Critical Elements Of CAF & Cloud Impact on Programming Languages

Objectives: The objective of this article is to detail about conceptual view on “Cloud Adoption Framework” along with cloud impact on software development programming languages following scope of AI & ChatGPT. This article provides initial guidance to architects or automation team to setup cloud virtual environment while keeping below pointers in mind using any automation tool they would like to use.

Target Audience: Enterprise\Solution\Technical & Business Architect & Software Developers

Prerequisites:

Following assumptions have been made:

1.?????? Audiences have read through major cloud services provider’s cloud adoption framework document available on their portal for Azure, AWS and GCP.

2.?????? Audiences have been aware of software programming languages availability in IT Industry and growth further observed.

Conceptual view on Cloud Adoption Framework

??? About Cloud Adoption Framework

????? “Cloud Adoption Framework” is a guiding set of principles in terms of business as well as technical aspects and has been central part of cloud implementation, from the inception of idea of IT Industry journey from data- center towards cloud. This framework helps in cloud adoption in structured, organized hosting platform for Infrastructure\Platform services as well as business application, secured with zero trust tolerance, robust identity management services, and cloud management cum integration services. Such framework is provided by almost all major as well as open-source cloud services providers. This is required as almost all services offering and management from virtual services and heterogenous Infrastructure services, require availability of services in a structured and organized manner which could be managed by a programming language which handles environment variables in better ways.

Following is sample reference diagram while summarizing the CAF from all major CSP(cloud services providers) for critical components of "Cloud Adoption Framework"

Summary of core components: -

Group of hosting services layers (e.g. Infrastructure & Platform services) this comprises identity, connectivity, platform services, and application hosting-based landing zones services are structured in CAF. Connectivity services enable connectivity inside primary sites in production as well as disaster recovery sites.

Connectivity services enables connectivity between primary and secondary sites using enterprise services\tooling service. Connectivity services at each site, further enable connectivity among platform services as well. Enterprise may use existing WAN services for connectivity services as well to keep failover connectivity means. Multiple hosting services possibly be designed on subscription\accounts models or applications or departments units or business units as per specific requirement, however suitable options chosen based on business requirements. Designing of security aspects specially from connectivity as well as platform services are configured using approved security zones definitions from EAB (e.g. Enterprise Architecture Board) to ensure zero trust security controls are in place. Basis application requirement for connectivity even application tiers layer-based connectivity's are in place, for example application or data services. Same can be infer from above two diagrams of architecture overview along with security zones placement for network traffic controls measures to ensure zero trust security model in place.

Identity services enable authentication and authorization, same gets consumed basis application functionality. This service may be used as it is or may be consumed with custom solution as well. Cloud service provider offers identity solution along with its other IaaS\PaaS\SaaS services. Application requires dependencies on just internet may use cloud native identity services or it may setup new identity services using Microsoft active directory services or extend existing Microsoft active directive services in hybrid services availability model.

Management or Platform services enable hosting of infrastructure and platform services which will be consumed by either platform services or landing zones-based application services as per its business requirements. This single placeholder hosts all infrastructure as well as platform services in single or grouped subscriptions or accounts in any of the cloud services modelling options. If security tooling services are third party of nature then same should be setup under platform services to ensure grouping of similar nature services from one location.

Details of drivers for different scenarios: -

Following are details of drivers of scenarios in which CAF (cloud adoption framework) could be considered to be used: -

1. Industry type & size: Implementation of CAF with all recommended number of subscriptions or accounts requires a suitability assessment as it matters a lot when cloud services consumption bill touches high as cloud is driven by service size or length along with its limitations clubbed with costing. So, an organization size if not enterprise size, then it doesn't make any sense to go for full recommendation-based CAF implementations and wherever required and approval from security department is available, then it is good to go with merger of subscriptions either from platform services layers or landing zone services layer.
2. Security zones setup: Security requirement from industry types is different when several cloud services providers are certified by all major security certificate providing authorities (e.g. SOC, ISO, HIPPA, PCI DSS & FedRAMP to name few), now a days compared to phase when cloud services model just had hit IT Industry. For example, banking domain might have different security zones, & environment hardening requirement from rest of other industry types like e-commerce or retail. Ideally security zones requirements must be assessed and decided before considering cloud network topology as this will drive cloud network traffic request flow, which will ensure alignment of cloud design with security zones requirement for overall organization.
3. Cloud Native services setup: Every applications service requires compatible Infrastructure as well as platform services to function properly. Migrating application or services from on-prem or cloud, to cloud requires assessment on compatibility and suitability against target environment. Driven by countries different data security rule as per varying local government security model, designing cloud solution must have considerations on whether to keep dependencies on specific CSP (cloud services provider) native tooling\services or not. If same is not considered due to unknown reasons if migration is required, then looking for suitable replacement solution to support application services might appear challenging tasks from technology stack as well as cost, not only on technology, however from effort\engagement on application services compatibility and suitability for migrations.
4. Application requirement: Requirement of application must be met by cloud adoption framework-based availability of Infrastructure as well as platform services whilst alignment with application tech stack requirements, along with application authentication & authorization compatible solution.?Application transaction and data security should be ensured on "at rest" as well as "in transit" following application owner data security requirements while been in alignment with overall organization's security policies.
5. Hosting services location: Application hosting location should be close to business transaction-based end users' location to ensure there is no performance related challenges on primary site. This requires CSP (e.g. cloud services provider) virtual network services hosting location must be aligned with that. Application local as well as remote high availability should be ensured with choosing suitable geography as well as regional location of CSP (e.g. cloud services provider). This also requires in advance verification of services availability from CSP (e.g. cloud services provider) for the target location.
6. Capacity tracking: This must be assured that proper monitoring for BAU (e.g. business as usual) based monitoring as well as capacity tracking based monitoring in place at target geography as well as regional location from CSP (e.g. cloud services provider) to avoid capacity related challenges.
7. Cost management: Cost management is key for any business to flourish, and IT department must be enabled with this key goal in mind while designing the solution. This gets addressed while following cloud adoption framework which keeps grouping of applications possible for platform services as well landing zone where consumption of services in terms of cost is possible. With tracking of cost while alignment with capacity tracking, keeping OpEx and CapEx cost insight availability to enable IT department to take suitable decision on critical time as well as normal monitoring.

Cloud impact on programming language model\types

About Cloud impact on programming language model\types: -

With ideation of cloud services availability in IT Industry, IT Industry has already reached a "high level" phase of programming languages. Evolution of software programming languages up to generation 5th onwards, speaks loud about driving factors in line with IT Industry discovery of high-end processor, memory and standard storage services. Emergence of cloud along with its seriousness with its evolution in terms of IaaS, PaaS, SaaS and many more cloud services, pushed limits of virtualization, along with its interfaces for easily management of all services\tools\products. This required serious seek of automation in cloud services offerings. This further put ripple out effect on looking for automation on all degree of services along with software programming languages and intent of instructions to machine to produce product finally. This pushed all software development community to find easiest ways and means to develop a coding practice to get produce software service\product in easiest way. This is how AI and further product optimization came into being from ChapGPT by using enhancing existing coding instructions in form of "XML, Python" where extensions of dynamic elements into it.

Factors & backgrounds on software Languages progress: -

Software programming languages evolution did take place in phases and same is shown in below diagram.

Note: All programing languages have not been shown above, however one or two are mentioned for references purposes only.

As automation has been ruling IT Industry, automation's impact can be easily sensed on IT Industry, as all focus have been on discovering programming languages to move from machine-controlled orientation to human controlled orientation. And AI & ChatGPT is seen driving this discovery journey. IT Industry had utilized a lot of HTML tags in web or custom app, however driving factors gradually moved to bring dynamism along with structured model with XML, which further leads to YAML and finally Python technology-based coding practices. So, we observe there has been a serious movement phase came, to identify or converting coding practices from machine focused languages to a language which could train machine to develop code, and many other things for world, which likes to make all things easy and let machine develop software services\products in background after inferring instructions written in human read\writeable codes\language.

Below diagram shows impact of AI & ChatGPT impact on programming languages & possible future state: -

Post entering robotics era, there were sequential development of machine learning & training. Model Machine training by master machine leads to covering & analysis of big size raw data, which enhances machine model building and predictions on its correctness in major ways. This requires suitable processor speeds, memory and standard storage services too.

Observing this pattern of software programming language evolution, & emergence of strong data sensor, along with native automation feature, there is no much time left when strategist and architects ideas\designs will be read from their mind using new age data sensor directly, and entire virtual design will be implemented by machine model using automation services. Future state can be visualized as next generation phase of migration of services & BAU (e.g. "business as usual") requirements will be controlled and managed by next generation machine models. So future state requires least contribution from human specially in terms of strategy and architecture and rest will be controlled & managed by machine models. Therefore, it can be stated safely that there will be no data center which will be managed by human. Since these aspects will be managed by machine models then all human related requirements & issues will be dissolved by machines models, and no human delivery services or human business as usual support will be required in time to come, or it has been already in place for few private organizations!

Conclusion:

????????????? Conceptual view on Cloud Adoption Framework

?Above conceptual view on cloud adoption framework only illustrates basic concepts to touch, plan for implementation as per requirements from Industry type and size and no need to follow same T shirt size design for all Industry type & size. There are good number of factors need to be considered too before let automation services to build and standup a brand-new cloud environment for any organization. These factors are good for planning during architecture brain- storming phase before freezing design for implementation.

????????????? Cloud Impact on programming language model\types

?Evolution of IT Industry software programming languages have been depending majorly on processors, memory and storage capacities & specific portions of Infrastructure as well as platform components, however with enhancement on these parameters, software programming languages left no stone unturned to discovery new nimble ways to get things done with new practices of writing programming code. Same aspects moved from the era of writing code to train machine with more and more data set, to get productivity with highest success rate, along with performance stats verifications, & predictions. Not far the day will be, when entire IT Industry will get designed, implemented and managed with almost no effort from human.

References:

Azure Cloud Adoption Framework Document Link: https://learn.microsoft.com/en-us/azure/cloud-adoption-framework/

AWS Cloud Adoption Framework Document Link: https://aws.amazon.com/cloud-adoption-framework/

Google Cloud Adoption Framework Document Link: https://cloud.google.com/adoption-framework