Intelligent Load Balancing

[Nanle-code]

Description:
Develop an AI system that optimizes load balancing across API endpoints, data sources, and processing units. The system should predict load and distribute resources accordingly.

Technical Details:
Implement load prediction using time-series models. Build dynamic load distribution algorithm. Create performance monitoring system. Integrate with existing infrastructure.

Acceptance Criteria:
Load distribution is optimal 85% of the time, predictions are accurate, monitoring is comprehensive, and response time improves.

[olu-cmd]

@olu-cmd has applied to work on this issue as part of the Stellar Wave Program's 7th wave.

I would love to work on this issue

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[Theraxia]

@Theraxia has applied to work on this issue as part of the Stellar Wave Program's 7th wave.

hi maintainer, i would like to work on this issue, thanks

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[Yaks24]

@Yaks24 has applied to work on this issue as part of the Stellar Wave Program's 7th wave.

I want to work on this issue because it matches my skills and interests, and I would like to contribute while gaining practical experience. I am full stack blockchain engineer with over 4 years of experience

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[GdAyo19]

@GdAyo19 has applied to work on this issue as part of the Stellar Wave Program's 7th wave.

I would like to work on this issue

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[drips-wave]

Congratulations, @GdAyo19! 🎉 Your application was accepted by the repo's maintainers, and the issue is due on July 30, 2026.

🧑‍💻 @GdAyo19: Please resolve the issue such that the repo's maintainers have enough time to review your contribution before the due date. You'll earn Points for completing the issue on-time, which will make you eligible for a share of the Stellar Wave Program's reward pool.

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[drips-wave]

This issue has been completed by @GdAyo19 as part of the Stellar Wave Program's 7th Wave 🥳

😎 @GdAyo19: You earned 200 Points for completing this issue! After the current Wave ends, you'll be eligible for a percentage of the Wave's reward pool based on the percentage of total points you've earned. Learn more here. You can also Leave a review to share your experience working on this issue.

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