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  • Overview
    • SEDA Overview
      • SEDA Primer for Key Features
        • SEDAโ€™s Intent-Centric Framework
        • Modular Design Benefits
        • Programmable Tooling and Permissionless Development
        • Fast Settlement & Horizontally Scalable
        • Fork-less Upgrades
      • RWAs, Price Feeds, AI and More
        • Custom Data Feeds
      • SEDA Token Primer
        • Network Utilization
        • Network Participation & Chain Security
        • Network Governance
      • Introducing SEDA's Flagship Product - The IVM
        • ๐ŸŒ‰Intro to Interop 3.0 & Emerging Verification Markets
        • Programmable Modules
        • Triggering A Verification Data Request With An IVM
        • SEDA IVM Security
        • An IVM Summary
    • SEDA Network Architecture
      • Walking Through SEDAโ€™s Architectural Features
      • The PoS SEDA Chain
      • Oracle Programs
      • The Overlay Network
      • Decentralized Solver Network
      • SEDAโ€™s Prover Contract
  • For Developers
    • ๐Ÿ“ˆData Requests
      • โ“What is a Data Request?
      • ๐Ÿ”ƒData Request Life Cycle
    • ๐Ÿ’พBuilding an Oracle Program
      • Price Feed Example
        • ๐Ÿ‘‹Getting Started: Price Feed
        • ๐ŸงชTesting Your Oracle Program
        • ๐Ÿš€Deploying Your Oracle Program
      • ๐ŸŒFetching Open Data
      • ๐Ÿ”Advanced: API-key Gated Data
    • โšกAccess Data from Any Network
      • ๐Ÿ”ŽAccess from EVM Networks
        • ๐Ÿ”งUsing SEDA in a Contract
        • ๐Ÿš€Contract Deployment
      • ๐Ÿ”œAccess from other Networks
      • ๐Ÿ”œAdvanced: Run your own Solver
    • ๐Ÿ—๏ธDeployments
    • ๐Ÿ‘ฝInteroperability Verification Module (IVM)
      • ๐Ÿ›ธInterop Verification Module for Message-Based Bridge Protocols
      • Powering Intents and Chain Abstraction with SEDA
  • For Users
    • โญGetting Started
      • ๐ŸฆWallet Overview
      • โฌInstalling Cosmos Hub on Ledger
      • โ›“๏ธAdding SEDA Chain to Keplr
      • ๐ŸŒŒDelegating your SEDA
        • ๐Ÿ“จSelecting a Validator
        • ๐Ÿ“กDelegating to a Validator
    • ๐Ÿ‘Tools and Dashboards
      • ๐ŸŒSEDA Explorers and Dashboards
      • ๐Ÿ”ญThird-party Explorers
      • ๐Ÿ“ถPublic RPCs + APIs
    • ๐Ÿ”ตSEDA Token Info
      • ๐Ÿ“ˆToken Charts and Tracking
      • ๐Ÿ“ŠExchanges
      • ใ€ฐ๏ธSEDA Distribution Schedule
  • For Data Providers
    • Data Proxy
      • โ„น๏ธIntroduction to Data Proxy
      • ๐Ÿ’ปSystem Requirements
      • ๐Ÿ”ขOperating and Running a Data Proxy
      • ๐Ÿ”Advanced: API-key Gated Data
  • For Node Operators
    • ๐Ÿ“ถSEDA Chain Guide and Requirements
      • ๐ŸŽฌInstallation and System Requirements
      • ๐Ÿ‘ŸOperating and Running a Node
      • ๐Ÿ”—Linking to an External Node
      • ๐Ÿ—๏ธValidator Onboarding
      • ๐Ÿ”‘SEDA Keys
      • ๐Ÿ“ธJoining Testnet Using Snapshot
      • ๐ŸคJoining Testnet Using State Sync
  • Resources
    • ๐Ÿ›ก๏ธAudits
      • Trail of Bits Audit Report Repo Link - March 2024
      • Sherlock Audit of SEDA Network Full Feature Launch - April 2025
  • Legal
    • Privacy Policy
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  1. For Data Providers
  2. Data Proxy

System Requirements

The Data Proxy implementation is lightweight, allowing it to run with minimal infrastructure requirements:

  • Compute: 2 vCPU

  • Memory: 1 GB RAM

  • Storage: 100 MB for the binary (approx. 3 GB GNU/Linux instance)

The Data Proxy efficiently handles hundreds of requests per second, providing latency and throughput that are well-suited to meet current and near-future SEDA protocol demands.

Scaling Up

If performance needs to be boosted beyond vertical scaling, horizontal scaling is straightforward due to its minimal resource footprint. Depending on your existing infrastructure, consider the following strategies:

  • Load Balancing: Use tools like AWS ELB, NGINX, or HAProxy to distribute traffic across multiple proxy nodes.

  • Auto-Scaling: Implement cloud-based auto-scaling groups (e.g., Amazon EC2 Auto Scaling) to dynamically adjust instance counts based on traffic.

  • Container Orchestration: Utilize Kubernetes or managed services such as Amazon EKS/Fargate for efficient management and scaling of containerized instances.

These approaches ensure that your Data Proxy deployment remains scalable and resilient, adapting seamlessly to varying workloads.

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Last updated 7 months ago

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