This article aims to compare Apache Hadoop YARN and Kubernetes, two container management platforms that serve different purposes.

YARN was primarily designed for big data processing and later incorporated support for Docker containers, while Kubernetes was developed as an extension to the Docker container kernel.

This comparison will focus on resource management and security features offered by these platforms.

YARN provides global resource management and capacity queues for partitioning resources, whereas Kubernetes lacks an efficient global scheduler.

Additionally, YARN offers more comprehensive security features, including Kerberos, access control, and trusted docker images, compared to Kubernetes, which has default open security unless RBAC is defined.

Furthermore, YARN supports various distributed SQL engines such as Hive, Impala, SparkSQL, and IBM BigSQL.

YARN has gained popularity in large enterprises due to its lower security costs and availability of diverse developer toolchains like MapReduce, Hive, Pig, and Spark.

However, if outsourcing IT operations to a public cloud, Kubernetes is recommended, while for private/hybrid/multi-clouds, Apache YARN is more suitable.

Introduction and Background

Both Apache Hadoop YARN and Kubernetes are container management platforms.

YARN was originally developed for big data processing and later added support for Docker containers. It focuses on processing big data workloads and offers support for various distributed SQL engines like Hive, Impala, SparkSQL, and IBM BigSQL.

On the other hand, Kubernetes was designed as a platform for extending the Docker container kernel. It primarily deploys Docker containers.

YARN has a larger user base in large enterprises due to its lower security costs, while Kubernetes is often chosen when outsourcing IT operations to the public cloud.

In summary, both YARN and Kubernetes serve as container management platforms, but they have different focuses and are used in different contexts.

Resource Management

YARN provides global resource management and capacity queues for partitioning resources. This allows for better allocation and utilization of resources across the cluster, ensuring balanced and optimized workloads.

YARN’s global resource management enables fine-grained control over resource allocation. It ensures that different workloads do not interfere with each other by providing capacity queues. These queues allow for the partitioning of resources based on different criteria, such as user groups or application types.

On the other hand, Kubernetes lacks an effective global scheduler for partitioning resources. While it allows for multiple schedulers to run in the cluster, this can lead to instability when application demands exceed the physical system capacity. Without a central mechanism for managing and allocating resources, there is a risk of resource conflicts and inefficient resource utilization.

Security

Kubernetes security features can be enhanced through the implementation of Role-Based Access Control (RBAC), as its default settings are open.

RBAC allows administrators to define granular access controls and assign specific permissions to users or groups. This helps prevent unauthorized access and minimizes the risk of security breaches.

Additionally, RBAC provides a centralized management system for controlling access to Kubernetes resources, including pods, services, and namespaces. It allows administrators to define roles, role bindings, and service accounts, enabling fine-grained control over who can perform certain actions within the cluster.

By implementing RBAC, organizations can ensure that only authorized individuals have access to sensitive resources and maintain a secure environment for running containerized applications.