A/B testing with Ingress in Kubernetes - Time & Space Complexity
When using Kubernetes Ingress for A/B testing, it's important to understand how the routing rules affect processing time.
We want to know how the number of routing rules impacts the time it takes to handle incoming requests.
Analyze the time complexity of the following Ingress configuration snippet.
apiVersion: networking.k8s.io/v1
kind: Ingress
metadata:
name: ab-testing-ingress
spec:
rules:
- host: example.com
http:
paths:
- path: /v1
pathType: Prefix
backend:
service:
name: service-v1
port:
number: 80
- path: /v2
pathType: Prefix
backend:
service:
name: service-v2
port:
number: 80
This Ingress routes traffic to two different service versions based on the URL path for A/B testing.
Identify the loops, recursion, array traversals that repeat.
- Primary operation: Checking each path rule in the Ingress to find a match for the incoming request.
- How many times: The number of path rules (here 2) determines how many checks happen per request.
As the number of path rules grows, the Ingress controller checks more rules to find the right backend.
| Input Size (n) | Approx. Operations |
|---|---|
| 10 | 10 path checks |
| 100 | 100 path checks |
| 1000 | 1000 path checks |
Pattern observation: The number of checks grows directly with the number of path rules.
Time Complexity: O(n)
This means the time to route a request grows linearly with the number of path rules in the Ingress.
[X] Wrong: "Adding more path rules won't affect request routing time because it's just configuration."
[OK] Correct: Each incoming request is checked against all path rules until a match is found, so more rules mean more checks and longer routing time.
Understanding how routing rules scale helps you design efficient Kubernetes Ingress setups and shows you can think about system performance beyond just writing configs.
"What if we changed the Ingress to use a single rule with a more complex path matching pattern? How would the time complexity change?"