Apache APISIX Canary Deployments
This guide shows you how to use the Apache APISIX and Flagger to automate canary deployments.
Prerequisites
Flagger requires a Kubernetes cluster v1.19 or newer and Apache APISIX v2.15 or newer and Apache APISIX Ingress Controller v1.5.0 or newer.
Install Apache APISIX and Apache APISIX Ingress Controller with Helm v3:
helm repo add apisix https://charts.apiseven.com
kubectl create ns apisix
helm upgrade -i apisix apisix/apisix --version=0.11.3 \
--namespace apisix \
--set apisix.podAnnotations."prometheus\.io/scrape"=true \
--set apisix.podAnnotations."prometheus\.io/port"=9091 \
--set apisix.podAnnotations."prometheus\.io/path"=/apisix/prometheus/metrics \
--set pluginAttrs.prometheus.export_addr.ip=0.0.0.0 \
--set pluginAttrs.prometheus.export_addr.port=9091 \
--set pluginAttrs.prometheus.export_uri=/apisix/prometheus/metrics \
--set pluginAttrs.prometheus.metric_prefix=apisix_ \
--set ingress-controller.enabled=true \
--set ingress-controller.config.apisix.serviceNamespace=apisix
Install Flagger and the Prometheus add-on in the same namespace as Apache APISIX:
helm repo add flagger https://flagger.app
helm upgrade -i flagger flagger/flagger \
--namespace apisix \
--set prometheus.install=true \
--set meshProvider=apisix
Bootstrap
Flagger takes a Kubernetes deployment and optionally a horizontal pod autoscaler (HPA), then creates a series of objects (Kubernetes deployments, ClusterIP services and an ApisixRoute). These objects expose the application outside the cluster and drive the canary analysis and promotion.
Create a test namespace:
kubectl create ns test
Create a deployment and a horizontal pod autoscaler:
kubectl apply -k https://github.com/fluxcd/flagger//kustomize/podinfo?ref=main
Deploy the load testing service to generate traffic during the canary analysis:
helm upgrade -i flagger-loadtester flagger/loadtester \
--namespace=test
Create an Apache APISIX ApisixRoute, Flagger will reference and generate the canary Apache APISIX ApisixRoute (replace app.example.com with your own domain):
apiVersion: apisix.apache.org/v2
kind: ApisixRoute
metadata:
name: podinfo
namespace: test
spec:
http:
- backends:
- serviceName: podinfo
servicePort: 80
match:
hosts:
- app.example.com
methods:
- GET
paths:
- /*
name: method
plugins:
- name: prometheus
enable: true
config:
disable: false
prefer_name: true
Save the above resource as podinfo-apisixroute.yaml and then apply it:
kubectl apply -f ./podinfo-apisixroute.yaml
Create a canary custom resource (replace app.example.com with your own domain):
apiVersion: flagger.app/v1beta1
kind: Canary
metadata:
name: podinfo
namespace: test
spec:
provider: apisix
targetRef:
apiVersion: apps/v1
kind: Deployment
name: podinfo
# apisix route reference
routeRef:
apiVersion: apisix.apache.org/v2
kind: ApisixRoute
name: podinfo
# the maximum time in seconds for the canary deployment
# to make progress before it is rollback (default 600s)
progressDeadlineSeconds: 60
service:
# ClusterIP port number
port: 80
# container port number or name
targetPort: 9898
analysis:
# schedule interval (default 60s)
interval: 10s
# max number of failed metric checks before rollback
threshold: 10
# max traffic percentage routed to canary
# percentage (0-100)
maxWeight: 50
# canary increment step
# percentage (0-100)
stepWeight: 10
# APISIX Prometheus checks
metrics:
- name: request-success-rate
# minimum req success rate (non 5xx responses)
# percentage (0-100)
thresholdRange:
min: 99
interval: 1m
- name: request-duration
# builtin Prometheus check
# maximum req duration P99
# milliseconds
thresholdRange:
max: 500
interval: 30s
webhooks:
- name: load-test
url: http://flagger-loadtester.test/
timeout: 5s
type: rollout
metadata:
cmd: |-
hey -z 1m -q 10 -c 2 -h2 -host app.example.com http://apisix-gateway.apisix/api/info
Save the above resource as podinfo-canary.yaml and then apply it:
kubectl apply -f ./podinfo-canary.yaml
After a couple of seconds Flagger will create the canary objects:
# applied
deployment.apps/podinfo
horizontalpodautoscaler.autoscaling/podinfo
apisixroute/podinfo
canary.flagger.app/podinfo
# generated
deployment.apps/podinfo-primary
horizontalpodautoscaler.autoscaling/podinfo-primary
service/podinfo
service/podinfo-canary
service/podinfo-primary
apisixroute/podinfo-podinfo-canary
Automated canary promotion
Flagger implements a control loop that gradually shifts traffic to the canary while measuring key performance indicators like HTTP requests success rate, requests average duration and pod health. Based on analysis of the KPIs a canary is promoted or aborted, and the analysis result is published to Slack or MS Teams.
Trigger a canary deployment by updating the container image:
kubectl -n test set image deployment/podinfo \
podinfod=stefanprodan/podinfo:6.0.1
Flagger detects that the deployment revision changed and starts a new rollout:
kubectl -n test describe canary/podinfo
Status:
Canary Weight: 0
Conditions:
Message: Canary analysis completed successfully, promotion finished.
Reason: Succeeded
Status: True
Type: Promoted
Failed Checks: 1
Iterations: 0
Phase: Succeeded
Events:
Type Reason Age From Message
---- ------ ---- ---- -------
Warning Synced 2m59s flagger podinfo-primary.test not ready: waiting for rollout to finish: observed deployment generation less than desired generation
Warning Synced 2m50s flagger podinfo-primary.test not ready: waiting for rollout to finish: 0 of 1 (readyThreshold 100%) updated replicas are available
Normal Synced 2m40s (x3 over 2m59s) flagger all the metrics providers are available!
Normal Synced 2m39s flagger Initialization done! podinfo.test
Normal Synced 2m20s flagger New revision detected! Scaling up podinfo.test
Warning Synced 2m (x2 over 2m10s) flagger canary deployment podinfo.test not ready: waiting for rollout to finish: 0 of 1 (readyThreshold 100%) updated replicas are available
Normal Synced 110s flagger Starting canary analysis for podinfo.test
Normal Synced 109s flagger Advance podinfo.test canary weight 10
Warning Synced 100s flagger Halt advancement no values found for apisix metric request-success-rate probably podinfo.test is not receiving traffic: running query failed: no values found
Normal Synced 90s flagger Advance podinfo.test canary weight 20
Normal Synced 80s flagger Advance podinfo.test canary weight 30
Normal Synced 69s flagger Advance podinfo.test canary weight 40
Normal Synced 59s flagger Advance podinfo.test canary weight 50
Warning Synced 30s (x2 over 40s) flagger podinfo-primary.test not ready: waiting for rollout to finish: 1 old replicas are pending termination
Normal Synced 9s (x3 over 50s) flagger (combined from similar events): Promotion completed! Scaling down podinfo.test
Note that if you apply new changes to the deployment during the canary analysis, Flagger will restart the analysis.
You can monitor all canaries with:
watch kubectl get canaries --all-namespaces
NAMESPACE NAME STATUS WEIGHT LASTTRANSITIONTIME
test podinfo-2 Progressing 10 2022-11-23T05:00:54Z
test podinfo Succeeded 0 2022-11-23T06:00:54Z
Automated rollback
During the canary analysis you can generate HTTP 500 errors to test if Flagger pauses and rolls back the faulted version.
Trigger another canary deployment:
kubectl -n test set image deployment/podinfo \
podinfod=stefanprodan/podinfo:6.0.2
Exec into the load tester pod with:
kubectl -n test exec -it deploy/flagger-loadtester bash
Generate HTTP 500 errors:
hey -z 1m -c 5 -q 5 -host app.example.com http://apisix-gateway.apisix/status/500
Generate latency:
watch -n 1 curl -H \"host: app.example.com\" http://apisix-gateway.apisix/delay/1
When the number of failed checks reaches the canary analysis threshold, the traffic is routed back to the primary, the canary is scaled to zero and the rollout is marked as failed.
kubectl -n apisix logs deploy/flagger -f | jq .msg
"New revision detected! Scaling up podinfo.test"
"canary deployment podinfo.test not ready: waiting for rollout to finish: 0 of 1 (readyThreshold 100%) updated replicas are available"
"Starting canary analysis for podinfo.test"
"Advance podinfo.test canary weight 10"
"Halt podinfo.test advancement success rate 0.00% < 99%"
"Halt podinfo.test advancement success rate 26.76% < 99%"
"Halt podinfo.test advancement success rate 34.19% < 99%"
"Halt podinfo.test advancement success rate 37.32% < 99%"
"Halt podinfo.test advancement success rate 39.04% < 99%"
"Halt podinfo.test advancement success rate 40.13% < 99%"
"Halt podinfo.test advancement success rate 48.28% < 99%"
"Halt podinfo.test advancement success rate 50.35% < 99%"
"Halt podinfo.test advancement success rate 56.92% < 99%"
"Halt podinfo.test advancement success rate 67.70% < 99%"
"Rolling back podinfo.test failed checks threshold reached 10"
"Canary failed! Scaling down podinfo.test"
Custom metrics
The canary analysis can be extended with Prometheus queries.
Create a metric template and apply it on the cluster:
apiVersion: flagger.app/v1beta1
kind: MetricTemplate
metadata:
name: not-found-percentage
namespace: test
spec:
provider:
type: prometheus
address: http://flagger-prometheus.apisix:9090
query: |
sum(
rate(
apisix_http_status{
route=~"{{ namespace }}_{{ route }}-{{ target }}-canary_.+",
code!~"4.."
}[{{ interval }}]
)
)
/
sum(
rate(
apisix_http_status{
route=~"{{ namespace }}_{{ route }}-{{ target }}-canary_.+"
}[{{ interval }}]
)
) * 100
Edit the canary analysis and add the not found error rate check:
analysis:
metrics:
- name: "404s percentage"
templateRef:
name: not-found-percentage
thresholdRange:
max: 5
interval: 1m
The above configuration validates the canary by checking if the HTTP 404 req/sec percentage is below 5 percent of the total traffic. If the 404s rate reaches the 5% threshold, then the canary fails.
The above procedures can be extended with more custom metrics checks, webhooks, manual promotion approval and Slack or MS Teams notifications.