Kubernetes has become the default platform for running modern applications, but managing Kubernetes configurations is still one of the biggest challenges teams face in 2025. Even a simple application can require multiple YAML files, repeated values, and careful coordination across environments like development, staging, and production. As applications grow, this complexity quickly becomes difficult to manage.
This is where Helm charts play a critical role. Helm charts provide a standardized way to package, configure, and deploy Kubernetes applications. Instead of handling dozens of YAML files manually, teams use Helm charts to bundle everything into a single, reusable unit that can be installed, upgraded, or rolled back with confidence.
Today, Helm charts are no longer just a convenience - they are an industry standard. Most production-grade Kubernetes workloads rely on Helm charts for consistency, scalability, and operational efficiency. From startups to large enterprises, teams use Helm to reduce errors, simplify deployments, and manage applications across multiple environments.
This guide will walk you through Helm charts step by step, from the basics to real-world best practices, helping you understand how and why they are used in modern Kubernetes workflows.
What Is a Helm Chart Explained for Real Kubernetes Teams
A Helm chart is the standard way modern teams package and deploy applications on Kubernetes.
In real Kubernetes environments, applications are rarely defined by a single YAML file. Even a basic setup usually includes a Deployment, Service, ConfigMap, Ingress, Secrets, autoscaling rules, and environment specific configuration. Managing these files manually across multiple environments quickly becomes difficult to scale and easy to break.
Helm charts solve this by bundling all required Kubernetes resources into one structured package. Instead of applying multiple YAML files one by one, teams deploy applications using a chart that defines what should be deployed and how it should behave in different environments.
From an operational perspective, a Helm chart acts as a single source of truth for an application’s Kubernetes configuration. The same chart can be used across development, staging, and production by changing only configuration values, without copying or rewriting YAML files.
This approach is why Helm charts are widely adopted by DevOps and platform engineering teams. They make deployments predictable, upgrades safer, and rollbacks fast and reliable.
For teams operating Kubernetes at scale, especially those using platforms like Atmosly, Helm charts form the foundation for consistent deployments, environment parity, and dependable application operations.
Anatomy of a Helm Chart Folder and Files Explained
A Helm chart follows a clear and predictable folder structure. Understanding this structure is important because every file inside a chart has a specific purpose. Once you understand what each file does, working with Helm becomes far less intimidating and much easier to maintain in real production environments.
At the top level of a chart, you will always find a file called Chart.yaml. This file contains basic metadata about the chart, such as the chart name, version, and description. Kubernetes and Helm use this information to identify the chart and track its versions over time. For teams, this file is critical for release management and version control.
Next is the values.yaml file. This is where all configurable settings live. Things like image versions, replica counts, ports, resource limits, and environment specific values are defined here. Instead of editing Kubernetes manifests directly, teams update values in this file to control how an application behaves in different environments.
The templates folder contains the actual Kubernetes resource definitions. These files look like regular Kubernetes YAML, but they include placeholders that Helm fills using values from values.yaml. When Helm installs or upgrades a chart, it processes these templates and generates valid Kubernetes manifests automatically.
You may also see a file named _helpers.tpl inside the templates folder. This file stores reusable snippets such as naming logic or labels. It helps keep templates clean and consistent, especially in larger charts.
Some charts include a charts folder, which holds dependencies. This allows one chart to include and manage other charts, a common pattern in complex applications.
Finally, the NOTES.txt file provides helpful messages that appear after installation, such as access instructions or next steps. This improves usability and reduces confusion for operators.
Together, this structure makes Helm charts easy to understand, reusable, and safe to operate at scale.
How Helm Charts Work Behind the Scenes
When you run a Helm command, a lot happens quietly in the background. Understanding this process helps teams debug issues faster and trust what Helm is doing during deployments.
The process starts when Helm reads the chart files. It looks at Chart.yaml to understand what chart is being used and which version is being deployed. It then loads the configuration from values.yaml along with any additional values you pass during installation or upgrades.
Next, Helm processes the files inside the templates folder. These files contain placeholders that reference values. Helm replaces those placeholders with real values and generates standard Kubernetes YAML manifests. At this stage, there is nothing Helm specific left. The output is plain Kubernetes configuration that the cluster understands.
Once the templates are rendered, Helm sends the generated manifests to the Kubernetes API server. Kubernetes then creates or updates the resources such as Deployments, Services, and ConfigMaps based on those manifests. From Kubernetes’ point of view, it is receiving normal YAML, not a Helm chart.
Helm also tracks what it deployed by creating a release. A release represents a specific version of a chart deployed with a specific set of values. Helm stores this release information inside the cluster, which allows it to understand what is currently running.
Because Helm keeps this release history, it can perform upgrades and rollbacks safely. During an upgrade, Helm compares the new rendered manifests with what is already deployed and applies only the necessary changes. If something goes wrong, Helm can revert the cluster back to a previous known state.
This workflow is what makes Helm charts reliable for real production use. They provide repeatable deployments, controlled updates, and predictable behavior across environments.
Creating a Helm Chart from Scratch Step by Step
Creating a Helm chart from scratch is the best way to truly understand how Helm works in real Kubernetes environments. While Helm can generate a lot of boilerplate for you, knowing what to keep and what to remove is important for clean and maintainable charts.
The easiest way to start is by using the Helm CLI. Run the following command:
helm create myapp
Helm will generate a folder named myapp with a complete chart structure. This default chart is intentionally verbose because it tries to cover many use cases. In real projects, teams usually simplify it.
The first file to review is Chart.yaml. Update the chart name, description, and version so they clearly represent your application. This file helps teams track releases and understand what the chart is responsible for.
Next, open values.yaml. This file is the heart of your chart. Keep only the values your application actually needs. Common examples include image repository, image tag, replica count, service port, and resource limits. Removing unused values keeps the chart easy to understand and safer to modify.
Inside the templates folder, you will see multiple Kubernetes resources. Start by keeping only what your application requires. For a basic service, this is usually a Deployment and a Service. Remove unused files such as ingress or autoscaling if your app does not need them yet.
Edit the Deployment template to reference values from values.yaml instead of hardcoding anything. This ensures the chart can be reused across environments without changing the template logic.
Once cleaned up, your chart becomes a simple and reusable deployment package. It can now be installed, upgraded, and rolled back consistently in any Kubernetes cluster.
This approach aligns well with how teams use Helm in production. Simple charts are easier to review, safer to deploy, and far more maintainable as applications evolve.
Creating a Helm Chart from Scratch Step by Step
Creating a Helm chart from scratch helps teams understand how Helm is used in real Kubernetes environments. While Helm generates default files for you, production teams usually simplify charts to keep them clean and maintainable.
To create a new chart, run:
helm create myapp
This generates a folder called myapp with a complete chart structure. The default chart includes many features to support different use cases, but not all of them are required for every application.
Start by reviewing Chart.yaml. Update the chart name, description, and version so they clearly describe the application. This file helps with version tracking and release management.
Next, focus on values.yaml. This file controls how your application behaves. Keep only essential values such as image repository, image tag, replica count, and service port. Removing unused values makes the chart easier to understand and safer to modify.
Inside the templates folder, keep only the Kubernetes resources your application needs. For most services, this means a Deployment and a Service. Remove unused templates such as ingress or autoscaling until they are actually required.
Update the templates so all configurable fields reference values from values.yaml instead of hardcoded values. This allows the same chart to be reused across development, staging, and production without changing template logic.
Once simplified, the chart becomes a reusable deployment unit that can be installed, upgraded, and rolled back consistently across environments. This clean approach reflects how Helm charts are used in real production teams and aligns well with platform driven workflows like those supported by Atmosly.
Using Values Properly in Helm Charts
Values are the most important part of a Helm chart. They control how an application behaves without requiring changes to the underlying Kubernetes templates. When used correctly, values make charts reusable, predictable, and safe across multiple environments.
The values.yaml file acts as the configuration layer for a chart. This is where teams define things like container image versions, replica counts, ports, resource limits, and environment specific settings. Instead of modifying templates for each environment, teams adjust values to control behavior.
For example, a development environment may use fewer replicas and lower resource limits, while production uses higher values. The chart remains the same. Only the values change.
Helm allows values to be overridden in multiple ways. Teams can use different values files for each environment, such as values-dev.yaml or values-prod.yaml. During deployment, the correct file is passed to Helm, ensuring the right configuration is applied without changing the chart itself.
Values can also be overridden directly at deployment time using the Helm command line. This is useful for quick changes or testing, but for long term use, values files are easier to manage and review.
A common mistake is putting environment logic directly into templates. This makes charts complex and hard to maintain. A better approach is to keep templates simple and push all variability into values.
When values are structured clearly and documented well, Helm charts become easy to understand and safe to operate. This approach scales well as applications grow and aligns with how modern teams manage Kubernetes deployments using platforms like Atmosly.
Installing Upgrading and Rolling Back Helm Charts
Once a Helm chart is ready, the next step is managing its lifecycle in a Kubernetes cluster. Helm makes this process predictable by treating every deployment as a release that can be installed, upgraded, or rolled back safely.
To install a chart, teams use the Helm install command. This creates a new release in the cluster using the chart and the provided values. Helm renders the templates, applies the generated Kubernetes manifests, and records what was deployed.
Upgrading an application is just as straightforward. When values or templates change, the Helm upgrade command applies the updates. Helm compares the new configuration with the existing release and updates only what is necessary. This reduces risk and avoids unnecessary restarts.
One of Helm’s most valuable features is rollback. Every upgrade creates a new revision of the release. If an upgrade causes issues, teams can roll back to a previous revision quickly. This restores the application to a known working state without manual intervention.
Uninstalling a release removes all Kubernetes resources created by the chart. This keeps clusters clean and avoids leftover resources that can cause confusion or unexpected costs.
This lifecycle management is a major reason Helm is trusted in production environments. It gives teams confidence to deploy changes frequently while maintaining control and safety. For teams operating Kubernetes at scale, this release based workflow fits naturally into CI CD pipelines and platform level tooling such as Atmosly.
Helm Chart Repositories Public and Private
Helm charts are usually stored and shared through chart repositories. A chart repository is simply a location where Helm charts are packaged, versioned, and made available for installation. This allows teams to reuse charts instead of creating everything from scratch.
Public chart repositories are commonly used for widely adopted software. Platforms like Artifact Hub list thousands of community maintained Helm charts for tools such as NGINX, Prometheus, Grafana, and databases. Teams can add a public repository once and then install charts with a single command. This saves time and ensures proven configurations are used.
Private chart repositories are more common in real production teams. Companies use them to store internal application charts that should not be publicly accessible. These repositories help teams control versions, enforce standards, and manage access securely. Charts in private repositories are often tied to internal CI CD workflows.
After adding a repository, Helm allows teams to search available charts, install specific versions, and update repositories to fetch the latest releases. Keeping repositories updated ensures teams are deploying supported and secure chart versions.
Using repositories also makes collaboration easier. Teams do not need to copy chart folders manually or worry about mismatched versions. Everyone installs charts from the same source, which improves consistency across environments.
In production Kubernetes environments, chart repositories act as the distribution layer for applications. They work well alongside deployment platforms like Atmosly, where visibility, version control, and operational clarity are essential for managing Helm based workloads at scale.
Helm Charts vs Kustomize vs Plain Kubernetes YAML in 2025
Teams deploying applications on Kubernetes usually choose between three approaches: plain Kubernetes YAML, Kustomize, or Helm charts. Each has a place, but they solve different problems.
Plain Kubernetes YAML is the most basic option. It is simple and transparent, which makes it useful for learning Kubernetes concepts or deploying very small applications. However, as applications grow, plain YAML quickly becomes repetitive. Managing multiple environments requires copying files and manually changing values, which increases the risk of mistakes and configuration drift.
Kustomize improves on plain YAML by allowing teams to overlay environment specific changes on top of a base configuration. This works well when differences between environments are minimal. Kustomize keeps YAML readable and avoids templating logic, but it becomes harder to manage when applications need frequent version changes, feature toggles, or complex configuration options.
Helm charts are best suited for real world applications that evolve over time. Helm introduces templating, values, versioning, and release management. This makes it easier to deploy the same application across multiple environments, upgrade it safely, and roll back changes when needed. Helm also integrates well with CI CD pipelines and supports distribution through chart repositories.
In 2025, most teams follow a simple pattern. Plain YAML is used for learning and quick experiments. Kustomize is used for small to medium setups with limited variation. Helm charts are used for production workloads where consistency, upgrades, and operational safety matter.
For platform driven Kubernetes workflows and tools like Atmosly, Helm charts provide the flexibility and control needed to manage applications at scale while keeping deployments predictable.
Helm Chart Best Practices for 2025
Helm charts work best when they are simple, predictable, and easy to maintain. Over time, teams that follow a few core practices avoid most operational issues.
The first rule is to keep templates generic. Templates should describe structure, not environment specific behavior. Any value that may change between environments should live in values.yaml, not inside templates.
Versioning is equally important. Every meaningful change to a chart should update the chart version in Chart.yaml. This allows teams to track deployments, debug issues, and roll back safely when needed.
Avoid excessive logic in templates. Complex conditionals make charts hard to read and harder to debug. If a chart starts to feel complicated, it is usually a sign that configuration should move into values or be simplified.
Documentation also matters. A well written values.yaml with comments and a clear NOTES.txt file reduces onboarding time and prevents misconfiguration.
Finally, validate charts before deployment. Linting and dry runs help catch errors early and build confidence in releases.
These practices keep Helm charts reliable as applications scale and align well with platform based Kubernetes operations such as those supported by Atmosly.
Common Helm Chart Mistakes to Avoid
Even well written Helm charts can cause problems if a few common mistakes are repeated. One of the most frequent issues is hardcoding values directly into templates. This removes flexibility and forces teams to modify templates for every environment change, which defeats the purpose of using Helm.
Another common mistake is editing templates to handle environment specific behavior instead of relying on values files. This leads to complex conditional logic that becomes difficult to maintain and debug over time.
Ignoring chart versioning is also risky. When chart versions are not updated consistently, it becomes hard to track what was deployed and when, making rollbacks unreliable.
Teams also sometimes over customize charts too early. Adding unnecessary options and conditionals increases complexity without real benefit. Charts should start simple and evolve only when requirements demand it.
Avoiding these mistakes keeps Helm charts clean, predictable, and easy to operate. This disciplined approach is especially important in production Kubernetes environments and aligns well with platform driven workflows like those used with Atmosly.
Operating Helm Charts at Scale with Atmosly
Helm charts solve a critical problem in Kubernetes by standardizing how applications are packaged, configured, and deployed. But once those applications are live, teams face a new challenge: operating them reliably across environments while deployments, upgrades, and changes happen continuously.
This is where Atmosly fits naturally into Helm based workflows.
Atmosly helps teams manage Kubernetes applications deployed with Helm by providing clear visibility into environments, deployments, and failures. Instead of switching between YAML files, logs, and dashboards, teams get a centralized view that makes it easier to understand what is running, what changed, and why something failed.
With features like visual CI CD pipelines, AI-assisted Kubernetes troubleshooting, environment cloning, and cost insights, Atmosly reduces the operational overhead that often follows Helm deployments. It allows teams to move faster while maintaining control and reliability.
If Helm charts are how you deploy applications, Atmosly is how you operate them with confidence.
Sign up for Atmosly and simplify how you deploy, manage, and scale Helm based Kubernetes applications.
