Managed Kubernetes vs Self-Hosted Solutions for DevOps Teams

Summary

• Managed Kubernetes greatly decreases operational overhead, but there is a trade-off in terms of customization flexibility compared to self-hosted solutions
• Self-hosted Kubernetes provides total control over your infrastructure, but it demands a lot of expertise and a 24/7 maintenance commitment
• A majority of enterprises are moving towards managed Kubernetes solutions, with 71% of organizations now using managed services
• The total cost of ownership for self-hosted Kubernetes is often underestimated when the operational staff requirements are not taken into account
• Gcore Managed Kubernetes provides simplified operations while still offering enterprise-grade security and performance for DevOps teams

Deciding between managed and self-hosted Kubernetes is not just a technical decision, it’s a strategic one that affects your entire DevOps workflow. The best choice depends on your team’s expertise, business needs, and long-term growth plans.

With the speed of development increasing rapidly, managing microservices at scale has become vital, and container orchestration is the key. Kubernetes is leading the charge in this space, but to implement it effectively, you need to think carefully about how you manage it. Managed Kubernetes gives teams a more straightforward way to orchestrate their containers, without the operational complexity of managing it themselves.

What Separates Managed Kubernetes from Self-Hosted Solutions?

When you get down to it, the main difference between self-hosted and managed Kubernetes lies in who takes care of the control plane and underlying infrastructure. If you’re using self-hosted Kubernetes, your team is in charge of everything. This includes managing master nodes and etcd clusters, as well as networking, storage integration, and security configurations. On the other hand, managed services take a lot of this off your plate. Your provider will handle control plane management, leaving you free to concentrate on your applications and workloads.

The choice isn’t just about ease versus power. It’s about matching how you manage your infrastructure with your business goals, what your team can do, and how you plan to use resources. Each choice is a different way to operate that will have effects all over your business.

The Balance Between Control and Convenience

When you host Kubernetes yourself, you get an incredible amount of control over every single detail of your cluster configuration. You can tailor your networking solutions, your storage integrations, and your security policies to your exact specifications. However, this kind of flexibility isn’t free. It comes with a lot of operational complexity and a need for specialized knowledge. Your team has to handle cluster upgrades, security patches, and system-level troubleshooting. All of this requires a deep understanding of Kubernetes.

Managed Kubernetes emphasizes easy operations and dependability. The service provider takes care of infrastructure setup, control plane handling, and core component upkeep. This method significantly lessens the operational load on your team, freeing them up to concentrate on deploying applications and business logic instead of managing infrastructure. The simplicity does come with some restrictions on customization and potentially greater upfront costs, but these are usually balanced out by lower operational costs.

Managed Kubernetes: Pros and Cons

Managed Kubernetes services such as GKE, EKS, and AKS are popular for a reason. They take away much of the difficulty that comes with deploying and maintaining Kubernetes. The provider takes care of cluster provisioning, control plane management, etcd backup and restoration, and automatic updates to the Kubernetes version. Your team just interacts with the cluster through standard Kubernetes APIs without having to concern themselves with the underlying infrastructure.

What you give up is extensive personalization at the infrastructure level. While you keep full control over your workloads, applications, and deployment strategies, certain infrastructure-level configurations may be standardized or limited. The trade-off is generally worthwhile for teams without specialized Kubernetes expertise or those who prefer to focus their engineering resources on application development rather than infrastructure management.

Security and Maintenance Included

Managed Kubernetes holds a strong advantage in its built-in security. This is because service providers have security teams on staff that are always on the lookout for vulnerabilities. These teams also apply patches and use best practices across thousands of clusters. This level of security is hard to achieve with in-house resources, especially for smaller organizations.

Another huge advantage is the automation of maintenance. Managed services take care of regular tasks such as control plane updates, node health monitoring, and certificate rotation on their own. These operations are necessary but can be time-consuming and prone to mistakes when done manually. By automating these tasks, managed services not only free up your team from routine maintenance work but also decrease the chance of human error. For more insights on why automation is crucial, check out this article on manual configuration pitfalls.

Security advantages are not limited to patching alone. A majority of managed Kubernetes providers offer built-in security features such as role-based access control (RBAC), network policies, and secrets management. These features are set up following industry’s best practices and are updated regularly as security standards change.

Scalability and Reliability

Managed Kubernetes services shine when it comes to dealing with fluctuating workloads thanks to their automatic scaling capabilities. The control plane scales on its own to handle more API requests, while node pools can grow or shrink as needed based on the demands of the workload. This flexibility guarantees that resources are used efficiently and that performance remains steady no matter what traffic patterns look like. Most managed services include high availability as a standard feature, with control plane components spread out over multiple availability zones and automatic failover mechanisms ready to go.

Easy-to-use Management Interface

There is a significant difference in the user experience between managed Kubernetes and self-hosted Kubernetes. Managed services usually offer user-friendly web consoles, simplified CLI tools, and well-documented APIs that hide much of the complexity of Kubernetes. These interfaces make it easier for teams with different levels of Kubernetes expertise to interact effectively with clusters.

Managed solutions also stand out when it comes to integration with other cloud services. They usually provide smooth links to monitoring, logging, identity management, and CI/CD services within the same ecosystem. This integration lowers the amount of setup work needed to create a full application platform.

Anticipating Costs

Managed Kubernetes services usually have a pricing model that you can anticipate, making it easier to budget. Most services charge based on the number of clusters, nodes, or resources used, with clear pricing levels. This predictability removes any surprise infrastructure costs that can occur when managing your own clusters, like emergency scaling events or hardware failures.

There are also financial benefits when it comes to staffing. By using managed services to take care of the operational side of things, you can reduce the number of specialized Kubernetes administrators you need on your team. This can have a big effect on your total cost of ownership (TCO), especially if you’re a smaller organization that doesn’t have a lot of Kubernetes expertise already.

Worries About Vendor Lock-in

The main disadvantage of managed Kubernetes is the risk of vendor lock-in. Kubernetes itself is standardized, but managed services often deeply integrate with features specific to the provider for storage, networking, identity management, and monitoring. These integrations can make it more difficult to migrate to another provider or to self-hosted Kubernetes.

Many companies are avoiding the risk of being locked into one provider by using a cloud-agnostic approach with their Kubernetes deployments. They use standard Kubernetes resources and try to avoid APIs that are specific to a particular provider. This might mean giving up some of the convenience of managed services, but it also means they have the flexibility to move to a different provider in the future.

Self-Hosted Kubernetes: The Power and the Responsibility

With self-hosted Kubernetes, you have the ultimate power to configure and control your system. Your team can design the cluster to your exact specifications, from the networking plugin you choose to the configuration of your storage and security policies. This flexibility allows for highly specialized deployments that managed services may not be able to accommodate.

You have control over every aspect of the Kubernetes ecosystem. You can implement custom monitoring solutions, integrate with on-premises systems, implement specialized security controls, or optimize performance in ways that may not be possible with managed offerings. For organizations with unique compliance requirements or specialized workloads, this level of customization is critical.

Full Control Over Configuration

Self-hosted Kubernetes lets you implement any configuration that the Kubernetes API supports. This includes custom configurations for specialized network plugins like Calico, Cilium, or Flannel, storage systems that meet your specific performance needs, and custom admission controllers that enforce your organization’s policies. The ability to adjust every part of the cluster makes self-hosted Kubernetes especially useful for applications that require high performance or environments with unique requirements.

Another area where self-hosted Kubernetes shines is in custom scheduling rules. You have the ability to implement complex node affinity rules, taints and tolerations, or custom schedulers that optimize resource allocation based on your specific workload patterns. These optimizations can greatly enhance resource utilization and application performance in specialized environments.

Independence of Infrastructure

Self-hosted Kubernetes can be installed anywhere—from bare metal servers in your data center to virtual machines in any cloud provider. This flexibility allows you to take advantage of existing infrastructure investments or choose the most cost-effective hosting option for your specific needs. You can even implement hybrid deployments spanning multiple environments, with workloads distributed according to their performance, cost, or compliance requirements.

Having the liberty to select your base infrastructure also allows for specialized hardware configurations. You have the option to choose servers with particular CPU, memory, or storage features that align with your workload needs, or incorporate specialized hardware like GPUs or FPGAs for certain applications. This degree of hardware customization is usually more restricted with managed services.

No Ties to a Single Vendor

One of the biggest benefits of self-hosting Kubernetes is that you’re not tied to any one provider. Your deployments will be the same no matter where they’re hosted, and you can move between environments without having to change your basic architecture. This flexibility can be especially helpful for organizations that have multi-cloud strategies or those who are worried about being locked into a long-term relationship with a vendor.

Not having vendor-specific extensions also promotes compliance with Kubernetes standards and best practices. Your team becomes proficient in core Kubernetes features instead of provider-specific abstractions, making your knowledge applicable in any Kubernetes environment. This standardization can enhance team flexibility and streamline training requirements over time.

Technical Skills Needed

Running self-hosted Kubernetes successfully demands a high level of proficiency in several areas. Your team should be well-versed in the intricacies of Kubernetes, networking concepts, storage systems, security best practices, and infrastructure management. The skills needed for this are becoming more specialized and harder to come by, which makes finding the right staff a big hurdle for many companies.

Self-hosted Kubernetes demands a high learning curve that is not only steep but also continuous. The project is developing at a fast pace, and there are new releases every few months that introduce new features and deprecate old ones. This means that you need to constantly learn and adapt to these changes, which can put more pressure on your team. If you don’t have enough knowledge and experience, self-hosted Kubernetes can easily turn from an asset into a liability.

Round-the-Clock Maintenance

Choosing to operate self-hosted Kubernetes means taking on full responsibility for the availability and performance of the cluster. Your team will need to constantly monitor the health of the cluster, respond to alerts at all hours, and resolve issues as quickly as possible to maintain the availability of the service. This operational burden either requires a large enough team to provide 24/7 coverage or accepting the possibility of delays in responding to incidents.

Responding to incidents is just the tip of the iceberg when it comes to maintenance workloads. Regular tasks such as version upgrades, certificate rotation, backup verification, and security patching all require a substantial amount of time and focus. All of these activities need to be meticulously planned and carried out to avoid any disruption to the service, which adds another layer of complexity to your operational processes.

Comparing Performance in the Real World

Contrary to what you might think, a well-configured managed service often provides the same or better performance than a self-hosted cluster for most standard workloads. This is because the providers of managed services are experts in infrastructure optimization and can leverage economies of scale, which often results in efficient resource utilization and consistent performance.

Availability and Dependability Metrics

Managed Kubernetes services generally provide more reliable guarantees than what most companies can achieve with self-hosted clusters. Major vendors maintain uptime SLAs of approximately 99.9% to 99.95% for the control plane, with extensive monitoring and automated remediation systems ensuring consistent availability. Achieving similar reliability with self-hosted Kubernetes requires substantial investment in redundant infrastructure, monitoring systems, and operational processes.

Stability and Dependability Measurements

Managed Kubernetes services usually come with impressive uptime statistics, with most of the big-name providers promising 99.9% to 99.99% SLAs for their control planes. This level of dependability comes from infrastructure that was built with a specific purpose in mind and has redundancy across multiple availability zones, automatic failover mechanisms, and dedicated site reliability engineering teams. These benefits are hard for most companies to duplicate in-house without making a significant investment.

On the other hand, self-hosted Kubernetes clusters frequently achieve less reliable metrics in actual use. A 2022 survey by CNCF revealed that companies running self-managed Kubernetes had an average of 5.8 hours of unplanned downtime per year, compared to 2.4 hours for managed services. This gap demonstrates the difficulty of maintaining highly available distributed systems without specialized knowledge and tools.

Response Times for Scaling

For Kubernetes deployments, a key performance metric is the capacity to scale quickly in response to fluctuations in workload demands. This is an area where managed services generally shine, with automated node provisioning that can scale clusters in a matter of minutes. Most providers offer automatic scaling based on CPU usage, memory usage, or custom metrics, ensuring that performance remains responsive during periods of increased traffic.

While self-hosted Kubernetes can offer the same capabilities, it requires a substantial amount of engineering work. You will need to create and maintain automation for node provisioning, set up cluster autoscaling, and ensure there is enough capacity available when necessary. If not implemented correctly, scaling operations can be slow or unreliable, which can impact application performance during periods of high demand.

Capabilities for Recovering from Disasters

Another area where managed services often excel compared to self-hosted solutions is disaster recovery. Big providers will automatically back up etcd data and control plane configurations, and they have documented procedures for restoring the cluster in the event of a catastrophic failure. These capabilities are standardized, they are tested regularly, and they are carried out by teams with a lot of experience in recovery operations.

Self-hosted Kubernetes necessitates substantial planning and continuous upkeep to create equivalent disaster recovery features. You must establish backup procedures for etcd, regularly test restoration processes, and document recovery workflows for a variety of failure scenarios. Recovery operations may be sluggish and prone to mistakes if testing and documentation are not thorough, potentially lengthening outages during critical incidents.

Comparing Costs: The Real Cost of Each Choice

The monetary comparison between managed and self-hosted Kubernetes goes much further than just the obvious infrastructure costs. While managed services usually have clear per-cluster or per-node charges, self-hosted Kubernetes has many hidden costs that need to be taken into account for a fair comparison.

Expenses

Managed Kubernetes services operate on clear pricing models, with costs usually based on the number of clusters, worker nodes, or consumed resources. These fees range from roughly $70 to $200 per month per cluster for the control plane, plus the cost of worker nodes and associated resources. The predictability of these costs makes budgeting easy, with clear scaling expectations as your deployment grows.

With self-hosted Kubernetes, there are no direct service charges, but you do need infrastructure for the control plane and worker nodes. This infrastructure usually includes a minimum of three master nodes for high availability, load balancers, and persistent storage for etcd. This can cost between $300 and $500 per month for a production-grade cluster, and that’s before you even consider the worker nodes that run your actual workloads.

Unseen Operational Costs

The largest expenses of self-hosted Kubernetes are frequently not seen on infrastructure bills. Your team needs to dedicate a lot of time to managing clusters, troubleshooting, updates, and maintenance—activities that could be otherwise focused on developing applications or innovating in business. These opportunity costs are hard to measure but they do have a real impact on business. For insights on reducing operational overhead, consider reviewing this case study on CI/CD automation.

Another unexpected expense is incident response. If issues arise in self-hosted clusters, your team is responsible for figuring out what went wrong and fixing it, regardless of when it happens. These incidents often happen outside of regular work hours, which means you either have to pay for on-call rotations or accept that it will take longer to resolve the issue. Managed services can help reduce these costs because they can handle many incidents automatically. In many cases, they can resolve issues before they have any impact on your workloads.

Personnel Needs and Education

Personnel is the most significant cost difference between managed and self-hosted Kubernetes. To properly manage self-hosted clusters, you need at least one dedicated Kubernetes expert. For larger deployments, you need teams of 3-5 engineers to provide round-the-clock coverage. Considering that Kubernetes experts earn $120,000-180,000 a year, these staffing costs greatly affect the overall cost calculation.

Self-hosted deployments come with additional costs for training and skill development. Your team will need to constantly update their knowledge of Kubernetes through formal training, attending conferences, and setting aside time specifically for learning. These investments are necessary for your team to be able to effectively manage the ever-changing Kubernetes technologies, but they also add significant costs that you wouldn’t have with managed services.

Comparing the Total Cost: A Three-Year Projection for a 10-Node Cluster

When evaluating the total cost of a 10-node cluster over three years, it’s essential to consider various components, including infrastructure, software, and potential security measures like a firewall to protect against cyber threats.

Managed Kubernetes: $75,600 ($2,100/month for 36 months)
Self-Hosted Kubernetes: $615,600 ($17,100/month for 36 months)

When you factor in the infrastructure costs of $1,700 a month and the allocation of a 3-person SRE team, which is only a partial cost of $15,400 a month, you get the total cost of a self-hosted solution.

What’s the Industry Doing? What Are Most Businesses Opting For?

Since its inception, the Kubernetes landscape has changed dramatically, with distinct trends emerging in the patterns of adoption. Understanding these trends can provide a valuable framework for your own decision-making process.

Patterns in Enterprise Adoption

More and more large enterprises are leaning towards managed Kubernetes for new deployments, though some legacy self-hosted clusters are still being maintained. According to Dynatrace’s Kubernetes in the Wild report for 2025 managed Kubernetes adoption had grown to 64% by 2024. This is a significant increase from 45% in 2022. This shift reflects the growing recognition of the operational efficiencies and reliability benefits of managed services.

Businesses with intricate needs are increasingly adopting hybrid methods. Numerous companies keep managed clusters for regular workloads but use self-hosted Kubernetes for applications that have unique compliance, performance, or integration requirements with on-premises systems. This targeted approach enables teams to fine-tune the management model based on distinct workload traits.

Preferences of Startups

Startups and companies in the growth stage show a strong preference for managed Kubernetes services. These organizations, which often have limited engineering resources and are focused on developing their product as quickly as possible, find it beneficial to also outsource the management of their infrastructure to providers that specialize in this area. The pricing is predictable, and the operational burden is reduced, allowing smaller teams to take advantage of the capabilities of Kubernetes that would otherwise require the services of dedicated platform engineering personnel.

As startups grow, they often prefer to stick with managed services. Many companies that start with managed services stick with them as they grow, finding that the benefits of efficiency outweigh the direct cost premiums at scale. The ability to focus engineering resources on core product development rather than managing infrastructure provides strategic benefits that go beyond pure cost calculations.

Picking the Best Solution for Your Team

Choosing between managed and self-hosted Kubernetes necessitates a thoughtful analysis of your company’s unique situation. The best decision relies on your team’s skills, workload needs, budget limitations, and expansion plans.

Assessing the Size and Expertise of Your Team

Before you make a decision, you should honestly evaluate the level of Kubernetes expertise within your team. If your organization doesn’t have engineers who are deeply familiar with Kubernetes, managed services can provide a fast track to production readiness. Even if your staff is experienced, you should consider whether it’s better for them to manage infrastructure or to focus on higher-value development activities.

Managed Kubernetes is usually the best choice for teams with less than 20 engineers. This allows them to concentrate their limited resources on developing applications instead of managing infrastructure. Larger organizations with dedicated platform teams might find self-hosted Kubernetes to be a viable option. However, they should still consider the opportunity cost of assigning specialized talent to manage infrastructure.

Checklist for Workload Requirements

Each workload has its own infrastructure requirements, and this can impact how you deploy Kubernetes. If your applications have specific networking, storage, or security needs, you might find that self-hosted Kubernetes allows for more customization. On the other hand, standard web applications and microservices usually run just as well on managed services, and they often require much less operational overhead.

• Do your applications require specialized kernel settings or host-level access?
• Are there specific networking plugins or configurations your workloads require?
• Do you have unique security or compliance requirements that demand custom configurations?
• Are your applications sensitive to specific resource allocation or scheduling policies?
• Do you need integration with on-premises systems or specialized hardware?

If you answered yes to multiple questions above, self-hosted Kubernetes might offer advantages for your specific workloads. However, many managed services now support customization options that can accommodate specialized requirements without full self-management.

Your workloads’ performance features also factor into this decision. Applications with predictable resource needs usually perform well on managed services, while those with highly variable or unpredictable demand patterns may benefit from the detailed control provided by self-hosted deployments.

Another important factor to consider in this comparison is regulatory compliance. Most managed services provide compliance certifications for popular standards such as SOC 2, PCI-DSS, and HIPAA. However, organizations with unique compliance requirements may require the extra customization that self-hosted Kubernetes can provide.

Cost Considerations

When weighing the options, it’s important to consider both direct and indirect costs. Managed services come with clear-cut costs, but the total cost of self-hosted Kubernetes includes the cost of infrastructure, staff, training, and opportunity costs. For many businesses, especially those with smaller deployments, managed services tend to have a lower total cost when all these factors are taken into account.

When considering the impact on your budget, you should also consider the risk profile of each option. Self-hosted Kubernetes carries a higher risk of unexpected costs from incidents, scaling challenges, or staffing changes. Managed services provide greater cost predictability, with clearly defined fees that scale linearly with your deployment size.

How Your Projected Growth Affects Your Decision

How much you expect your company to grow should play a role in your Kubernetes strategy. Companies that expect to scale quickly often find that managed services are the most beneficial, as they can handle this growth without adding a lot of complexity or needing to hire more staff. Being able to create new clusters quickly and manage them in a consistent way becomes more and more important as you expand your deployment.

Comparing the Complexity of Growth

Managed Kubernetes: The complexity increases in a straight line with the size of the deployment
Self-Hosted Kubernetes: The complexity increases exponentially once you pass certain thresholds

Think about how your management strategy could change over time. A lot of businesses start with managed services to speed up the initial deployment, then selectively put in place self-hosted clusters for certain workloads as their know-how and needs mature. This stepped approach lets teams gradually build up their Kubernetes skills while keeping operational efficiency.

Where you deploy also affects this choice. Companies that need to deploy in multiple regions often find that managed services make global deployment easier, thanks to consistent management interfaces and built-in multi-region features. To achieve the same global distribution with self-hosted Kubernetes, you’ll need to put in a lot more engineering work.

Hybrid Approaches: Reaping the Benefits of Both Models

The decision to use managed or self-hosted Kubernetes isn’t always black and white. A lot of companies utilize hybrid strategies that take advantage of the benefits of both models for various workloads or environments. These hybrid methods can provide more flexibility and optimization than using just one model for all deployments.

Strategies for Multi-Cloud Kubernetes

It’s become more and more common for organizations to use multi-cloud Kubernetes deployments. They do this to take advantage of specific capabilities, optimize costs, or ensure resilience by running clusters across multiple providers. These deployments often involve managed services from different providers. Each provider is chosen for their specific strengths in certain regions or for certain types of workloads.

Multi-cloud Kubernetes management has been made easier with tools like Rancher, Anthos, and Terraform. These tools provide consistent interfaces across environments and automate deployment and configuration. This allows teams to implement standardized policies and practices regardless of the underlying infrastructure, simplifying hybrid approaches.

Beginning with Managed and Transitioning Later

It’s common for companies to take an evolutionary approach, starting with fully managed Kubernetes and selectively moving specific workloads to self-hosted clusters as their needs and skills develop. This strategy lets teams slowly build their Kubernetes knowledge while keeping operations efficient during the learning curve.

Confidently Choose Your Kubernetes Solution

The decision to use managed or self-hosted Kubernetes is a significant one that will impact your team’s productivity, operational efficiency, and technical capabilities. By taking into account your team’s expertise, workload requirements, budget constraints, and growth projections, you can choose the solution that best fits your organization’s needs and goals. Regardless of whether you choose the ease of use of managed services or the total control of self-hosted Kubernetes, implementing container orchestration effectively will set your team up for success in the current cloud-native environment. Gcore Managed Kubernetes is a great option for teams that want to use Kubernetes without the operational complexity.

Common Questions

Below are some of the most frequently asked questions when deciding between a managed or self-hosted Kubernetes setup:

What level of DevOps knowledge is required to manage self-hosted Kubernetes?

Managing self-hosted Kubernetes effectively requires a high level of DevOps knowledge in several areas. Your team should be proficient in Linux systems administration, networking (including topics such as overlay networks, load balancing, and network policies), principles of distributed systems, and infrastructure automation. In addition, you need specific knowledge of Kubernetes, including understanding its architecture, troubleshooting, and familiarity with the Kubernetes API and CLI tools.

Most companies that have successfully adopted self-hosted Kubernetes usually have at least one team member who has 2-3 years of hands-on experience with Kubernetes. This person is often supported by engineers who have skills in areas like networking, security, and automation. If your team does not have this baseline level of expertise, the learning curve for self-hosted Kubernetes could significantly affect your operational efficiency and the reliability of your applications.

Is it possible to switch from managed to self-hosted Kubernetes at a later date?

Indeed, as your needs and skill set grow, you can transition from a managed to a self-hosted Kubernetes setup. The standardized Kubernetes API simplifies the process of migrating workloads, especially if you haven’t used any provider-specific features in your setup. Migration usually involves exporting resources from your managed cluster, setting up a new self-hosted cluster, and re-deploying your workloads with minimal changes to the application settings.

Which managed Kubernetes provider has the most robust security features?

Most of the big-name managed Kubernetes providers have robust security capabilities, each with its own unique strengths. GKE stands out with strong defaults, automatic node hardening, binary authorization, and integrated vulnerability scanning. EKS shines with its integration with AWS security services like IAM and KMS. AKS has a tight integration with Azure Security Center and Azure Policy. Gcore Managed Kubernetes has comprehensive network security features, integrated RBAC, and automated security updates. The “best” provider really depends on what your specific security needs are and what your existing cloud footprint looks like.

What are the differences in upgrade processes between managed and self-hosted solutions?

Managed Kubernetes services usually provide an easier upgrade process, including automated testing, staged rollouts, and one-click approvals. The provider takes care of control plane upgrades automatically or with minimal interaction, while node upgrades typically need explicit approval but use standardized, tested procedures. On the other hand, self-hosted Kubernetes upgrades need your team to carefully plan and execute, including compatibility testing, backup procedures, and potentially complex upgrade sequences across multiple components.

What is the smallest team size that can effectively manage self-hosted Kubernetes?

When it comes to production environments, you typically need at least three engineers who are experts in Kubernetes to maintain self-hosted clusters with sufficient coverage and redundancy. This team size allows for 24/7 on-call rotations, the sharing of knowledge, and areas of specialized focus while keeping workloads manageable. Smaller teams can manage self-hosted Kubernetes for development or non-critical environments, but when it comes to production deployments that need to be reliable, you generally need this minimum level of staffing.

The makeup of the team is just as important as its size. To manage Kubernetes effectively, you need a variety of skills, including infrastructure management, networking, security, and application deployment. Your team should be made up of engineers with different specialties so you can cover all aspects of Kubernetes operations.

Who’s Responsible for What in Kubernetes Management?

Understanding the roles and responsibilities in Kubernetes management is crucial for any DevOps team. To gain insights into industry trends and best practices, attending events like KubeCon Europe 2025 can be highly beneficial.

Managed Kubernetes: The provider takes care of the control plane, infrastructure, component lifecycle, and core security
Self-Hosted Kubernetes: Your team has to handle all components including the control plane, etcd, networking, and infrastructure

When assessing whether your team is prepared for self-hosted Kubernetes, it’s important to not only consider the current capabilities of your team, but also your ability to maintain this expertise through changes in staff. Due to the specialized nature of Kubernetes skills, knowledge transfer and documentation are particularly important for self-hosted deployments.

In the end, whether you choose managed or self-hosted Kubernetes should be in line with your overall tech strategy, taking into account both your immediate needs and long-term goals. By tailoring your management approach to your organization’s unique situation, you can make the most of Kubernetes while also maximizing your operational efficiency and engineering focus.