Ambari vs Kubernetes: What are the differences?

Introduction

Ambari and Kubernetes are both popular technologies used for managing and orchestrating containerized applications. While they have some similarities, there are key differences that set them apart.

1. Deployment and Scaling: One major difference between Ambari and Kubernetes is their approach to deployment and scaling. Ambari is primarily designed for managing and provisioning Hadoop clusters, making it suitable for big data applications. It provides tools and interfaces for installing, configuring, and scaling Hadoop clusters. On the other hand, Kubernetes is a general-purpose container orchestration platform that can be used for deploying and scaling any containerized application, not limited to big data.

2. Container Management: Another significant difference is the level of control and management over containers. Ambari focuses more on the management of the entire Hadoop ecosystem, including the various services and components within it. It provides a high-level view of the cluster and simplifies the management of Hadoop services. In contrast, Kubernetes is more granular in its container management approach. It provides fine-grained control over individual containers, allowing for precise resource allocation, scheduling, and networking.

3. Service Discovery and Load Balancing: Ambari provides built-in service discovery and load balancing capabilities for Hadoop clusters. It can automatically discover and register new services, and distribute client requests to the appropriate instances. Kubernetes also offers service discovery and load balancing, but it goes a step further with its advanced networking features. It provides a flexible and robust networking model, allowing for complex network configurations and traffic routing.

4. Fault Tolerance and High Availability: Ambari focuses on fault tolerance and high availability within the Hadoop ecosystem. It provides monitoring, alerting, and automatic recovery mechanisms for Hadoop services. Kubernetes, on the other hand, provides fault tolerance and high availability at the container level. It can automatically restart failed containers, reschedule pods to healthy nodes, and replicate containers for increased availability.

5. Resource Management: Ambari offers resource management for Hadoop clusters through its integration with YARN (Yet Another Resource Negotiator). It provides tools for monitoring and managing cluster resources such as CPU, memory, and disk. Kubernetes also provides resource management capabilities, but it is more generic and agnostic to the underlying resource type. It can manage resources for any containerized application, not limited to Hadoop.

6. Community and Ecosystem: Ambari has a strong community and ecosystem focused on Hadoop and big data technologies. It is tightly integrated with the Apache Hadoop stack and provides support for a wide range of Hadoop components. Kubernetes, on the other hand, has a larger and more diverse community. It is not limited to a specific technology stack and is widely adopted for a broad range of containerized applications.

In summary, Ambari is specialized for managing and provisioning Hadoop clusters, while Kubernetes is a general-purpose container orchestration platform that can be used for any containerized application. Ambari focuses on managing the Hadoop ecosystem, while Kubernetes provides more granular control over containers. Both offer service discovery and load balancing capabilities, but Kubernetes has more advanced networking features. Ambari focuses on fault tolerance and high availability within the Hadoop ecosystem, while Kubernetes provides these features at the container level. Ambari integrates tightly with the Apache Hadoop stack, while Kubernetes has a larger and more diverse community.