Cloudify Adds ‘Cloudify Discovery’ Capability to Automate Kubernetes Multi-Cluster Discovery, Set-Up of Self-Service Environments
Cloudify has introduced “Cloudify Discovery”—a powerful new automation feature for identifying and registering Kubernetes clusters—in Cloudify, the platform for automating cloud management and orchestration.
The Cloudify platform provides infrastructure automation using Environment-as-a-Service technology to deploy and continuously manage any cloud, private data center or Kubernetes service from one central point, while enabling developers to self-service their environments.
The new Cloudify Discovery feature automates the process of identifying Kubernetes clusters and registering them as self-service DevOps environments in the Cloudify platform. Developers’ burden of manually managing multi-cluster Kubernetes environments is replaced by an automated, scalable service that can handle even the most demanding multi-cluster edge environments.
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Problem: Developers Challenged by Manual, Unscalable Multi-Cluster Management
Organizations are increasingly deploying multiple Kubernetes clusters across on-premises, cloud and edge environments. The complexity of multi-cluster use cases ranges from simple (separate clusters between development and production environments) to moderate (segregated departments within the same enterprise) to extreme (managing hundreds and potentially thousands of clusters across edge networks). According to Gartner, by 2025, multi-cluster management and security will emerge as the top challenges for organizations deploying Kubernetes applications.
Solution: Cloudify Discovery Automatically Turns Kubernetes Clusters Into Self-Service Environments
Cloudify Discovery boosts developer productivity by abstracting the developers from the underlying Kubernetes infrastructure. The Cloudify Discovery mechanism provides a generic implementation that scans a given account and looks for existing Kubernetes resources under this account. Once a Kubernetes cluster is discovered, it is registered as a self-service environment under the Cloudify environment section. Each environment includes the relevant authentication token, namespaces and other configuration properties associated with that cluster. Cloudify Discovery provides out-of-the-box discovery on all major clouds, including EKS, AKS and GCP, and is available through the Cloudify catalog service.
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“The shift from monolithic to microservices in distributed, multi-cluster Kubernetes environments is maddeningly complex from a cloud management perspective,” said Nati Shalom, founder and CTO of Cloudify. “With the new Discovery feature, Cloudify lets platform engineers make Kubernetes clusters accessible as a self-service environment. It can do this regardless of whether these clusters are running in the cloud or on-prem, and it provides a consistent layer of abstraction across different clusters such as EKS, AKS and GKE. Developers can finally deploy microservices into environments as though they were all part of a single cluster using a simple filter and tagging mechanism. Developers can also deploy the same microservices across multiple clusters through a single command. In the future, Cloudify will also support policy-based deployment which will further abstract those environments.”
Cloudify Discovery is Highly Customizable
Cloudify Discovery implementation is based on the workflow and blueprint engine of Cloudify. The Discovery workflow executes the relevant API call to find the Kubernetes cluster resources and, in turn, calls Cloudify to set the respective environments per Kubernetes cluster. This generic mechanism can be easily modified or extended to support any other resource or map any resource information that will be needed to be part of the environment.
Cloudify Discover’s deploy-on feature allows users to deploy services on the discovered environments. The deploy-on feature also provides a means to deploy the same service on multiple environments using a single command. Users can group the environments based on location, tagging and filters.
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