockchain technologies can be accelerated. In this blog, we will discuss how some Cloud-based blockchain applications use the Chainlink oracle smart contract to make BigQuery data available on-chain.

First of all, let’s discuss Hybrid Blockchain Cloud App

Focusing on mathematical efforts, blockchain builds shared consensus and contracts. These smart contracts are included in the blockchain app development and thereby cannot be changed after it gets into a few blocks deep. You can commit crypto-economic resources to automatically enforce the trusted contract terms without third party involvement.

Sometimes the data added on-chain doesn’t reflect the data. In such situations, you need trusted external data such as Oracle. Moreover, you will see how Ethereum, a smart contract platform, can work along BigQuery, a cloud data warehouse through Chainlink.

How is the hybrid blockchain cloud app built?

The developed Ethereum Dapps asked Chainlink for the data which comes from a web service created with BigQuery and Google App Engine. The smart contract recalls the Chainlink oracle to induce data from BigQuery. Blockchain app development platform invokes external adapters to provide better support to authentic APIs, external blockchains, and payment gateways.

After that, the Chainlink node requests the oracle contract with the returned data, which is induced from the Dapp contract. In such a situation, the Chainlink node comes in contact with the App Engine web service.

How to use the BigQuery Chainlink oracle

Let’s look into some of the ways to build useful applications with Google Cloud and Chainlink:

Case 1: Prediction marketplaces

Different people quantify the success of different platforms differently thereby opinions on their suggested platform also differ. Smart contracts’ value is based on power-law distributions, so it is interesting to determine which one will predominate.

One can successfully pull the complicated prediction with the help of crypto public datasets. For instance, currently, a bet on Ethereum’s future state of $500,000 was accomplished on-chain. Google has also recorded that the volume, variety, frequency and time of Ethereum Dapps development can be measured by retrieving with daily-, weekly-, and monthly- functions for a specific Dapp.

Case 2: Hedging against blockchain platform risk

Due to the existing trustworthy and transparent financial system in the blockchain environment, decentralized finance is highly adopted by developers. However, with the help of finance & contracts, enterprises can optimize and increase the efficiency of their operating resources.

Dapp developers can create blockchain cloud app development without worrying about the exposed risk because of the high-quality data from the crypto public datasets. This results in more innovative and rapid blockchain creation.

You can find detailed information about Ethereum smart contract interacting with the BigQuery oracle to bring back the required data at the right time. You can also learn to use the oracle for executing the collateralized contracts.

Case 3: Provide exposure over Ethereum using submarine sends

The major setbacks of Ethereum blockchain as a service is its lack of transaction privacy and taking benefit from leaked on-chain data of smart contract users. This could also be a front running transaction including distributed exchange addresses.

With the help of the submarine send approach, you can expand the security and privacy of your transactions, defeat the front-running adversaries and increase the DExs efficiency. Make sure you use this approach with oracle to save yourself from its limitations.

However, if you don’t use oracle while implementing submarine sends, it will develop blockchain bloat. The contract can see a maximum of 256 blocks upstream or around one hour by the Ethereum virtual machine. This maximum scope provides useless denormalization while the required data is rebroadcast. But, with oracle, the bloat gets removed due to the inclusion of all the historical chain data.

Conclusion:

We hope that now you have some clarity about the usage of Cloud-based blockchain applications to gain datasets on-chain. This technique will help you decrease submarine send use cases and also add new functions to your smart contract. This will be useful for many industries to create new business models, in cases like a prediction market.

The main purpose of the approach is to exchange a bit of latency and transaction overhead for a decent amount of economic utility. This will lead the developers to optimally use the features of smart contracts in developing hybrid blockchain cloud apps. The smart contract is filled with amazing features, so make sure you use it wisely and as per your project requirements.

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