The Manager: Apache Mesos

Estrada, Raúl Eduardo López; Ruiz, Isaac

doi:10.1007/978-1-4842-2175-4_7

Cited by 3 publications

(2 citation statements)

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“…Kafka cluster scenario: Kafka is a distributed messaging system used to collect or send high amounts of data. It is commonly used in many Big Data stacks [48] and its architecture consists of a set of brokers that store the messages, producers sending those messages and consumers that pull the data from the brokers. There are no master nodes as the brokers are coordinated by means of a Zookeeper instance.…”

Section: Service-oriented Scenarios Usedmentioning

confidence: 99%

Graph-based root cause analysis for service-oriented and microservice architectures

Brandon

Solé²,

Huélamo³

et al. 2020

Journal of Systems and Software

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Section: Service-oriented Scenarios Usedmentioning

confidence: 99%

Graph-based root cause analysis for service-oriented and microservice architectures

Brandon

Solé²,

Huélamo³

et al. 2020

Journal of Systems and Software

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“…Therefore, data streaming and transmission are necessarily required in such projects. According to the results of recent papers [12,13,14,15], it is believed that the Apache Spark and Apache Kafka could be one of the best choices in terms of the real-time data streaming and transmitting. We can use these technologies to overcome the problems between the factory and other parties, so that the data that are transmitted from the factory will be consistent with every party.…”

Section: Introductionmentioning

confidence: 99%

Improvement of Kafka Streaming Using Partition and Multi-Threading in Big Data Environment

Leang

Ean

Ryu

et al. 2019

Sensors

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The large amount of programmable logic controller (PLC) sensing data has rapidly increased in the manufacturing environment. Therefore, a large data store is necessary for Big Data platforms. In this paper, we propose a Hadoop ecosystem for the support of many features in the manufacturing industry. In this ecosystem, Apache Hadoop and HBase are used as Big Data storage and handle large scale data. In addition, Apache Kafka is used as a data streaming pipeline which contains many configurations and properties that are used to make a better-designed environment and a reliable system, such as Kafka offset and partition, which is used for program scaling purposes. Moreover, Apache Spark closely works with Kafka consumers to create a real-time processing and analysis of the data. Meanwhile, data security is applied in the data transmission phase between the Kafka producers and consumers. Public-key cryptography is performed as a security method which contains public and private keys. Additionally, the public-key is located in the Kafka producer, and the private-key is stored in the Kafka consumer. The integration of these above technologies will enhance the performance and accuracy of data storing, processing, and securing in the manufacturing environment.

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Adaptation of Classical Machine Learning Algorithms to Big Data Context: Problems and Challenges : Case Study: Hidden Markov Models Under Spark

Sassi

Ouaftouh

Anter

2019

2019 1st International Conference on Smart Systems and Data Science (ICSSD)

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The Manager: Apache Mesos

Cited by 3 publications

References 0 publications

Graph-based root cause analysis for service-oriented and microservice architectures

Graph-based root cause analysis for service-oriented and microservice architectures

Improvement of Kafka Streaming Using Partition and Multi-Threading in Big Data Environment

Adaptation of Classical Machine Learning Algorithms to Big Data Context: Problems and Challenges : Case Study: Hidden Markov Models Under Spark

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