Kubernetes streamlines the management of large-scale container deployments and plays an imperative role in managing modern and complex infrastructure. And as Gartner's report called "The CTO's Guide to Containers and Kubernetes" predicts that by 2027, more than 90% of global organisations will be running containerised applications in production, showing the growing importance of Kubernetes.
Hwowever, when you choose Kubernetes to deploy your applications, one of the first questions you’ll face is whether to use a fully managed Kubernetes service or self-managed Kubernetes setup. These two approaches for running kubernetes clusters vary in several aspects, including infrastructure management, operations and ongoing maintenance. Our latest article will help you understand the key differences between managed and self-managed Kubernetes.
A fully managed Kubernetes service is managed by a cloud provider who takes care of the entire lifecycle of Kubernetes clusters. They handle the infrastructure setup, scaling, updates, and maintenance. With managed Kubernetes, the cloud provider manages the entire lifecycle of your Kubernetes clusters, freeing you to focus solely on your applications and business goals. The provider ensures everything runs smoothly by automatically provisioning, updating, and securing the infrastructure.
The key features of fully managed Kubernetes include:
Self-Managed Kubernetes, as the name suggests. You're responsible for deploying, configuring, and managing every aspect of the infrastructure, from setting up the cluster and managing worker nodes to configuring storage, networking and updates. While this provides control, it also adds significant complexity. However, service providers typically manage the Kubernetes control plane—the brain of the cluster, while users retain control over worker nodes, scaling and some updates.
The key features of Self-Managed Kubernetes include:
Below is a detailed comparison of key differences between fully managed and self- managed Kubernetes:
|
Feature |
Fully Managed Kubernetes |
Self-Managed Kubernetes |
|
Cluster Provisioning |
Automated | Manual |
|
Scaling |
Automated | Manual |
|
Updates and Maintenance |
Automated | Manual |
|
Security |
Managed by provider |
Customisable by the user |
|
Support |
Expert support on cluster resources and app-related issues | No support |
In a fully managed Kubernetes environment, almost all operational responsibilities lie with the provider, covering everything from provisioning to security. While Self-Managed Kubernetes shifts some responsibilities like managing worker nodes and scaling to the user requiring technical expertise.
Fully managed solutions offer simplified interfaces and streamlined processes, making them ideal for teams unfamiliar with Kubernetes operations. Self-Managed Kubernetes demands hands-on management, appealing to teams with prior experience.
Fully managed Kubernetes excels at scalability. With built-in automation, clusters can scale horizontally or vertically with minimal intervention. However, Self-Managed Kubernetes often requires users to configure scaling policies manually, increasing the learning curve.
Fully managed Kubernetes excels in scenarios requiring minimal operational overhead, such as:
Kubernetes clusters optimised for AI/ML streamline scaling and resource management for compute-heavy tasks like model training and inference. Fully managed solutions allow data scientists to efficiently allocate resources, automate workflows, and easily scale their infrastructure to handle data-intensive operations. This minimises setup and maintenance overhead for faster iterations and model deployments and boosts productivity for researchers and AI teams.
Startups and small to medium-sized businesses (SMBs) often lack dedicated technical teams for managing complex infrastructure. Fully managed Kubernetes offers these companies the ability to focus on building, scaling, and deploying their applications while outsourcing infrastructure management to cloud experts. This reduces costs, minimises overhead, and ensures reliability, empowering smaller teams to stay competitive in a resource-constrained environment without deep Kubernetes expertise.
Fully managed Kubernetes provides enterprises with high availability, robust SLAs and seamless scalability- key elements required for mission-critical and large-scale applications. It supports complex workloads and ensures minimal downtime through automated failover and self-healing capabilities. With advanced monitoring tools, enterprises can monitor performance in real time, ensure secure deployments, and improve the reliability of their applications, reducing the risks associated with high-impact workloads in fast-paced business environments.
Self-Managed Kubernetes offers flexibility and cost-effectiveness, making it ideal for:
Managed Kubernetes allows DevOps teams to leverage robust orchestration tools for automating deployment, scaling, and management. It provides the flexibility to customise configurations to align with specific requirements while offloading operational complexity. DevOps teams can focus on optimising CI/CD pipelines, improving deployment speed, and ensuring operational reliability without worrying about the underlying infrastructure maintenance and updates.
Managed Kubernetes offers a cost-effective solution for teams with in-house infrastructure management capabilities. By offloading the day-to-day maintenance and scaling to a third-party provider, organisations can reduce operational overhead and infrastructure costs. This setup allows businesses to optimise resource usage, scale dynamically according to demand, and only pay for the resources they use, maximising cost efficiency while maintaining performance.
Managed Kubernetes provides an excellent solution for hybrid cloud environments, where organisations need to run workloads both on-premises and across public cloud platforms. It ensures consistent performance and seamless integration between on-premises infrastructure and cloud environments, enabling effective resource management across both. This flexibility allows businesses to maintain a unified experience while optimising workloads for cost, performance, and availability across varied environments.
Your choice between Fully Managed Kubernetes and Managed Kubernetes depends on your workload requirements. To give you a fair idea:
Our AI Supercloud offers a fully managed Kubernetes environment optimised for enterprise-grade AI workloads with:
Choosing between fully managed Kubernetes and Self-Managed Kubernetes depends on your operational expertise, workload requirements, and budget. Fully managed Kubernetes delivers simplicity and scalability, making it ideal for teams lacking operational expertise or handling mission-critical workloads. While, Self-Managed Kubernetes offers flexibility and control, catering to experienced teams seeking cost-effective solutions.
Are you an enterprise looking to deploy large-scale and mission-critical applications? The AI Supercloud could be your ideal partner. Schedule a call with our solutions engineer today to discover the best solution for your project’s budget, timeline and technologies.
Fully Managed Kubernetes handles the entire cluster lifecycle, while Self-Managed Kubernetes only takes care of the control plane, leaving users responsible for worker nodes.
The benefits of Fully Managed Kubernetes are wide including automated cluster management, scalability, enhanced security, high availability and no operational burden, so teams can focus on their applications.
Fully Managed Kubernetes is ideal for startups as it reduces the need for technical expertise and operational overhead while ensuring high availability and scalability.
Yes, Fully Managed Kubernetes is ideal for high-demand environments like AI/ML applications. It provides automated scaling, optimised resources, and a highly available infrastructure for mission-critical tasks.
Yes. We provide fully Managed Kubernetes environments optimised for AI and support custom configurations to support specific workloads/applications