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‎_docs/kb/articles/upgrade-deprecated-docker-images.md‎

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support-reviewed:2025-07-14 AA
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---
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As part of our ongoing platform upgrades, Codefresh is moving to a newer Classic Runner version based onDocker27. This change deprecates older Docker image formats such as Docker Image Format v1 and Docker manifest version 2, schema 1.
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#How to: Upgrade DeprecatedDockerImages in Classic Pipelines
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This guide walks you through:
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- Identifying deprecated Docker images in your Classic Pipelines.
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- Upgrading those images to a modern supported format (OCI or Docker manifest v2, schema 2).
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As part of our ongoing platform upgrades, Codefresh is moving to a newer Classic runner version based on Docker v27. This version**deprecates Docker image format v1 and Docker manifest schema 1**, which may impact Classic Pipelines using these legacy image types.
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##Step 1: Find Deprecated Docker Images
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This guide will help you:
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You can identify deprecated images using one of the following methods:
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- Identify deprecated Docker images in your Classic Pipelines
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- Upgrade those images to a supported format
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###Option A: Analyze Build Logs (Manual Method)
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---
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##Step 1: Identify Deprecated Docker Images
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The latest`dind` versions output a deprecation warning in the build log each time a deprecated image is pulled.
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There are two recommended approaches:
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**Pros**
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- No setup required
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- Works retroactively on historical builds
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###Option 1: Analyze Build Logs
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**Cons**
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- Time-consuming for large accounts
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- Requires script execution and manual review
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This method scans historical build logs for deprecation warnings. The latest versions of`dind` log a warning each time the Docker daemon pulls a deprecated image.
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Examplewarning in logs:
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**Examplelog output:**
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```
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[DEPRECATION NOTICE] Docker Image Format v1 and Docker Image manifest version 2, schema 1 support is disabled by default...
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```
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Use the following script toscanyour buildlogs and extract deprecatedimages:
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👉[Find deprecated images used in previous builds](https://gist.github.com/francisco-cocozza/6046028184cc12b5ee4513bdcb4217c5)
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Toscan logs and extract deprecatedimage names, use the provided script:
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➡️**Find deprecated images used in previous builds**
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>💡 For large-scale environments withthousands ofbuilds,we offer a morescalable, metrics-baseddetectionmethod.See[Appendix I](#appendix-i-monitor-engine-metrics) for details.
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>💡 For large-scale environments withmanybuilds,ascalable, metrics-based method is available.[See Appendix I](#appendix-i-monitor-engine-metrics) for details.
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---
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##Step 2: Upgrade Deprecated Docker Images
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Once you’ve identified deprecated imagesusing enginemetrics, the next step is toupgradethose imagesto a modern format (OCI or Docker manifest v2, schema 2). Thisis required to ensurecompatibility with docker-27 and futurereleases.
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Once you’ve identified deprecated images(via logs ormetrics),upgradethemto a modern format (OCI or Docker manifest v2, schema 2). Thisensurescompatibility with docker-27 and futurerunner versions.
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###HowIt Works
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###Howit works
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Re-pushing an image using a modern Docker clientwillautomaticallyconvert its manifest to a supported version.
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Re-pushing an image using a modern Docker client automaticallyupdates its manifest to a supported version.
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###Sample Codefresh Pipeline to Upgrade an Image
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image_name:<target-image-name>
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```
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**Example:**
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```yaml
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# Example:
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# push:
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# title: "Re-pushing deprecated image"
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# type: push
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# candidate: docker/whalesay:latest
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# registry: docker
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# tag: new-manifest
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# image_name: codefresh/whalesay
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push:
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title:"Re-pushing deprecated image"
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type:push
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candidate:docker/whalesay:latest
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registry:docker
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tag:new-manifest
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image_name:codefresh/whalesay
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```
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This pulls the deprecated image and re-pushes it under a new name/tag with a compliant manifest format.
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This pulls the deprecated image and re-pushes it under a new name ortag with a compliant manifest format.
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>💡You can repeatthis process for each deprecated image discovered via metrics or logs.
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> 💡Repeatthis process for each deprecated image discovered.
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---
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## Appendix I: Monitor Engine Metrics
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This method enables scalable detection of deprecated imagesbyusing real-time enginemetrics. Recommended for high-volume or automated environments.
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For large environments, use real-time metrics emittedbythe Codefresh engineto detect deprecated image usage.
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###Monitor engine metrics
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###About the Metric
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Starting from Runtime v7.5.0,engine emits:
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Starting from Runtime`v7.5.0`, theengine emits the following Prometheus metric:
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```
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codefresh_engine_deprecated_images_pulled_total{account_name, pipeline_id, workflow, image_name}
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codefresh_engine_deprecated_images_pulled_total{account_name, pipeline_id, workflow, image_name}
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```
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Thismetric is acounterincreased by 1 each timeDocker daemon pullsa deprecated image.
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This counterincreases by 1 each time a deprecated image is pulled.
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###How toenable
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### How toEnable Metrics
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Set the following valuesfor the Hybrid RuntimeChart:
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Set the following valuesin your Hybrid Runtimechart:
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```yaml
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runtime:
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enabled: true
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```
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Toensure that the Prometheus operator will scrape the latestmetricvalues before the engine exits, set:
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Toavoidmetricloss during shutdown, also configure:
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```yaml
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runtime:
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engine:
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env:
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METRICS_PROMETHEUS_SCRAPE_TIMEOUT:'120000'#Timeout in ms
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METRICS_PROMETHEUS_SCRAPE_TIMEOUT:'120000'#120 seconds
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```
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###How to monitor
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###Install Monitoring Stack (Optional)
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Installation of themonitoringstack is up to the customer and not covered by our support. The following is a basic setup example:
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If nomonitoringsolution exists in your cluster, install the [kube-prometheus-stack](https://artifacthub.io/packages/helm/prometheus-community/kube-prometheus-stack) chart:
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#### kube-prom-storage-class.yaml
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```bash
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helm repo add prometheus-community https://prometheus-community.github.io/helm-charts
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helm repo update
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helm install kube-prom prometheus-community/kube-prometheus-stack --create-namespace --namespace kube-prom -f ./kube-prom-values.yaml
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```
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```yaml
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# kube-prom-storage-class.yaml
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**Example storage configuration:**
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`kube-prom-storage-class.yaml`
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```yaml
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apiVersion:storage.k8s.io/v1
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kind:StorageClass
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metadata:
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type:gp3
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```
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####kube-prom-values.yaml
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`kube-prom-values.yaml`
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```yaml
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# kube-prom-values.yaml
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prometheus:
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podMonitorSelectorNilUsesHelmValues: false
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- marcusolsson-json-datasource
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```
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### Helm installation
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helm repo add prometheus-community https://prometheus-community.github.io/helm-charts
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helm repo update
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helm install kube-prom prometheus-community/kube-prometheus-stack --create-namespace --namespace kube-prom -f ./kube-prom-values.yaml
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```
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###Grafana access and verification
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### Access Grafana
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kubectl --namespace kube-prom get pods -l "release=kube-prom"
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kubectl --namespace kube-prom get secrets kube-prom-grafana -o jsonpath="{.data.admin-password}" | base64 -d ; echo
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export POD_NAME=$(kubectl --namespace kube-prom get pod -l "app.kubernetes.io/name=grafana,app.kubernetes.io/instance=kube-prom" -oname)
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kubectl --namespace kube-prom port-forward $POD_NAME 3000
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```
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Open[http://localhost:3000](http://localhost:3000) and log in using the admin password retrieved above.
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###Verifying metrics
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Then access Grafana at `http://localhost:3000`.
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To ensure that engine metrics are collected correctly, run a build on the monitored Runtime. InGrafana:
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### Verify Metrics inGrafana
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-Go to**Explore → Metrics**
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-Navigate to **Explore → Metrics**
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-Search for `codefresh_`
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- Make sure the time range includes a running build
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---
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##Appendix II: Grafana dashboard
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###How to use/understand metrics
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The metric`codefresh_engine_deprecated_images_pulled_total` is a counter increased by 1 each time Docker daemon pulls a deprecated image. Labels`{account_name, pipeline_id, workflow, image_name}` allow grouping results.
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###Dashboard setup
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-Run a build to generate metric events
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1. Download Dashboard JSON in APPENDIX II
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2. Log in to Grafana
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3. Go to**Dashboards → New → Import**
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4. Upload the JSON
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5. Select`Mimir API` as data source → Click**Import**
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### Query Prometheus Directly
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###Dashboard overview
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Example query:
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- Filter by account name
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- Adjust time range
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- View builds and deprecated image names
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- Clickable links to Admin Panel
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###Query Prometheus metric
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You can query the metric directly:
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```promql
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```text
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sum(
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rate(
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codefresh_engine_deprecated_images_pulled_total[$__rate_interval]
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)
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) by (account_name, pipeline_id, workflow, image_name)
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```
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Example deprecated images:
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-`docker.io/tutum/dnsutils:latest`
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-`docker.io/docker/whalesay:latest`
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This returns the pull rate of deprecated images by account and pipeline.
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### Grafana Dashboard (Optional)
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-Download the provided dashboard JSON
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-Go to **Dashboards → New → Import**
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-Upload the file and select `Mimir API` as the data source
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Done! 🎉 You can now monitor deprecated image usage at scale.
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---
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**Examples from monitoring:**
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Pulled in Pipeline:`#67867cfe8307bd8f9b7b034e`
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-`docker.io/tutum/dnsutils:latest`pulled in pipeline `#67867cfe8307bd8f9b7b034e`
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-`docker.io/docker/whalesay:latest`pulled in the same pipeline

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