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Your First Experiment

Scenario: Validate service-level objectives (SLOs) for a K8s app

Problem: You have a K8s app. You want to verify that it satisfies latency and error rate SLOs.

Solution: In this tutorial, you will launch a K8s app along with an Iter8 experiment. Iter8 will validate that the new satisfies latency and error-based objectives (SLOs) using built-in metrics.

SLO Validation

Setup K8s cluster and local environment
  1. Setup K8s cluster
  2. Install Iter8 in K8s cluster
  3. Get Helm 3.4+.
  4. Get iter8ctl
  5. Fork the Iter8 GitHub repo. Clone your fork, and set the ITER8 environment variable as follows.
    export USERNAME=<your GitHub username>
    git clone$USERNAME/iter8.git
    cd iter8
    export ITER8=$(pwd)

1. Create app

The hello world app consists of a K8s deployment and service. Deploy the app as follows.

kubectl apply -n default -f $ITER8/samples/deployments/app/deploy.yaml
kubectl apply -n default -f $ITER8/samples/deployments/app/service.yaml

Verify app

Verify that the app is running using these instructions
# do this in a separate terminal
kubectl port-forward -n default svc/hello 8080:8080
curl localhost:8080
# output will be similar to the following (notice 1.0.0 version tag)
# hostname will be different in your environment
Hello, world!
Version: 1.0.0
Hostname: hello-bc95d9b56-xp9kv

2. Create Iter8 experiment

Deploy an Iter8 experiment for SLO validation of the app as follows.

helm upgrade -n default my-exp $ITER8/samples/first-exp \
  --set URL='http://hello.default.svc.cluster.local:8080' \
  --set limitMeanLatency=50.0 \
  --set limitErrorRate=0.0 \
  --set limit95thPercentileLatency=100.0 \

The above command creates an Iter8 experiment that generates requests, collects latency and error rate metrics for the app, and verifies that the app satisfies mean latency (50 msec), error rate (0.0), 95th percentile tail latency SLO (100 msec) SLOs.

View Iter8 experiment

View the Iter8 experiment as follows.

helm get manifest -n default my-exp

3. Observe experiment

Assert that the experiment completed and found a winning version. Wait 20 seconds before trying the following command. If the assertions are not satisfied, try again after a few seconds.

iter8ctl assert -c completed -c winnerFound

Describe the results of the Iter8 experiment.

iter8ctl describe

Experiment results will look similar to this ...
****** Overview ******
Experiment name: my-experiment
Experiment namespace: default
Target: my-app
Testing pattern: Conformance
Deployment pattern: Progressive

****** Progress Summary ******
Experiment stage: Completed
Number of completed iterations: 1

****** Winner Assessment ******
> If the version being validated; i.e., the baseline version, satisfies the experiment objectives, it is the winner.
> Otherwise, there is no winner.
Winning version: my-app

****** Objective Assessment ******
> Identifies whether or not the experiment objectives are satisfied by the most recently observed metrics values for each version.
|              OBJECTIVE               | MY-APP |
| iter8-system/mean-latency <=         | true   |
|                               50.000 |        |
| iter8-system/error-rate <=           | true   |
|                                0.000 |        |
| iter8-system/latency-95th-percentile | true   |
| <= 100.000                           |        |

****** Metrics Assessment ******
> Most recently read values of experiment metrics for each version.
|                METRIC                | MY-APP |
| iter8-system/mean-latency            |  1.233 |
| iter8-system/error-rate              |  0.000 |
| iter8-system/latency-95th-percentile |  2.311 |
| iter8-system/request-count           | 40.000 |
| iter8-system/error-count             |  0.000 |

4. Cleanup

# remove experiment
helm uninstall -n default my-exp
# remove app
kubectl delete -n default -f $ITER8/samples/deployments/app/service.yaml
kubectl delete -n default -f $ITER8/samples/deployments/app/deploy.yaml

Next Steps

Use with your app

  1. Run the above experiment with your app by setting the URL value in the Helm command to the URL of your app.

  2. You can also customize the mean latency, error rate, and tail latency limits.

  3. This experiment can be run in any K8s environment such as a dev, test, staging, or production cluster.

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