Debugging With Skaffold

Skaffold lets you set breakpoints and step through your application, even when deployed to remote Kubernetes clusters, as if the code were running locally on your machine. Skaffold detects the language runtimes of your container images, reconfigures the pods for debugging, forwards debugging ports, and then monitors for when debuggable containers come online. IDE integrations like Cloud Code leverage Skaffold’s events to automatically set up debugging sessions.

Debugging is currently supported for five language runtimes.

  • Go 1.13+ (runtime ID: go) using Delve
  • NodeJS (runtime ID: nodejs) using the NodeJS Inspector (Chrome DevTools)
  • Java and JVM languages (runtime ID: jvm) using JDWP
  • Python 3.5-3.10 runtimes (runtime ID: python) using debugpy (Debug Adapter Protocol) or pydevd
    • NOTE: Python 3.11 support is planned and coming soon but is currently still in progress
  • .NET Core (runtime ID: netcore) using vsdbg (only for VS Code)

Skaffold can usually detect the correct language runtime if present. However if you encounter difficulties then checkout the Supported Language Runtimes section for the exact heuristics that Skaffold uses and you can modify your application accordingly, or read about how you can manually configure your container image.

The easiest way to debug using Skaffold is by using the Cloud Code IDE extension for Visual Studio Code, JetBrains IDEs, and Cloud Shell. Cloud Code will automatically configure container images for debugging so you can debug Kubernetes services just like how you would debug a local service in your IDE.

For more information, see the corresponding documentation for VS Code, IntelliJ and Cloud Shell.

Detailed debugger configuration and setup

This section describes how Skaffold configures the container image for debugging for the supported language runtimes, and how to setup with certain IDEs.

Note that many debuggers may require additional information for the location of source files. We are looking for ways to identify this information and to pass it back if found.

Go (runtime: go, protocols: dlv)

Go-based applications are configured to run under Delve in its headless-server mode.

On recognizing a Go-based container image, debug rewrites the container image’s entrypoint to invoke your application using dlv:

dlv exec --headless --continue --accept-multiclient --listen=:56268 --api-version=2 <app> -- <args> ...
Skaffold debug using the JetBrains GoLand and IntelliJ Ultimate

Debugging is only supported in JetBrains IDEs for Go applications built using Go Modules. The IDE settings must also be explicitly configured to use Go Modules. Errors like cannot find debugger path indicate misconfiguration.

Skaffold debug using the VS Code Go extension

If you use the debug functionality of the VS Code Go extension to connect to dlv, you may need to configure local and remote source paths, via either the cwd and remotePath properties, or the substitutePath array property (reference).

The cwd or from properties should be the absolute path of the top-level directory of your source files and should generally match the artifact’s context directory in skaffold.yaml. You can represent this using the ${workspaceFolder} variable.

The remotePath or to properties should be set to the absolute path of the source location during compilation. For example, the golang images, which are often used in multi-stage builds, have a default working directory of /go. The following configuration works in this case:

    "name": "Skaffold Debug",
    "type": "go",
    "request": "attach",
    "mode": "remote",
    "host": "localhost",
    "port": 56268,
    "cwd": "${workspaceFolder}",
    "remotePath": "/go"

You can use the substitutePath property instead of cwd and remotePath:

    "name": "Skaffold Debug",
    "type": "go",
    "request": "attach",
    "mode": "remote",
    "host": "localhost",
    "port": 56268,
    "substitutePath": [
            "from": "${workspaceFolder}",
            "to": "/go",

If you use the ko local builder, the source path during compilation matches the source path in your IDE. In this case, the value for remotePath will match cwd. If the values of both cwd and remotePath are ${workspaceFolder}, you can omit these properties.

NodeJS (runtime: nodejs, protocols: devtools)

NodeJS applications are configured to use the Chrome DevTools inspector via the --inspect argument.

On recognizing a NodeJS-based container image, debug rewrites the container image’s entrypoint to invoke your application with --inspect:

node --inspect=9229 <app.js>

A debugging client must first obtain the inspector UUID.

Java and Other JVM Languages (runtime: jvm, protocols: jdwp)

Java/JVM applications are configured to expose the JDWP agent using the JAVA_TOOL_OPTIONS environment variable. Note that the use of JAVA_TOOL_OPTIONS causes extra debugging output from the JVM on launch.

On recognizing a JVM-based container image, debug rewrites the container image’s environment to set:


Python (runtime: python, protocols: dap or pydevd)

Python applications are configured to use either debugpy or pydevd. debugpy uses the debug adapter protocol (DAP) which is supported by Visual Studio Code, Eclipse LSP4e, and other editors and IDEs.

On recognizing a Python-based container image, debug rewrites the container image’s entrypoint to invoke Python using either the pydevd or debugpy modules:

python -m debugpy --listen 5678 <app>


python -m pydevd --server --port 5678 <>

.NET Core (runtime: dotnet, protocols: vsdbg)

.NET Core applications are configured to be deployed along with vsdbg for VS Code.

Supported Language Runtimes

The language runtime for the artifacts can be specified in the skaffold.yaml file.

  - image:
    runtimeType: go # specify one of `go`, `nodejs`, `jvm`, `python`, or `netcore`
  local: {}

Otherwise Skaffold debug recognizes the language runtime used in a container image for specific language runtimes using standard heuristics described below.

Go (runtime: go)

Go-based container images are recognized by:

Unless you built your container image using ko, set one of the standard Go environment variables to allow Skaffold to detect your container as Go. GOTRACEBACK=single is the default setting for Go, so you can add this environment variable without changing behavior. Alternatively, GOTRACEBACK=all is a useful setting in many situtions.

Your application should be built with the -gcflags='all=-N -l' flag to disable optimizations and inlining. If you do not add this flag, debugging can becoming confusing due to seemingly-random execution jumps that happen due to statement reordering and inlining. Skaffold configures Docker builds with a SKAFFOLD_GO_GCFLAGS build argument that you should use in your Dockerfile:

FROM golang
COPY . .
RUN go build -gcflags="${SKAFFOLD_GO_GCFLAGS}" -o /app .

Note that the Alpine Linux-based golang container images do not include a C compiler which is required to build with -gcflags='all=-N -l'.

The ko builder adds -gcflags='all=-N -l' automatically when you use skaffold debug.

We recommend that you do not add the -trimpath flag when debugging, as this flag removes information from the resulting binary that aids debugging.

Java and Other JVM Languages (runtime: jvm)

JVM application are recognized by:

  • the presence of a JAVA_VERSION or JAVA_TOOL_OPTIONS environment variable, or
  • the container command-line invokes java.

NodeJS (runtime: nodejs)

NodeJS images are recognized by:

  • the presence of a NODE_VERSION, NODEJS_VERSION, or NODE_ENV environment variable, or
  • the container command-line invokes node or npm.

Python (runtime: python)

Python application are recognized by:

  • the container command-line invokes python, python2, or python3.

.NET Core (runtime: dotnet)

.NET Core application are recognized by:

  • the container command-line invokes the dotnet cli

Furthermore, your app must be built with the --configuration Debug options to disable optimizations.

How It works

skaffold debug acts like skaffold dev, but it configures containers in pods for debugging as required for each container’s runtime technology. The associated debugging ports are exposed and labelled so that they can be port-forwarded to the local machine. One notable difference from skaffold dev is that debug disables image rebuilding and syncing as it leads to users accidentally terminating debugging sessions by saving file changes. These behaviours can be re-enabled with the --auto-build, --auto-deploy, and --auto-sync flags, or triggering a devloop iteration using the Skaffold API.

Enabling debugging has two phases:

  1. Configuring: Skaffold automatically examines each built container image and attempts to recognize the underlying language runtime. Container images can be explicitly configured too.
  2. Monitoring: Skaffold watches the cluster to detect when debuggable containers start execution.

Configuring container images for debugging

skaffold debug examines the built artifacts to determine the underlying language runtime technology. Kubernetes manifests that reference these artifacts are transformed on-the-fly to enable the language runtime’s debugging functionality. These transforms add or alter environment variables and entrypoints, and more.

Some language runtimes require additional support files to enable debugging. For these languages, a special set of runtime-specific images are configured as init-containers to populate a shared-volume that is mounted into each of the appropriate containers. These images are hosted at; alternative locations can be specified in Skaffold’s global configuration.

For images that are successfully recognized, Skaffold adds a annotation to the corresponding Kubernetes pod-spec that encode the debugging parameters.

Monitoring for debuggable containers

Once the application is deployed, debug monitors the cluster looking for debuggable pods with a annotation. For each new debuggable pod, Skaffold emits an event that can be used by tools like IDEs to establish a debug session.

Additional changes

debug makes some other adjustments to simplify the debug experience:

  • Replica Counts: debug rewrites the replica counts to 1 for deployments, replica sets, and stateful sets. This results in requests being serialized so that one request is processed at a time.

  • Kubernetes Probes: debug changes the timeouts on HTTP-based liveness, readiness, and startup probes to 600 seconds (10 minutes) from the default of 1 second. This change allows probes to be debugged, and avoids negative consequences from blocked probes when the app is already suspended during a debugging session. Failed liveness probes in particular result in the container being terminated and restarted.

    The probe timeout value can be set on a per-podspec basis by setting a annotation on the podspec’s metadata with a valid duration (see Go’s time.ParseDuration()). This probe timeout-rewriting can be skipped entirely by using skip. For example:

      annotations: skip
    spec: ...


My container is not being made debuggable?

Was this image built by Skaffold? debug only works for images that were built by Skaffold so as to avoid affecting system- or infrastructure-level containers such as proxy sidecars.

Was Skaffold able to recognize the image? debug emits a warning when it is unable to configure an image for debugging:

WARN[0005] Image "image-name" not configured for debugging: unable to determine runtime for "image-name"

See the language runtime section details on how container images are recognized.

Is your container command-line using shell constructs?

Automatic debugging of Go and Python applications requires that Skaffold adjust the command-line to use a specific launcher (dlv for Go, or our custom Python launcher to configure the appropriate debugging module). These launchers require that the container command-line invokes the binary or launch script (i.e., a pip-generated launcher script such as gunicorn). Skaffold cannot debug Go and Python applications that use user-created shell scripts, or that use shell constructs like exec or eval. Either rewrite your container image command-line or manually configure your container for debugging. For example:

❌ CMD exec gunicorn app:app
✅ CMD gunicorn app:app
✅ CMD [gunicorn, app:app]
✅ CMD [python, -m, gunicorn, app:app]

Why aren’t my breakpoints being hit?

Missing required language extension. Go, Python, and JavaScript debugging in IDEA Ultimate requires the corresponding language plugin to be installed. If it is not installed, the debugger will not attach and breakpoints will not be hit.

Breakpoints are not hit during program startup. Skaffold configures the containers to run-on-start (sometimes called continue mode), such that the containers do not wait for the debugger to connect. The container will have likely finished its startup by the time the debugger is able to connect and configure the breakpoints, and so breakpoints in the normal startup path are unlikely to be hit.

File mapping misconfiguration between local and container filesystems. Some language runtimes require configuring the IDE with a source map to map files in the container to their corresponding local files. If this mapping is incorrect, then the remote debugging runtime will not be able to find the source file for the breakpoint. The Cloud Code plugins generally prompt the user when required.

  • Some builds use multi-stage dockerfiles to compile the binary using a build-time image and then copy the binary into a smaller image intended for deployment. In these cases, the source mapping must use the build-time paths. For example, many Go builds use a golang image for building, where the source files are typically copied into /go.
  • JetBrains GoLand and IDEA Ultimate only support remote breakpoints for Go applications built using Go Modules. The IDE settings must also be explicitly configured to use Go Modules.
  • JVM languages do not require the mapping as the JVM uses class names rather than file paths.

Can images be debugged without the runtime support images?

The special runtime-support images are provided as a convenience for automatic configuration. You can manually configure your images for debugging by one of the following means:

  • skaffold debug usually recognizes already-configured container images that use the appropriate debugger. For example, you could use a multi-stage Dockerfile with a debug stage that invokes the application using the debugger.
  • Use a workload annotation on the pod-spec to describe the debug configuration of each container image in the pod, as described in Workload Annotations.


skaffold debug has some limitations.

Unsupported Container Entrypoints

skaffold debug requires being able to examine and alter the command-line used in the container entrypoint. This transformation will not work with images that use intermediate launch scripts or binaries.

Supported Deployers

skaffold debug is only supported with the kubectl, kustomize, and helm deployers.

Deprecated Workload API Objects

skaffold debug does not support deprecated versions of Workload API objects:

Applications should transition to the apps/v1 APIs, introduced in Kubernetes 1.9.

Appendix: IDE Support via Events and Metadata

debug provides additional support for IDEs to detect the debuggable containers and to determine appropriate configuration parameters.

Workload Annotations

Each transformed workload object carries a annotation with a JSON object describing the debug configurations for the pod’s containers (linebreaks for readability):{

For example the following annotation indicates that the container named web is a Go application that is being debugged by a headless Delve session on port 56268 (linebreaks for readability):{

artifact is the corresponding artifact’s image name in the skaffold.yaml. runtime is the language runtime detected (one of: go, jvm, nodejs, python). ports is a list of debug ports keyed by the language runtime debugging protocol. workingDir is the working directory (if not an empty string).

API: Events

Each debuggable container being started or stopped raises a debug-container-event through Skaffold’s event mechanism (gRPC, REST).

`/v1/events` stream of `skaffold debug` within `examples/jib`

In this example, we do a skaffold debug, and then kill the deployed pod. The deployment starts a new pod. We get a terminated event for the container for the killed pod.

  "result": {
    "timestamp": "2020-02-05T03:27:30.114354Z",
    "event": {
      "debuggingContainerEvent": {
        "status": "Started",
        "podName": "web-f6d56bcc5-6csgs",
        "containerName": "web",
        "namespace": "default",
        "artifact": "skaffold-jib",
        "runtime": "jvm",
        "debugPorts": {
          "jdwp": 5005
    "entry": "Debuggable container started pod/web-f6d56bcc5-6csgs:web (default)"

API: State

The API’s state (gRPC, REST) also includes a list of debuggable containers.

The `/v1/state` listing debugging containers
  "buildState": {
    "artifacts": {
      "skaffold-jib": "Complete"
  "deployState": {
    "status": "Complete"
  "forwardedPorts": {
    "5005": {
      "localPort": 5005,
      "remotePort": 5005,
      "podName": "web-f6d56bcc5-6csgs",
      "containerName": "web",
      "namespace": "default",
      "portName": "jdwp",
      "resourceType": "pod",
      "resourceName": "web-f6d56bcc5-6csgs",
      "address": ""
    "8080": {
      "localPort": 8080,
      "remotePort": 8080,
      "namespace": "default",
      "resourceType": "service",
      "resourceName": "web",
      "address": ""
    "8081": {
      "localPort": 8081,
      "remotePort": 8080,
      "podName": "web-f6d56bcc5-6csgs",
      "containerName": "web",
      "namespace": "default",
      "resourceType": "pod",
      "resourceName": "web-f6d56bcc5-6csgs",
      "address": ""
  "statusCheckState": {
    "status": "Not Started"
  "fileSyncState": {
    "status": "Not Started"
  "debuggingContainers": [
      "status": "Started",
      "podName": "web-f6d56bcc5-6csgs",
      "containerName": "web",
      "namespace": "default",
      "artifact": "skaffold-jib",
      "runtime": "jvm",
      "debugPorts": {
        "jdwp": 5005