Ambari vs Kubernetes

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Ambari

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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.

Decisions about Ambari and Kubernetes
Simon Reymann
Senior Fullstack Developer at QUANTUSflow Software GmbH · | 30 upvotes · 9.9M views

Our whole DevOps stack consists of the following tools:

  • GitHub (incl. GitHub Pages/Markdown for Documentation, GettingStarted and HowTo's) for collaborative review and code management tool
  • Respectively Git as revision control system
  • SourceTree as Git GUI
  • Visual Studio Code as IDE
  • CircleCI for continuous integration (automatize development process)
  • Prettier / TSLint / ESLint as code linter
  • SonarQube as quality gate
  • Docker as container management (incl. Docker Compose for multi-container application management)
  • VirtualBox for operating system simulation tests
  • Kubernetes as cluster management for docker containers
  • Heroku for deploying in test environments
  • nginx as web server (preferably used as facade server in production environment)
  • SSLMate (using OpenSSL) for certificate management
  • Amazon EC2 (incl. Amazon S3) for deploying in stage (production-like) and production environments
  • PostgreSQL as preferred database system
  • Redis as preferred in-memory database/store (great for caching)

The main reason we have chosen Kubernetes over Docker Swarm is related to the following artifacts:

  • Key features: Easy and flexible installation, Clear dashboard, Great scaling operations, Monitoring is an integral part, Great load balancing concepts, Monitors the condition and ensures compensation in the event of failure.
  • Applications: An application can be deployed using a combination of pods, deployments, and services (or micro-services).
  • Functionality: Kubernetes as a complex installation and setup process, but it not as limited as Docker Swarm.
  • Monitoring: It supports multiple versions of logging and monitoring when the services are deployed within the cluster (Elasticsearch/Kibana (ELK), Heapster/Grafana, Sysdig cloud integration).
  • Scalability: All-in-one framework for distributed systems.
  • Other Benefits: Kubernetes is backed by the Cloud Native Computing Foundation (CNCF), huge community among container orchestration tools, it is an open source and modular tool that works with any OS.
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Pros of Ambari
Pros of Kubernetes
  • 2
    Ease of use
  • 164
    Leading docker container management solution
  • 128
    Simple and powerful
  • 107
    Open source
  • 76
    Backed by google
  • 58
    The right abstractions
  • 25
    Scale services
  • 20
    Replication controller
  • 11
    Permission managment
  • 9
    Supports autoscaling
  • 8
    Cheap
  • 8
    Simple
  • 6
    Self-healing
  • 5
    Promotes modern/good infrascture practice
  • 5
    Open, powerful, stable
  • 5
    Reliable
  • 5
    No cloud platform lock-in
  • 4
    Scalable
  • 4
    Quick cloud setup
  • 3
    Custom and extensibility
  • 3
    A self healing environment with rich metadata
  • 3
    Cloud Agnostic
  • 3
    Backed by Red Hat
  • 3
    Runs on azure
  • 3
    Captain of Container Ship
  • 2
    Expandable
  • 2
    Sfg
  • 2
    Everything of CaaS
  • 2
    Golang
  • 2
    Easy setup
  • 2
    Gke

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Cons of Ambari
Cons of Kubernetes
    Be the first to leave a con
    • 16
      Steep learning curve
    • 15
      Poor workflow for development
    • 8
      Orchestrates only infrastructure
    • 4
      High resource requirements for on-prem clusters
    • 2
      Too heavy for simple systems
    • 1
      Additional vendor lock-in (Docker)
    • 1
      More moving parts to secure
    • 1
      Additional Technology Overhead

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    What is Ambari?

    This project is aimed at making Hadoop management simpler by developing software for provisioning, managing, and monitoring Apache Hadoop clusters. It provides an intuitive, easy-to-use Hadoop management web UI backed by its RESTful APIs.

    What is Kubernetes?

    Kubernetes is an open source orchestration system for Docker containers. It handles scheduling onto nodes in a compute cluster and actively manages workloads to ensure that their state matches the users declared intentions.

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    Hue
    It is open source and lets regular users import their big data, query it, search it, visualize it and build dashboards on top of it, all from their browser.
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    A centralized service for maintaining configuration information, naming, providing distributed synchronization, and providing group services. All of these kinds of services are used in some form or another by distributed applications.
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