AWS Web3 Blog

Category: Technical How-to

Accelerate Ethereum synchronization time with storage-optimized Amazon EC2 instances

Syncing an Ethereum node can be a time-consuming and costly process if not well optimized, with the need to find the right balance between speed and security. Compute requirements are different between the initial synchronization phase with the network and the steady-state phase where the node only needs to process new blocks (for additional details, refer to Synchronization modes in the Ethereum documentation). This challenge can be addressed by using different types of Amazon EC2 instances corresponding to your requirements. In this post, we demonstrate how to use the latest generation of storage optimized EC2 instances during the synchronization process, and switch back to right-sized memory optimized instances for the run phase to minimize cost.

Establishing verifiable security: Reproducible builds and AWS Nitro Enclaves

Recent security incidents across blockchain and broader IT sectors underscore the persistent risk of sophisticated attacks on software supply chains and build environments. Reproducible builds offer a powerful mitigation strategy by making sure that software compiled from the same source code and dependencies consistently produces identical binaries, making it possible to detect tampering. In this […]

Optimize tick-to-trade latency for digital assets exchanges and trading platforms on AWS

Digital assets is a rapidly maturing set of asset class, and customers are choosing AWS to build exchanges and trading platforms to differentiate their offerings across this dynamic and growing industry. In this multi part series, we explore the world of centralized exchange (CEX) and market maker (MM) infrastructure on AWS. In Part 1, we […]

Implement a USDC bridge on AWS

Stablecoins offer significant advantages in the crypto space. They provide price stability and can serve as a reliable medium of exchange, store of value, or bridge between the fiat and crypto ecosystems. The ability to transfer stablecoins across multiple blockchains further enhances their utility by improving cross-chain interoperability and letting users take advantage of the […]

Build crypto AI agents on Amazon Bedrock

As Web3 and generative AI technologies continue to rapidly evolve, a new category of applications known as crypto AI agents has emerged. These agents use large language models (LLMs) for their intelligence to accomplish a variety of blockchain-related tasks through a supervisor-collaborator architecture. A supervisor agent orchestrates specialized collaborator agents to analyze blockchain data, identify […]

Use a DAO to govern LLM training data, Part 4: MetaMask authentication

In Part 1 of this series, we introduced the concept of using a decentralized autonomous organization (DAO) to govern the lifecycle of an AI model, focusing on the ingestion of training data. In Part 2, we created and deployed a minimalistic smart contract on the Ethereum Sepolia using Remix and MetaMask, establishing a mechanism to govern which training data can be uploaded to the knowledge base and by whom. In Part 3, we set up Amazon API Gateway and deployed AWS Lambda functions to copy data from InterPlanetary File System (IPFS) to Amazon Simple Storage Service (Amazon S3) and start a knowledge base ingestion job, creating a seamless data flow from IPFS to the knowledge base. In this post, we demonstrate how to configure MetaMask authentication, create a frontend interface, and test the solution.

Use a DAO to govern LLM training data, Part 3: From IPFS to the knowledge base

In Part 1 of this series, we introduced the concept of using a decentralized autonomous organization (DAO) to govern the lifecycle of an AI model, focusing on the ingestion of training data. In Part 2, we created and deployed a minimalistic smart contract on the Ethereum Sepolia testnet using Remix and MetaMask, establishing a mechanism to govern which training data can be uploaded to the knowledge base and by whom. In this post, we set up Amazon API Gateway and deploy AWS Lambda functions to copy data from InterPlanetary File System (IPFS) to Amazon Simple Storage Service (Amazon S3) and start a knowledge base ingestion job.

Use a DAO to govern LLM training data, Part 2: The smart contract

In Part 1 of this series, we introduced the concept of using a decentralized autonomous organization (DAO) to govern the lifecycle of an AI model, specifically focusing on the ingestion of training data. In this post, we focus on the writing and deployment of the Ethereum smart contract that contains the outcome of the DAO decisions.

Use a DAO to govern LLM training data, Part 1: Retrieval Augmented Generation

Blockchain and generative AI are two technical fields that have received a lot of attention in the recent years. There is an emerging set of use cases that can benefit from these two technologies. In this four-part series, we build a solution that governs the training data ingestion process of an AI model, using a smart contract and serverless components. We guide you through the different steps to build the solution. In this post, we review the overall architecture of the solution, and set up a large language model (LLM) knowledge base.

How to deploy Stacks blockchain nodes on AWS with the AWS Blockchain Node Runners Stacks blueprint

Bitcoin is the most widely adopted and valuable cryptocurrency, known for its decentralization and security. Stacks, a Layer 2 solution built on top of Bitcoin, aims to unlock Bitcoin’s full potential by enabling fast, cheap, Bitcoin-secured transactions and smart contract functionality without modifying the Bitcoin protocol itself. Stacks uses a consensus mechanism called Proof of […]