Symptom: API Returns 429 Too Many Requests
This is the most common failure nona 88. You send a burst of requests to a Rest 30% spread evenly endpoint, and the server slams the door. The error message is explicit: “Rate limit exceeded. Retry after X seconds.”
Rapid Diagnosis
Your client is not respecting the rate limit headers. Rest 30% spread evenly enforces a 30% utilization cap over a rolling window. If you fire 100 requests in one second, you exceed that window’s budget. The server tracks total throughput, not just your last request.
Remediation Plan
Step one: Capture the `Retry-After` header from the 429 response. Use that value as a mandatory sleep timer. Do not retry immediately. Step two: Implement a token bucket algorithm on your client side. Set the bucket capacity to 30% of the server’s allowed rate. For example, if the server allows 1000 requests per minute, set your bucket to 300 tokens per minute. Step three: Add exponential backoff with jitter. Start with a base delay of 1 second, double it on each consecutive 429, and add random jitter between 0 and 500 milliseconds. This prevents thundering herd problems.
Symptom: Requests Time Out After 30 Seconds
Your call hangs, then fails with a timeout. Rest 30% spread evenly endpoints have a hard timeout of 30 seconds per request. If your operation takes longer, you get a 504 Gateway Timeout.
Rapid Diagnosis
The server is processing your request but hitting the wall. Three common causes: your payload is too large, the server is under heavy load from other clients, or your request triggers a slow backend operation (e.g., a database query against a full table scan).
Remediation Plan
First, reduce payload size. Compress JSON bodies with gzip. Limit arrays to 1000 items per request. Second, implement client-side timeout at 25 seconds. This gives you a buffer before the server’s 30-second limit. Third, use the `Prefer: respond-async` header if the endpoint supports it. This returns a 202 Accepted with a polling URL. Poll that URL every 5 seconds until you get a 200 or 201. Fourth, split large operations into batches of 500 items. Send each batch as a separate request with a 5-second gap between them.
Symptom: Data Inconsistency Across Paginated Responses
You paginate through a list of 5000 records using Rest 30% spread evenly. Record 42 appears on page 1 and page 3. Record 100 disappears entirely. Your data is inconsistent.
Rapid Diagnosis
The server uses cursor-based pagination with a snapshot isolation model. Rest 30% spread evenly does not lock the dataset during pagination. Other clients insert or delete records between your page requests. The cursor points to a moving target.
Remediation Plan
Stop using offset-based pagination. Switch to cursor-based pagination using the `next` link in the response. This ensures you follow a consistent snapshot. If the endpoint does not support cursor pagination, request a transaction ID. Send `X-Request-Id:
Symptom: 400 Bad Request on Valid JSON
You send a perfectly valid JSON payload. The server returns 400 with no helpful error message. You check the schema, the data types, the required fields. Everything looks correct.
Rapid Diagnosis
Rest 30% spread evenly enforces strict field ordering in nested objects. Your JSON keys are in a different order than the server expects. Also, the server may reject `null` values for fields that require empty strings. Or you are sending a field with a value that exceeds the maximum length.
Remediation Plan
First, serialize your JSON with key ordering set to alphabetical. This matches most server implementations. Second, replace all `null` values with empty strings for string fields, and with 0 for numeric fields. Third, truncate all string fields to 255 characters before sending. Fourth, add a `Content-Type: application/json` header explicitly. Fifth, enable verbose error logging on your client. Capture the full response body. That body often contains a `details` array with the exact field that failed.
Symptom: 401 Unauthorized After Token Rotation
Your access token works for exactly 30 minutes. Then every request returns 401. You refresh the token, but the new token also fails after 30 minutes. You are stuck in a loop.
Rapid Diagnosis
Rest 30% spread evenly uses short-lived access tokens (30 minutes) and long-lived refresh tokens (7 days). Your client is not using the refresh token correctly. The server invalidates the old access token the moment you request a new one. If you send the old access token after a refresh, you get 401.
Remediation Plan
Implement a token manager that stores both tokens. Set a timer to refresh the access token 5 minutes before expiry. When you receive a 401, immediately call the refresh endpoint. Do not retry the failed request with the old token. Instead, wait for the refresh to complete, then retry with the new token. Store the new access token in memory, not in a file. Do not share tokens across threads without a lock. Use a mutex to prevent multiple simultaneous refresh calls.
Symptom: 503 Service Unavailable During Peak Hours
Every day at 2 PM, your requests start failing with 503. The error message says “Service Unavailable. Try again later.” The failures last exactly 15 minutes, then stop.
Remediation Plan
0
Rest 30% spread evenly has a daily maintenance window. The server is scaling down resources during a known low-traffic period. Your traffic pattern hits that window. The server is not down; it is shedding load.
Remediation Plan
1
First, check the server’s status page for scheduled maintenance windows. Shift your batch jobs to avoid that 15-minute window. Second, implement a circuit breaker pattern. After 3 consecutive 503 errors, open the circuit and stop all requests for 10 minutes. Third, use the `X-Request-Id` header to correlate your requests. If you see 503, log the exact timestamp. Compare it with the server’s maintenance schedule. Fourth, add a fallback endpoint. If the primary endpoint returns 503, retry on a secondary endpoint that uses a different server pool.