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Apache Mesos is a cluster manager that simplifies the complexity of running applications on a shared pool of servers.
260
entreprises
Nous disposons de données sur 260 entreprises qui utilisent Apache Mesos. Notre liste de clients Apache Mesos est disponible en téléchargement et est enrichie de spécificités essentielles de l'entreprise, y compris la classification de l'industrie, la taille de l'organisation, la localisation géographique, les tours de financement et les chiffres d'affaires, entre autres.
Entreprise | Pays | Industrie | Employés | Chiffre d'affaires |
---|---|---|---|---|
Houghton Mifflin Harcourt | États-Unis | E-Learning Providers | 6K | $1.1B |
Capital One | États-Unis | Financial Services | 56K | $36B |
![]() ServiceNow | États-Unis | Software Development | 27K | $7.6B |
Verimi GmbH | Allemagne | It Services And It Consulting | 110 | |
Verimi | Allemagne | It Services And It Consulting | 74 | |
KPMG | Canada | Accounting | 265K | $75M |
Comcentric | États-Unis | Staffing And Recruiting | 54 | $6.4M |
![]() Zuora | États-Unis | Software Development | 1.7K | $384M |
AHEAD | États-Unis | It Services And It Consulting | 2.9K | $2.1B |
Avertium | États-Unis | Computer And Network Security | 220 | $30M |
Getty Images | États-Unis | Photography | 6.1K | $900M |
Intel | États-Unis | Computer Hardware Manufacturing | 132K | $56B |
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Statistiques d'Utilisation Technologique et Part de Marché
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Il y a 10 alternatives à Apache Mesos
Apache Mesos est utilisé dans 21 pays
Questions fréquemment posées
Nos données proviennent d'offres d'emploi collectées auprès de millions d'entreprises. Nous surveillons ces offres sur les sites web des entreprises, les plateformes d'emploi et d'autres plateformes de recrutement. L'analyse des offres d'emploi constitue une méthode fiable pour comprendre les technologies utilisées par les entreprises, y compris l'utilisation de leurs outils internes.
Nous actualisons nos données quotidiennement pour vous garantir un accès à l'information la plus récente disponible. Ce processus de mise à jour fréquente assure que nos insights et notre intelligence reflètent les derniers développements et tendances au sein de l'industrie.
Apache Mesos is a powerful open-source cluster manager that provides efficient resource isolation and sharing across distributed applications or frameworks. It aims to abstract CPU, memory, storage, and other compute resources away from machines, enabling these resources to be shared across applications seamlessly. Mesos offers a highly scalable and fault-tolerant solution for managing large-scale cluster infrastructure.
Cluster Management is the category to which Apache Mesos belongs. Cluster Management involves the efficient allocation and management of computing resources across multiple machines to ensure optimal performance and resource utilization. Apache Mesos plays a crucial role in this category by offering a flexible and robust platform for deploying and managing diverse frameworks and applications in a distributed environment.
Apache Mesos was founded in 2009 by Benjamin Hindman, Matei Zaharia, and others at the University of California, Berkeley. The motivation behind the development of Mesos was to address the challenges of resource management and scalability in large-scale distributed systems. It was initially designed to improve the efficiency of data processing frameworks like Hadoop and MPI by providing a unified and abstracted view of cluster resources.
As of the latest data, Apache Mesos holds a notable market share within the Cluster Management category. With the increasing demand for scalable and efficient cluster management solutions, Mesos is poised to maintain its market presence and potentially grow in the future. Its robust features, active community support, and compatibility with various application frameworks make it a preferred choice for organizations aiming to streamline their cluster operations and enhance resource utilization.
Apache Mesos is a versatile and powerful cluster management technology utilized by companies for various reasons. With its ability to efficiently manage resources across distributed systems, Apache Mesos has become a popular choice among organizations looking to streamline their operations.
Apache Mesos offers outstanding scalability, allowing companies to easily scale their applications and services as needed. Unlike traditional solutions that may require manual intervention and complex configurations to scale, Mesos provides a flexible and automated way to expand resources seamlessly.
One of the key advantages of Apache Mesos is its resource efficiency. By dynamically sharing resources across applications and services, Mesos optimizes resource utilization, reducing wastage and overall costs. This efficient resource management sets Mesos apart from other cluster management technologies that may not offer such fine-grained control.
Apache Mesos boasts robust fault tolerance capabilities, ensuring high availability and reliability for critical workloads. Its fault tolerance mechanisms automatically handle failures and recover from errors without compromising system performance. This reliability makes Mesos a preferred choice for companies requiring resilient cluster management solutions.
Mesos excels in intelligent task scheduling, enabling companies to prioritize and allocate tasks based on specific requirements and constraints. Its advanced scheduling algorithms optimize task distribution, resulting in improved performance and reduced latency compared to conventional scheduling methods. This fine-grained control over task scheduling distinguishes Mesos as a sophisticated cluster management technology.
Another significant benefit of Apache Mesos is its seamless integration with a wide range of frameworks and tools. Companies can easily integrate Mesos into their existing infrastructure, leveraging its compatibility with various applications and services. This interoperability sets Mesos apart from other cluster management platforms that may have limited integration capabilities.
In conclusion, Apache Mesos stands out as a preferred choice for companies seeking a robust, scalable, and resource-efficient cluster management solution. Its unique features and benefits make it a valuable technology for optimizing resource utilization, enhancing fault tolerance, and streamlining task scheduling across distributed systems.
Apache Mesos is a popular choice for companies looking to streamline their cluster management processes. Several well-known companies have successfully implemented Apache Mesos to enhance their data center efficiency and reliability. Here are a few case studies showcasing how Apache Mesos has been leveraged by real companies:
Twitter: Twitter is one of the early adopters of Apache Mesos. The company uses Mesos to dynamically manage resources across thousands of servers in their data centers. Twitter started using Mesos in 2011 to improve the scalability and reliability of their microservices architecture. By leveraging Mesos, Twitter has been able to achieve better resource utilization, faster deployment times, and improved fault tolerance in their infrastructure.
Airbnb: Airbnb relies on Apache Mesos to power its data processing and analytics workflows. The company utilizes Mesos for resource isolation and allocation, allowing different teams to run diverse workloads efficiently. Airbnb began using Mesos in 2014 to address the growing complexity of its infrastructure and the need for a scalable cluster management solution. With Mesos, Airbnb has achieved higher utilization rates, reduced operational overhead, and increased flexibility in managing its data pipelines.
Apple: Apple is another prominent user of Apache Mesos for its cluster management needs. The tech giant employs Mesos to orchestrate containerized applications and services across its massive infrastructure. Apple integrated Mesos into its environment in 2016 to simplify the deployment and scaling of applications on its private cloud. By adopting Mesos, Apple has streamlined resource allocation, enhanced application performance, and optimized resource utilization across its data centers.
These case studies highlight the diverse applications of Apache Mesos in addressing the complex cluster management requirements of industry-leading companies like Twitter, Airbnb, and Apple. By embracing Mesos, these organizations have been able to unlock new levels of operational efficiency, scalability, and resilience in their IT infrastructures.
Vous pouvez accéder à une liste actualisée des entreprises utilisant Apache Mesos en visitant TheirStack.com. Notre plateforme fournit une base de données complète des entreprises utilisant diverses technologies et outils internes.
À ce jour, nous disposons de données sur 260 entreprises qui utilisent Apache Mesos.
Apache Mesos est utilisé par une large gamme d'organisations dans divers secteurs, y compris "E-Learning Providers", "Financial Services", "Software Development", "It Services And It Consulting", "It Services And It Consulting", "Accounting", "Staffing And Recruiting", "Software Development", "It Services And It Consulting", "Computer And Network Security". Pour une liste complète de tous les secteurs utilisant Apache Mesos, veuillez visiter TheirStack.com.
Certaines des entreprises qui utilisent Apache Mesos incluent Houghton Mifflin Harcourt, Capital One, ServiceNow, Verimi GmbH, Verimi, KPMG, Comcentric, Zuora, AHEAD, Avertium et bien d'autres encore. Vous pouvez trouver une liste complète des 260 entreprises qui utilisent Apache Mesos sur TheirStack.com.
Selon nos données, Apache Mesos est le plus populaire dans États-Unis (136 companies), Royaume-Uni (13 companies), France (9 companies), Inde (9 companies), Canada (7 companies), Allemagne (4 companies), Brésil (3 companies), Australie (2 companies), Irlande (2 companies), Suisse (2 companies). Toutefois, il est utilisé par des entreprises du monde entier.
Vous pouvez trouver des entreprises utilisant Apache Mesos en le recherchant sur TheirStack.com. Nous suivons les offres d'emploi de millions d'entreprises et les utilisons pour découvrir quelles technologies et outils internes elles emploient.