Advanced Route Rules
Before Start
You should have NO virtualservice nor destinationrule (in
|
Smart routing based on user-agent header (Canary Deployment)
What is your user-agent?
Note: the "user-agent" header is added to OpenTracing baggage in the Customer service. From
there it is automatically propagated to all downstream services. To enable automatic
baggage propagation all intermediate services have to be instrumented with OpenTracing.
The baggage header for user agent has following form baggage-user-agent: <value>
.
Set recommendation to all v1
kubectl create -f istiofiles/destination-rule-recommendation-v1-v2.yml -n tutorial
kubectl create -f istiofiles/virtual-service-recommendation-v1.yml -n tutorial
Set Safari users to v2
kubectl replace -f istiofiles/virtual-service-safari-recommendation-v2.yml -n tutorial
kubectl get virtualservice -n tutorial
and test with a Safari (or even Chrome on Mac since it includes Safari in the string). Safari only sees v2 responses from recommendation
and test with a Firefox browser, it should only see v1 responses from recommendation.
You can also attempt to use the curl -A command to test with different user-agent strings.
curl -A Safari $GATEWAY_URL/customer
curl -A Firefox $GATEWAY_URL/customer
You can describe the virtualservice to see its configuration
kubectl get virtualservice -o yaml -n tutorial
Set mobile users to v2
kubectl create -f istiofiles/virtual-service-mobile-recommendation-v2.yml -n tutorial
curl -A "Mozilla/5.0 (iPhone; U; CPU iPhone OS 4(KHTML, like Gecko) Version/5.0.2 Mobile/8J2 Safari/6533.18.5" $GATEWAY_URL/customer
Mirroring Traffic (Dark Launch)
kubectl get pods -l app=recommendation -n tutorial
You should have 2 pods for recommendation based on the steps above
kubectl get virtualservice -n tutorial
kubectl get destinationrule
You should have NO virtualservice nor destinationrule (in tutorial
namespace) kubectl get virtualservice
kubectl get destinationrule
if so run:
./scripts/clean.sh tutorial
Make sure you are in the main directory of "istio-tutorial".
kubectl create -f istiofiles/destination-rule-recommendation-v1-v2.yml -n tutorial
kubectl create -f istiofiles/virtual-service-recommendation-v1-mirror-v2.yml -n tutorial
curl $GATEWAY_URL/customer
Check the logs of recommendation-v2
kubectl logs -f `kubectl get pods -n tutorial|grep recommendation-v2|awk '{ print $1 }'` -c recommendation -n tutorial
Load Balancer
By default, you will see "round-robin" style load-balancing, but you can change it up, with the RANDOM option being fairly visible to the naked eye.
Add another v2 pod to the mix
kubectl scale deployment recommendation-v2 --replicas=2 -n tutorial
Wait a bit (oc get pods -w to watch) and curl the customer endpoint many times
curl $GATEWAY_URL/customer
Add a 3rd v2 pod to the mix
kubectl scale deployment recommendation-v2 --replicas=3 -n tutorial
kubectl get pods -n tutorial
NAME READY STATUS RESTARTS AGE
customer-1755156816-cjd2z 2/2 Running 0 1h
preference-3336288630-2cc6f 2/2 Running 0 1h
recommendation-v1-3719512284-bn42p 2/2 Running 0 59m
recommendation-v2-2815683430-97nnf 2/2 Running 0 43m
recommendation-v2-2815683430-d49n6 2/2 Running 0 51m
recommendation-v2-2815683430-tptf2 2/2 Running 0 33m
Wait for those 2/2 (two containers in each pod) and then poll the customer endpoint:
./scripts/run.sh $GATEWAY_URL/customer
The results should follow a fairly normal round-robin distribution pattern
customer => preference => recommendation v1 from 'recommendation-v1-6cf5ff55d9-7zbj8': 1145
customer => preference => recommendation v2 from 'recommendation-v2-2819441432-525lh': 1
customer => preference => recommendation v2 from 'recommendation-v2-2819441432-rg45q': 2
customer => preference => recommendation v2 from 'recommendation-v2-2819441432-bs5ck': 181
customer => preference => recommendation v1 from 'recommendation-v1-6cf5ff55d9-7zbj8': 1146
customer => preference => recommendation v2 from 'recommendation-v2-2819441432-rg45q': 3
customer => preference => recommendation v2 from 'recommendation-v2-2819441432-rg45q': 4
customer => preference => recommendation v2 from 'recommendation-v2-2819441432-bs5ck': 182
Now, add the Random LB DestinationPolicy
kubectl create -f istiofiles/destination-rule-recommendation_lb_policy_app.yml -n tutorial
And you should see a different pattern of which pod is being selected
customer => preference => recommendation v2 from 'recommendation-v2-2819441432-rg45q': 10
customer => preference => recommendation v2 from 'recommendation-v2-2819441432-525lh': 3
customer => preference => recommendation v2 from 'recommendation-v2-2819441432-rg45q': 11
customer => preference => recommendation v1 from 'recommendation-v1-99634814-d2z2t': 1153
customer => preference => recommendation v1 from 'recommendation-v1-99634814-d2z2t': 1154
customer => preference => recommendation v1 from 'recommendation-v1-99634814-d2z2t': 1155
customer => preference => recommendation v2 from 'recommendation-v2-2819441432-rg45q': 12
customer => preference => recommendation v2 from 'recommendation-v2-2819441432-525lh': 4
customer => preference => recommendation v2 from 'recommendation-v2-2819441432-525lh': 5
customer => preference => recommendation v2 from 'recommendation-v2-2819441432-rg45q': 13
customer => preference => recommendation v2 from 'recommendation-v2-2819441432-rg45q': 14