At first, Helm makes Kubernetes (K8s) deployments feel effortless. Writing a chart for each service keeps things modular and manageable. But as the number of applications grows, so does the maintenance overhead.
A small tweak in a shared dependency means updating hundreds of charts, each with slight variations. Updating configurations, dependencies and versioning across multiple services turns into a time-consuming process.
If you think the mono-repo vs. multi-repo debate sparks flame wars, don’t even get me started on Helm chart vs. super Helm chart. Welcome to the Kubernetes version of the age-old argument: Should you optimize for flexibility or centralization?
Instead of managing hundreds of Helm charts, teams can use a super Helm chart, a single, structured chart that manages all applications. This unified approach streamlines versioning, improves maintainability and reduces duplication.
But how exactly do you use a super Helm chart — and how do you know if it is the best solution for your Helm-based deployments? My recommended approach simplifies updates and standardizes deployments, but it also introduces trade-offs.
Originally published in The New Stack, this article will dig into the pros, cons and real-world implications of the super Helm chart. (Think: how to ensure it’s a scalable solution, and not just another layer of complexity.)
Helm Chart Sprawl? Super Helm Chart to the Rescue
Many organizations rely on a mix of internal tools, business services and supporting infrastructure. When organizations scale their Kubernetes environments, they often start by defining a Helm chart for each service, microservice or application. This approach works initially but quickly leads to major bottlenecks.
For example, a company might have a collection of services including a user authentication API, an order-processing system and a background job scheduler. Each of these services starts with its own Helm chart, but as the number of internal applications grows, so does the operational overhead.
A super Helm chart can group these services together, defining them as modular components. Instead of managing separate ConfigMaps and Kubernetes objects for each application, teams can structure their charts to handle shared configurations — such as database credentials, logging settings and resource limits — centrally.
This can be done by defining one large chart that includes all applications, using dependencies within the chart to call subcharts dynamically, or standardizing Helm templates so that all applications share a common deployment logic. This approach allows teams to update configurations in one place, ensuring that changes propagate seamlessly across all services. In this way, when a change is needed, whether it’s updating a Redis cache configuration or modifying an ingress rule, it can be done in one place instead of across dozens of separate Helm charts.
Weighing Your Options: Pros and Cons of Using a Super Helm Chart
A super Helm chart offers several advantages, particularly for organizations managing a large number of Kubernetes applications. By centralizing deployments, teams can reduce redundancy, enforce consistency and streamline updates. However, this approach also introduces trade-offs in terms of complexity, customization and governance.
A super Helm chart can become too large and difficult to manage, especially when handling edge cases that require custom logic. Applications with highly specific requirements may need overrides, making the chart harder to maintain. This approach also requires centralized governance, meaning teams must adopt consistent engineering practices, such as enforcing CI/CD workflows in Terraform or using a standardized Makefile system.
The Pros of a Super Helm Chart
With a Super Helm Chart, updates and fixes can be applied centrally, eliminating redundant work. For example, a security vulnerability in an Nginx sidecar used across multiple services can be patched once in the super Helm chart, automatically propagating to all applications.
Plus, you also get:
- Versioning benefits: Managing dependencies and releases from a single place minimizes cascading failures. Instead of each service using a slightly different version of Istio, Redis or another core component, a super Helm chart ensures consistency.
- Consistency in configuration management: A super Helm chart avoids maintaining hundreds of versions of Kubernetes objects like ConfigMaps and Secrets. A shared PostgreSQL configuration, for example, can define standard connection pooling, replication settings and backup policies, reducing risk across deployments.
- Security and stability: A versioned super chart prevents uncontrolled changes across multiple applications at once. Instead of upgrading Istio independently across 50 microservices, changes can be rolled out in structured phases, reducing the likelihood of breaking production workloads.
Challenges and Trade-offs to Consider
Super Helm Charts, however, can come with complexity at scale. As the number of edge cases grows, the chart can become bloated with overrides and conditional logic. An organization running both stateless web services and stateful applications may struggle to fit all needs into a single template without excessive complexity.
What else could you be faced with?
- Customization challenges: Not all services fit neatly into a uniform deployment structure. A machine learning workload requiring GPU scheduling and taints may need configurations that a standard web service does not, making per-application overrides difficult to manage.
- Centralized governance required: A super Helm chart only works if teams adopt consistent engineering practices. Without strict CI/CD workflows and GitOps enforcement, teams might introduce ad-hoc changes that undermine standardization. For example, if some teams deploy manually with Helm commands while others use automated pipelines, configuration drift becomes a problem.
Is a Super Helm Chart For You?
Maybe I have, or maybe I haven’t, convinced you to take the super Helm chart plunge. Much like the endless mono-repo vs. multi-repo debate, there’s no single right answer — only trade-offs that depend on your team’s scale, architecture and operational discipline.
While a super Helm chart offers a scalable approach to Kubernetes application management, it is not always the right solution for every organization. Teams must weigh the balance between maintainability and flexibility. For those managing large-scale deployments, consolidating Helm charts can improve efficiency, security and reliability, but only if strong engineering principles are followed.
For a super Helm chart approach to be effective, strong governance and best practices must be in place. Defining stringent guidelines, such as avoiding persistent volumes or enforcing naming conventions, ensures consistency across deployments. Standardizing CI/CD workflows helps maintain a unified deployment process. Leveraging GitOps tools like ArgoCD automates deployments and enforces best practices.
Would this approach work for your organization?
