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It is common for microservices architectures to be adopted for cloud-native applications, serverless computing, and applications using lightweight container deployment. . According to Fowler, because of the large number (when compared to monolithic application implementations) of services, decentralized continuous delivery and DevOps with holistic service monitoring are necessary to ...
The Twelve Factors [1] [2]; Factor Description I: Codebase: There should be exactly one codebase for a deployed service with the codebase being used for many deployments.
Cloud mining is the process of cryptocurrency mining utilizing a remote data center with shared processing power. [1] Cloud mining has been used by ransomware groups and scammers to launder cryptocurrency. [2] This type of cloud mining enables users to mine bitcoins or alternative cryptocurrencies without managing the hardware.
AWS App Runner is a fully managed container application service offered by Amazon Web Services (AWS). Launched in May 2021, it is designed to simplify the process of building, deploying, and scaling containerized applications for developers. [1]
Application-release automation (ARA) refers to the process of packaging and deploying an application or update of an application from development, across various environments, and ultimately to production. [1] ARA solutions must combine the capabilities of deployment automation, environment management and modeling, and release coordination. [2]
ServiceComb: microservice framework that provides a set of tools and components to make development and deployment of cloud applications easier; ServiceMix: enterprise service bus that supports JBI and OSGi; ShardingSphere: related to a database clustering system providing data sharding, distributed transactions, and distributed database management
RapidMiner uses a client/server model with the server offered either on-premises or in public or private cloud infrastructures.. RapidMiner provides data mining and machine learning procedures including: data loading and transformation (ETL), data preprocessing and visualization, predictive analytics and statistical modeling, evaluation, and deployment.
Edge computing involves running computer programs that deliver quick responses close to where requests are made.Karim Arabi, during an IEEE DAC 2014 keynote [6] and later at an MIT MTL Seminar in 2015, described edge computing as computing that occurs outside the cloud, at the network's edge, particularly for applications needing immediate data processing.