Automated Cloud Native Consulting

The rapidly growing interest in cloud native applications means more users than ever are needing guidance on how to design and deploy their systems. The Cloud Native Computing Foundation (CNCF) has developed a landscape map that provides the most current collection of both open source and proprietary tools and services, but the breadth of options and the complex relationships between various tools and services can be quite overwhelming. Most users interested in exploring the cloud native space will need to hire an experienced consultant to guide them through the choices, but this can be both cost prohibitive and logistically challenging. Our goal is to automate this consulting process and enable users to make intelligent, informed decisions about their architecture design and then deploy the architecture for immediate use.

Project Overview

The CNCF Cloud Native Landscape interactive map is a living project to collect information about tools and services to enable cloud native development. This landscape provides the most current collection of both open source and proprietary products, currently numbering over 1000, organized in categories according to purpose and layer in the cloud native stack. The interactive image below illustrates how the six main categories of the landscape are then further divided into subcategories. Each subcategory has anywhere from half a dozen to over one hundred tool options included.

While the CNCF Cloud Native Landscape and it’s accompanying guide and trail map are excellent tools for navigating the ecosystem, the breadth of options and the complex relationships between various tools and services can be quite overwhelming. In addition, as previously noted, the CNCF project provides only objective data and does not include tool comparisons or evaluation strategies. Most users interested in exploring the cloud native space will need to hire an experienced consultant to guide them through the choices, but this can be both cost prohibitive and logistically challenging.

We recognize the need for a more self-service oriented solution and believe that sufficient data about the ecosystem exists to be able to automate the consulting process. We plan to make a use of data science and machine learning techniques to make cloud native more accessible to a wider variety of users.

We have divided this automated consulting project info four stages, beginning with tool recommendations and ending with a fully deployed system, as shown in the image below.

Related Papers

Related Links

• Tool Recommendation Web App under development