gbraad / istio-tutorial

Java (Spring Boot) + Istio on Kubernetes/OpenShift

There are three different and super simple microservices in this system and they are chained together in the following sequence:

customer -> preferences -> recommendations

For now, they have a simple exception handling solution for dealing with a missing dependent service, it just returns the error message to the end-user.

There are two more simple apps that illustrate how Istio handles egress routes: egressgithub and egresshttpbin

Table of Contents

• Prerequisite CLI tools
• Setup minishift
• Setup environment
• Istio installation script
• Deploy customer
• Deploy preferences
• Deploy recommendations
• Updating & redeploying code
• Tracing
• Monitoring
• Istio RouteRule Changes
  • recommendations:v2
• Changing Istio RouteRules
  • All users to recommendations:v2
  • All users to recommendations:v1
  • All users to recommendations v1 and v2
  • Split traffic between v1 and v2
• Fault Injection
  • HTTP Error 503
  • Delay
• Retry
• Timeout
• Smart routing based on user-agent header (Canary Deployment)
  • Set recommendations to all v1
  • Set Safari users to v2
  • Set mobile users to v2
  • Clean up
• Mirroring Traffic (Dark Launch)
• Access Control
  • Whitelist
  • Blacklist
• Load Balancer
• Circuit Breaker
  • Fail Fast with Max Connections & Max Pending Requests
  • Pool ejection
• Egress
  • Create HTTPBin Java App
  • Create the Github Java App
  • Istio-ize Egress
• Rate Limiting
• Tips & Tricks

Prerequisite CLI tools

You will need in this tutorial

• minishift (https://github.com/minishift/minishift/releases)
• docker (https://www.docker.com/docker-mac)
• kubectl (https://kubernetes.io/docs/tasks/tools/install-kubectl/#install-kubectl-binary-via-curl)
• oc (eval $(minishift oc-env))
• mvn (https://archive.apache.org/dist/maven/maven-3/3.3.9/binaries/apache-maven-3.3.9-bin.tar.gz)
• stern (brew install stern)
• istioctl (will be installed via the steps below)
• curl, gunzip, tar are built-in to MacOS or part of your bash shell
• git (everybody needs the git CLI)

Setup minishift

Assumes minishift, tested with minshift v1.10.0+10461c6

Minishift creation script

#!/bin/bash

# add the location of minishift execuatable to PATH
# I also keep other handy tools like kubectl and kubetail.sh
# in that directory

export PATH=/Users/burr/minishift_1.10.0/:$PATH

minishift profile set tutorial
minishift config set memory 8GB
minishift config set cpus 3
minishift config set vm-driver virtualbox
minishift config set image-caching true
minishift addon enable admin-user
minishift config set openshift-version v3.7.0

MINISHIFT_ENABLE_EXPERIMENTAL=y minishift start --metrics

Setup environment

eval $(minishift oc-env)
eval $(minishift docker-env)
oc login $(minishift ip):8443 -u admin -p admin

Istio installation script

#!/bin/bash

curl -LO https://github.com/istio/istio/releases/download/0.4.0/istio-0.4.0-osx.tar.gz

gunzip istio-0.4.0-osx.tar.gz

tar -xvzf istio-0.4.0-osx.tar

cd istio-0.4.0

# make sure we are logged in
oc login $(minishift ip):8443 -u admin -p admin

oc adm policy add-scc-to-user anyuid -z istio-ingress-service-account -n istio-system

oc adm policy add-scc-to-user anyuid -z istio-egress-service-account -n istio-system

oc adm policy add-scc-to-user anyuid -z default -n istio-system

oc create -f install/kubernetes/istio.yaml

oc project istio-system

oc expose svc istio-ingress

oc apply -f install/kubernetes/addons/prometheus.yaml

oc apply -f install/kubernetes/addons/grafana.yaml

oc apply -f install/kubernetes/addons/servicegraph.yaml

oc expose svc servicegraph

oc expose svc grafana

oc expose svc prometheus

oc process -f https://raw.githubusercontent.com/jaegertracing/jaeger-openshift/master/all-in-one/jaeger-all-in-one-template.yml | oc create -f -

Wait for Istio's components to be ready

oc get pods
NAME                             READY     STATUS    RESTARTS   AGE
grafana-3617079618-4qs2b         1/1       Running   0          4m
istio-ca-1363003450-tfnjp        1/1       Running   0          4m
istio-ingress-1005666339-vrjln   1/1       Running   0          4m
istio-mixer-465004155-zn78n      3/3       Running   0          5m
istio-pilot-1861292947-25hnm     2/2       Running   0          4m
jaeger-210917857-2w24f           1/1       Running   0          4m
prometheus-168775884-dr5dm       1/1       Running   0          4m
servicegraph-1100735962-tdh78    1/1       Running   0          4m

And if you need quick access to the OpenShift console

minishift console

Deploy customer

Make sure you have are logged in

oc whoami

and you have setup the project/namespace

oc new-project tutorial
oc adm policy add-scc-to-user privileged -z default -n tutorial

git clone https://github.com/redhat-developer-demos/istio-tutorial
cd istio-tutorial
cd customer
mvn clean package
docker build -t example/customer .
docker images | grep customer

Note: Your very first docker build will take a bit of time as it downloads all the layers. Subsequent rebuilds of the docker image, updating only the jar/app layer will be very fast.

Currently using the "manual" way of injecting the Envoy sidecar

Add istioctl to your $PATH, you downloaded it a few steps back. An example

export PATH=/Users/burr/minishift_1.10.0/istio-0.4.0/bin:$PATH

istioctl version

Version: 0.4.0
GitRevision: 24089ea97c8d244493c93b499a666ddf4010b547-dirty
GitBranch: 6401744b90b43901b2aa4a8bced33c7bd54ffc13
User: root@cc5c34bbd1ee
GolangVersion: go1.8

Now let's deploy the customer pod with its sidecar

oc apply -f <(istioctl kube-inject -f src/main/kubernetes/Deployment.yml) -n tutorial

oc create -f src/main/kubernetes/Service.yml -n tutorial

Since customer is the forward most microservice (customer -> preferences -> recommendations), let's add an OpenShift Route that exposes that endpoint.

oc expose service customer

oc get route

oc get pods -w

Waiting for Ready 2/2, to break out of the waiting use "ctrl-c"

curl customer-tutorial.$(minishift ip).nip.io

You should see the following error because preferences is not yet deployed, so you only get a partial response of "C100" plus the error message since preferences and recommendations are not yet deployed.

C100 *I/O error on GET request for "http://preferences:8080/"

Back to the main istio-tutorial directory

cd ..

Deploy preferences

cd preferences

mvn clean package

docker build -t example/preferences .

docker images | grep preferences

oc apply -f <(istioctl kube-inject -f src/main/kubernetes/Deployment.yml) -n tutorial

oc create -f src/main/kubernetes/Service.yml

oc get pods -w

Wait for the Ready 2/2

curl customer-tutorial.$(minishift ip).nip.io

Preferences returns a value but also an error message based on the missing recommendations service

C100 *{"P1":"Red", "P2":"Big"} && I/O error on GET request for "http://recommendations:8080/"

cd ..

Deploy recommendations

cd recommendations

mvn clean package

docker build -t example/recommendations:v1 .

docker images | grep recommendations

oc apply -f <(istioctl kube-inject -f src/main/kubernetes/Deployment.yml) -n tutorial

oc create -f src/main/kubernetes/Service.yml

oc get pods -w

curl customer-tutorial.$(minishift ip).nip.io

it returns

C100 *{"P1":"Red", "P2":"Big"} && Clifford v1 1 *

Back to the main istio-tutorial directory

cd ..

Updating & redeploying code

When you wish to change code (e.g. editing the .java files) and wish to "redeploy", simply:

cd {servicename}

vi src/main/java/com/example/{servicename}/{Servicename}Controller.java

Make your edits and esc-w-q

mvn clean package
docker build -t example/{servicename} .
oc get pods -o jsonpath='{.items[*].metadata.name}' -l app={servicename}
oc get pods -o jsonpath='{.items[*].metadata.name}' -l app={servicename},version=v1

oc delete pod -l app={servicename},version=v1

Why the delete pod? Based on the Deployment configuration, Kubernetes/OpenShift will recreate the pod, based on the new docker image as it attempts to keep the desired replicas available

oc describe deployment {servicename} | grep Replicas

Monitoring

Out of the box, you get monitoring via Prometheus and Grafana.

minishift openshift service grafana --in-browser

Make sure to select "Istio Dashboard" in the Grafana Dashboard

Scroll-down to see the stats for customer, preferences and recommendations

Custom Metrics

Istio also allows you to specify custom metrics which can be seen inside of the Prometheus dashboard

minishift openshift service prometheus --in-browser

Add the custom metric and rule. First make sure you are in the "istio-tutorial" directory and then

oc apply -f istiofiles/recommendations_requestcount.yml -n istio-system

In the Prometheus dashboard, add the following

round(increase(istio_recommendations_request_count{destination="recommendations.tutorial.svc.cluster.local" }[60m]))

and select Execute

Then run several requests through the system

curl customer-tutorial.$(minishift ip).nip.io

Note: you may have to refresh the browser for the Prometheus graph to update.

Tracing

Tracing requires a bit of work on the Java side. Each microservice needs to pass on the headers which are used to enable the traces.

https://github.com/redhat-developer-demos/istio-tutorial/blob/master/customer/src/main/java/com/example/customer/CustomerController.java#L21-L42

and https://github.com/redhat-developer-demos/istio-tutorial/blob/master/customer/src/main/java/com/example/customer/CustomerController.java#L49

To open the Jaeger console, select customer from the list of services and Find Traces

minishift openshift service jaeger-query --in-browser

Istio RouteRule Changes

recommendations:v2

We can experiment with Istio routing rules by making a change to RecommendationsController.java like

System.out.println("Big Red Dog v2 " + cnt);

return "Clifford v2 " + cnt;

The "v2" tag during the docker build is significant.

There is also a 2nd deployment.yml file to label things correctly

cd recommendations

mvn clean compile package

docker build -t example/recommendations:v2 .

docker images | grep recommendations
example/recommendations                  v2                  c31e399a9628        5 seconds ago       438MB
example/recommendations                  latest              f072978d9cf6        8 minutes ago      438MB

Important: back up one directory before applying the deployment yaml

cd ..

oc apply -f <(istioctl kube-inject -f kubernetesfiles/recommendations_v2_deployment.yml) -n tutorial

oc get pods -w

Wait for those pods to show "2/2", the istio-proxy/envoy sidecar is part of that pod

curl customer-tutorial.$(minishift ip).nip.io

you likely see "Clifford v1 5", where the 5 is basically the number of times you hit the endpoint.

curl customer-tutorial.$(minishift ip).nip.io

you likely see "Clifford v2 1" as by default you get random load-balancing when there is more than one Pod behind a Service

Double-check that you are logged in as admin.

oc whoami

and login as admin if necessary

oc login $(minishift ip):8443 -u admin -p admin

Changing Istio RouteRules

All users to recommendations:v2

From the istio-tutorial directory,

oc create -f istiofiles/route-rule-recommendations-v2.yml -n tutorial

curl customer-tutorial.$(minishift ip).nip.io

you should only see v2 being returned

All users to recommendations:v1

Note: "replace" instead of "create" since we are overlaying the previous rule

oc replace -f istiofiles/route-rule-recommendations-v1.yml -n tutorial

oc get routerules -n tutorial

oc get routerules/recommendations-default -o yaml -n tutorial

All users to recommendations v1 and v2

By simply removing the rule

oc delete routerules/recommendations-default -n tutorial

and you should see the default behavior of load-balancing between v1 and v2

curl customer-tutorial.$(minishift ip).nip.io

Split traffic between v1 and v2

Canary Deployment scenario: push v2 into the cluster but slowing send end-user traffic to it, if you continue to see success, continue shifting more traffic over time

oc get pods -l app=recommendations -n tutorial
NAME                                  READY     STATUS    RESTARTS   AGE
recommendations-v1-3719512284-7mlzw   2/2       Running   6          2h
recommendations-v2-2815683430-vn77w   2/2       Running   0          1h

Create the routerule that will send 90% of requests to v1 and 10% to v2

oc create -f istiofiles/route-rule-recommendations-v1_and_v2.yml -n tutorial

and send in several requests

#!/bin/bash

while true
do curl customer-tutorial.$(minishift ip).nip.io
echo
sleep .1
done

In another terminal, change the mixture to be 75/25

oc replace -f istiofiles/route-rule-recommendations-v1_and_v2_75_25.yml -n tutorial

Clean up

oc delete routerule recommendations-v1-v2 -n tutorial

Fault Injection

Apply some chaos engineering by throwing in some HTTP errors or network delays. Understanding failure scenarios is a critical aspect of microservices architecture (aka distributed computing)

HTTP Error 503

By default, recommendations v1 and v2 are being randomly load-balanced as that is the default behavior in Kubernetes/OpenShift

oc get pods -l app=recommendations -n tutorial
NAME                                  READY     STATUS    RESTARTS   AGE
recommendations-v1-3719512284-7mlzw   2/2       Running   6          18h
recommendations-v2-2815683430-vn77w   2/2       Running   0          3h

You can inject 503's, for approximately 50% of the requests

oc create -f istiofiles/route-rule-recommendations-503.yml -n tutorial

curl customer-tutorial.$(minishift ip).nip.io
C100 *{"P1":"Red", "P2":"Big"} && Clifford v1 *
curl customer-tutorial.$(minishift ip).nip.io
C100 *{"P1":"Red", "P2":"Big"} && 503 Service Unavailable *
curl customer-tutorial.$(minishift ip).nip.io
C100 *{"P1":"Red", "P2":"Big"} && Clifford v2 *

Clean up

oc delete routerule recommendations-503 -n tutorial

Delay

The most insidious of possible distributed computing faults is not a "down" service but a service that is responding slowly, potentially causing a cascading failure in your network of services.

oc create -f istiofiles/route-rule-recommendations-delay.yml -n tutorial

And hit the customer endpoint

#!/bin/bash
  
while true
do
time curl customer-tutorial.$(minishift ip).nip.io
echo
sleep .1
done

You will notice many requets to the customer endpoint now have a delay. If you are monitoring the logs for recommendations v1 and v2, you will also see the delay happens BEFORE the recommendations service is actually called

stern recommendations -n tutorial
or
./kubetail.sh recommendations -n tutorial

Clean up

oc delete routerule recommendations-delay -n tutorial

Retry

Instead of failing immediately, retry the Service N more times

We will use Istio and return 503's about 50% of the time. Send all users to v2 which will throw out some 503's

oc create -f istiofiles/route-rule-recommendations-v2_503.yml -n tutorial

Now, if you hit the customer endpoint several times, you should see some 503's

curl customer-tutorial.$(minishift ip).nip.io
C100 *{"P1":"Red", "P2":"Big"} && 503 Service Unavailable *

Now add the retry rule

oc create -f istiofiles/route-rule-recommendations-v2_retry.yml -n tutorial

and after a few seconds, things will settle down and you will see it work every time

curl customer-tutorial.$(minishift ip).nip.io
C100 *{"P1":"Red", "P2":"Big"} && Clifford v2 123*

You can see the active RouteRules via

oc get routerules -n tutorial

Now, delete the retry rule and see the old behavior, some random 503s

oc delete routerule recommendations-v2-retry -n tutorial

curl customer-tutorial.$(minishift ip).nip.io

Now, delete the 503 rule and back to random load-balancing between v1 and v2

oc delete routerule recommendations-v2-503 -n tutorial

curl customer-tutorial.$(minishift ip).nip.io

Timeout

Wait only N seconds before giving up and failing. At this point, no other route rules should be in effect. oc get routerules and oc delete routerule rulename if there are some.

First, introduce some wait time in recommendations v2. Update RecommendationsController.java to include a Thread.sleep, making it a slow perfomer

    @RequestMapping("/")
    public String getRecommendations() {
        
        cnt ++;        
        System.out.println("Big Red Dog v2 " + cnt);

        // begin circuit-breaker example
        try {
            Thread.sleep(3000);
		} catch (InterruptedException e) {			
            e.printStackTrace();
		}
        System.out.println("recommendations ready to return");
        // end circuit-breaker example
        return "Clifford v2 " + cnt ;

Rebuild and redeploy

cd recommendations

mvn clean compile package

docker build -t example/recommendations:v2 .

docker images | grep recommendations

oc delete pod -l app=recommendations,version=v2 -n tutorial

cd ..

Hit the customer endpoint a few times, to see the load-balancing between v1 and v2 but with v2 taking a bit of time to respond

#!/bin/bash
  
while true
do
time curl customer-tutorial.$(minishift ip).nip.io
echo
sleep .1
done

Then add the timeout rule

oc create -f istiofiles/route-rule-recommendations-timeout.yml -n tutorial

time curl customer-tutorial.$(minishift ip).nip.io

You will see it return v1 OR 504 after waiting about 1 second

time curl customer-tutorial.$(minishift ip).nip.io
C100 *{"P1":"Red", "P2":"Big"} && Clifford v1 *
time curl customer-tutorial.$(minishift ip).nip.io
C100 *{"P1":"Red", "P2":"Big"} && 504 Gateway Timeout *

Clean up, delete the timeout rule

oc delete routerule recommendations-timeout -n tutorial

Smart routing based on user-agent header (Canary Deployment)

What is your user-agent?

https://www.whoishostingthis.com/tools/user-agent/

Note: the "user-agent" header being forwarded in the Customer and Preferences controllers in order for route rule modications around recommendations

Set recommendations to all v1

oc create -f istiofiles/route-rule-recommendations-v1.yml -n tutorial

Set Safari users to v2

oc create -f istiofiles/route-rule-safari-recommendations-v2.yml -n tutorial

oc get routerules -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 recommendations

and test with a Firefox browser, it should only see v1 responses from recommendations.

There are two ways to get the URL for your browser:

echo customer-tutorial.$(minishift ip).nip.io

customer-tutorial.192.168.99.102.nip.io

That will expand the IP address to something you can copy & paste into your browser's location field.

Or

minishift openshift service customer --url
http://customer-tutorial.192.168.99.102.nip.io

You can also attempt to use the curl -A command to test with different user-agent strings.

curl -A Safari customer-tutorial.$(minishift ip).nip.io
curl -A Firefox customer-tutorial.$(minishift ip).nip.io

You can describe the routerule to see its configuration

oc describe routerule recommendations-safari -n tutorial

Remove the Safari rule

oc delete routerule recommendations-safari -n tutorial

Set mobile users to v2

oc create -f istiofiles/route-rule-mobile-recommendations-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" http://customer-tutorial.$(minishift ip).nip.io/

Clean up

oc delete routerule recommendations-mobile -n tutorial

Mirroring Traffic (Dark Launch)

Wiretap, eavesdropping Note: does not seem to work in 0.4.0

oc get pods -l app=recommendations -n tutorial

You should have 2 pods for recommendations based on the steps above

oc get routerules -n tutorial

You should have NO routerules if so "oc delete routerule rulename -n tutorial"

Make sure you are in the main directory of "istio-tutorial"

oc create -f istiofiles/route-rule-recommendations-v1-mirror-v2.yml -n tutorial

curl customer-tutorial.$(minishift ip).nip.io

Access Control

Whitelist

We'll create a whitelist on the preferences service to only allow requests from the recommendations service, which will make the preferences service invisible to the customer service. Requests from the customer service to the preferences service will return a 404 Not Found HTTP error code.

istioctl create -f istiofiles/act-whitelist.yml -n tutorial

curl customer-tutorial.$(minishift ip).nip.io
C100 *404 Not Found *

To reset the environment:

istioctl delete -f istiofiles/act-whitelist.yml -n tutorial

Blacklist

We'll create a blacklist making the customer service blacklist to the preferences service. Requests from the customer service to the preferences service will return a 403 Forbidden HTTP error code.

istioctl create -f istiofiles/act-blacklist.yml -n tutorial

curl customer-tutorial.$(minishift ip).nip.io
C100 *403 Forbidden * 

To reset the environment:

istioctl delete -f istiofiles/act-blacklist.yml -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

oc scale deployment recommendations-v2 --replicas=2 -n tutorial

Wait a bit (oc get pods -w to watch) and curl the customer endpoint many times

curl customer-tutorial.$(minishift ip).nip.io

Add a 3rd v2 pod to the mix

oc scale deployment recommendations-v2 --replicas=3 -n tutorial

oc get pods -n tutorial
NAME                                  READY     STATUS    RESTARTS   AGE
customer-1755156816-cjd2z             2/2       Running   0          1h
preferences-3336288630-2cc6f          2/2       Running   0          1h
recommendations-v1-3719512284-bn42p   2/2       Running   0          59m
recommendations-v2-2815683430-97nnf   2/2       Running   0          43m
recommendations-v2-2815683430-d49n6   2/2       Running   0          51m
recommendations-v2-2815683430-tptf2   2/2       Running   0          33m

Wait for those 2/2 (two containers in each pod) and then poll the customer endpoint

#!/bin/bash

while true
do curl customer-tutorial.$(minishift ip).nip.io
echo
sleep .1
done

The results should follow a fairly normal round-robin distribution pattern

C100 *{"P1":"Red", "P2":"Big"} && Clifford v1 9 * 
C100 *{"P1":"Red", "P2":"Big"} && Clifford v2 7 * 
C100 *{"P1":"Red", "P2":"Big"} && Clifford v2 1 * 
C100 *{"P1":"Red", "P2":"Big"} && Clifford v2 1 * 
C100 *{"P1":"Red", "P2":"Big"} && Clifford v1 10 * 
C100 *{"P1":"Red", "P2":"Big"} && Clifford v2 8 * 
C100 *{"P1":"Red", "P2":"Big"} && Clifford v2 2 * 
C100 *{"P1":"Red", "P2":"Big"} && Clifford v2 2 * 

Now, add the Random LB DestinationPolicy

oc create -f istiofiles/recommendations_lb_policy_app.yml -n tutorial

And you should see a different pattern of which pod is being selected

C100 *{"P1":"Red", "P2":"Big"} && Clifford v2 5 * 
C100 *{"P1":"Red", "P2":"Big"} && Clifford v2 12 * 
C100 *{"P1":"Red", "P2":"Big"} && Clifford v2 5 * 
C100 *{"P1":"Red", "P2":"Big"} && Clifford v2 6 * 
C100 *{"P1":"Red", "P2":"Big"} && Clifford v2 6 * 
C100 *{"P1":"Red", "P2":"Big"} && Clifford v2 13 * 
C100 *{"P1":"Red", "P2":"Big"} && Clifford v2 14 * 
C100 *{"P1":"Red", "P2":"Big"} && Clifford v2 15 * 
C100 *{"P1":"Red", "P2":"Big"} && Clifford v2 7 * 
C100 *{"P1":"Red", "P2":"Big"} && Clifford v1 14 * 

Clean up

oc delete -f istiofiles/recommendations_lb_policy_app.yml -n tutorial

oc scale deployment recommendations-v2 --replicas=1 -n tutorial

Circuit Breaker

Note: Does not work!

Fail Fast with Max Connections & Max Pending Requests

Update RecommendationsController.java to include some logic that throws out some 503s.

        System.out.println("Big Red Dog v2 " + cnt);

        // begin circuit-breaker example
        try {
			Thread.sleep(3000);
		} catch (InterruptedException e) {			
			e.printStackTrace();
		}
        System.out.println("recommendations ready to return");
        // end circuit-breaker example */
        // inject some poor behavior
        if (misbehave) {
            cnt = 0;
            misbehave = false;
            throw new ServiceUnavailableException();            
        }
        // */   
        return "Clifford v2 " + cnt;
    }

    @RequestMapping("/misbehave")
    public HttpStatus misbehave() {
        this.misbehave = true;
        return HttpStatus.OK;
    }

Rebuild, redeploy

cd recommendations

mvn clean compile package

docker build -t example/recommendations:v2 .

docker images | grep recommendations

oc delete pod -l app=recommendations,version=v2 -n tutorial

The deletion of the previously running pod will cause Kubernetes/OpenShift to restart it based on the new docker image.

Back to the main directory

cd ..

curl customer-tutorial.$(minishift ip).nip.io

Whenever you are hitting v2, you will notice the slowness in the response based on the Thread.sleep(3000)

Watch the logging output of recommendations

Terminal 1:
./kubetail.sh recommendations -n tutorial
or
brew install stern
stern recommendations -n tutorial

Terminal 2:
curl customer-tutorial.$(minishift ip).nip.io

Now add the circuit breaker.

istioctl create -f istiofiles/recommendations_cb_policy_version_v2.yml -n tutorial

istioctl get destinationpolicies -n tutorial

More information on the fields for the simple circuit-breaker https://istio.io/docs/reference/config/traffic-rules/destination-policies.html#simplecircuitbreakerpolicy

Add some load by polling the customer endpoint

#!/bin/bash

while true
do curl customer-tutorial.$(minishift ip).nip.io
echo
sleep .5
done

or use ab

note: the trailing slash is important

ab -n 10 -c 2 http://customer-tutorial.192.168.99.103.nip.io/

or use gatling, but first modify the URL gatling is pointing at https://github.com/redhat-developer-demos/istio-tutorial/blob/master/gatling_test/src/test/scala/RecordedSimulation.scala#L11

then

cd gatling_test
mvn integration-test

and open the generated report

If you wish to peer inside the CB

istioctl get destinationpolicies recommendations-circuitbreaker -o yaml -n default

Clean up

istioctl delete -f istiofiles/recommendations_cb_policy_app.yml -n tutorial

Pool ejection

There is a 2nd circuit-breaker policy yaml file. In this case, we are attempting load-balancing pool ejection. We want that slow misbehaving recommendations v2 to be kicked out and all requests handled by v1.

Expose the recommendations via an OpenShift Route

oc expose service recommendations -n tutorial

Up the replica count on v2

oc scale deployment recommendations-v2 --replicas=2 -n tutorial

Hit the newly exposed Route via its url

oc get route
curl recommendations-tutorial.$(minishift ip).nip.io

By default, you will see load-balancing behind that URL, across the 3 pods (single v1 and two v2 pods) that are currently in play

istioctl create -f istiofiles/recommendations_cb_policy_app.yml -n tutorial

and throw some more requests at the customer endpoint, while also watching the logs for recommendations to see the behavior change.

#!/bin/bash

while true
do curl customer-tutorial.$(minishift ip).nip.io
echo
sleep .1
done

Now throw in some misbehavior

curl recommendations-tutorial.$(minishift ip).nip.io/misbehave

Clean up

istioctl delete destinationpolocies recommendations-circuitbreaker -n tutorial

Egress

There are two examples of egress routing, one for httpbin.org and one for github. Egress routes allow you to apply rules to how internal services interact with external APIs/services.

Create HTTPBin Java App

cd egresshttpbin/

mvn spring-boot:run

curl locahost:8080

ctrl-c

mvn clean package

docker build -t example/egresshttpbin:v1 .

docker images | grep egress

docker run -it -p 8080:8080 --rm example/egresshttpbin:v1

curl $(minishift ip):8080

ctrl-c

docker ps | grep egress

docker ps -a | grep egress

oc apply -f <(istioctl kube-inject -f src/main/kubernetes/Deployment.yml) -n istioegress

oc create -f src/main/kubernetes/Service.yml

oc expose service egresshttpbin

curl egresshttpbin-istioegress.$(minishift ip).nip.io

Note: It does not work...yet

cd ..

Create the Github Java App

cd egressgithub/

mvn clean package

docker build -t example/egressgithub:v1 .

docker images | grep egress

docker run -it -p 8080:8080 --rm example/egressgithub:v1

curl $(minishift ip):8080

Note: it will not work now but it will once Istio-ized

ctrl-c

docker ps | grep egress

oc apply -f <(istioctl kube-inject -f src/main/kubernetes/Deployment.yml) -n istioegress

oc create -f src/main/kubernetes/Service.yml

oc expose service egressgithub

curl egressgithub-istioegress.$(minishift ip).nip.io

cd ..

Istio-ize Egress

istioctl create -f istiofiles/egress_httpbin.yml

istioctl get egressrules

curl egresshttpbin-istioegress.$(minishift ip).nip.io

or

oc get pods

oc exec -it egresshttpbin-v1-1125123520-4599t /bin/bash

curl localhost:8080

curl httpbin.org/user-agent

curl httpbin.org/headers

exit

add a egressrule for google

cat <<EOF | istioctl create -f -
apiVersion: config.istio.io/v1alpha2
kind: EgressRule
metadata:
  name: google-egress-rule
spec:
  destination:
    service: www.google.com
  ports:
    - port: 443
      protocol: https
EOF

oc exec -it egresshttpbin-v1-1125123520-4599t /bin/bash

curl http://www.google.com:443

exit

istioctl create -f istiofiles/egress_github.yml

curl egressgithub-istioegress.$(minishift ip).nip.io

Rate Limiting

Here we will limit the number of concurrent requests into recommendations v2

Current view of RecommendationsController.java

package com.example.recommendations;

import org.springframework.web.bind.annotation.RequestMapping;
import org.springframework.web.bind.annotation.RestController;
import org.springframework.web.bind.annotation.ResponseStatus;
import org.springframework.http.HttpStatus;

@RestController
public class RecommendationsController {

    @RequestMapping("/")
    public String getRecommendations() {

        System.out.println("Big Red Dog v2");

        // begin timeout and/or circuit-breaker example
        try {
			Thread.sleep(3000);
		} catch (InterruptedException e) {			
			e.printStackTrace();
		}
        System.out.println("recommendations ready to return");
        // end circuit-breaker example */
        // throw new ServiceUnavailableException();
        return "Clifford v2";
    }

}

@ResponseStatus(HttpStatus.SERVICE_UNAVAILABLE)
class ServiceUnavailableException extends RuntimeException {

}

Now apply the rate limit handler

istioctl create -f istiofiles/recommendations_rate_limit_handler.yml

Now setup the requestcount quota

istioctl create -f istiofiles/recommendations_rate_limit_handler.yml

Throw some requests at customer

#!/bin/bash

while true
do curl customer-tutorial.$(minishift ip).nip.io
echo
sleep .1
done

And you should see some 429 Too Many Requests

C100 *{"P1":"Red", "P2":"Big"} && 429 Too Many Requests *

Clean up

istioctl delete -f istiofiles/rate_limit_rule.yml

istioctl delete -f istiofiles/recommendations_rate_limit_handler.yml

Tips & Tricks

You have two containers in a pod

oc get pods -o jsonpath="{.items[*].spec.containers[*].name}" -l app=customer

From these images

oc get pods -o jsonpath="{.items[*].spec.containers[*].image}" -l app=customer

Get the pod ids

CPOD=$(oc get pods -o jsonpath='{.items[*].metadata.name}' -l app=customer)
PPOD=$(oc get pods -o jsonpath='{.items[*].metadata.name}' -l app=preferences)
RPOD1=$(oc get pods -o jsonpath='{.items[*].metadata.name}' -l app=recommendations,
version=v1)
RPOD2=$(oc get pods -o jsonpath='{.items[*].metadata.name}' -l app=recommendations,version=v2)

The pods all see each other's services

oc exec $CPOD -c customer curl http://preferences:8080
oc exec $CPOD -c customer curl http://recommendations:8080
oc exec $RPOD2 -c recommendations curl http://customer:8080

oc exec $CPOD -c customer curl http://localhost:15000/routes > afile.json

Look for "route_config_name": "8080", you should see 3 entries for customer, preferences and recommendations https://gist.github.com/burrsutter/9117266f84efe124590e9014793c10f6

Now add a new routerule

oc create -f istiofiles/route-rule-recommendations-v2.yml

The review the routes again

oc exec $CPOD -c customer curl http://localhost:15000/routes > bfile.json

Here is the Before: https://gist.github.com/burrsutter/9117266f84efe124590e9014793c10f6#file-gistfile1-txt-L41

and

https://gist.github.com/burrsutter/9117266f84efe124590e9014793c10f6#file-gistfile1-txt-L45

And the After: https://gist.github.com/burrsutter/8b92da2ad0a8ec1b975f5dfa6ddc17f8#file-gistfile1-txt-L41

and

https://gist.github.com/burrsutter/8b92da2ad0a8ec1b975f5dfa6ddc17f8#file-gistfile1-txt-L45

If you need the Pod IP

oc get pods -o jsonpath='{.items[*].status.podIP}' -l app=customer

Dive into the istio-proxy container

oc exec -it $CPOD -c istio-proxy /bin/bash
cd /etc/istio/proxy
ls
cat envoy-rev3.json

Snowdrop Troubleshooting https://github.com/snowdrop/spring-boot-quickstart-istio/blob/master/TROUBLESHOOT.md