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Master Helm Dry Run: Best Practices for Kubernetes Deployments

Master Helm Dry Run: Best Practices for Kubernetes Deployments

August 27, 2023
Master Helm Dry Run: Best Practices for Kubernetes Deployments
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Kubernetes, the de-facto standard for container orchestration, supports two deployment options: imperative and declarative.

Because they are more conducive to automation, declarative deployments are typically considered better than imperative. A declarative paradigm involves:

  • Writing YAML manifest files that describe the desired state of your Kubernetes cluster.
  • Applying the manifest files
  • Letting the Kubernetes controllers work out their magic

The issue with the declarative approach is that YAML manifest files are static. What if you want to deploy the same app in two different environments (for example, “staging” and “production”) with some slight changes (for instance, allocating resources to production)? Having two YAML files is inefficient. A single parameterized YAML file is ideal for this scenario.

Helm is a package manager for Kubernetes that solves this problem. It supports manifest templating and enables parameterization of otherwise static YAML configurations. A set of templated manifest files.

A Helm chart is a package consisting of templated manifest files and metadata that can be deployed into a Kubernetes cluster. A Helm chart takes input variables and uses them to process templated YAML files to produce a manifest that can be sent to the Kubernetes API.

Before deploying a Helm chart into your Kubernetes cluster, it’s wise to understand how it will behave. Helm dry run — specifically the helm install --dry-run command — addresses this use case and enables a preview of what a Helm chart will do without deploying resources on a cluster. Helm dry run also streamlines troubleshooting and testing Helm charts.

This article will take a closer look at Helm dry run concepts, including related Helm commands and how to use Helm dry run to troubleshoot templates.

Summary of key Helm dry run concepts

The table below summarizes the Helm dry run concepts we will explore in this article.

Concept Description
Helm lint Performs some static analysis to check a Helm chart for potential bugs, suspicious constructs, and deviations from best practices.
Helm template Generates the output manifest and prints it out. Only checks for YAML syntax and not whether the generated YAML is a valid Kubernetes manifest.
Helm install --dry-run Generates the output manifest and sends it to the Kubernetes API for verification.

Helm dry run and related Helm commands

The three Helm commands we will explore in this article are:

  • helm template
  • helm lint
  • helm install --dry-run.

The helm template command renders the template but does not check the validity of the generated YAML files beyond a simple YAML syntax check. It will stop generating the output when it encounters invalid YAML. Use the --debug flag to force the helm template command to display full output, including invalid YAML.

The helm template command has the advantage of not needing a running cluster. Use cases for helm template include:

  • To test the output of a Helm chart you are developing
  • To see how certain values will change the output manifest file

The helm lint command runs a basic static analysis that checks a Helm chart for potential bugs, suspicious constructs, and best practices deviations. This command is only useful when writing a Helm chart.

The helm install --dry-run command requires a running Kubernetes cluster and will test the manifest against that specific cluster. This is useful because a Helm chart may be compatible with one cluster but not another. Potential differences across clusters include:

How to run “helm template”

Now let’s look at how to run the helm template command.

First, let’s create a simple Helm chart:

$ helm create mychart

This will create a simple chart deploying NGINX. Now let’s see what the helm template command shows:

$ helm template mychart mychart
---
# Source: mychart/templates/serviceaccount.yaml
apiVersion: v1
kind: ServiceAccount
metadata:
  name: mychart
  labels:
    helm.sh/chart: mychart-0.1.0
    app.kubernetes.io/name: mychart
    app.kubernetes.io/instance: mychart
    app.kubernetes.io/version: "1.16.0"
    app.kubernetes.io/managed-by: Helm
<--- snip --->

Next, let’s introduce an error in one of the YAML manifest files. Edit the “mychart/templates/serviceaccount.yaml” file and add some invalid YAML like this:

{{- if .Values.serviceAccount.create -}}
apiVersion: v1
kind: ServiceAccount
  invalid: yaml
metadata:
  name: {{ include "mychart.serviceAccountName" . }}
  labels:
<--- snip --->

Let’s see what the helm template command does now:

$ helm template mychart mychart
Error: YAML parse error on mychart/templates/serviceaccount.yaml: error converting YAML to JSON: yaml: line 3: mapping values are not allowed in this context

Use --debug flag to render out invalid YAML

As we can see, it failed because the YAML is invalid. We can view the invalid output with the --debug flag:

$ helm template mychart mychart --debug
install.go:178: [debug] Original chart version: ""
install.go:195: [debug] CHART PATH: /home/muaddib/Work/Square/tmp/mychart


<--- snip --->

---
# Source: mychart/templates/serviceaccount.yaml
apiVersion: v1
kind: ServiceAccount
  invalid: yaml
metadata:
  name: mychart
  labels:
    helm.sh/chart: mychart-0.1.0
    app.kubernetes.io/name: mychart
    app.kubernetes.io/instance: mychart
    app.kubernetes.io/version: "1.16.0"
    app.kubernetes.io/managed-by: Helm

<--- snip --->

Error: YAML parse error on mychart/templates/serviceaccount.yaml: error converting YAML to JSON: yaml: line 3: mapping values are not allowed in this context
helm.go:84: [debug] error converting YAML to JSON: yaml: line 3: mapping values are not allowed in this context
YAML parse error on mychart/templates/serviceaccount.yaml
helm.sh/helm/v3/pkg/releaseutil.(*manifestFile).sort
	helm.sh/helm/v3/pkg/releaseutil/manifest_sorter.go:146

<--- snip --->

As you can see, the errors eventually cause Helm to crash. But at least you should have gotten enough output to troubleshoot your problem. Using helm template --debug is mostly useful when writing a Helm chart and you need to understand whether your Helm chart is doing what you want.

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Lastly, let’s explore the helm template command’s main limitation: it generates output even if the result is not a valid Kubernetes manifest. To demonstrate, edit the previous file, undo the error we introduced, and modify it like this:

{{- if .Values.serviceAccount.create -}}
apiVersion: v1
kind: ServiceAccountInvalid
metadata:
  name: {{ include "mychart.serviceAccountName" . }}
  labels:

There is no kind “ServiceAccountInvalid” in Kubernetes, so let’s see what the helm template command will do:

$ helm template mychart mychart

<--- snip --->

---
# Source: mychart/templates/serviceaccount.yaml
apiVersion: v1
kind: ServiceAccountInvalid
metadata:
  name: mychart
  labels:
    helm.sh/chart: mychart-0.1.0
    app.kubernetes.io/name: mychart
    app.kubernetes.io/instance: mychart
    app.kubernetes.io/version: "1.16.0"
    app.kubernetes.io/managed-by: Helm

<--- snip --->

As you can see, helm template happily generates the output, even though it is not a valid Kubernetes manifest file.

How to run “helm lint”

The helm lint command tests whether a generated manifest can be deployed on a specific Kubernetes cluster. This helps address issues such as helm template generating invalid manifest files and provides static analysis during chart creation.

The helm lint command is run like this:

$ helm lint mychart
==> Linting mychart
[INFO] Chart.yaml: icon is recommended

1 chart(s) linted, 0 chart(s) failed

Helm will flag potential issues and make some recommendations related to best practices.

How to use Helm dry run to validate Helm charts

In this tutorial, we’ll use the helm install --dry-run command to validate a Helm chart without actually deploying it on a cluster.  

To keep things simple for this tutorial, we’ll run a local minikube cluster, but you can use any compatible cluster deployment to follow along.

$ minikube start
😄  minikube v1.25.2 on Ubuntu 22.04
✨  Using the virtualbox driver based on user configuration
👍  Starting control plane node minikube in cluster minikube
🔥  Creating virtualbox VM (CPUs=2, Memory=6000MB, Disk=20000MB) ...
🐳  Preparing Kubernetes v1.23.3 on Docker 20.10.12 ...
    ▪ kubelet.housekeeping-interval=5m
    ▪ Generating certificates and keys ...
    ▪ Booting up control plane ...
    ▪ Configuring RBAC rules ...
🔎  Verifying Kubernetes components...
    ▪ Using image gcr.io/k8s-minikube/storage-provisioner:v5
🌟  Enabled addons: default-storageclass, storage-provisioner
🏄  Done! kubectl is now configured to use "minikube" cluster and "default" namespace by default

If we run the helm install --dry-run command with the flawed Helm chart we used in the previous section, here is what happens:

$ helm install mychart mychart --dry-run
Error: INSTALLATION FAILED: unable to build kubernetes objects from release manifest: unable to recognize "": no matches for kind "ServiceAccountInvalid" in version "v1"

As we can see, the helm install --dry-run command connects to the Kubernetes API and sends the resulting manifest file for verification, which fails as expected. Now let’s edit the “mychart/templates/serviceaccount.yaml” again and fix the error we introduced.

After the edits, the command will succeed:

$ helm install mychart mychart --dry-run
NAME: mychart
LAST DEPLOYED: Sat Jul 22 09:57:03 2023
NAMESPACE: default
STATUS: pending-install
REVISION: 1
HOOKS:
---
# Source: mychart/templates/tests/test-connection.yaml
apiVersion: v1
kind: Pod
metadata:

<--- snip --->

Finally, to demonstrate that the command connects to the Kubernetes API, let’s delete the minikube cluster and rerun the command:

$ minikube delete
🔥  Deleting "minikube" in virtualbox ...
💀  Removed all traces of the "minikube" cluster.
$ helm install mychart mychart --dry-run
Error: INSTALLATION FAILED: Kubernetes cluster unreachable: Get "http://localhost:8080/version": dial tcp 127.0.0.1:8080: connect: connection refused

Conclusion

The helm template command generates a given Helm chart's output manifest and simulates the output for input variables, checking the YAML syntax but not verifying whether the output is a valid Kubernetes manifest. This is particularly useful when writing or deploying a Helm chart into an existing cluster.

The helm lint command performs static analysis to identify potential bugs, suspicious constructs, and deviations from best practices, making it essential when developing a Helm chart.

For an even more thorough check, the helm install --dry-run command goes a step further by sending the manifest to the Kubernetes API for verification, allowing you to test a Helm chart and its variables on an existing cluster before actual installation.

By leveraging these Helm commands, including the helm dry run, you can enhance the quality of your Helm charts and effectively troubleshoot complex Kubernetes issues.

Written By:
August 27, 2023
Vishal Padghan
Vishal Padghan
August 27, 2023
Best Practices
Kubernetes
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Master Helm Dry Run: Best Practices for Kubernetes Deployments

Aug 27, 2023
Last Updated:
November 20, 2024
Share this post:
Master Helm Dry Run: Best Practices for Kubernetes Deployments
Table of Contents:

    Kubernetes, the de-facto standard for container orchestration, supports two deployment options: imperative and declarative.

    Because they are more conducive to automation, declarative deployments are typically considered better than imperative. A declarative paradigm involves:

    • Writing YAML manifest files that describe the desired state of your Kubernetes cluster.
    • Applying the manifest files
    • Letting the Kubernetes controllers work out their magic

    The issue with the declarative approach is that YAML manifest files are static. What if you want to deploy the same app in two different environments (for example, “staging” and “production”) with some slight changes (for instance, allocating resources to production)? Having two YAML files is inefficient. A single parameterized YAML file is ideal for this scenario.

    Helm is a package manager for Kubernetes that solves this problem. It supports manifest templating and enables parameterization of otherwise static YAML configurations. A set of templated manifest files.

    A Helm chart is a package consisting of templated manifest files and metadata that can be deployed into a Kubernetes cluster. A Helm chart takes input variables and uses them to process templated YAML files to produce a manifest that can be sent to the Kubernetes API.

    Before deploying a Helm chart into your Kubernetes cluster, it’s wise to understand how it will behave. Helm dry run — specifically the helm install --dry-run command — addresses this use case and enables a preview of what a Helm chart will do without deploying resources on a cluster. Helm dry run also streamlines troubleshooting and testing Helm charts.

    This article will take a closer look at Helm dry run concepts, including related Helm commands and how to use Helm dry run to troubleshoot templates.

    Summary of key Helm dry run concepts

    The table below summarizes the Helm dry run concepts we will explore in this article.

    Concept Description
    Helm lint Performs some static analysis to check a Helm chart for potential bugs, suspicious constructs, and deviations from best practices.
    Helm template Generates the output manifest and prints it out. Only checks for YAML syntax and not whether the generated YAML is a valid Kubernetes manifest.
    Helm install --dry-run Generates the output manifest and sends it to the Kubernetes API for verification.

    Helm dry run and related Helm commands

    The three Helm commands we will explore in this article are:

    • helm template
    • helm lint
    • helm install --dry-run.

    The helm template command renders the template but does not check the validity of the generated YAML files beyond a simple YAML syntax check. It will stop generating the output when it encounters invalid YAML. Use the --debug flag to force the helm template command to display full output, including invalid YAML.

    The helm template command has the advantage of not needing a running cluster. Use cases for helm template include:

    • To test the output of a Helm chart you are developing
    • To see how certain values will change the output manifest file

    The helm lint command runs a basic static analysis that checks a Helm chart for potential bugs, suspicious constructs, and best practices deviations. This command is only useful when writing a Helm chart.

    The helm install --dry-run command requires a running Kubernetes cluster and will test the manifest against that specific cluster. This is useful because a Helm chart may be compatible with one cluster but not another. Potential differences across clusters include:

    How to run “helm template”

    Now let’s look at how to run the helm template command.

    First, let’s create a simple Helm chart:

    $ helm create mychart

    This will create a simple chart deploying NGINX. Now let’s see what the helm template command shows:

    $ helm template mychart mychart
    ---
    # Source: mychart/templates/serviceaccount.yaml
    apiVersion: v1
    kind: ServiceAccount
    metadata:
      name: mychart
      labels:
        helm.sh/chart: mychart-0.1.0
        app.kubernetes.io/name: mychart
        app.kubernetes.io/instance: mychart
        app.kubernetes.io/version: "1.16.0"
        app.kubernetes.io/managed-by: Helm
    <--- snip --->
    

    Next, let’s introduce an error in one of the YAML manifest files. Edit the “mychart/templates/serviceaccount.yaml” file and add some invalid YAML like this:

    {{- if .Values.serviceAccount.create -}}
    apiVersion: v1
    kind: ServiceAccount
      invalid: yaml
    metadata:
      name: {{ include "mychart.serviceAccountName" . }}
      labels:
    <--- snip --->
    

    Let’s see what the helm template command does now:

    $ helm template mychart mychart
    Error: YAML parse error on mychart/templates/serviceaccount.yaml: error converting YAML to JSON: yaml: line 3: mapping values are not allowed in this context
    
    Use --debug flag to render out invalid YAML

    As we can see, it failed because the YAML is invalid. We can view the invalid output with the --debug flag:

    $ helm template mychart mychart --debug
    install.go:178: [debug] Original chart version: ""
    install.go:195: [debug] CHART PATH: /home/muaddib/Work/Square/tmp/mychart
    
    
    <--- snip --->
    
    ---
    # Source: mychart/templates/serviceaccount.yaml
    apiVersion: v1
    kind: ServiceAccount
      invalid: yaml
    metadata:
      name: mychart
      labels:
        helm.sh/chart: mychart-0.1.0
        app.kubernetes.io/name: mychart
        app.kubernetes.io/instance: mychart
        app.kubernetes.io/version: "1.16.0"
        app.kubernetes.io/managed-by: Helm
    
    <--- snip --->
    
    Error: YAML parse error on mychart/templates/serviceaccount.yaml: error converting YAML to JSON: yaml: line 3: mapping values are not allowed in this context
    helm.go:84: [debug] error converting YAML to JSON: yaml: line 3: mapping values are not allowed in this context
    YAML parse error on mychart/templates/serviceaccount.yaml
    helm.sh/helm/v3/pkg/releaseutil.(*manifestFile).sort
    	helm.sh/helm/v3/pkg/releaseutil/manifest_sorter.go:146
    
    <--- snip --->
    
    

    As you can see, the errors eventually cause Helm to crash. But at least you should have gotten enough output to troubleshoot your problem. Using helm template --debug is mostly useful when writing a Helm chart and you need to understand whether your Helm chart is doing what you want.

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    Try for free

    Lastly, let’s explore the helm template command’s main limitation: it generates output even if the result is not a valid Kubernetes manifest. To demonstrate, edit the previous file, undo the error we introduced, and modify it like this:

    {{- if .Values.serviceAccount.create -}}
    apiVersion: v1
    kind: ServiceAccountInvalid
    metadata:
      name: {{ include "mychart.serviceAccountName" . }}
      labels:

    There is no kind “ServiceAccountInvalid” in Kubernetes, so let’s see what the helm template command will do:

    $ helm template mychart mychart
    
    <--- snip --->
    
    ---
    # Source: mychart/templates/serviceaccount.yaml
    apiVersion: v1
    kind: ServiceAccountInvalid
    metadata:
      name: mychart
      labels:
        helm.sh/chart: mychart-0.1.0
        app.kubernetes.io/name: mychart
        app.kubernetes.io/instance: mychart
        app.kubernetes.io/version: "1.16.0"
        app.kubernetes.io/managed-by: Helm
    
    <--- snip --->
    
    

    As you can see, helm template happily generates the output, even though it is not a valid Kubernetes manifest file.

    How to run “helm lint”

    The helm lint command tests whether a generated manifest can be deployed on a specific Kubernetes cluster. This helps address issues such as helm template generating invalid manifest files and provides static analysis during chart creation.

    The helm lint command is run like this:

    $ helm lint mychart
    ==> Linting mychart
    [INFO] Chart.yaml: icon is recommended
    
    1 chart(s) linted, 0 chart(s) failed

    Helm will flag potential issues and make some recommendations related to best practices.

    How to use Helm dry run to validate Helm charts

    In this tutorial, we’ll use the helm install --dry-run command to validate a Helm chart without actually deploying it on a cluster.  

    To keep things simple for this tutorial, we’ll run a local minikube cluster, but you can use any compatible cluster deployment to follow along.

    $ minikube start
    😄  minikube v1.25.2 on Ubuntu 22.04
    ✨  Using the virtualbox driver based on user configuration
    👍  Starting control plane node minikube in cluster minikube
    🔥  Creating virtualbox VM (CPUs=2, Memory=6000MB, Disk=20000MB) ...
    🐳  Preparing Kubernetes v1.23.3 on Docker 20.10.12 ...
        ▪ kubelet.housekeeping-interval=5m
        ▪ Generating certificates and keys ...
        ▪ Booting up control plane ...
        ▪ Configuring RBAC rules ...
    🔎  Verifying Kubernetes components...
        ▪ Using image gcr.io/k8s-minikube/storage-provisioner:v5
    🌟  Enabled addons: default-storageclass, storage-provisioner
    🏄  Done! kubectl is now configured to use "minikube" cluster and "default" namespace by default

    If we run the helm install --dry-run command with the flawed Helm chart we used in the previous section, here is what happens:

    $ helm install mychart mychart --dry-run
    Error: INSTALLATION FAILED: unable to build kubernetes objects from release manifest: unable to recognize "": no matches for kind "ServiceAccountInvalid" in version "v1"

    As we can see, the helm install --dry-run command connects to the Kubernetes API and sends the resulting manifest file for verification, which fails as expected. Now let’s edit the “mychart/templates/serviceaccount.yaml” again and fix the error we introduced.

    After the edits, the command will succeed:

    $ helm install mychart mychart --dry-run
    NAME: mychart
    LAST DEPLOYED: Sat Jul 22 09:57:03 2023
    NAMESPACE: default
    STATUS: pending-install
    REVISION: 1
    HOOKS:
    ---
    # Source: mychart/templates/tests/test-connection.yaml
    apiVersion: v1
    kind: Pod
    metadata:
    
    <--- snip --->
    

    Finally, to demonstrate that the command connects to the Kubernetes API, let’s delete the minikube cluster and rerun the command:

    $ minikube delete
    🔥  Deleting "minikube" in virtualbox ...
    💀  Removed all traces of the "minikube" cluster.
    $ helm install mychart mychart --dry-run
    Error: INSTALLATION FAILED: Kubernetes cluster unreachable: Get "http://localhost:8080/version": dial tcp 127.0.0.1:8080: connect: connection refused
    

    Conclusion

    The helm template command generates a given Helm chart's output manifest and simulates the output for input variables, checking the YAML syntax but not verifying whether the output is a valid Kubernetes manifest. This is particularly useful when writing or deploying a Helm chart into an existing cluster.

    The helm lint command performs static analysis to identify potential bugs, suspicious constructs, and deviations from best practices, making it essential when developing a Helm chart.

    For an even more thorough check, the helm install --dry-run command goes a step further by sending the manifest to the Kubernetes API for verification, allowing you to test a Helm chart and its variables on an existing cluster before actual installation.

    By leveraging these Helm commands, including the helm dry run, you can enhance the quality of your Helm charts and effectively troubleshoot complex Kubernetes issues.

    What you should do now
    • Schedule a demo with Squadcast to learn about the platform, answer your questions, and evaluate if Squadcast is the right fit for you.
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    August 27, 2023
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    bibam
    "Bibam found their best PagerDuty alternative in Squadcast.
    By moving to Squadcast from Pagerduty, we have seen a serious reduction in alert fatigue, allowing us to focus...
    tanner
    "Squadcast helped Tanner gain system insights and boost team productivity.
    Squadcast has integrated seamlessly into our DevOps and on-call team's workflows. Thanks to their reliability...
    Alexandre Lessard
    System Analyst
    Martin do Santos
    Platform and Architecture Tech Lead
    Sandro Franchi
    CTO
    Squadcast is a leader in Incident Management on G2 Squadcast is a leader in Mid-Market IT Service Management (ITSM) Tools on G2 Squadcast is a leader in Americas IT Alerting on G2 Best IT Management Products 2022 Squadcast is a leader in Europe IT Alerting on G2 Squadcast is a leader in Mid-Market Asia Pacific Incident Management on G2 Users love Squadcast on G2
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    mapgears
    "Mapgears simplified their complex On-call Alerting process with Squadcast.
    Squadcast has helped us aggregate alerts coming in from hundreds of services into one single platform. We no longer have hundreds of...
    Alexandre Lessard
    System Analyst
    bibam
    "Bibam found their best PagerDuty alternative in Squadcast.
    By moving to Squadcast from Pagerduty, we have seen a serious reduction in alert fatigue, allowing us to focus...
    Martin do Santos
    Platform and Architecture Tech Lead
    tanner
    "Squadcast helped Tanner gain system insights and boost team productivity.
    Squadcast has integrated seamlessly into our DevOps and on-call team's workflows. Thanks to their reliability metrics we have...
    Sandro Franchi
    CTO
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