As an open source container platform, KubeSphere provides enterprises with a robust, secure and feature-rich platform, including most common functionalities needed for enterprise adopting Kubernetes, such as workload management, Service Mesh (Istio-based), DevOps projects (CI/CD), Source to Image and Binary to Image, multi-tenancy management, multi-dimensional monitoring, log query and collection, alerting and notification, service and network management, application management, infrastructure management, image registry management, application management. It also supports various open source storage and network solutions, as well as cloud storage services. Meanwhile, KubeSphere provides an easy-to-use web console to ease the learning curve and drive the adoption of Kubernetes.
The following modules elaborate the key features and benefits provided by KubeSphere container platform.
KubeSphere Installer allows you to deploy Kubernetes on your infrastructure out of box, provisioning Kubernetes cluster with high availability. It is recommended that at least three master nodes are configured behind a load balancer for production environment.
KubeSphere provides graphical interface for creating and managing Kubernetes resources, including Pods and Containers, Workloads, Secrets and ConfigMaps, Services and Ingress, Jobs and CronJobs, HPA, etc. As well as powerful observability including resources monitoring, events, logging, alerting and notification.
KubeSphere Installer provides ease of setup, installation, management and maintenance. Moreover, it supports rolling upgrades of Kubernetes clusters so that the cluster service is always available while being upgraded. Additionally, it provides the ability to roll back to previous stable version in case of failure. Also, you can add new nodes to a Kubernetes cluster in order to support more workloads by using KubeSphere Installer.
KubeSphere provides pluggable DevOps component based on popular CI/CD tools such as Jenkins, and offers automated workflow and tools including binary-to-image (B2I) and source-to-image (S2I) to get source code or binary artifacts into ready-to-run container images. The following are the detailed description of CI/CD pipeline, S2I and B2I.
Source-to-Image (S2I) is a toolkit and automated workflow for building reproducible container images from source code. S2I produces ready-to-run images by injecting source code into a container image and making the container ready to execute from source code.
S2I allows you to publish your service to Kubernetes without writing Dockerfile. You just need to provide source code repository address, and specify the target image registry. All configurations will be stored as different resources in Kubernetes. Your service will be automatically published to Kubernetes, and the image will be pushed to target registry as well.
As similar as S2I, Binary to Image (B2I) is a toolkit and automated workflow for building reproducible container images from binary (e.g. Jar, War, Binary package).
You just need to upload your application binary package, and specify the image registry to which you want to push. The rest is exactly same as S2I.
KubeSphere service mesh is composed of a set of ecosystem projects, including Istio, Envoy and Jaeger, etc. We design a unified user interface to use and manage these tools. Most features are out-of-box and have been designed from developer's perspective, which means KubeSphere can help you to reduce the learning curve since you do not need to deep dive into those tools individually.
KubeSphere service mesh provides fine-grained traffic management, observability, tracing, and service identity and security for a distributed microservice application, so the developer can focus on core business. With a service mesh management on KubeSphere, users can better track, route and optimize communications within Kubernetes for cloud native apps.
KubeSphere service mesh has the ability to visualize the connections between microservices and the topology of how they interconnect. As we know, observability is extremely useful in understanding cloud-native microservice interconnections.
Based on Jaeger, KubeSphere service mesh enables users to track how each service interacts with other services. It brings a deeper understanding about request latency, bottlenecks, serialization and parallelism via visualization.
Comprehensive and second-level precision monitoring metrics.
Support storage management, host management and monitoring, resource quota management, image registry management, authorization management.