In this tutorial you'll get a full tour through Keptn. Before we get started you'll get to know what you will learn while you walk yourself through this tutorial.
You'll find a time estimate until the end of this tutorial in the right top corner of your screen - this should give you guidance how much time is needed for each step.
Before you can get started, please make sure to have Keptn installed on your Kubernetes cluster.
If not, please follow one of these tutorials to install Keptn on your favourite Kubernetes distribution.
A project in Keptn is the logical unit that can hold multiple (micro)services. Therefore, it is the starting point for each Keptn installation.
To get all files you need for this tutorial, please clone the example repo to your local machine.
git clone --branch release-0.6.2 https://github.com/keptn/examples.git --single-branch
cd examples/onboarding-carts
Create a new project for your services using the keptn create project
command. In this example, the project is called sockshop. Before executing the following command, make sure you are in the examples/onboarding-carts
folder.
Recommended: Create a new project with Git upstream:
To configure a Git upstream for this tutorial, the Git user (--git-user
), an access token (--git-token
), and the remote URL (--git-remote-url
) are required. If a requirement is not met, go to the Keptn documentation where instructions for GitHub, GitLab, and Bitbucket are provided.
keptn create project sockshop --shipyard=./shipyard.yaml --git-user=GIT_USER --git-token=GIT_TOKEN --git-remote-url=GIT_REMOTE_URL
Alternatively: If you don't want to use a Git upstream, you can create a new project without it but please note that this is not the recommended way:
keptn create project sockshop --shipyard=./shipyard.yaml
For creating the project, the tutorial relies on a shipyard.yaml
file as shown below:
stages:
- name: "dev"
deployment_strategy: "direct"
test_strategy: "functional"
- name: "staging"
deployment_strategy: "blue_green_service"
test_strategy: "performance"
- name: "production"
deployment_strategy: "blue_green_service"
remediation_strategy: "automated"
This shipyard contains three stages: dev, staging, and production. This results in the three Kubernetes namespaces: sockshop-dev, sockshop-staging, and sockshop-production.
After creating the project, services can be onboarded to our project.
keptn onboard service carts --project=sockshop --chart=./carts
keptn add-resource --project=sockshop --stage=dev --service=carts --resource=jmeter/basiccheck.jmx --resourceUri=jmeter/basiccheck.jmx
keptn add-resource --project=sockshop --stage=staging --service=carts --resource=jmeter/load.jmx --resourceUri=jmeter/load.jmx
basiccheck.jmx
as well as load.jmx
for your service. However, you must not rename the files because there is a hardcoded dependency on these file names in the current implementation of Keptn's jmeter-service.Since the carts service requires a mongodb database, a second service needs to be onboarded.
--deployment-strategy
flag specifies that for this service a direct deployment strategy in all stages should be used regardless of the deployment strategy specified in the shipyard. Thus, the database is not blue/green deployed.keptn onboard service carts-db --project=sockshop --chart=./carts-db --deployment-strategy=direct
After onboarding the services, a built artifact of each service can be deployed.
keptn send event new-artifact --project=sockshop --service=carts-db --image=docker.io/mongo --tag=4.2.2
keptn send event new-artifact --project=sockshop --service=carts --image=docker.io/keptnexamples/carts --tag=0.11.1
kubectl port-forward svc/bridge -n keptn 9000:8080
Configuration change
events). During a deployment, Keptn generates events for controlling the deployment process. These events will also show up in Keptn's Bridge. Please note that if events are sent at the same time, their order in the Keptn's Bridge might be arbitrary since they are sorted on the granularity of one second.kubectl get pods --all-namespaces | grep carts
sockshop-dev carts-77dfdc664b-25b74 1/1 Running 0 10m
sockshop-dev carts-db-54d9b6775-lmhf6 1/1 Running 0 13m
sockshop-production carts-db-54d9b6775-4hlwn 2/2 Running 0 12m
sockshop-production carts-primary-79bcc7c99f-bwdhg 2/2 Running 0 2m15s
sockshop-staging carts-db-54d9b6775-rm8rw 2/2 Running 0 12m
sockshop-staging carts-primary-79bcc7c99f-mbbgq 2/2 Running 0 7m24s
echo http://carts.sockshop-dev.$(kubectl get cm keptn-domain -n keptn -o=jsonpath='{.data.app_domain}')
echo http://carts.sockshop-staging.$(kubectl get cm keptn-domain -n keptn -o=jsonpath='{.data.app_domain}')
echo http://carts.sockshop-production.$(kubectl get cm keptn-domain -n keptn -o=jsonpath='{.data.app_domain}')
Now that the service is running in all three stages, let us generate some traffic so we have some data we can base the evaluation on.
Change the directory to examples/load-generation/cartsloadgen
. If you are still in the onboarding-carts directory, use the following command or change it accordingly:
cd ../load-generation/cartsloadgen
Now let us deploy a pod that will generate some traffic for all three stages of our demo environment.
kubectl apply -f deploy/cartsloadgen-base.yaml
The output will look similar to this.
namespace/loadgen created
deployment.extensions/cartsloadgen created
Optionally, you can verify that the load generator has been started.
kubectl get pods -n loadgen
NAME READY STATUS RESTARTS AGE
cartsloadgen-5dc47c85cf-kqggb 1/1 Running 0 117s
After creating a project and service, you can setup Prometheus monitoring and configure scrape jobs using the Keptn CLI.
kubectl apply -f https://raw.githubusercontent.com/keptn-contrib/prometheus-service/release-0.3.3/deploy/service.yaml
keptn configure monitoring prometheus --project=sockshop --service=carts
kubectl port-forward svc/prometheus-service 8080 -n monitoring
Prometheus is then available on localhost:8080/targets where you can see the targets for the service:
During the evaluation of a quality gate, the Prometheus SLI provider is required that is implemented by an internal Keptn service, the prometheus-sli-service. This service will fetch the values for the SLIs that are referenced in a SLO configuration.
To install the prometheus-sli-service, execute:
kubectl apply -f https://raw.githubusercontent.com/keptn-contrib/prometheus-sli-service/0.2.3/deploy/service.yaml -n keptn
Keptn requires a performance specification for the quality gate. This specification is described in a file called slo.yaml
, which specifies a Service Level Objective (SLO) that should be met by a service. To learn more about the slo.yaml file, go to Specifications for Site Reliability Engineering with Keptn.
Activate the quality gates for the carts service. Therefore, navigate to the examples/onboarding-carts
folder and upload the slo-quality-gates.yaml
file using the add-resource command:
Make sure you are in the correct folder examples/onboarding-carts
. If not, change the directory accordingly, e.g., cd ../../onboarding-carts
.
keptn add-resource --project=sockshop --stage=staging --service=carts --resource=slo-quality-gates.yaml --resourceUri=slo.yaml
This will add the SLO.yaml
file to your Keptn - which is the declarative definition of a quality gate. Let's take a look at the file contents:
---
spec_version: "0.1.1"
comparison:
aggregate_function: "avg"
compare_with: "single_result"
include_result_with_score: "pass"
number_of_comparison_results: 1
filter:
objectives:
- sli: "response_time_p95"
key_sli: false
pass: # pass if (relative change <= 10% AND absolute value is < 600ms)
- criteria:
- "<=+10%" # relative values require a prefixed sign (plus or minus)
- "<600" # absolute values only require a logical operator
warning: # if the response time is below 800ms, the result should be a warning
- criteria:
- "<=800"
weight: 1
total_score:
pass: "90%"
warning: "75%"
You can take a look at the currently deployed version of our "carts" microservice before we deploy the next build of our microservice.
echo http://carts.sockshop-dev.$(kubectl get cm keptn-domain -n keptn -o=jsonpath='{.data.app_domain}')
echo http://carts.sockshop-staging.$(kubectl get cm keptn-domain -n keptn -o=jsonpath='{.data.app_domain}')
echo http://carts.sockshop-production.$(kubectl get cm keptn-domain -n keptn -o=jsonpath='{.data.app_domain}')
http://carts.sockshop-production.YOUR.DOMAIN
for viewing the carts service in your production environment and you should receive an output similar to the following:keptn send event new-artifact --project=sockshop --service=carts --image=docker.io/keptnexamples/carts --tag=0.11.2
dev
and staging
environments by opening a browser for both environments. Get the URLs with these commands:echo http://carts.sockshop-dev.$(kubectl get cm keptn-domain -n keptn -o=jsonpath='{.data.app_domain}')
echo http://carts.sockshop-staging.$(kubectl get cm keptn-domain -n keptn -o=jsonpath='{.data.app_domain}')
After triggering the deployment of the carts service in version v0.11.2, the following status is expected:
echo http://carts.sockshop-dev.$(kubectl get cm keptn-domain -n keptn -o=jsonpath='{.data.app_domain}')
echo http://carts.sockshop-production.$(kubectl get cm keptn-domain -n keptn -o=jsonpath='{.data.app_domain}')
Take a look in the Keptn's bridge (that you opened earlier in this tutorial) and navigate to the last deployment. You will find a quality gate evaluation that got a fail
result when evaluation the SLOs of our carts microservice. Thanks to this quality gate the slow build won't be promoted to production but instead automatically rolled back.
keptn send event new-artifact --project=sockshop --service=carts --image=docker.io/keptnexamples/carts --tag=0.11.3
Version: v3
.kubectl get deployments -n sockshop-production
NAME DESIRED CURRENT UP-TO-DATE AVAILABLE AGE
carts-db 1 1 1 1 63m
carts-primary 1 1 1 1 98m
kubectl describe deployment carts-primary -n sockshop-production
...
Pod Template:
Labels: app=carts-primary
Containers:
carts:
Image: docker.io/keptnexamples/carts:0.11.3
Next, you will learn how to use the capabilities of Keptn to provide self-healing for an application without modifying code. In the next part, we configure Keptn to scale up the pods of an application if the application undergoes heavy CPU saturation.
First, make sure you are in the correct folder examples/onboarding-carts
otherwise the next commands will fail!
Add an SLO file for the production stage using the Keptn CLIs add-resource command:
keptn add-resource --project=sockshop --stage=production --service=carts --resource=slo-self-healing.yaml --resourceUri=slo.yaml
Note: The SLO file contains an objective for response_time_p90.
Configure Prometheus with the Keptn CLI (this configures the Alert Manager based on the slo.yaml file):
keptn configure monitoring prometheus --project=sockshop --service=carts
Configure remediation actions for up-scaling based on Prometheus alerts:
keptn add-resource --project=sockshop --stage=production --service=carts --resource=remediation.yaml --resourceUri=remediation.yaml
This is the content of the file that has being added:
remediations:
- name: response_time_p90
actions:
- action: scaling
value: +1
- name: Response time degradation
actions:
- action: scaling
value: +1
To simulate user traffic that is causing an unhealthy behavior in the carts service, please execute the following script. This will add special items into the shopping cart that cause some extensive calculation.
cd ../load-generation/cartsloadgen/deploy
kubectl apply -f cartsloadgen-faulty.yaml
kubectl port-forward svc/prometheus-server 8080:80 -n monitoring
histogram_quantile(0.9, sum by(le) (rate(http_response_time_milliseconds_bucket{job="carts-sockshop-production"}[3m])))
carts
service in the sockshop-production
environment.After approximately 10-15 minutes, the Alert Manager will send out an alert since the service level objective is not met anymore.
To verify that an alert was fired, select the Alerts view where you should see that the alert response_time_p90
is in the firing
state:
After receiving the problem notification, the prometheus-service will translate it into a Keptn CloudEvent. This event will eventually be received by the remediation-service that will look for a remediation action specified for this type of problem and, if found, execute it.
In this tutorial, the number of pods will be increased to remediate the issue of the response time increase.
kubectl get deployments -n sockshop-production
You can see that the carts-primary
deployment is now served by two pods:NAME DESIRED CURRENT UP-TO-DATE AVAILABLE AGE
carts-db 1 1 1 1 37m
carts-primary 2 2 2 2 32m
kubectl get pods -n sockshop-production
NAME READY STATUS RESTARTS AGE
carts-db-57cd95557b-r6cg8 1/1 Running 0 38m
carts-primary-7c96d87df9-75pg7 2/2 Running 0 33m
carts-primary-7c96d87df9-78fh2 2/2 Running 0 5m
kubectl port-forward svc/bridge -n keptn 9000:8080
Now, access the bridge from your browser on http://localhost:9000.In this example, the bridge shows that the remediation service triggered an update of the configuration of the carts service by increasing the number of replicas to 2. When the additional replica was available, the wait-service waited for ten minutes for the remediation action to take effect. Afterwards, an evaluation by the lighthouse-service was triggered to check if the remediation action resolved the problem. In this case, increasing the number of replicas achieved the desired effect, since the evaluation of the service level objectives has been successful.Thanks for taking a full tour through Keptn!
Although Keptn has even more to offer that should have given you a good overview what you can do with Keptn.
shipyard
filestages:
- name: "dev"
deployment_strategy: "direct"
test_strategy: "functional"
- name: "staging"
deployment_strategy: "blue_green_service"
test_strategy: "performance"
- name: "production"
deployment_strategy: "blue_green_service"
remediation_strategy: "automated"
slo
file---
spec_version: "0.1.1"
comparison:
aggregate_function: "avg"
compare_with: "single_result"
include_result_with_score: "pass"
number_of_comparison_results: 1
filter:
objectives:
- sli: "response_time_p95"
key_sli: false
pass: # pass if (relative change <= 10% AND absolute value is < 600ms)
- criteria:
- "<=+10%" # relative values require a prefixed sign (plus or minus)
- "<600" # absolute values only require a logical operator
warning: # if the response time is below 800ms, the result should be a warning
- criteria:
- "<=800"
weight: 1
total_score:
pass: "90%"
warning: "75%"
Keptn can be easily extended with external tools such as notification tools, other SLI providers, bots to interact with Keptn, etc.
While we do not cover additional integrations in this tutorial, please feel fee to take a look at our integration repositories:
Please visit us in our Keptn Slack and tell us how you like Keptn and this tutorial! We are happy to hear your thoughts & suggestions!
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