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teslim
@@ -14,7 +14,7 @@ Your task is to extract the high-throughput ticket purchasing component and exte
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- `GET /metrics`: Expose real-time metrics (e.g., tickets sold, available tickets per event) in a format compatible with Prometheus.
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- **Atomic Ticket Purchase:** Implement the purchase logic using a Redis Lua script to atomically verify and pop a ticket from the ticket pool. This ensures no duplicate ticket sales even under massive concurrent access.
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- **Fallback Mechanism:** If Redis is unavailable or fails during a purchase operation, gracefully fallback to an in-memory store (with appropriate warnings and logs), ensuring the system remains responsive (for demonstration purposes only, as in-memory stores are not persistent).
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- **Performance and Load Testing:** The service must be designed to handle tens of thousands of requests and be tested under a simulated load of at least 2000 concurrent connections. You should include logging of key performance metrics and purchase statistics.
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- **Performance and Load Testing:** The service must be designed to handle tens of thousands of requests and be tested under a simulated load of at least 5000 concurrent connections. You should include logging of key performance metrics and purchase statistics.
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- **Design Documentation:** Provide a detailed design document (`design.md`) that explains your architectural decisions, how you ensure scalability, measures to handle potential bottlenecks, and details on your fallback strategy.
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- **Dockerization:** Extend the docker-compose setup to include not only Redis but also (optionally) a Prometheus container to scrape and monitor the metrics from your service.
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- **PDF Ticket Generation:** For every successful ticket purchase, a PDF receipt must be generated. You are free to choose any open-source PDF generation package of your choice (e.g., pdfkit, jsPDF, etc.) to implement this functionality. Ensure that PDF generation is integrated into the purchase flow without significant performance degradation.
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@@ -26,7 +26,7 @@ Your task is to extract the high-throughput ticket purchasing component and exte
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3. **Atomic Operations with Lua:** Replace simple atomic operations (like LPOP) with a Redis Lua script that handles the ticket purchase process atomically.
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4. **Fallback to In-Memory Store:** Implement a fallback mechanism that activates if Redis operations fail, ensuring continued functionality with clear logging that this is a non-persistent backup.
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5. **Metrics Endpoint:** Provide a `/metrics` endpoint that returns JSON data with real-time statistics (tickets sold, tickets remaining per event, errors, etc.).
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6. **Robust Testing:** Write comprehensive unit tests and integration tests. The integration tests must simulate high load (>=2000 concurrent requests) and prove that no ticket is sold more than once.
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6. **Robust Testing:** Write comprehensive unit tests and integration tests. The integration tests must simulate high load (>=5000 concurrent requests) and prove that no ticket is sold more than once.
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7. **Logging:** Implement detailed logging for purchase operations, errors, and fallback activations.
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8. **Design Document:** Include a `design.md` file that outlines your architecture, scalability considerations, and design rationale.
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9. **Docker Support:** Update the docker-compose file to run Redis and optionally Prometheus. Provide clear instructions for running the entire stack.
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@@ -59,9 +59,9 @@ Your task is to extract the high-throughput ticket purchasing component and exte
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### Load Testing
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Simulate high load using a tool like [autocannon](https://github.com/mcollina/autocannon) or [wrk](https://github.com/wg/wrk). For example, to simulate 2000 concurrent connections on event 1:
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Simulate high load using a tool like [autocannon](https://github.com/mcollina/autocannon) or [wrk](https://github.com/wg/wrk). For example, to simulate 5000 concurrent connections on event 1:
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npx autocannon -c 2000 -d 30 http://localhost:3049/buy/1
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npx autocannon -c 5000 -d 30 http://localhost:3049/buy/1
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### Metrics
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+13
-27
@@ -2,23 +2,10 @@
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<html lang="en">
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<head>
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<meta charset="UTF-8" />
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<meta
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http-equiv="X-UA-Compatible"
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content="IE=edge"
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/>
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<meta
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name="viewport"
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content="width=device-width, initial-scale=1.0"
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/>
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<link
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rel="preconnect"
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href="https://fonts.googleapis.com"
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/>
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<link
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rel="preconnect"
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href="https://fonts.gstatic.com"
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crossorigin
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/>
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<meta http-equiv="X-UA-Compatible" content="IE=edge" />
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<meta name="viewport" content="width=device-width, initial-scale=1.0" />
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<link rel="preconnect" href="https://fonts.googleapis.com" />
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<link rel="preconnect" href="https://fonts.gstatic.com" crossorigin />
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<link
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href="https://fonts.googleapis.com/css2?family=Roboto:wght@100;500;700;900&display=swap"
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rel="stylesheet"
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@@ -28,16 +15,16 @@
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<style>
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body {
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font-family: 'Roboto', sans-serif;
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font-family: "Roboto", sans-serif;
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}
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.ferrari {
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background-image: url(https://s3.us-west-1.amazonaws.com/com.mkdlab.images/baas/nordin/076532395068ferrari.png);
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background-image: url(https://placehold.co/600x400/EEE/31343C);
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background-repeat: no-repeat;
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background-position: center left;
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}
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.wing {
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background-image: url(https://s3.us-west-1.amazonaws.com/com.mkdlab.images/baas/nordin/076532395068wing.png);
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background-image: url(https://placehold.co/600x400/EEE/31343C);
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background-repeat: no-repeat;
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background-position: center right;
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}
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@@ -47,7 +34,7 @@
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<div class="js bg-white grid grid-cols-3 gap-1 bg-[red] p-3"></div>
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<script>
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const js = document.querySelector(".js")
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const js = document.querySelector(".js");
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for (let i = 0; i < 240; i++) {
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js.innerHTML += ` <div class="border-2 border-black border-dashed relative ">
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<div class="h-[12px] w-full bg-[#B3E1AB]"></div>
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@@ -55,12 +42,12 @@
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<div class="w-[25%] z-[100]">
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<img
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class="block w-[96%] h-[50%]"
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src="https://s3.us-west-1.amazonaws.com/com.mkdlab.images/baas/nordin/076532395068redLottery.png"
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src="https://placehold.co/600x400/EEE/31343C"
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alt="lottery car"
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/>
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<img
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class="block w-[98%] h-[50%]"
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src="https://s3.us-west-1.amazonaws.com/com.mkdlab.images/baas/nordin/076532395068darkLottery.png"
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src="https://placehold.co/600x400/EEE/31343C"
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alt="lottery car"
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/>
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</div>
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@@ -101,7 +88,7 @@
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</h5>
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<img
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src="https://s3.us-west-1.amazonaws.com/com.mkdlab.images/baas/nordin/076532395068appLogo.svg"
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src="https://placehold.co/600x400/EEE/31343C"
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class="h-[35px]"
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alt=""
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/>
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@@ -114,13 +101,12 @@
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</div>
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<div class="h-[12px] w-full bg-[#B3E1AB]"></div>
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<img
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src="https://s3.us-west-1.amazonaws.com/com.mkdlab.images/baas/nordin/076532395068barcode.png"
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src=https://placehold.co/600x400/EEE/31343C"
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alt="barcode"
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class="absolute top-1/2 right-0 transform -translate-y-1/2"
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/>
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</div>
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`
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`;
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}
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</script>
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</body>
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