---
weight: 9
title: Open Service Mesh Canary Deployments
---

This guide shows you how to use Open Service Mesh (OSM) and Flagger to automate canary deployments.

![Flagger OSM Traffic Split](/img/diagrams/flagger-osm-traffic-split.png)

## Prerequisites

Flagger requires a Kubernetes cluster **v1.16** or newer and Open Service Mesh **0.9.1** or newer.

OSM must have permissive traffic policy enabled and have an instance of Prometheus for metrics.

- If the OSM CLI is being used for installation, install OSM using the following command:
    ```bash
    osm install \
    --set=OpenServiceMesh.deployPrometheus=true \
    --set=OpenServiceMesh.enablePermissiveTrafficPolicy=true
    ```
- If a managed instance of OSM is being used:
  - [Bring your own instance](https://docs.openservicemesh.io/docs/guides/observability/metrics/#bring-your-own) of Prometheus,
    setting the namespace to match the managed OSM controller namespace
  - Enable permissive traffic policy after installation by updating the OSM MeshConfig resource:
    ```bash
    # Replace <osm-namespace> with OSM controller's namespace
    kubectl patch meshconfig osm-mesh-config -n <osm-namespace> -p '{"spec":{"traffic":{"enablePermissiveTrafficPolicyMode":true}}}' --type=merge
    ```   

To install Flagger in the default `osm-system` namespace, use:
```bash
kubectl apply -k https://github.com/fluxcd/flagger//kustomize/osm?ref=main
```
    
Alternatively, if a non-default namespace or managed instance of OSM is in use, install Flagger with Helm, replacing the <osm-namespace>
values as appropriate. If a custom instance of Prometheus is being used, replace `osm-prometheus` with the relevant Prometheus service name.
```bash
helm upgrade -i flagger flagger/flagger \
--namespace=<osm-namespace> \
--set meshProvider=osm \
--set metricsServer=http://osm-prometheus.<osm-namespace>.svc:7070
```

## Bootstrap

Flagger takes a Kubernetes deployment and optionally a horizontal pod autoscaler (HPA),
then creates a series of objects (Kubernetes deployments, ClusterIP services and SMI traffic split).
These objects expose the application inside the mesh and drive the canary analysis and promotion.

Create a `test` namespace and enable OSM namespace monitoring and metrics scraping for the namespace.

```bash
kubectl create namespace test
osm namespace add test
osm metrics enable --namespace test
```

Create a `podinfo` deployment and a horizontal pod autoscaler:

```bash
kubectl apply -k https://github.com/fluxcd/flagger//kustomize/podinfo?ref=main
```

Install the load testing service to generate traffic during the canary analysis:

```bash
kubectl apply -k https://github.com/fluxcd/flagger//kustomize/tester?ref=main
```

Create a canary custom resource for the `podinfo` deployment.
The following `podinfo` canary custom resource instructs Flagger to:
1. monitor any changes to the `podinfo` deployment created earlier,
2. detect `podinfo` deployment revision changes, and
3. start a Flagger canary analysis, rollout, and promotion if there were deployment revision changes.

```yaml
apiVersion: flagger.app/v1beta1
kind: Canary
metadata:
  name: podinfo
  namespace: test
spec:
  provider: osm
  # deployment reference
  targetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: podinfo
  # HPA reference (optional)
  autoscalerRef:
    apiVersion: autoscaling/v2beta2
    kind: HorizontalPodAutoscaler
    name: podinfo
  # the maximum time in seconds for the canary deployment
  # to make progress before it is rolled back (default 600s)
  progressDeadlineSeconds: 60
  service:
    # ClusterIP port number
    port: 9898
    # container port number or name (optional)
    targetPort: 9898
  analysis:
    # schedule interval (default 60s)
    interval: 30s
    # max number of failed metric checks before rollback
    threshold: 5
    # max traffic percentage routed to canary
    # percentage (0-100)
    maxWeight: 50
    # canary increment step
    # percentage (0-100)
    stepWeight: 5
    # OSM 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
      # maximum req duration P99
      # milliseconds
      thresholdRange:
        max: 500
      interval: 30s
    # testing (optional)
    webhooks:
      - name: acceptance-test
        type: pre-rollout
        url: http://flagger-loadtester.test/
        timeout: 30s
        metadata:
          type: bash
          cmd: "curl -sd 'test' http://podinfo-canary.test:9898/token | grep token"
      - name: load-test
        type: rollout
        url: http://flagger-loadtester.test/
        timeout: 5s
        metadata:
          cmd: "hey -z 2m -q 10 -c 2 http://podinfo-canary.test:9898/"
```

Save the above resource as podinfo-canary.yaml and then apply it:

```bash
kubectl apply -f ./podinfo-canary.yaml
```

When the canary analysis starts, Flagger will call the pre-rollout webhooks before routing traffic to the canary.
The canary analysis will run for five minutes while validating the HTTP metrics and rollout hooks every half a minute.

After a couple of seconds Flagger will create the canary objects.

```bash
# applied
deployment.apps/podinfo
horizontalpodautoscaler.autoscaling/podinfo
ingresses.extensions/podinfo
canary.flagger.app/podinfo

# generated
deployment.apps/podinfo-primary
horizontalpodautoscaler.autoscaling/podinfo-primary
service/podinfo
service/podinfo-canary
service/podinfo-primary
trafficsplits.split.smi-spec.io/podinfo
```

After the bootstrap, the `podinfo` deployment will be scaled to zero and the traffic to `podinfo.test` will be routed to the primary pods.
During the canary analysis, the `podinfo-canary.test` address can be used to target directly the canary pods.

## 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.

![Flagger Canary Stages](/img/diagrams/flagger-canary-steps.png)

Trigger a canary deployment by updating the container image:

```bash
kubectl -n test set image deployment/podinfo \
podinfod=ghcr.io/stefanprodan/podinfo:6.0.1
```

Flagger detects that the deployment revision changed and starts a new rollout.


```text
kubectl -n test describe canary/podinfo

Status:
  Canary Weight:         0
  Failed Checks:         0
  Phase:                 Succeeded
Events:
 New revision detected! Scaling up podinfo.test
 Waiting for podinfo.test rollout to finish: 0 of 1 updated replicas are available
 Pre-rollout check acceptance-test passed
 Advance podinfo.test canary weight 5
 Advance podinfo.test canary weight 10
 Advance podinfo.test canary weight 15
 Advance podinfo.test canary weight 20
 Advance podinfo.test canary weight 25
 Waiting for podinfo.test rollout to finish: 1 of 2 updated replicas are available
 Advance podinfo.test canary weight 30
 Advance podinfo.test canary weight 35
 Advance podinfo.test canary weight 40
 Advance podinfo.test canary weight 45
 Advance podinfo.test canary weight 50
 Copying podinfo.test template spec to podinfo-primary.test
 Waiting for podinfo-primary.test rollout to finish: 1 of 2 updated replicas are available
 Promotion completed! Scaling down podinfo.test
```

**Note** that if you apply any new changes to the `podinfo` deployment during the canary analysis, Flagger will restart the analysis.

A canary deployment is triggered by changes in any of the following objects:

* Deployment PodSpec \(container image, command, ports, env, resources, etc\)
* ConfigMaps mounted as volumes or mapped to environment variables
* Secrets mounted as volumes or mapped to environment variables

You can monitor all canaries with:

```bash
watch kubectl get canaries --all-namespaces

NAMESPACE   NAME      STATUS        WEIGHT   LASTTRANSITIONTIME
test        podinfo   Progressing   15       2019-06-30T14:05:07Z
prod        frontend  Succeeded     0        2019-06-30T16:15:07Z
prod        backend   Failed        0        2019-06-30T17:05:07Z
```

## Automated Rollback

During the canary analysis you can generate HTTP 500 errors and high latency to test if Flagger pauses and rolls back the faulted version.

Trigger another canary deployment:

```bash
kubectl -n test set image deployment/podinfo \
podinfod=ghcr.io/stefanprodan/podinfo:6.0.2
```

Exec into the load tester pod with:

```bash
kubectl -n test exec -it flagger-loadtester-xx-xx sh
```

Repeatedly generate HTTP 500 errors until the `kubectl describe` output below shows canary rollout failure:

```bash
watch -n 0.1 curl http://podinfo-canary.test:9898/status/500
```

Repeatedly generate latency until canary rollout fails:

```bash
watch -n 0.1 curl http://podinfo-canary.test:9898/delay/1
```

When the number of failed checks reaches the canary analysis thresholds defined in the `podinfo` canary custom resource earlier, the traffic is routed back to the primary, the canary is scaled to zero and the rollout is marked as failed.

```text
kubectl -n test describe canary/podinfo

Status:
  Canary Weight:         0
  Failed Checks:         10
  Phase:                 Failed
Events:
 Starting canary analysis for podinfo.test
 Pre-rollout check acceptance-test passed
 Advance podinfo.test canary weight 5
 Advance podinfo.test canary weight 10
 Advance podinfo.test canary weight 15
 Halt podinfo.test advancement success rate 69.17% < 99%
 Halt podinfo.test advancement success rate 61.39% < 99%
 Halt podinfo.test advancement success rate 55.06% < 99%
 Halt podinfo.test advancement request duration 1.20s > 0.5s
 Halt podinfo.test advancement request duration 1.45s > 0.5s
 Rolling back podinfo.test failed checks threshold reached 5
 Canary failed! Scaling down podinfo.test
```

## Custom Metrics

The canary analysis can be extended with Prometheus queries.

Let's define a check for 404 not found errors.
Edit the canary analysis (`podinfo-canary.yaml` file) and add the following metric.
For more information on creating additional custom metrics using OSM metrics, please check the [metrics available in OSM](https://docs.openservicemesh.io/docs/guides/observability/metrics/#available-metrics).

```yaml
  analysis:
    metrics:
    - name: "404s percentage"
      threshold: 3
      query: |
        100 - (
          sum(
              rate(
                  osm_request_total{
                    destination_namespace="test",
                    destination_kind="Deployment",
                    destination_name="podinfo",
                    response_code!="404"
                  }[1m]
              )
          )
          /
          sum(
              rate(
                  osm_request_total{
                    destination_namespace="test",
                    destination_kind="Deployment",
                    destination_name="podinfo"
                  }[1m]
              )
          ) * 100
        )
```

The above configuration validates the canary version by checking if the HTTP 404 req/sec percentage is below three percent of the total traffic.
If the 404s rate reaches the 3% threshold, then the analysis is aborted and the canary is marked as failed.

Trigger a canary deployment by updating the container image:

```bash
kubectl -n test set image deployment/podinfo \
podinfod=ghcr.io/stefanprodan/podinfo:6.0.3
```

Exec into the load tester pod with:

```bash
kubectl -n test exec -it flagger-loadtester-xx-xx sh
```

Repeatedly generate 404s until canary rollout fails:

```bash
watch -n 0.1 curl http://podinfo-canary.test:9898/status/404
```

Watch Flagger logs to confirm successful canary rollback.

```text
kubectl -n osm-system logs deployment/flagger -f | jq .msg

Starting canary deployment for podinfo.test
Pre-rollout check acceptance-test passed
Advance podinfo.test canary weight 5
Halt podinfo.test advancement 404s percentage 6.20 > 3
Halt podinfo.test advancement 404s percentage 6.45 > 3
Halt podinfo.test advancement 404s percentage 7.22 > 3
Halt podinfo.test advancement 404s percentage 6.50 > 3
Halt podinfo.test advancement 404s percentage 6.34 > 3
Rolling back podinfo.test failed checks threshold reached 5
Canary failed! Scaling down podinfo.test
```
