Kubernetes (also known as k8s or “Kube”) is an open-source container orchestration platform that automates many manual processes in deploying, managing, and scaling applications on systems. Containers. In other words, you can group groups of hosts running Linux® containers, and Kubernetes helps you manage these clusters quickly and efficiently.
Kubernetes clusters can span hosts in local, public, private, or hybrid clouds. For this reason, Kubernetes is an ideal platform for hosting cloud-native applications that require rapid escalation, such as real-time data streaming via Apache Kafka.
Kubernetes was initially developed and designed by Google engineers. Google was an early contributor to Linux container technology and has spoken publicly about how everything in Google works in containers. (This is the technology behind Google’s cloud services.) Google generates over 2 billion container deployments per week, all powered by its internal platform, Borg. Borg was the predecessor of Kubernetes, and the lessons learned from Borg’s development over the years have become the primary influence behind much of Kubernetes technology. Red Hat was one of the first companies to work with Google on Kubernetes, even before its launch, and became the second major contributor to the Kubernetes project upstream. Google donated the Kubernetes project to the new Cloud Native Computing Foundation (CNCF) in 2015.
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What can you do with Kubernetes?
The primary benefit of using Kubernetes in your environment, especially if you are optimizing application development for the cloud, is to provide the platform to plan and run containers in clusters of physical or virtual machines. (VM).
More generally, it makes it possible to deploy and rely on container-based infrastructure in production environments entirely. And because Kubernetes is all about automating operational tasks, you can do many of the same things other application platforms or management systems allow, but for your containers.
Developers can also build cloud-native applications with Kubernetes as a runtime platform using Kubernetes standards. Standards are the tools a Kubernetes developer needs to build container-based applications and services.
With Kubernetes, you can:
- Orchestrate containers on multiple hosts.
- Make better use of hardware to maximize the resources needed to run business applications.
- Control and automate application deployment and updates.
- Assemble and add storage to run stateful applications.
- Dynamically resize applications in containers and their resources.
- Manage services declaratively, ensuring that distributed applications always work the way you want them.
- Verify your applications’ integrity and automatic repair with automatic positioning, automatic restart, automatic replication, and automatic escalation.
However, Kubernetes depends on other projects to fully deliver these orchestrated services. By adding more open source projects, you can take full advantage of the power of Kubernetes. These necessary parts include (among others):
- The registry, through projects such as Docker Registry.
- Networking, through projects such as OpenvSwitch and Smart Edge Routing.
- Telemetry, through projects such as Kibana, Hawkular, and Elastic.
- Security, through projects such as LDAP, SELinux, RBAC, and OAUTH with multi-tenant levels.
- Automation, with the addition of Ansible manuals for cluster installation and lifecycle management.
- Services, through a rich catalog of popular application templates.
Why is Kubernetes so popular?
As more and more companies migrate to native microservices and cloud architectures using containers, they look for robust and proven platforms. Pros are switching to Kubernetes for four main reasons:
- Kubernetes helps you progress faster. In effect, Kubernetes allows you to provide a Self-Service as a Service (PaaS) platform that creates a hardware-level abstraction for development teams. Your development teams can order the resources they need quickly and efficiently. If they need more resources to handle an additional load, they can get it just as quickly, because all the resources come from an infrastructure shared by all their teams.
You no longer have to fill out forms to request new machines to run your application. It would help if you provisioned, get started, and leverage tools built around Kubernetes to automate packaging, deployment, and testing, like Helm (below).
- Kubernetes is cheap. Kubernetes and containers make much better use of resources than hypervisors and VMs; since containers are very light, they require less CPU and memory resources to function.
- Kubernetes is cloud independent. Kubernetes works on Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP), and you can also run it locally. You can move workloads without redesigning your applications or completely redesigning your infrastructure, allowing you to standardize on one platform and avoid trapping vendors.
Companies like Kublr, Cloud Foundry, and Rancher provide tools to help you deploy and manage your Kubernetes cluster on-premise or at any cloud provider, you choose.
- The cloud service providers will manage Kubernetes for you. As stated earlier, Kubernetes is currently the exact standard for container orchestration tools. So it’s no surprise that major cloud providers offer a lot of Kubernetes as a service. Amazon EKS, Google Cloud Kubernetes Engine, Azure Kubernetes Service (AKS), Red Hat Openshift. IBM Cloud Kubernetes Service provides comprehensive management of the Kubernetes platform, so you can focus on what matters most to you: shipping applications that meet your needs.
So, how does Kubernetes work?
The main component of Kubernetes is the cluster. A cluster comprises many virtual or physical machines, each of which plays a specialized role as a master or node. Each node hosts groups of one or more containers (which contain its applications), and the master communicates with the nodes to know when to create or destroy the containers. At the same time, it tells nodes how to redirect traffic based on new container alignments.
The Kubernetes master
The Kubernetes master is the access point (or control plane) from which administrators and other users interact with the cluster to manage container scheduling and deployment. A group will always have at least one master but may have more depending on the cluster replication model.
The master stores status and configuration data for the entire cluster, a distributed and persistent key-value data store. Each node has access, and through it, the nodes learn to maintain the configurations of the containers they run. You can run, etcd, on the Kubernetes master or in standalone configurations.
The masters communicate with the rest of the cluster through the Kube-Episerver, the main access point to the control plane. For example, the Kube-Episerver ensures that the settings in etcd match the containers’ settings in the cluster.
Kube-controller-manager manages the control loops that tend cluster status through the Kubernetes API server. Deployments, replicas, and nodes have controls collected by this service. For example, the node controller is responsible for registering a node and monitoring its health throughout its life cycle.
The workloads of the node in the cluster are tracked and managed by the Kube-scheduler. This service follows the capacity and resources of nodes and assigns work to nodes based on their availability.
Cloud Controller Manager is a service that runs on Kubernetes and helps you stay “cloud independent.” Cloud Controller Manager serves as the abstraction layer between a cloud provider’s APIs and tools (for example, storage volumes or load balancers) and their representative counterparts in Kubernetes.
All nodes in a Kubernetes cluster must be configured with a container runtime environment, Docker. The container runtime starts and manages containers as they are deployed to cluster nodes by Kubernetes. Your applications (web server, database, API server, etc.) run inside containers.
Each Kubernetes node runs an agent process called kubelet, which is responsible for managing the state of the node: starting, stopping, and maintaining the application containers according to the control plan instructions. The kubelet collects performance and health information from the node, pods, and containers it runs and shares this information with the control plan to help you make planning decisions.
Kube-proxy is a network proxy that runs on cluster nodes. It also acts as a load balancer for services running on a node.
The primary programming unit is a pod, consisting of one or more containers that are guaranteed to be co-located on the host machine and can share resources. Each pod is assigned a unique IP address within the cluster, allowing the application to use the ports without conflicts.
A pod can define one or more volumes, such as a local or network drive, and expose them to pod containers, allowing different containers to share storage space. For example, works can be used when one container unloads its content, and another empties it elsewhere.
Since the containers within pods are often ephemeral, Kubernetes offers a type of load balancer called a service to make it easier to send requests to a pod group. A service targets a logical set of pods selected by labels (explained below). By default, the benefits are accessible only from the cluster, but you can also enable public access to them if you want them to receive requests from outside the cluster.
Distributions and replicas
A distribution is a YAML object that defines the pods and the number of container instances, called replicas, for each pod. Set the number of models you want to run on the cluster using a ReplicaSet, which is part of the deployment object. For example, if a node running a pod dies, the replica set will ensure that another pod is scheduled on another available node.
A DaemonSet deploys and runs a specific daemon (in a pod) on specified nodes. They are often used for pod maintenance or maintenance. A set of daemons, for example, is how New Relic Infrastructure gets the infrastructure agent deployed to all nodes in a cluster.
Namespaces allow you to create virtual clusters on a physical cluster. Namespaces should be used in environments with many users spread across multiple teams or projects. They allocate resource quotas and logically isolate cluster resources.
Labels are key / value pairs that you can assign to pods and other objects in Kubernetes. Tags allow Kubernetes operators to organize and select a subset of objects. For example, when monitoring Kubernetes objects, labels will enable you to detail the most interesting information quickly.
Stateful pools and persistent storage volumes
StatefulSets provide the ability to assign unique IDs to pods in case you need to move pods to other nodes, maintain the network between pods, or keep data between them. Similarly, persistent storage volumes provide storage resources for a cluster that pods can request access to during deployment.
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Kubernetes provides this mechanism for discovering DNS services between pods. This DNS server works in addition to any other DNS servers you can use in your infrastructure.
If you have a logging tool, you can integrate it with Kubernetes to extract and archive application and system logs from a cluster, written to standard output and standard error. If you want to use cluster-level logging, it is essential to note that Kubernetes does not provide native record storage; you need to provide your own log archiving solution.
Helm: Kubernetes application management
Helm is an application package management record for Kubernetes maintained by the CNCF. Helm “graphics” features the pre-configured software application that you can download and deploy in your Kubernetes environment. According to a 2018 CNCF survey, 68% of respondents said Helm is the package management tool of choice for Kubernetes applications. Helm graphs can help DevOps teams become familiar with application management in Kubernetes; allows them to leverage existing graphics to share, edit, and deploy in their development and production environments.
Kubernetes and Istio: a popular association
In a microservices architecture such as those running on Kubernetes, a service mesh is an infrastructure layer that allows service instances to communicate with each other. Service Fabric also enables you to configure how service instances perform critical actions, such as service discovery, load balancing, data encryption, authentication, and authorization. Istio is a network of services, and current thinking from technology leaders like Google and IBM suggests they are becoming more and more inseparable.
The IBM Cloud team, for example, uses Istio to address the control, visibility, and security issues encountered when deploying Kubernetes at scale. More specifically, Istio helps IBM:
- Connect services and control traffic flow
- Secure interactions between microservices with flexible authorization and authentication policies
- Provides IBM with a point of control for managing production services
- See what’s happening in their services, with an adapter that sends data from Istio to New Relic, allowing you to monitor Kubernetes microservice performance data as well as application data you’re already collecting.
The challenges of adopting Kubernetes
Kubernetes has come a long way in the first five years of its life. This type of rapid growth, however, also results in occasional growing pains. Here are some difficulties in adopting Kubernetes:
- The Kubernetes technology landscape can be confusing. One of the things developers love about open source technologies, like Kubernetes, is the potential for rapid innovation. But sometimes, too much design creates confusion, especially when the Kubernetes code base moves faster than users can keep up. Add a plethora of platforms and managed service providers, and it can be difficult for new users to understand the scenario.
- Forward-thinking IT and development teams don’t always align with business priorities. When budgets are allocated to maintain the status quo, it can be difficult for teams to secure the funds to experiment with Kubernetes adoption initiatives. These experiences often consume a significant amount of team time and resources. Additionally, corporate IT teams are often risk-averse and slow to change.
- Teams always learn the skills they need to take advantage of Kubernetes. It wasn’t until a few years ago that developers and IT operations staff had to readjust their practices to adopt containers, and now they must also embrace container orchestration. Organizations looking to adopt Kubernetes should hire professionals who can code, manage operations, and understand the architecture of applications, storage, and data workflows.
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