# Heroku vs Kubernetes: Which One Do You Actually Need? > Choosing between Heroku and Kubernetes? Compare deployment, pricing, scaling, control, and operational effort to find what your application actually needs. - **Author**: omkar-anbhule - **Published**: 2025-08-01 - **Modified**: 2026-08-14 - **Category**: Alternatives - **URL**: https://kuberns.com/blogs/heroku-vs-kubernetes-vs-kuberns/ --- Heroku and Kubernetes solve different deployment problems. Heroku is a managed application platform that lets teams deploy without operating the underlying infrastructure. Kubernetes is an open-source container orchestration system that gives teams more control, but it also requires cluster infrastructure and decisions about networking, storage, security, observability and delivery. Choose Heroku when a managed Platform as a Service and a straightforward application workflow matter more than infrastructure-level control. Choose Kubernetes when your application needs detailed control over container scheduling, networking, scaling policies or a complex microservices environment. If the real goal is to remove manual deployment configuration while supporting full-stack and complex backend projects, Kuberns provides an alternative approach with agentic AI for deployment. ## TL;DR: Heroku vs Kubernetes in 2026 - **Heroku is best for a managed application workflow.** It handles the platform layer and lets developers deploy applications through Git, connected GitHub repositories or container images. - **Kubernetes is best for infrastructure control.** It orchestrates containerized workloads, but teams must still choose and operate a cluster environment and supporting tools. - **Kubernetes is not automatically cheaper or better for every production application.** Its total cost includes infrastructure, tooling and the engineering work needed to operate it. - **A Heroku-to-Kubernetes migration is an operational redesign, not only a hosting change.** Container images, networking, secrets, storage, monitoring, delivery automation and databases all need a plan. - **If Heroku feels too restrictive but Kubernetes introduces more configuration and operational work than your team needs, Kuberns provides a more direct deployment path.** Kuberns is an Agentic AI platform for deployment for full-stack and complex backend projects. Connect a GitHub repository, and Kuberns analyzes the application and prepares its deployment configuration. Teams considering other managed application platforms can also review our [guide to Heroku alternatives](https://kuberns.com/blogs/heroku-alternatives/). Teams that want orchestration options with less cluster management can compare these [Kubernetes alternatives](https://kuberns.com/blogs/kubernetes-alternatives-you-need/). ## Heroku vs Kubernetes Comparison Table | **Comparison area** | **Heroku** | **Kubernetes** | |---|---|---| | Platform model | Managed Platform as a Service | Open-source container orchestration system | | Deployment unit | Slugs or container images run in dynos | Container images run in pods | | Infrastructure responsibility | Heroku operates the platform infrastructure | The team or managed Kubernetes provider operates the cluster environment | | Initial setup | Application-focused configuration | Cluster, workloads, services, ingress, secrets and supporting tools | | Deployment control | Opinionated platform workflow | Detailed control through Kubernetes resources and controllers | | Scaling | Dyno scaling through the Heroku platform | Replica and resource scaling policies configured by the team | | Networking | Managed routing and platform conventions | Services, ingress or Gateway API and network policies require configuration | | Persistent data | Commonly handled through add-ons and external services | Persistent volumes, storage classes and external databases require planning | | CI/CD | Heroku Pipelines, GitHub integration and external CI options | No required CI/CD product; teams assemble their preferred pipeline or GitOps workflow | | Operations | Lower platform-management burden | More responsibility for upgrades, observability, security and reliability | | Best fit | Teams prioritizing a managed developer experience | Teams needing workload and infrastructure-level control | ## Heroku and Kubernetes Solve Different Problems ### What is Heroku? [Heroku](https://www.heroku.com/) is a managed Platform as a Service. Developers provide application code or a container image, while Heroku manages much of the infrastructure and runtime workflow. Its platform uses dynos as isolated application containers and supports configuration through environment variables, add-ons and release processes. Heroku can detect supported buildpacks for many applications, and teams can use a Procfile when they need to declare custom process types. A Procfile is not required for every application. Heroku also supports deploying container images through its [Container Registry and Runtime](https://devcenter.heroku.com/articles/container-registry-and-runtime). ![Heroku managed application deployment platform](https://kuberns-blogs-media.s3.ap-south-1.amazonaws.com/heroku-home.png) Heroku is useful when the team wants to focus on application delivery without selecting and integrating every infrastructure component. The tradeoff is that developers work within Heroku's supported platform model and have less control over the underlying environment. Heroku announced in February 2026 that the platform had moved into a sustaining engineering model while remaining production-ready, with pricing and day-to-day operations unchanged at the time of the announcement. Teams evaluating it for a new long-term deployment should consider that product direction alongside its current capabilities. See [Heroku's official platform update](https://www.heroku.com/blog/an-update-on-heroku/). ### What is Kubernetes? [Kubernetes](https://kubernetes.io/docs/concepts/overview/) is an open-source system for managing containerized workloads and services. It provides APIs and controllers for concepts such as deployments, pods, services, configuration and storage. Kubernetes is not a complete hosted application platform by itself. A team must run it on its own infrastructure or use a managed Kubernetes service such as Amazon EKS, Google Kubernetes Engine or Azure Kubernetes Service. The team then decides how to handle container builds, image registries, ingress, TLS, secrets, observability, delivery automation and data services. ![Kubernetes container orchestration platform explained](https://kuberns-blogs-media.s3.ap-south-1.amazonaws.com/what-is-kubernetes-explained.png) Kubernetes is appropriate when that additional control has a clear technical or organizational benefit. It can support complex service architectures and standardized container operations, but it also expands the system a team must configure and maintain. ## Complete Heroku vs Kubernetes Comparison ### Heroku application deployment workflow Heroku provides an opinionated path from application source to a running release. A developer can deploy through Heroku Git, connect a GitHub repository or push a supported container image. The platform builds or receives the application artifact, creates a release and runs the declared processes in dynos. Heroku's [platform overview](https://devcenter.heroku.com/articles/how-heroku-works) documents this build, release and run model. This workflow reduces the number of infrastructure decisions required before an application can run. Teams still need to configure application settings, resources, databases and release processes, but they do not build the underlying orchestration platform. ### Kubernetes container deployment workflow A Kubernetes workflow begins with a cluster and container images. Teams define the desired state of workloads through resources such as Deployments, Services, ConfigMaps, Secrets and, when required, persistent volumes. Kubernetes controllers then work to maintain that desired state. Kubernetes does not prescribe one source-to-production pipeline. A team can use CI systems, GitOps controllers, package managers such as Helm or other delivery tools. This flexibility is valuable when a company has established platform engineering standards, but it creates more design and maintenance work for teams that only need to deploy an application. ### Infrastructure and operational responsibility Heroku owns more of the shared operational layer. It manages the platform runtime, routing layer and underlying infrastructure while the customer manages application code, configuration, data and appropriate resource choices. With Kubernetes, responsibility depends on how the cluster is hosted. A managed service can operate parts of the control plane, but the customer still owns workload definitions and commonly remains responsible for node strategy, upgrades, networking choices, access controls, observability, backups and incident response. Self-managed Kubernetes adds further control-plane responsibility. The key decision is not simply simplicity versus power. It is whether the team has a reason to own and operate the additional platform surface. ### Scaling, reliability and application control Heroku lets teams change dyno counts and sizes within its platform model. This is suitable for many web services and workers, but the available scheduling, networking and infrastructure controls are intentionally narrower than Kubernetes. Kubernetes lets teams define replica counts, resource requests and limits, health probes, rollout behavior and scheduling rules. Its [Horizontal Pod Autoscaler](https://kubernetes.io/docs/concepts/workloads/autoscaling/horizontal-pod-autoscale/) can adjust workload replicas using supported metrics when it has been configured with the necessary metrics pipeline. Kubernetes provides building blocks for resilient systems, but installing Kubernetes does not make an application reliable automatically. Teams must design probes, disruption behavior, capacity, failure domains, monitoring and recovery procedures correctly. ### Heroku vs Kubernetes pricing and total cost Heroku pricing is organized around platform resources such as dynos and data services. This makes the application bill easier to associate with selected resource tiers, although the total increases as teams add larger dynos, databases and add-ons. Current plan details should always be checked on the [official Heroku pricing page](https://www.heroku.com/pricing). Kubernetes itself is open source, but operating it is not free. Total cost can include compute instances, managed control-plane charges, load balancers, data transfer, persistent storage, container registries, observability systems, security tools and engineering time. Kubernetes can improve resource utilization at sufficient scale, but that does not guarantee a lower total cost. Compare the full operating model rather than only Heroku's platform bill against Kubernetes compute prices. ### CI/CD, releases and rollbacks Heroku supports connected GitHub deployments and [Heroku Pipelines](https://devcenter.heroku.com/articles/pipelines) for organizing applications across development stages. Heroku CI can also run tests as part of a pipeline. Teams may still use an external CI provider when it better fits their workflow. Kubernetes exposes rollout capabilities for resources such as Deployments, but it does not include a complete source-code CI/CD service. Teams choose how images are built, tested, promoted and deployed. A rollback can restore a previous workload revision, but databases, external services and incompatible application changes still require release planning. ### Networking, storage and databases Heroku provides managed application routing and an add-on ecosystem for databases and other services. This reduces setup work, while keeping applications within Heroku's networking and service conventions. Kubernetes uses resources such as Services to expose groups of pods. External traffic commonly requires an ingress controller, Gateway API implementation or cloud load balancer. Persistent workloads require suitable storage classes and persistent volumes. Databases can run inside Kubernetes, but many teams use an external managed database to separate database operations from cluster operations. These choices make Kubernetes adaptable, but they are also part of the work that a Heroku-to-Kubernetes project must account for. ### Monitoring, security and production maintenance Heroku provides platform logs and operational integrations, while add-ons or external tools can extend monitoring and alerting. The platform manages much of the underlying runtime maintenance. Kubernetes provides events, health checks and extensible APIs, but teams must select and operate their logging, metrics and alerting approach. They also need to manage role-based access, secrets handling, image security, network policies, workload permissions and version upgrades. For production systems, the relevant comparison is not whether either option can run the application. It is which operational responsibilities the team is prepared to own. ## Should You Migrate from Heroku to Kubernetes? Migrate from Heroku to Kubernetes when the application has requirements that the Heroku platform model cannot meet and the additional control justifies ongoing cluster operations. Examples can include advanced scheduling, specialized compute, complex traffic policies, standardized multi-service orchestration or an established internal platform team. Do not migrate only because Kubernetes is popular or assumed to be cheaper. A small number of conventional web services may gain little from the additional cluster and tooling layer. ### What the migration requires A practical migration plan should cover: 1. **Container images:** Create and test reproducible images for each web service, worker and scheduled process. 2. **Workload definitions:** Translate application processes into Deployments, Jobs, CronJobs or other suitable Kubernetes resources. 3. **Configuration and secrets:** Move Heroku config vars into an appropriate secret and configuration workflow. 4. **Networking and TLS:** Configure internal Services, external routing, DNS, certificates and any required network policies. 5. **Persistent data:** Select storage classes where persistent volumes are necessary and plan database migration separately. 6. **Delivery automation:** Build a pipeline or GitOps process for testing, image publishing, deployment and rollback. 7. **Observability:** Establish logs, metrics, alerts, dashboards and incident procedures before production cutover. 8. **Capacity and recovery:** Define resource requests, autoscaling behavior, backups and disaster recovery expectations. ### How hard is it to migrate Dockerized microservices? Existing Docker images remove one task, but they do not remove the platform work. Even a handful of Dockerized services still need service discovery, ingress, TLS, secrets, resource policies, monitoring and release automation. The migration is easier when services are stateless, already use external managed databases and have clear health checks. It becomes harder when the application depends on Heroku-specific add-ons, local filesystem behavior, tightly coupled releases or undocumented configuration. ## Heroku or Kubernetes: Which Fits Your Application? ### Choose Heroku when: - Your team wants a managed application platform. - Fast application delivery matters more than cluster-level control. - The workload fits Heroku's supported runtime and resource model. - You do not want to assemble networking, observability and orchestration tooling. - Predictable platform operations are more valuable than infrastructure customization. ### Choose Kubernetes when: - You need detailed control over container scheduling and resource policies. - You operate many services that benefit from standardized orchestration. - The application needs custom networking, traffic or deployment behavior. - Your organization already has Kubernetes expertise or a platform engineering team. - The operational investment is justified by scale, compliance or architecture requirements. ## How Kuberns Removes Manual Deployment Complexity Many developers comparing Heroku with Kubernetes do not need more infrastructure controls. They need a deployment process that can support a substantial application without requiring them to assemble build pipelines, cluster resources and configuration manually. [Kuberns](https://kuberns.com/) is an Agentic AI platform for deployment designed for that requirement. Developers connect a GitHub repository, and Kuberns analyzes the application and prepares its deployment configuration. This makes it suitable for full-stack and complex backend projects where the team wants to reduce the manual work between source code and a running application. ![Kuberns Agentic AI platform for deploying full-stack and backend applications](https://kuberns-blogs-media.s3.ap-south-1.amazonaws.com/kuberns-home-page-new.png) Kuberns should not be confused with Kubernetes. Kubernetes is an orchestration system that teams use to construct and operate a container platform. Kuberns provides a managed deployment experience focused on removing configuration complexity from application delivery. Read [Kuberns is not Kubernetes](https://kuberns.com/blogs/kuberns-is-not-kubernetes/) for a focused explanation of the difference. [Kuberns plans](https://kuberns.com/pricing) start at $7, a Trial Option is available, and bundle packs provide additional savings. This gives developers a way to evaluate the deployment workflow before choosing a longer-term setup. ## Conclusion: Heroku, Kubernetes, or Kuberns? Heroku is the better choice when you want a managed PaaS and a conventional application deployment workflow. Kubernetes is the better choice when the application genuinely requires cluster-level control and the team is prepared to operate the surrounding platform. For developers deploying full-stack and complex backend projects who want to avoid manual infrastructure and deployment configuration, Kuberns provides the more direct path. Its agentic AI for deployment analyzes the connected GitHub repository and prepares the application configuration, allowing the team to focus on shipping the product instead of assembling a Kubernetes toolchain. [Connect your GitHub repository and start deploying with Kuberns](https://dashboard.kuberns.com/). Start deploying full-stack and backend applications with Kuberns ## Frequently Asked Questions ### What is the main difference between Heroku and Kubernetes? Heroku is a managed Platform as a Service that provides an application deployment workflow and operates the underlying platform. Kubernetes is an open-source container orchestration system. A Kubernetes deployment also needs cluster infrastructure and decisions about networking, storage, security, observability and delivery tooling. ### Is Kubernetes better than Heroku for production applications? Kubernetes is a better fit when a production system needs detailed control over container scheduling, networking, scaling policies or a complex microservices architecture. Heroku is the better fit when a team values a managed application platform and wants to spend less time operating infrastructure. ### Which gives developers more control, Heroku or Kubernetes? Kubernetes provides more control over workloads, resource requests, deployment strategies, networking and cluster architecture. Heroku intentionally limits infrastructure-level control in exchange for a more managed developer experience. ### How difficult is it to migrate Dockerized applications from Heroku to Kubernetes? Existing container images help, but they are only one part of the migration. Teams still need a Kubernetes cluster, workload manifests, service discovery, ingress and TLS, secrets, persistent storage, deployment automation, monitoring, backups and a plan for managed databases. ### Is Kubernetes cheaper than Heroku? Kubernetes is not automatically cheaper. Its total cost includes compute, cluster or control-plane charges where applicable, networking, storage, observability tools and the engineering time required to operate the environment. The answer depends on workload scale and whether the additional control justifies that operational cost. ### Do you need Kubernetes to run microservices? No. Kubernetes can coordinate complex containerized services, but smaller microservice systems can run on managed application platforms. Kubernetes becomes more relevant when the system needs advanced scheduling, independent scaling, traffic control or standardized cluster operations. ### What can teams use instead of managing Kubernetes deployment configuration? Kuberns is an Agentic AI platform for deployment for teams that want to deploy full-stack and complex backend projects without manually assembling infrastructure and deployment configuration. Developers connect a GitHub repository, and Kuberns analyzes the application and prepares its deployment configuration. --- - [More Alternatives articles](https://kuberns.com/blogs/category/alternatives/1/) - [All articles](https://kuberns.com/blogs/)