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Harbor
Harbor

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KubeAdvisor
KubeAdvisor

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Harbor vs KubeAdvisor: What are the differences?

What is Harbor? Manage and serve container images in a secure environment (created at VMware). Harbor is an open source cloud native registry that stores, signs, and scans container images for vulnerabilities Harbor solves common challenges by delivering trust, compliance, performance, and interoperability. It fills a gap for organ.

What is KubeAdvisor? It helps DevOps adopt best practices for Kubernetes. It helps teams adopt best practices to accelerate the adoption of Kubernetes, and optimize their existing stack, with machine learning. It scans K8s to make infrastructure and cloud-native applications reliable, resilient, and observable.

Harbor can be classified as a tool in the "Docker Registry" category, while KubeAdvisor is grouped under "Container Tools".

Some of the features offered by Harbor are:

  • Multi-tenant content signing and validation
  • Image replication between instances
  • Extensible API and graphical UI

On the other hand, KubeAdvisor provides the following key features:

  • Performance by continuously watching throttled containers/apps and recommending improvements
  • Utilization by comparing used resources with the available capacity to reallocate them based on variable workloads
  • Cost Optimization by suggesting changes at the VM level to save money in case of cloud infrastructure or identify the best configurations if you are running Kubernetes on-prem

Harbor is an open source tool with 10.8K GitHub stars and 3.01K GitHub forks. Here's a link to Harbor's open source repository on GitHub.

- No public GitHub repository available -

What is Harbor?

Harbor is an open source cloud native registry that stores, signs, and scans container images for vulnerabilities. Harbor solves common challenges by delivering trust, compliance, performance, and interoperability. It fills a gap for organ

What is KubeAdvisor?

It helps teams adopt best practices to accelerate the adoption of Kubernetes, and optimize their existing stack, with machine learning. It scans K8s to make infrastructure and cloud-native applications reliable, resilient, and observable.
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