Yes, 20 TPS (Transactions Per Second) is considered low for most production workloads — unless:

✅ When 20 TPS is reasonable:

• You’re testing or doing a soft launch.
• The API serves high-cost or sensitive operations (e.g., financial transactions).
• You want to protect legacy backends that can’t handle high concurrency.
• You’re applying it per client (per consumer) rather than globally.

❗ When 20 TPS is too low:

• You’re limiting at the global or service level and expect hundreds or thousands of users.
• Your application is public-facing, and users experience 429 errors (rate limit exceeded).
• You’re throttling batch jobs, mobile apps, or systems that burst above 20 TPS.

📊 Typical API Rate Benchmarks:

🔁 Recommendation:

• Set burst + sustained limits, e.g.,:
  • config.second=20
  • config.hour=72_000 (20 * 3600)
• Use Redis policy for accurate global limits across nodes.
• Add consumer-based limits if needed.

Would you like a rate-limiting strategy per user tier (e.g., free vs. premium)?

Here’s a practical rate-limiting strategy per user tier (e.g., Free, Standard, Premium) using Kong Gateway, suitable for API plans on AWS or anywhere Kong is deployed.

Here’s a practical rate-limiting strategy per user tier (e.g., Free, Standard, Premium) using Kong Gateway, suitable for API plans on AWS or anywhere Kong is deployed.

🎯 Goal: Per-Consumer Rate Limiting (e.g., Free = 20 TPS, Premium = 100 TPS)

✅ Assumptions:

• You’re using Kong consumers for authentication (e.g., via API key, JWT, OIDC).
• Rate limiting is applied per consumer.
• You want to prevent abuse while allowing scalability by tier.

🏷️ Example Rate Limits by Plan

⚙️ Step-by-Step in Kong

1. Create Consumers

curl -X POST http://<admin-api>:8001/consumers \
     --data "username=free_user"

curl -X POST http://<admin-api>:8001/consumers \
     --data "username=standard_user"

curl -X POST http://<admin-api>:8001/consumers \
     --data "username=premium_user"

2. Assign Auth (e.g., API key)

curl -X POST http://<admin-api>:8001/consumers/free_user/key-auth

3. Apply Rate Limit Plugin to Each Consumer

Free (20 TPS, 50k/day)

curl -X POST http://<admin-api>:8001/consumers/free_user/plugins \
  --data "name=rate-limiting" \
  --data "config.second=20" \
  --data "config.day=50000" \
  --data "config.policy=local" \
  --data "config.limit_by=consumer"

Standard (60 TPS)

curl -X POST http://<admin-api>:8001/consumers/standard_user/plugins \
  --data "name=rate-limiting" \
  --data "config.second=60" \
  --data "config.day=250000" \
  --data "config.policy=local" \
  --data "config.limit_by=consumer"

Premium (100 TPS)

curl -X POST http://<admin-api>:8001/consumers/premium_user/plugins \
  --data "name=rate-limiting" \
  --data "config.second=100" \
  --data "config.day=1000000" \
  --data "config.policy=local" \
  --data "config.limit_by=consumer"

🧠 Optional: Use Redis for Distributed Rate Limiting

In multi-node setups, replace policy=local with:

--data "config.policy=redis" \
--data "config.redis_host=<your_redis_host>" \
--data "config.redis_port=6379"

🛠️ Tip: Monitor for 429 Errors

Watch for HTTP 429 Too Many Requests in Kong logs, Splunk, or Prometheus dashboards.

📘 Want Automation?

Let me know if you’d like:

• Ansible playbook
• deck YAML for versioned config
• Kong Ingress YAML (for EKS)
• Terraform for Kong setup

Just tell me your setup.

The “upstream status 500” in Kong Gateway means that Kong successfully forwarded the client request to the upstream service (your backend/API), but the upstream service itself responded with a 500 Internal Server Error.

🔍 What this typically indicates:

• The issue is with the upstream service, not Kong.
• Kong acted as a proxy and did its job correctly; the 500 came from your backend application.

🔁 Common causes on the upstream (backend) side:

1. Unhandled exceptions (e.g., null pointer, syntax errors).
2. Backend server crashed or restarted.
3. Database connection failures.
4. Application logic bug.
5. Timeouts or memory issues in the backend.

🧪 How to troubleshoot:

1. Check upstream (backend) logs at the time of the 500.
2. Use curl directly on the backend API to verify behavior: curl -i http://<upstream_host>:<port>/<path>
3. Enable debug logging in Kong if you want to trace the request: kong reload exit --conf kong.conf --vv
4. Look in Kong logs:
   • /usr/local/kong/logs/error.log
   • See if Kong shows errors related to the upstream or if it just reports the 500.

🧩 Helpful Kong log fields:

If using Splunk or another log aggregator:

• status: final status returned to client
• upstream_status: status from upstream (i.e. 500)
• upstream_uri: target path Kong used to reach the service
• latencies.proxy, latencies.kong, latencies.request: for performance analysis

Let me know if you’d like a diagram of the request flow or want help decoding a specific log line.

Yes, when using Kong Konnect with an OIDC (OpenID Connect) client, SSL (TLS) is typically required in production environments for both security and functional reasons. Here’s a breakdown of why:

✅ Why SSL/TLS is Required for OIDC with Kong Konnect

1. OIDC Specification Requires HTTPS

• The OIDC standard mandates that communication between clients and identity providers (IdPs) must use HTTPS to protect tokens and credentials.
• For example, the redirect_uri used in the OIDC flow must be HTTPS, or most IdPs will reject it.

2. Kong Konnect’s OIDC Plugin Requires HTTPS for Secure Redirects

• If you’re using the Kong OIDC plugin, especially in Authorization Code Flow, Kong must redirect users to the IdP and then receive the callback securely.
• Without SSL, the redirect URI may be considered invalid or insecure by the IdP.

Common Causes

1. Upstream service is slow or down
2. DNS resolution delay or failure
3. Incorrect protocol (HTTP vs HTTPS)
4. Upstream timeout too low in Kong config
5. Load balancer or firewall in between is blocking/delaying

If you’re seeing upstream_status=504 in Kong logs, it means:

Kong sent the request to the upstream (your backend service), but did not receive a response within the configured timeout, so it returned a 504 Gateway Timeout to the client.

🔍 What to Check When You See upstream_status=504

✅ 1. Verify Upstream is Healthy

Try to access your upstream from the Kong host directly:

curl -v http://<upstream-host>:<port>/<endpoint>

• If this is slow or hangs → your backend is the problem.
• If it fails to connect → network or DNS issue.

✅ 2. Increase Kong Timeouts

Timeouts are per-service. You can increase them using the Admin API:

curl -X PATCH http://localhost:8001/services/{service_name} \
  --data "connect_timeout=10000" \
  --data "read_timeout=15000" \
  --data "write_timeout=10000"

All values are in milliseconds.

✅ 3. Check Protocol Mismatch (HTTP vs HTTPS)

If your upstream uses HTTPS but the service is configured with protocol = http, Kong cannot complete the TLS handshake and may hang.

Fix it with:

curl -X PATCH http://localhost:8001/services/{service_name} \
  --data "protocol=https"

✅ 4. Check Kong Error Log

Run:

tail -n 100 /usr/local/kong/logs/error.log | grep timeout

You may see:

[error] ... upstream timed out (110: Connection timed out) while reading response header from upstream

✅ 5. Check Health of Upstream Targets (If Using Upstreams)

curl http://localhost:8001/upstreams/{upstream_name}/health

If all targets are unhealthy, Kong will return 504s.

✅ 6. Review Load Balancer / Firewall Rules

If Kong goes through:

• A corporate firewall
• A cloud load balancer
• An IPsec/VPN tunnel

Timeouts or dropped packets there can also lead to 504.

📘 Example Full Troubleshooting Flow

1. Run from Kong host/container: curl -v http://your-upstream-host:port/health
2. If that times out:
   • Check if service is running.
   • Check firewall rules.
3. Increase Kong timeouts: curl -X PATCH http://localhost:8001/services/my-api \ --data "read_timeout=20000"
4. Check logs: tail -f /usr/local/kong/logs/error.log

If you paste the exact Kong service config and a log snippet with upstream_status=504, I can give you a more specific fix.

A 504 Gateway Timeout from Kong means:

🔴 Kong Gateway sent a request to your upstream service, but didn’t get a response in time, so it gave up and returned a 504 to the client.

✅ QUICK FIX CHECKLIST

🧪 1. Test the Backend Directly

From Kong host or container:

curl -v http://<upstream-host>:<port>/health

If this hangs or fails, the issue is upstream—not Kong.

🛠️ 2. Increase Kong Timeouts

Use the Admin API:

curl -X PATCH http://localhost:8001/services/{service_name} \
  --data "connect_timeout=10000" \
  --data "read_timeout=15000" \
  --data "write_timeout=10000"

(All values are in milliseconds.)

🔐 3. Check Protocol Mismatch

Is your backend using HTTPS but your service uses HTTP?

Fix:

curl -X PATCH http://localhost:8001/services/{service_name} \
  --data "protocol=https"

📄 4. Check Kong Logs

Look in:

/usr/local/kong/logs/error.log

Typical timeout error:

upstream timed out (110: Connection timed out) while reading response header from upstream

🧰 5. Enable Correlation ID for Tracing

Enable this to track requests:

curl -X POST http://localhost:8001/plugins \
  --data "name=correlation-id" \
  --data "config.header_name=X-Correlation-ID" \
  --data "config.generator=uuid" \
  --data "config.echo_downstream=true"

Now check logs using the X-Correlation-ID.

If you send your service config or a log example with upstream_status=504, I’ll pinpoint the issue faster.

The error “An invalid response from upstream server” in Kong typically means:

Kong was able to connect to the upstream service, but the response it got back was malformed, empty, or violated protocol expectations.

🔍 Common Root Causes

✅ How to Troubleshoot

1. Check Logs

Look for this in Kong’s error log:

tail -f /usr/local/kong/logs/error.log

Common message:

upstream prematurely closed connection while reading response header

2. Test Upstream Manually

Run from the Kong host or container:

curl -i http://<upstream-host>:<port>/<path>

If you get no response or a malformed one, the problem is the upstream.

3. Verify Protocol

Make sure you’re not calling an HTTPS backend as HTTP:

# Fix protocol
curl -X PATCH http://localhost:8001/services/{service_name} \
  --data "protocol=https"

4. Increase Read Timeout

Sometimes upstreams are just too slow:

curl -X PATCH http://localhost:8001/services/{service_name} \
  --data "read_timeout=15000"

5. Check Upstream for Non-Standard Response

If the upstream returns:

• Non-HTTP data (e.g., binary, gRPC without HTTP/1.1 framing)
• Incorrect headers
• Incomplete response

It will break Kong’s HTTP parser.

🧪 Bonus: Use Request Termination for Testing

Temporarily override the upstream to test Kong behavior:

curl -X POST http://localhost:8001/services/{service_name}/plugins \
  --data "name=request-termination" \
  --data "config.status_code=200"

If this works, the issue is 100% upstream-related.

If you can share the log snippet or the upstream service config (or test curl output), I can give you a pinpointed fix.

If a token is issued with a 20-minute expiration time, it remains valid until it expires, regardless of whether a new token is issued afterward.

So:

• Token A is issued at 14:00 → expires at 14:20.
• Token B is issued at 14:05 → expires at 14:25.

Token A is still valid until 14:20, even though Token B was generated later.

Exceptions:

Some systems revoke old tokens when a new one is issued. This depends on the implementation:

• Stateless tokens (e.g., JWT): Typically not revoked unless explicitly blacklisted or the signing key is rotated.
• Stateful tokens (e.g., stored in a DB): The server might mark previous tokens as invalid upon issuing a new one.

To summarize:

Yes, the first token is still valid unless your system has explicit revocation logic

he size of an API response can vary depending on several factors like the data being returned, server and client limits, and performance considerations. Here’s a breakdown of key aspects:

🔹 Typical Size Limits

• REST APIs (JSON):
  • Common practical limits: 1–10 MB
  • Best practice: Keep responses under 1 MB for speed and reliability
• GraphQL APIs:
  • Can return large nested objects, but pagination and limits are recommended
  • Many GraphQL servers default to 1 MB–5 MB limits
• gRPC / Protobuf APIs:
  • Binary and more compact
  • Common limit: 4 MB (can be increased with config)

🔹 Platform & Framework Default Limits

🔹 Practical Guidelines

• Use pagination for large datasets (e.g., limit=100&offset=0)
• Enable compression (e.g., Gzip or Brotli) to reduce response size
• Stream data (if large file or binary) rather than returning in a single response
• Split large responses across multiple endpoints if needed

🔹 API Response Size Debugging

You can check actual size using tools like:

bashCopyEditcurl -s -w "%{size_download}\n" -o /dev/null https://api.example.com/data

Let me know your use case — REST, GraphQL, or gRPC — and I can give optimized recommendations.