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What You Need to Know

  • Breakouts in the Serverless computing predictive analytics are Amazon Lambda, Microservices, Platform as a service. Seriously consider these technologies to gain a strategic advantage.
  • The technologies who are at the peak of their interest are Serverless Framework, Microservices, Amazon Lambda.
  • By far most employment needs are found in the Web application, Back-end, JSON technologies.
  • These 3 fields have the most active practitioners who have the specific skill set or experience: Cloud computing, Web application, Back-end.
  • GitHub, JSON, Cloud computing lead in searches for information online.
  • These three technologies are receiving the highest investments to gain clients: Cloud computing, Platform as a service, Application Performance Management.
  • These three technologies have the most active advertisers: Cloud computing, Application Performance Management, Platform as a service.
  • In patents, these three technologies have the most coverage Back-end, Cloud computing, Web application.
  • The most publications are available for Back-end, Web application, eShop.
  • Instruction and courseware availability is highest in these technologies: GMS, Oriana, Cloud computing.

The Serverless computing report evaluates technologies and applications in terms of their business impact, adoption rate and maturity level to help users decide where and when to invest.

Serverless Computing simply means that developers no longer have to think that much about them. Computing resources get used as services without having to manage around physical capacities or limits, you no longer have to deal with over/under capacity, deployments, scaling and fault tolerance, OS or language updates, metrics, and logging.

The Predictive Analytics Scores below – ordered on Forecasted Future Needs and Demand from High to Low – shows you Serverless computing’s Predictive Analysis. The link takes you to a corresponding product in The Art of Service’s store to get started.

The Art of Service’s predictive model results enable businesses to discover and apply the most profitable technologies and applications, attracting the most profitable customers, and therefore helping maximize value from their investments. The Predictive Analytics algorithm evaluates and scores technologies and applications.

The platform monitors over ten thousand technologies and applications for months, looking for interest swings in a topic, concept, technology or application, not just a count of mentions. It then makes forecasts about the velocity of the interest over time, with peaks representing it breaking into the mainstream. Data sources include trend data, employment data, employee skills data, and signals like advertising spent, advertisers, search-counts, Instruction and courseware available activity, patents, and books published.

Predictive Analytics Scores:

001099 – Amazon Lambda
000821 – Microservices
000621 – Platform as a service
000418 – RedHorse
000395 – REST API
000391 – Autoscaling
000381 – Function as a Service
000311 – JSON
000304 – Amazon Cognito
000289 – API management platform
000288 – GMS
000217 – Serverless Framework
000217 – GitHub
000194 – Python (programming language)
000167 – Java (programming language)
000152 – Deployment environment
000094 – Software framework
000083 – Web application
000078 – Virtual machines
000076 – Back-end
000040 – Application Performance Management
000024 – Debugger
000012 – Cloud computing
000008 – eShop
000005 – Oriana
000000 – vSpace
000000 – TimeOff
000000 – Service Accent
000000 – PiCloud
000000 – MasterTools
000000 – MAISi
000000 – HC3
000000 – Haskell (programming language)
000000 – EMDECS
000000 – E-Hub

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