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Improved Storage Latency for Polygon Nodes on AWS through Agnostic Engineering

Improved Storage Latency for Polygon Nodes on AWS through Agnostic Engineering

In a guest post co-written by Arnaud Briche, the founder of Agnostic, the company’s mission is to democratize access to well-structured blockchain data. Agnostic aims to provide a fast, easy-to-use, and reliable method for querying the large volumes of data generated by smart contract blockchains. Initially using basic service providers for performance reasons, Agnostic later turned to AWS’s global presence to expand its business and improve service reliability.

A key blockchain network supported by Agnostic is Polygon, a high-performance network requiring ultra-low latency for read operations to keep blockchain clients up to date with the latest network status. When utilizing Amazon Elastic Blocks Store (EBS) gp3 volumes, Agnostic found that the tail latency did not consistently meet its goals, and EBS io2 volumes were not cost-effective for its setup.

To address this issue, Agnostic developed a workaround to achieve the required ultra-low latency read operations. The solution involves combining Amazon Elastic Compute Cloud (EC2) instance store volumes with durable general-purpose EBS GP3 block storage. By configuring RAID arrays with instance store volumes and EBS gp3 volume, Agnostic optimized storage performance while maintaining data integrity.

The solution also leverages the OpenZFS file system for data compression and space optimization benefits. Furthermore, Agnostic created an AWS CloudFormation template with a user data script to simplify deployment and configuration for users.

The deployment process involves selecting an EC2 instance type with multiple instance store volumes, configuring RAID arrays, installing the OpenZFS file system, and mounting the data volume at /data. Users can then proceed with deploying a blockchain node using the Polygon Erigon client.

Once the deployment is complete, users can connect to their EC2 instance, configure storage using predefined commands, and proceed with installing their Erigon client for Polygon. To remove deployed resources, users can navigate to the CloudFormation service in their AWS console and delete the stack.

In conclusion, Agnostic successfully created a node that matches the speed of a basic configuration while enhancing durability and data replication capabilities. This achievement represents a blend of high performance and flexibility. For further information, readers can explore Agnostic Engineering and seek assistance through AWS re:Publish or the AWS Blockchain Node Runners repository on GitHub.

Article Source
https://aws.amazon.com/blogs/database/how-agnostic-engineering-improved-storage-latency-for-running-polygon-nodes-on-aws/

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