In today's fast-paced technological landscape, organizations are embracing containerized applications for their scalability and flexibility. However, managing these containers at scale can be challenging. Enter Kubernetes – an open-source container orchestration platform that revolutionizes application deployment and management. In this blog, we explore how Kubernetes empowers organizations, the best approach for deployment, and key considerations to ensure success.
Introducing Kubernetes: Empowering Organizations in the World of Containers
The adoption of containerized applications has become a game-changer for organizations seeking agility, scalability, and seamless application deployment. However, as the number of containers multiplies, so do the challenges in managing them efficiently. This is where Kubernetes comes into the spotlight, offering a powerful solution for container orchestration and management. In this blog post, we will explore how Kubernetes can empower organizations, the approach to take for successful deployment, and key considerations to watch out for.
What is Kubernetes? Kubernetes, often abbreviated as K8s, is an open-source container orchestration platform that automates the deployment, scaling, and management of containerized applications. Developed by Google, Kubernetes has rapidly gained popularity and has become the de facto standard for modern containerized environments. It allows organizations to run and manage applications consistently across various infrastructure environments, whether on-premises, in the cloud, or at the edge.
Kubernetes (often abbreviated as K8s) is an open-source container orchestration platform developed by Google. It is designed to automate the deployment, scaling, and management of containerized applications. Kubernetes enables organizations to efficiently manage and run containerized applications in a scalable and fault-tolerant manner.
Key concepts and components of Kubernetes:
1. Containerization: Kubernetes is closely associated with the concept of containers. Containers are lightweight and portable units that package an application and its dependencies, allowing it to run consistently across different environments.
2. Nodes: In a Kubernetes cluster, a node is a physical or virtual machine that runs containers. Each node is responsible for running one or more containers and has the necessary tools to communicate with the Kubernetes master.
3. Master: The master is the central control plane of the Kubernetes cluster. It manages the cluster's state and orchestrates the scheduling and deployment of applications on the nodes. The master components include the API server, controller manager, scheduler, etcd (a distributed key-value store for cluster data).
4. Pods: A pod is the smallest deployable unit in Kubernetes. It represents one or more containers that are deployed together on the same node and share the same network namespace. Pods are used to group containers that require shared resources or need to co-locate.
5. ReplicaSets and Deployments: These are higher-level abstractions that allow you to define the desired state of your application and automatically handle scaling, fault tolerance, and updates. ReplicaSets ensure a specified number of replicas (identical pods) are running at all times, while Deployments manage updates and rollbacks.
6. Services: Services enable network access to a set of pods. They provide a stable IP address and DNS name to access the pods, even if the underlying pods or nodes change.
7. Labels and Selectors: Labels are key-value pairs attached to Kubernetes objects (e.g., pods, services) to identify and organize them. Selectors are used to query and filter objects based on their labels.
8. Namespace: Kubernetes supports multiple virtual clusters within the same physical cluster, called namespaces. Namespaces are used to organize and isolate resources, making it easier to manage applications and teams within a shared Kubernetes environment.
9. ConfigMaps and Secrets: ConfigMaps are used to store configuration data, and Secrets are used to store sensitive information, such as passwords or API keys. These objects allow you to decouple configuration data from the container images, making it easier to manage and update configurations.
Kubernetes provides a powerful platform for managing containerized applications, allowing developers to focus on building applications without worrying about the underlying infrastructure complexities. It has become a standard for deploying and managing applications in cloud-native and microservices-based environments.
Kubernetes works by providing a robust set of tools and components to manage containerized applications in a distributed environment. Let's go through the high-level steps of how Kubernetes works:
1. Cluster Creation: A Kubernetes cluster is set up by configuring a group of physical or virtual machines, called nodes. These nodes form the infrastructure on which containers will run. The cluster typically consists of a master node and multiple worker nodes.
2. Master Node: The master node is the control plane of the Kubernetes cluster. It hosts several components:
o API Server: It acts as the front end for the
Kubernetes control plane. It handles requests from various tools (e.g., kubectl)
and ensures the desired state of the cluster matches the actual state.
o Scheduler: The scheduler is responsible for determining where to place newly created pods based on resource requirements, node availability, and any user-defined constraints.
o Controller Manager: This component manages various controllers that handle different aspects of the cluster, such as ReplicaSets, Deployments, and more. The controllers continuously work to bring the cluster to the desired state.
o etcd: This is a distributed key-value store that stores the cluster's configuration data and state. All components in the master node read from and write to etcd to ensure they have consistent information about the cluster.
3. Worker Nodes: The worker nodes run the actual application containers. Each node runs a set of services, such as the Kubernetes Node Agent (kubelet), which communicates with the master node and manages containers on the node.
4. Pods: A pod is the smallest deployable unit
in Kubernetes. It represents one or more containers that are scheduled to run
together on the same node. Containers within a pod share the same network
namespace, which means they can communicate with each other over localhost.
Pods are ephemeral; they can be created, destroyed, and replaced as needed.
5. ReplicaSets and Deployments: ReplicaSets and Deployments are abstractions that define the desired state of your application. ReplicaSets ensure a specified number of replicas (pods) are running at all times, while Deployments manage updates and rollbacks of the application by creating and managing ReplicaSets.
6. Services: A Kubernetes Service is an abstraction that defines a stable endpoint to access a set of pods. Services provide load balancing, allowing client applications to communicate with pods using a single, stable IP address and DNS name, even if the pods or nodes change.
7. Labels and Selectors: Labels are key-value pairs attached to Kubernetes objects (e.g., pods, services). They are used to identify and organize objects. Selectors are used to query and filter objects based on their labels.
8. ConfigMaps and Secrets: ConfigMaps and Secrets are used to store configuration data and sensitive information, respectively, decoupling them from container images and making them easier to manage and update.
9. Networking: Kubernetes handles networking between pods and nodes, ensuring that containers can communicate with each other across the cluster. The container runtime (e.g., Docker, containerd) takes care of container networking within a pod.
10. Scaling and Self-Healing: Kubernetes automatically manages to scale based on defined rules and ensures that the desired number of replicas are running. It also detects and replaces failed or unhealthy pods, ensuring the application remains available and reliable.
Kubernetes provides a powerful platform to manage containerized applications efficiently, offering automation, scalability, and fault tolerance for modern, cloud-native environments.
Kubernetes has a robust and modular architecture that follows a master-node model. The architecture is designed to provide high availability, scalability, and fault tolerance for containerized applications. Let's explore the key components and their interactions within the Kubernetes architecture:
- Master Node:
- API Server: The API server acts as the front end for all interactions with the Kubernetes cluster. It exposes the Kubernetes API, which allows users and various Kubernetes components to communicate with the cluster. The API server is responsible for accepting and processing RESTful API requests, validating them, and updating the cluster's state in etcd.
- etcd: This is a distributed key-value store that stores the entire configuration data and the state of the Kubernetes cluster. All the master components read from and write to etcd to ensure consistency and maintain the desired state.
- Scheduler: The scheduler is responsible for placing newly created pods onto available worker nodes. It considers factors such as resource requirements, node availability, and any user-defined constraints (affinity or anti-affinity rules) to make optimal scheduling decisions.
- Controller Manager: The controller manager runs several controllers, each responsible for monitoring and maintaining different aspects of the cluster's state. For example, the Replication Controller ensures the desired number of replicas are running, the Deployment Controller manages updates and rollbacks, and the Node Controller handles node-related operations.
- Worker Node:
- Kubelet: The Kubelet is the primary agent that runs on each worker node and communicates with the master node. It receives pod specifications from the API server and ensures that the containers described in those pods are running and healthy on the node. It also reports the node's health back to the master.
- Container Runtime: The container runtime is responsible for running the containers on the worker node. Kubernetes supports multiple container runtimes, such as Docker, containerd, and CRI-O.
- Kube-proxy: The kube-proxy is responsible for managing the network connectivity for pods and services on the node. It maintains network rules to forward traffic to the appropriate pods based on the services' configurations.
- Pods and Controllers:
- Pods: A pod is the smallest deployable unit in Kubernetes. It represents one or more containers that are deployed together on the same node and share the same network namespace. Pods are the basic units on which scaling, healing, and other higher-level abstractions are built.
- ReplicaSets: A ReplicaSet is responsible for ensuring a specified number of replicas (identical pods) are running at all times. It continuously monitors the current state and reconciles it with the desired state defined by the user.
- Deployments: A Deployment manages updates and rollbacks of a ReplicaSet. It allows users to define declaratively how the application state should change over time, and Kubernetes ensures the desired state is met.
- Services:
- Service: A Service is an abstraction that defines a stable endpoint to access a set of pods. It provides load balancing and ensures client applications can communicate with pods using a single, stable IP address and DNS name, even if the pods or nodes change.
- Labels and Selectors:
- Labels: Labels are key-value pairs attached to Kubernetes objects (e.g., pods, services). They are used to identify, organize, and select objects.
- Selectors: Selectors are used to query and filter objects based on their labels. They allow components like Services to discover and target specific sets of pods based on labels.
The combination of these components and their interactions forms the core architecture of Kubernetes, enabling it to manage containerized applications efficiently in a distributed and scalable manner. The modular design allows Kubernetes to be extended and customized through the use of plugins and custom resources.
How Kubernetes Empowers Organizations:
1. Scalability and Flexibility: Kubernetes enables organizations to effortlessly scale applications up or down based on demand. It ensures that the required resources are allocated dynamically, keeping applications running smoothly during periods of high traffic.
2. High Availability and Fault Tolerance: Kubernetes ensures application availability by automatically recovering from failures. It achieves high availability by distributing application components across multiple nodes, mitigating the risk of single points of failure.
3. Automated Application Management: Kubernetes automates application deployment and management processes, reducing human intervention and potential errors. It simplifies the process of deploying complex microservices-based applications.
4. Resource Efficiency: Kubernetes optimizes resource allocation, ensuring efficient utilization of CPU, memory, and storage. This leads to cost savings and improved performance.
5. Cloud-Native Adoption: Kubernetes facilitates the adoption of cloud-native practices, making it easier for organizations to migrate, scale, and manage applications in cloud environments.
Kubernetes offers numerous advantages, making it a popular choice for container orchestration and application management. However, it also has some challenges and potential disadvantages. Let's explore both sides:
Advantages of Kubernetes:
1. Container Orchestration: Kubernetes provides robust container orchestration capabilities, enabling seamless deployment, scaling, and management of containerized applications.
2. Scalability: Kubernetes allows you to scale your applications easily, both vertically (by increasing resources for a single node) and horizontally (by adding more nodes to the cluster).
3. High Availability: Kubernetes supports high availability configurations, ensuring that applications remain accessible even if some nodes or components fail.
4. Automatic Healing: Kubernetes automatically restarts or replaces containers that fail or become unhealthy, ensuring the application's reliability.
5. Declarative Configuration: Kubernetes uses a declarative approach, allowing you to define the desired state of your application and leaving the platform to handle the implementation details.
6. Self-Healing: Kubernetes continually monitors the desired state of the cluster and automatically makes adjustments to bring it back to the desired state if any discrepancies occur.
7. Resource Utilization: Kubernetes effectively manages resources, optimizing the allocation of CPU, memory, and storage for running applications.
8. Horizontal Autoscaling: Kubernetes supports automatic horizontal pod autoscaling based on CPU utilization or custom metrics, ensuring efficient resource usage.
9. Ecosystem and Community: Kubernetes has a vast and active community, offering a rich ecosystem of tools, plugins, and integrations.
10. Multi-Cloud and Hybrid Cloud Support: Kubernetes is cloud-agnostic and works across various cloud providers, making it easier to build multi-cloud and hybrid cloud setups.
Disadvantages of Kubernetes:
1. Complexity: Kubernetes has a steep learning curve and can be complex to set up and manage, especially for small-scale projects or teams without prior containerization experience.
2. Resource Intensive: Running Kubernetes requires a certain level of resources and infrastructure, which might not be feasible for small applications or low-resource environments.
3. Cluster Networking: Setting up and managing networking in a Kubernetes cluster can be challenging, especially in complex network environments.
4. Security Concerns: Kubernetes clusters require proper security measures to prevent unauthorized access and potential vulnerabilities.
5. Version Compatibility: Upgrading Kubernetes versions can be challenging, especially when custom resources and plugins are involved.
6. Debugging and Troubleshooting: Troubleshooting issues in a Kubernetes cluster can be time-consuming and requires a deep understanding of the platform's architecture.
7. Vendor Lock-In: While Kubernetes itself is open-source, some cloud providers offer managed Kubernetes services that might lead to vendor lock-in.
8. Persistent Storage: Configuring and managing persistent storage for applications can be complex, particularly in dynamic environments.
Despite these disadvantages, Kubernetes remains a powerful and widely adopted solution for managing containerized applications in production environments. Proper planning, training, and expertise can help mitigate many of the challenges associated with using Kubernetes effectively.
Approach for Successful Kubernetes Deployment:
1. Thorough Planning: Start with a detailed assessment of your organization's requirements, infrastructure, and application architecture. Develop a clear plan for the deployment, considering factors like resource capacity, networking, and security needs.
2. Proper Training and Familiarization: Kubernetes can be complex, so ensure that your team receives proper training and hands-on experience. Familiarize yourself with Kubernetes concepts, components, and best practices before diving into deployment.
3. Start Small and Iterate: Begin with a small-scale deployment or a proof-of-concept to gain confidence in Kubernetes. Iterate and learn from the initial experience before scaling to larger environments.
4. Leverage Managed Services: If your organization lacks the expertise or resources to manage Kubernetes on its own, consider using managed Kubernetes services offered by cloud providers. These services handle the underlying infrastructure, allowing you to focus on application deployment and management.
Setting up a Kubernetes cluster requires installing and configuring various components, which can be a complex task. To simplify this process, there are several products and tools available that help you set up and manage Kubernetes clusters more easily. Here are some popular ones:
- Minikube:
- Minikube is a lightweight and easy-to-use tool that allows you to run a single-node Kubernetes cluster on your local machine. It is primarily intended for local development and testing. Minikube sets up a virtual machine with the Kubernetes components, enabling you to experiment with Kubernetes without the need for a full-fledged cluster.
- kubeadm:
- Kubeadm is a command-line tool provided by Kubernetes itself to bootstrap and manage a minimal and conformant Kubernetes cluster. It is a part of the Kubernetes project and helps simplify the process of creating a cluster by handling most of the complexity of setting up the control plane components.
- kops (Kubernetes Operations):
- Kops is a popular command-line tool used to create, upgrade, and manage Kubernetes clusters on cloud infrastructure providers such as AWS, GCP, and Azure. It automates the process of provisioning the required cloud resources and configuring the Kubernetes components.
- k3s:
- k3s is a lightweight and easy-to-install Kubernetes distribution designed for resource-constrained environments or edge computing scenarios. It is a fully compliant Kubernetes distribution but with a reduced memory footprint and simpler installation compared to standard Kubernetes.
- k3d (k3s in Docker):
- k3d is a tool that allows you to run k3s clusters using Docker containers. It simplifies the process of creating multiple lightweight Kubernetes clusters on your local machine for testing and development purposes.
- Rancher:
- Rancher is an open-source platform that provides a complete management interface for Kubernetes. It simplifies the deployment and management of Kubernetes clusters and offers additional features like cluster provisioning, monitoring, logging, and advanced security features.
- OpenShift:
- OpenShift is a Kubernetes distribution with added features and tools for enterprise use cases. It includes features like source-to-image (S2I) builds, built-in CI/CD capabilities, advanced security features, and developer-friendly interfaces.
- AKS (Azure Kubernetes Service), EKS (Amazon Elastic Kubernetes Service), GKE (Google Kubernetes Engine):
- These are managed Kubernetes services provided by cloud providers. They offer fully managed Kubernetes clusters, where the cloud provider handles the control plane, updates, and scaling, while users manage their applications and worker nodes.
- Kubermatic Kubernetes Platform (KKP):
- Kubermatic Kubernetes Platform is an enterprise-grade solution for deploying and managing Kubernetes clusters across different cloud providers, data centers, or edge locations. It provides a unified interface for managing multiple clusters and comes with advanced features like self-service provisioning, multi-tenancy, and RBAC.
Each of these products provides different features and capabilities to set up and manage Kubernetes clusters. The choice of which one to use depends on factors like your use case, infrastructure, and the level of control and customization you require.
Let's compare the products mentioned earlier based on several factors to help you make an informed decision:
- Ease of Setup and Use:
- Minikube, k3s, and k3d are designed for easy local setups and are straightforward to install and use.
- kubeadm requires more manual configuration but provides greater flexibility and control for cluster customization.
- Kops, Rancher, OpenShift, AKS, EKS, and GKE are more focused on production-ready, cloud-based, or enterprise setups, requiring more initial configuration and management.
- Resource Footprint:
- Minikube and k3d have smaller resource footprints as they run lightweight clusters on your local machine using containers.
- k3s is also designed with a reduced memory footprint, making it suitable for resource-constrained environments or edge computing.
- kubeadm, Kops, Rancher, OpenShift, AKS, EKS, and GKE require more resources due to their full-featured Kubernetes distributions.
- Deployment Flexibility:
- Minikube, kubeadm, k3s, and k3d allow more flexibility in choosing deployment environments and infrastructure.
- Kops is primarily focused on cloud environments like AWS, GCP, and Azure.
- Rancher, OpenShift, AKS, EKS, and GKE are tightly integrated with their respective cloud providers, offering a seamless deployment experience within their ecosystems.
- Features and Capabilities:
- Minikube and k3d provide basic Kubernetes functionality, suitable for local development and testing.
- k3s is fully compliant with Kubernetes but optimized for edge and resource-constrained environments.
- kubeadm, Kops, Rancher, OpenShift, AKS, EKS, and GKE offer a wide range of features, including advanced networking, monitoring, logging, CI/CD integration, and enterprise-grade security features.
- Management Interface:
- Minikube, k3s, and k3d do not provide a graphical management interface. Interaction is mostly through the command line.
- Rancher and OpenShift offer comprehensive management interfaces with additional features like multi-cluster management, app catalogs, and role-based access control (RBAC).
- AKS, EKS, and GKE provide managed Kubernetes services with built-in graphical interfaces for managing clusters and applications.
- Community and Support:
- Minikube, kubeadm, k3s, and k3d are open-source projects with active communities and documentation.
- Kops, Rancher, and OpenShift also have active communities and good support options.
- AKS, EKS, and GKE are managed services provided by their respective cloud providers, offering professional support and SLAs.
In summary, the choice of Kubernetes product depends on your specific requirements and the use case:
· If you need a simple, lightweight setup for local development, Minikube, k3s, or k3d would be suitable.
· For more control and customization in a production environment, kubeadm or Kops might be better options.
· For enterprise features and comprehensive management interfaces, Rancher, OpenShift, AKS, EKS, or GKE would be more appropriate, with the latter three being cloud-specific managed services.
Consider factors such as deployment environment, required features, resource constraints, and support options when selecting the best product for your needs.
Kubernetes is a versatile and widely adopted platform, and many organizations across various industries can leverage it in their environments. Here are some types of organizations that can benefit from using Kubernetes:
1. Technology Companies: Technology companies that develop and deploy software applications can leverage Kubernetes to manage their microservices-based architecture, scale applications, and achieve high availability.
2. Enterprises: Large enterprises can use Kubernetes to modernize their IT infrastructure, adopt cloud-native practices, and manage complex applications across multiple environments.
3. Startups and Small Businesses: Startups and small businesses can use Kubernetes to streamline their development and deployment processes, making it easier to scale their applications as they grow.
4. E-commerce Platforms: E-commerce companies can leverage Kubernetes to manage their web applications, handle high traffic loads during peak times, and ensure continuous availability.
5. Financial Institutions: Financial institutions can use Kubernetes to deploy and manage applications securely while meeting compliance and regulatory requirements.
6. Healthcare and Life Sciences: Organizations in the healthcare and life sciences sectors can use Kubernetes to manage complex data processing and analysis tasks, such as genomics, medical imaging, and electronic health records.
7. Gaming and Entertainment: Gaming and entertainment companies can use Kubernetes to manage multiplayer game servers, streaming platforms, and content delivery networks.
8. Media and Broadcasting: Media and broadcasting organizations can use Kubernetes to efficiently manage content distribution, video processing, and streaming services.
9. Education and Research: Educational institutions and research organizations can leverage Kubernetes for managing large-scale simulations, scientific computations, and data analytics.
10. Government and Public Sector: Government agencies and public sector organizations can adopt Kubernetes for their IT modernization initiatives, data-sharing platforms, and citizen-centric services.
11. Internet of Things (IoT): Companies working on IoT solutions can use Kubernetes to manage and orchestrate edge devices and IoT infrastructure.
12. DevOps and Cloud-Native Teams: Organizations embracing DevOps and cloud-native practices can benefit from Kubernetes to achieve automated deployments, continuous integration, and delivery pipelines.
In summary, Kubernetes is a powerful platform that can be applied across a wide range of industries and use cases. Its flexibility, scalability, and rich ecosystem of tools make it suitable for organizations of all sizes looking to improve application management, resource utilization, and scalability in their environments.
Deploying Kubernetes can be a complex task, but following best practices can help ensure a smooth and successful deployment. Here are some key best practices for deploying Kubernetes:
1. Plan and Design: Start with a clear plan and design for your Kubernetes deployment. Consider factors like cluster size, node capacity, networking, storage requirements, and security needs. Proper planning can help avoid issues later in the deployment process.
2. Choose the Right Platform: Select the appropriate Kubernetes distribution or managed service that suits your needs. Consider factors like ease of management, support options, and integration with your existing infrastructure.
3. High Availability: Set up your cluster in a highly available configuration to ensure continuous availability even if some components or nodes fail. Use multiple master nodes and distributed etcd clusters for resilience.
4. Networking: Choose a networking solution that suits your requirements, such as Kubernetes CNI plugins (Calico, Flannel, Weave) or cloud provider networking solutions. Ensure proper network isolation and connectivity between pods and services.
5. Security: Implement strong security measures for your cluster. Use RBAC (Role-Based Access Control) to control user access and permissions. Enable pod security policies to restrict the capabilities of pods.
6. Storage: Plan for your storage requirements. Decide on the type of storage (local, networked, cloud-based) and the storage class definitions to manage dynamic provisioning of persistent volumes.
7. Monitoring and Logging: Set up monitoring and logging solutions to gain insights into the cluster's performance, health, and application behavior. Tools like Prometheus for monitoring and ELK stack for logging are commonly used.
8. Backup and Disaster Recovery: Establish a backup and disaster recovery strategy to protect critical data and configurations. Regularly back up etcd data to ensure recoverability.
9. Namespace and Resource Quotas: Use namespaces to organize your resources and logically isolate different applications or teams. Apply resource quotas to control the resource consumption of namespaces.
10. Updates and Upgrades: Stay up to date with Kubernetes releases and security patches. Perform regular updates and upgrades in a controlled manner to avoid disruptions.
11. Automation and CI/CD: Automate cluster provisioning and application deployment using infrastructure-as-code (IaC) tools like Terraform or Kubernetes manifest files. Implement CI/CD pipelines for smooth application updates.
12. Documentation and Training: Document your deployment processes, configurations, and best practices. Provide training and knowledge sharing for your team members to ensure proper understanding and management of the Kubernetes environment.
13. Testing and Validation: Thoroughly test your deployment in staging environments before moving to production. Use testing tools like Sonobuoy to validate the conformance and performance of your cluster.
14. Community and Support: Leverage the Kubernetes community and available support channels to seek help and share experiences. Engage in discussions and forums to learn from others' experiences.
By following these best practices, you can deploy Kubernetes with confidence and create a robust, scalable, and reliable environment for managing your containerized applications effectively. Remember that each organization's requirements may vary, so tailor the deployment approach to suit your specific needs.
Key Considerations and Watch-Outs:
1. Security: Pay close attention to securing your Kubernetes cluster. Implement strong authentication, authorization, and network policies to protect against potential security breaches.
2. Monitoring and Observability: Set up monitoring and logging tools to gain insights into cluster health and application performance. Monitoring can help detect issues early and facilitate efficient troubleshooting.
3. Backup and Disaster Recovery: Have a robust backup and disaster recovery strategy in place, especially for the etcd data store, to ensure you can recover the cluster in case of failures.
4. Resource Management: Watch out for overprovisioning or underprovisioning resources in your cluster. Regularly monitor resource utilization to optimize efficiency.
5. Version Compatibility: Be cautious when upgrading Kubernetes versions, as it may lead to compatibility issues with existing applications and custom resources.
Kubernetes is a game-changing technology that empowers organizations to manage containerized applications effectively, streamline deployments, and achieve unprecedented scalability. By adopting Kubernetes, organizations can embrace cloud-native practices, ensure high availability, and future-proof their application infrastructure. However, it's essential to approach Kubernetes deployment methodically, considering the specific needs of your organization and closely monitoring key aspects like security, resource management, and observability. With careful planning and adherence to best practices, organizations can unlock the full potential of Kubernetes and revolutionize their approach to application management.
Kubernetes revolutionizes app management, enabling scalability and efficiency for organizations embracing containers.