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Benjamin Nguyen
Benjamin Nguyen

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System Stability and Performance Analysis

⚙️ System Stability and Performance Intelligence:

A self service diagnostic workflow powered by an AWS Lambda backend and an agentic AI layer built on Gemini 3 Flash. The system analyzes stability signals in real time, identifies root causes, and recommends targeted fixes. Designed for reliability critical environments, it automates troubleshooting while keeping operators fully informed and in control.

🔧 Automated Detection of Common Failure Modes:

The diagnostic engine continuously checks for issues such as network instability, corrupted cache, outdated versions, and expired tokens. RS256 secured authentication protects user sessions, while smart session recovery and crash aware restart restore previous states with minimal disruption.

🤖 Real Time Agentic Diagnosis and Guided Resolution:

Powered by Gemini 3 Flash, the agentic assistant interprets system behavior, surfaces anomalies, and provides clear, actionable remediation steps. It remains responsive under load, resolving a significant portion of incidents automatically and guiding users through best practice recovery paths without requiring deep technical expertise.

📊 Reliability Metrics That Demonstrate Impact:

Key performance indicators highlight measurable improvements in stability and user trust:

• Crash Free Sessions Rate: 98%+
• Login Success Rate: +15%
• Automated Issue Resolution: 40%+ of incidents
• Average Recovery Time: Reduced through automate workflows
• Support Ticket Reduction: 30% within 90 days

🚀 A System That Turns Diagnostics Into Competitive Advantage:

Beyond raw stability, the platform transforms troubleshooting into a strategic asset. With Gemini 3 Flash powering real time reasoning, the system doesn’t just fix problems — it anticipates them, accelerates recovery, and gives teams a level of operational clarity that traditional monitoring tools can’t match. The result is a faster, calmer, more confident user experience that scales effortlessly as the product grows

Portfolio: https://ben854719.github.io/

Project: https://github.com/ben854719/System-Stability-and-Performance-Analysis

Top comments (8)

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webdeveloperhyper profile image
Web Developer Hyper

Wow! You always have great skills as always. Combining AWS Lambda, security, and AI into one project is impressive!😃

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benjamin_nguyen_8ca6ff360 profile image
Benjamin Nguyen • Edited

Thank you buddy! It was my first time to use cloud computing combine with Gemini 3 flash for this project. It was so much fun :)

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webdeveloperhyper profile image
Web Developer Hyper

I also tried the free plan of Google Gemini 3 Flash before, but I hit the limit too easily. I wish I could use it more.🤔

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benjamin_nguyen_8ca6ff360 profile image
Benjamin Nguyen • Edited

It happens to me back in January:(. I started to use gemini 3 flash for my arctic project. I corrected a mistake and refresh my notebook. I received a notification that I reached my limits with gemini 3 flash. I had to wait about a month to use Gemini 3 flash again. I find that Gemini 2.5 flash a bit more stable and better than gemini 3 flash. It is my opinion. I know that Google will discontinue Gemini 2.5 flash shortly. I hope that Google will make some modification so Gemini 3 flash functions is more stable.

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webdeveloperhyper profile image
Web Developer Hyper

Waiting for about a month is a long time. I’ll be careful not to use too much. 🫡

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benjamin_nguyen_8ca6ff360 profile image
Benjamin Nguyen

Lol!

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bhavin-allinonetools profile image
Bhavin Sheth

Really nice approach. We built something similar for monitoring, and automatic root-cause hints made a huge difference — especially reducing support tickets. One thing that helped us a lot was logging the AI’s diagnosis alongside raw metrics, so we could verify accuracy later. Curious — are you storing the agent’s reasoning for audits/debugging?

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benjamin_nguyen_8ca6ff360 profile image
Benjamin Nguyen

Thank you for the comment! It is interesting what is your company is building. Yes, I am using the agent reasoning to detect any anomalies such as cache, token, system designs errors etc.... It will make recommendation in a script for the network/debugging/improving in the status of the application.