A 50 error refers to an HTTP status code that indicates an internal server error. HTTP status codes are 3-digit codes that are returned when a request is made to a web server, acting as response codes that provide information about the status of the request. A 50 code signals the occurrence of an unexpected condition that prevented the server from fulfilling the request.
HTTP Status Codes
HTTP status codes belong to five classes:
- 1xx Informational
- 2xx Success
- 3xx Redirection
- 4xx Client Error
- 5xx Server Error
The first digit defines the class. 50 falls under the Server Error class. Here is a breakdown of the five classes:
1xx Informational
100 – 199 status codes indicate a provisional response. This means the request is still processing and not yet completed.
2xx Success
200 – 299 status codes indicate a successful request. The most common is 200 OK.
3xx Redirection
300 – 399 status codes indicate the resource being requested has been moved to a new location. For example, 301 Moved Permanently.
4xx Client Error
400 – 499 status codes indicate an error on the client’s side, such as a malformed request. For example, 404 Not Found.
5xx Server Error
500 – 599 status codes indicate an error on the server’s side. This signals the server failed to fulfill a valid request.
50 Range Server Error Codes
The 50 range of status codes specifically indicate an internal server error where the request seemed valid but something unexpected went wrong on the server. Here are some common 50 errors:
500 Internal Server Error
A generic server error. The server encountered an unexpected condition.
501 Not Implemented
The server doesn’t support the functionality to fulfill the request.
502 Bad Gateway
The server received an invalid response from an upstream server.
503 Service Unavailable
The server is temporarily unable to handle the request due to maintenance or overloading.
504 Gateway Timeout
An upstream server failed to send a request in time.
Common Causes of 50 Errors
There are a variety of reasons a server may fail to complete a request and return a 50 error. Here are some of the most common causes:
- Server overload – Too many requests coming in.
- Software bugs – Errors in the server code.
- Server configuration issues – Something is misconfigured.
- Upstream dependency failures – An external service isn’t responding.
- Insufficient server resources – Out of memory, disk space, etc.
- Database errors – Failed queries, connectivity issues, etc.
Troubleshooting 50 Errors
Troubleshooting 50 errors involves reviewing server logs to identify the specific error being returned and then investigating the potential causes. Here are some troubleshooting tips:
- Check error logs – The logs will provide more details about the failure.
- Confirm the request is valid – Rule out client-side issues.
- Test upstream dependencies – Confirm external services are responsive.
- Monitor server resources – Check for peak usage spikes.
- Retry the request – Intermittent issues may resolve on retry.
- Load test environment – Replicate issue to identify root cause.
Additionally, reproducing the error in a test environment can help isolate the specific cause. Capturing metrics leading up to the failure is also beneficial for diagnosing capacity planning issues.
Example Error Log
Here is an example excerpt from a server error log for a 500 status code:
[Wed Oct 30 14:25:41 2019] 127.0.0.1, 500 Internal Server Error, Request Timeout, upstream timed out (110: Connection timed out) while connecting to upstream
This reveals that an upstream timeout caused a cascading 500 error for the client request.
50 Error Handling Best Practices
When architecting server infrastructure and applications, there are several best practices that can mitigate 50 errors:
- Handle exceptions gracefully – Don’t leak stack traces.
- Implement circuit breakers – Prevent cascading failures.
- Set timeouts – Fail fast for unresponsive dependencies.
- Limit retries – Avoid request backlogs.
- Check errors and validity – Fail fast on issues.
- Use monitoring – Get visibility into all dependencies.
- Perform load testing – Establish baseline capacity.
Additionally, returning user-friendly 50 error pages improves the client experience during a failure. This helps avoid confusion when an internal server issue occurs.
User-Friendly Error Page Example
Here is an example error page a client may see when a 500 internal server error occurs:
500 - Internal server error Oops, something went wrong! Our service is experiencing an internal issue right now. Please try again later. We've been notified of the issue and our engineers are working diligently to resolve it. Contact us at [email protected] if the issue persists. Thank you!
Consequences of 50 Errors
If 50 errors occur frequently, it can significantly impact the user experience on a site or application. Consequences include:
- Increased latencies
- Service disruptions
- Reduced client throughput
- Failures for time-sensitive requests
- Revenue and productivity losses
Additionally, 50 errors that leak stack traces and internal details can become security risks if exposed.
50 Error Rate Table
| Month | 50 Error Rate |
|---|---|
| January | 2.4% |
| February | 2.1% |
| March | 2.0% |
| April | 1.6% |
| May | 1.3% |
| June | 1.2% |
| July | 1.1% |
| August | 0.9% |
This table demonstrates a downward 50 error rate trend over eight months, indicating stability improvements.
Solutions for Reducing 50 Errors
Here are some key solutions for reducing 50 errors:
- Scaling server resources – Add capacity to handle peak loads.
- Code optimization – Improve efficiency to require fewer resources.
- Caching – Return responses from cache rather than processing.
- Load balancing – Distribute requests across multiple servers.
- Fault tolerance – Design a flexible architecture that fails gracefully.
- Request throttling – Limit number of incoming requests.
- Service degradation – Return simpler responses during overloads.
Scaling Vs Optimizing
Scaling out servers by adding capacity can resolve resource constraints. However, optimizing code and efficiency enables supporting higher demand levels with fewer resources required.
A balanced approach combining scaling together with code optimization delivers high performance and reliability in the most cost-effective manner.
Conclusion
In summary, 50 errors signify an internal server issue prevented fulfilling a valid request. Troubleshooting involves reviewing logs to identify the error cause and reproducing the issue in a test environment. Following best practices for architectural design, monitoring, and failure handling reduces the occurrence of 50 errors. For existing systems, solutions such as scaling resources, optimizing code efficiency, caching, and fault tolerance can decrease 50 error rates to acceptable levels.