Added explanation for P5011 error in Accelerate Troubleshooting guide

content/300-accelerate/650-troubleshoot.mdx

@@ -132,6 +132,36 @@ If the database is taking too long to respond to the connection request, Prisma
 **Suggested solution:** Verify that the database is active and reachable. If the database is in sleep mode, try to wake it up by sending a request to it using a direct database GUI tool or wake it up using the database's management console.
 
 
+## [`P5011`](/orm/reference/error-reference#p5011-too-many-requests) (`TooManyRequests`)
+
+This error occurs when Prisma Accelerate detects a high volume of requests that surpasses allowable thresholds. It acts as a protective measure to safeguard both Prisma Accelerate and your underlying database from excessive load.
+
+### Possible causes for [`P5011`](/orm/reference/error-reference#p5011-too-many-requests)
+
+#### Aggressive retry loops
+
+If your application retries queries immediately or with minimal delay, especially after receiving certain errors, the rapid accumulation of requests can surpass the threshold.
+
+**Suggested solution:**
+- Implement an exponential backoff strategy. Rather than retrying immediately or with a fixed delay, gradually increase the delay period after each failed attempt.  
+- This allows the system time to recover and reduces the likelihood of overwhelming Prisma Accelerate and your database.
+
+#### Sudden traffic spikes
+
+Unpredicted traffic surges (for example, during product launches, flash sales, or viral growth events) can cause the threshold to be met and result into `P5011`.
+
+**Suggested solution:**
+- Consider proactive scaling strategies for both Prisma Accelerate and your database.  
+- Monitor traffic and resource usage. If you anticipate a surge, please contact [support](/platform/support) for capacity planning and potential configuration adjustments.
+
+#### Prolonged or planned high workloads
+
+Certain processes, such as bulk data imports, ETL operations, or extended CRON jobs, can generate continuous high query volume over time.
+
+**Suggested solution:**
+- Use batching or chunking techniques to break large operations into smaller parts.  
+- Establish throttling or scheduling to distribute the load more evenly.  
+
 ## Other errors
 
 ### Error with MySQL (Aiven): "We were unable to process your request. Please refresh and try again."