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Google Kubernetes Engine VS Apache Mesos

Compare Google Kubernetes Engine VS Apache Mesos and see what are their differences

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Google Kubernetes Engine logo Google Kubernetes Engine

Google Kubernetes Engine is a powerful cluster manager and orchestration system for running your Docker containers. Set up a cluster in minutes.

Apache Mesos logo Apache Mesos

Apache Mesos abstracts resources away from machines, enabling fault-tolerant and elastic distributed systems to easily be built and run effectively.
  • Google Kubernetes Engine Landing page
    Landing page //
    2023-02-05
  • Apache Mesos Landing page
    Landing page //
    2018-09-30

Google Kubernetes Engine features and specs

  • Managed Service
    GKE is a fully managed service, which means Google takes care of tasks like provisioning, maintenance, and updates of the cluster, reducing the operational burden on users.
  • Scalability
    GKE offers robust scalability options, allowing you to easily scale your applications up or down based on demand. This is facilitated through auto-scaling features for both nodes and pods.
  • Integration with Google Cloud Services
    GKE integrates seamlessly with other Google Cloud services such as Cloud Storage, BigQuery, and more, providing a streamlined experience for leveraging multiple cloud tools.
  • Security
    GKE offers advanced security features like private clusters, and integrates with Google Cloud IAM, which allows for fine-grained access control, helping to secure your Kubernetes environment.
  • Ease of Use
    GKE's comprehensive dashboard, command-line interface, and supporting documentation make it easy to deploy, manage, and monitor Kubernetes clusters.
  • Global Reach
    With GKE, you can deploy clusters across multiple regions and zones, giving you the ability to build highly available, geographically dispersed applications.

Possible disadvantages of Google Kubernetes Engine

  • Cost
    While GKE offers extensive features, it can be more expensive compared to other Kubernetes solutions, especially when additional services and high-availability features are utilized.
  • Limited Customization
    As a managed service, GKE has some limitations in terms of customization and control over the underlying infrastructure compared to self-managed Kubernetes environments.
  • Complexity
    Despite its ease of use features, GKE still requires a certain level of expertise to efficiently manage Kubernetes clusters, which can be a steep learning curve for beginners.
  • Dependence on Google Cloud
    Using GKE ties you to the Google Cloud ecosystem, which may limit flexibility if you decide to migrate to a different cloud provider or adopt a multi-cloud strategy.
  • Resource Constraints
    Like all cloud services, GKE nodes can be subject to resource limits and quotas imposed by Google Cloud, which can impact performance if not properly managed.
  • SLA and Downtime
    While Google Cloud offers Service Level Agreements (SLAs), there is still a risk of downtime which could affect your applications. Additionally, relying on a third-party provider means issues may take time to resolve.

Apache Mesos features and specs

  • Scalability
    Apache Mesos is designed to scale to thousands of nodes, making it ideal for large-scale distributed systems.
  • Resource Isolation
    Mesos uses containerization techniques (like Docker and Mesos containers) to provide resource isolation, ensuring applications run in their own secure environments.
  • Fault Tolerance
    The framework is built with fault tolerance in mind. It continuously monitors the health of all nodes and can move tasks from failing nodes to healthy ones.
  • Multi-Framework Support
    Mesos can manage multiple types of workloads through different frameworks like Apache Spark, Apache Hadoop, and Kubernetes simultaneously on the same cluster.
  • Resource Efficient
    It provides fine-grained resource allocation, allowing multiple applications to share a single cluster, which leads to more efficient resource utilization.

Possible disadvantages of Apache Mesos

  • Steep Learning Curve
    Setting up and managing a Mesos cluster can be complex and requires a thorough understanding of the framework and its components.
  • Operational Complexity
    Mesos requires additional components like Marathon (for container orchestration) which adds to the operational overhead.
  • Maturity
    While Mesos is a robust system, it may not be as mature or feature-rich as some cloud-native solutions like Kubernetes, which have seen wider adoption.
  • Community Support
    As Mesos is somewhat overshadowed by Kubernetes, it has a smaller community and fewer third-party integrations compared to more popular orchestration tools.
  • Ecosystem Integration
    Many new-age DevOps tools and CI/CD pipelines are primarily designed with Kubernetes in mind, which might result in limited integration capabilities with Mesos.

Analysis of Google Kubernetes Engine

Overall verdict

  • Overall, many users find GKE to be a powerful and reliable platform for container orchestration, especially when leveraging other Google Cloud Platform services.

Why this product is good

  • Google Kubernetes Engine (GKE) is considered good because it is a managed environment for deploying, managing, and scaling containerized applications using Google infrastructure. It offers seamless integration with other Google Cloud services, robust cluster management, strong security features, auto-scaling capabilities, and a strong focus on performance and reliability. It also benefits from Google's expertise in Kubernetes, as Google was a primary contributor to the Kubernetes project.

Recommended for

  • Organizations adopting a microservices architecture.
  • Developers looking for a managed Kubernetes solution.
  • Teams that need seamless integration with other Google Cloud services.
  • Companies aiming to efficiently scale their applications with auto-scaling features.
  • Enterprises that require robust security features and compliance with industry standards.

Analysis of Apache Mesos

Overall verdict

  • Apache Mesos is a strong choice for organizations looking for a scalable and flexible resource management system, especially if they have diverse workloads that require efficient orchestration. However, its complexity might pose a challenge for smaller teams or use cases that do not require such extensive features.

Why this product is good

  • Apache Mesos is known for its ability to abstract the entire data center into a single pool of resources, thus simplifying resource management and allocation for distributed systems. It allows for efficient sharing of resources across different applications and offers strong support for container orchestration, microservices, and big data applications. Mesos is highly adaptable and can work with a variety of different workload types, making it suitable for diverse environments.

Recommended for

  • Large organizations with complex infrastructure needs.
  • Teams that require high scalability and flexibility.
  • Projects that involve big data frameworks like Apache Spark or Hadoop.
  • Development environments necessitating custom resource scheduling.

Google Kubernetes Engine videos

+ Add

Getting Started with Containers and Google Kubernetes Engine (Cloud Next '18)

More videos:

  • Review - Optimize cost to performance on Google Kubernetes Engine
  • Tutorial - Google Kubernetes Engine (GKE) | Coupon: UDEMYSEP20 - Kubernetes Made Easy | Kubernetes Tutorial

Apache Mesos videos

+ Add

Reactive Stream Processing Using Apache Mesos

Category Popularity

0-100% (relative to Google Kubernetes Engine and Apache Mesos)

Google Kubernetes Engine

Apache Mesos

Developer Tools
63 63%
Developer Tools
37% 37
Cloud Computing
100 100%
Cloud Computing
0% 0
Containers As A Service
0 0%
Containers As A Service
100% 100
DevOps Tools
62 62%
DevOps Tools
38% 38

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Google Kubernetes Engine and Apache Mesos

Google Kubernetes Engine Reviews

Top 12 Kubernetes Alternatives to Choose From in 2023
Google Kubernetes Engine (GKE) is a prominent choice for a Kubernetes alternative. It is provided and managed by Google Cloud, which offers fully managed Kubernetes services.
Source: humalect.com
11 Best Rancher Alternatives Multi Cluster Orchestration Platform
Google Kubernetes Engine is a CaaS (container as a service) platform that lets you easily create, resize, manage, update, upgrade, and debug container clusters. Google Kubernetes Engine, aka GKE, was the first managed Kubernetes service, and therefore, it is highly regarded in the industry.
Source: technicalustad.com
Top 10 Best Container Software in 2022
If you need a speedy creation of developer environments, working on micro services-based architecture and if you want to deploy production grade clusters then Docker and Google Kubernetes Engine would be the most suitable tools. They are very well suited for DevOps team.
Source: www.softwaretestinghelp.com
7 Best Containerization Software Solutions of 2022
If you’re looking for a managed solution to help you deploy and scale containerized apps on your virtual machines quickly, Google Kubernetes Engine is a great choice.
Source: techgumb.com

Apache Mesos Reviews

Docker Alternatives
Another Docker alternative is Apache Mesos. This tool is designed to leverage the features of modern kernels in order to carry out functions like resource isolation, prioritization, limiting & accounting. These functions are generally carried out by groups in the Linux or zones in the Solaris. What Mesos does is, it provides isolation for the Memory, I/O devices, file...
Source: www.educba.com

Social recommendations and mentions

Based on our record, Google Kubernetes Engine should be more popular than Apache Mesos. It has been mentiond 50 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Google Kubernetes Engine mentions (50)

  • Maximizing Efficiency with Dev Containers: A Developer's Guide
    In this section, we'll explore the scenario of connecting to a container that's running within a Kubernetes cluster pod. For demonstration purposes, we're using the Google Kubernetes Engine (GKE) service. - Source: dev.to / 3 months ago
  • Google Cloud Unveils A4 VMs with NVIDIA Blackwell GPUs for AI
    Integration with Google Kubernetes Engine (GKE), which supports up to 65,000 nodes per cluster, facilitating robust AI infrastructure. - Source: dev.to / 7 months ago
  • Deploy Gemini-powered LangChain applications on GKE
    In my previous post, we explored how LangChain simplifies the development of AI-powered applications. We saw how its modularity, flexibility, and extensibility make it a powerful tool for working with large language models (LLMs) like Gemini. Now, let's take it a step further and see how we can deploy and scale our LangChain applications using the robust infrastructure of Google Kubernetes Engine (GKE) and the... - Source: dev.to / 8 months ago
  • Securing Applications Using Keycloak's Helm Chart
    Kubernetes cluster: You need a running Kubernetes cluster that supports persistent volumes. You can use a local cluster, like kind or Minikube, or a cloud-based solution, like GKE%20orEKS or EKS. The cluster should expose ports 80 (HTTP) and 443 (HTTPS) for external access. Persistent storage should be configured to retain Keycloak data (e.g., user credentials, sessions) across restarts. - Source: dev.to / 10 months ago
  • Simplify development of AI-powered applications with LangChain
    In a later post, I will take a look at how you can use LangChain to connect to a local Gemma instance, all running in a Google Kubernetes Engine (GKE) cluster. - Source: dev.to / about 1 year ago
View more

Apache Mesos mentions (11)

  • Erlang's not about lightweight processes and message passing
    Erlang, OTP, and the BEAM offer much more than just behaviours. The VM is similar to a virtual kernel with supervisor, isolated processes, and distributed mode that treats multiple (physical or virtual) machines as a single pool of resources. OTP provides numerous useful modes, such as Mnesia (database) and atomic counters/ETS tables (for caching), among others. The runtime also supports bytecode hot-reloading, a... - Source: Hacker News / 6 months ago
  • Kubernetes Simplified: A Comprehensive Introduction for Beginners
    Apache Mesos, a robust cluster manager, excels at handling diverse workloads beyond just containers, offering flexibility for organizations with varying needs. - Source: dev.to / about 1 year ago
  • Containers Orchestration and Kubernetes
    Even though this article will be focused on Kubernetes I want to mention that there are multiple container orchestration platforms such as Mesos, Docker Swarm, OpenShift, Rancher, Hashicorp Nomad, etc. - Source: dev.to / over 1 year ago
  • eBPF, sidecars, and the future of the service mesh
    I worked at several Bay Area startups, mainly in NLP and machine learning roles. I was part of a company called PowerSet, which was building a natural language processing engine and was acquired by Microsoft. I then joined Twitter in its early days, around 2010, when it had about 200 employees. I started on the AI side but transitioned to infrastructure because I found it more satisfying and challenging. We were... - Source: dev.to / over 1 year ago
  • Upgrading Hundreds of Kubernetes Clusters
    When we adopted Kubernetes at Criteo, we encountered initial hurdles. In 2018, Kubernetes operators were still new, and there was internal competition from Mesos. We addressed these challenges by validating Kubernetes performance for our specific needs and building custom Chef recipes, StatefulSet hooks, and startup scripts. - Source: dev.to / over 1 year ago
View more

What are some alternatives?

When comparing Google Kubernetes Engine and Apache Mesos, you can also consider the following products

Kubernetes - Kubernetes is an open source orchestration system for Docker containers

Docker - Docker is an open platform that enables developers and system administrators to create distributed applications.

Amazon ECS - Amazon EC2 Container Service is a highly scalable, high-performance​ container management service that supports Docker containers.

Charity Engine - Charity Engine takes enormous, expensive computing jobs and chops them into 1000s of small pieces...

Amazon EKS - Amazon EKS makes it easy for you to run Kubernetes on AWS without needing to install and operate your own Kubernetes clusters.

JPPF - The open source grid computing solution.

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