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Executive Summary

The approach for deployment of cloud is essential as it not only impacts the current organization performance but also influences the future organizational operations. It implies that in case the deployment approach is not considered, then it might serious challenge for budget and usage in future. The programmatic approach of the cloud deployment enables transition to be reliable and smooth. The report is liable for providing scope for the cloud deployment planning and various programmatic approaches. Diverse tools are present within the market that will assist in deployment of the application and data within the cloud systematically and comparison among the tools will also be provided. Scalability is one of the critical programmatic deployment factor that enables to use it based on the demand.

Plan Scope

a. Overview

The plan will furnish information regarding the cloud strategies and deployment that is needed for application and configuration. The information regarding non-programmatic and programmatic approaches will be delivered in this plan along with kind of cloud and storage services that are needed within the deployment. Further, cloud comparison and configuration will be illustrated. Here, three kind of cloud configuration will be given within the plan that comprises puppet automate, chef automates, and opp’s stack. In this, the AWS services is the critical deployment prerequisite and the deployment strategies are based on the requirements of the cloud. The plan will furnish information regarding the data requirements and governance. The key deployment prerequisite will comprise of the information storage facility and stack layer (Chang, Lee and Hung, 2021). The different classification for the total dependence and deployment tools for the AWS services will be provided. The objective is to deliver precise insight into the cloud and tools needed for the data storage. The information regarding infrastructure will be depicted as cloud will not be deployed with the inclined infrastructure and tools.

b. Cloud configuration and deployment prerequisites

The key deployment prerequisite comprises kind of stack layer along with the information storage facility. The AWS OpsWork stack will be illustrated in detail along with the key recommendations that are needed to the deploy the program. The wide range of classification is present for the deployment of cloud tools along with the total dependence on the AWS services. The plan will be accomplished with the solid conclusion where precise information regarding the cloud and their deployment will be furnished to the IT team.

Cloud Deployment Programmatic Approaches Overview

The basic difference among non-programmatic and programmatic approach is automation. Within the programmatic approach, the program tends to take data and furnish them with the relevant data (Kritikos et al., 2017). The rationale of the programmatic approach is to attain the maximized services or applications performance with the use of orchestration and automation with the usage of the needed cloud computes in the relevant budget. In non-programmatic approach there are no relevant layers for furnishing the work and instructions depending on the unplanned steps. It is not planned and do not depend on the previous outcome for execution of the task. The programmatic approach is liable for accomplishment of the requirements for the data governance and it might deliver framework in which information collected and stored. The security and analysis are defined through the assistance of the separate protocols and program is liable for defining the instructions in which input slots will collect the data based on the user requirements. In case of cloud computing, the program is liable for taking the data control.

A programmatic approach will have secured infrastructure in which all the applications will be linked with the strict control and application security will be improvised and these requirements will be mentioned in context of diverse codes. There are different regulatory requirements that will be applied within the program functioning and design. The approach will be making use of the shift and lift methodology as inputs will be taken from the old system respective changes (Sturzinger et al., 2021). The programmatic approach will make use of the existent standards as it is the initial stage and it will include particular scale for conducting their operations. The scale will be defined either through the organizational requirements or the cloud properties. The nature of information and storage will be based on different scaling parameters.

4. Programmatic cloud deployment tools

a. Feature comparison

There are diverse cloud programmatic deployment tools that are being used by the organization for delivering their operations efficiently. Here, emphasis will be made on three tools, they are OpenWorks stacks, Chef automate, and Puppet interface. The comparison of features among these tools is illustrated below:

Basis

Stacks

Chef Automate

Puppet Enterprise

Availability

It acts as the stack for diverse layer. Thus, the availability will be based on the configuration for each layer.

In case primary server is down, the backup server will act as a stack (Eck et al., 2020).

The multi-master architecture is incorporated in this. If this goes down then there is another master for addressing the requirements.

Interface

AWS Cli is utilized for configuration and execution of stack.

It is code-driven approach that furnishes inclined control of configurations and flexibility. The knife tool can be utilised for eliminating the installation headaches.

There are powerful reporting capabilities and complete user interface. The grant access are is delivered to the support community.

Scalability

Autoscaling is done based on the requirements. For instance, if configuration of the web application firewall has to be changed then in new web server will be used online without using manual steps (Wurster et al., 2020).

It can easily deal with the infrastructure due to inclined scalability. User provides hostname and IP address for the nodes that has to be configured.

It is highly scalable that supports inclined infrastructure that has multi master architecture.

Configuration language

It supports execution of the applications using various languages like .Net, PHP, Java, Ruby, etc.

Domain specific language (Ruby DSL), and developer-oriented language is used.

Puppet DSL is employed in Puppet.

Cost

Cost of servers or instances on which Openwork stacks execute. The cost for on-premises is 0.02$ per hour.

The annual fee is approximately $137 per node.

Per year or node will be around $112 if standard support plan and for premium it will be around $199.

Interoperability

Multiple stacks possess multiple languages and here freedom is presented to users for using diverse languages (Foresta et al., 2018).

Chef server works only on Unix/Linux machine. The workstation and client execute on Windows

The Ruby server can only be executed on Unix/Linux machine. With the windows, agent is compatible.

b. Evaluation summary

AWS Ops stack supports wide range of architecture that will assist in defining the configuration through usage of any format, in case of Chef, it automates various requirements for the installation. It is liable for defining the server configuration but is only dependent on the source code. It has enabled scaling to conduct easy task for different groups. AWS OpsWork possess diverse role for the central servers and infrastructure has to be defined considering the environment (Davatz et al., 2017). In puppet code, most of the functions lead towards maintenance. In this section, comparison among three cloud deployment tools is provided and analysis for infrastructure, scaling, and usability is done. Chef automate furnish secured information regarding automation tools that present them with the nodes. Puppet Enterprise comprises data for the configuration management and services that host diverse automation tools. OpsWork stack provides information for management of the applications in the assistance of servers.

AWS OpsWorks stacks

a. Overview

AWS OpsWorks Stacks enable to handle servers and applications for on-premises and AWS. Through this, the applications can be modelled as a stack that comprises diverse layers such as application server, load balancing, and database (Štefanič et al., 2019). Here, deployment and configuration Amazon EC2 instances within each layer for connection with diverse resources such as Amazon RDS databases. It enables to set up the automatic scaling to the servers depending on the preset schedules and it acts as the response for the altering traffic levels and it utilizes lifecycle hooks for orchestrating the changing as the environment scales. The Chef can be executed through the usage of Chef Solo that enables to automate activities such as installation of the programming frameworks or languages, packages, configuration of software, etc. AWS OpeWoks stack act as the tool that is being utilized for the cloud deployment. The rationale is configuration of the cloud deployment in which database will be accessed through the usage of servers and applications while AWS cloud formation acts as the service that will assist in modelling Amazon web service (Halpern et al., 2019). It aims at saving the time for management of the resources for application. It enables automation of the task that needs programming language or their configurations, and the tools can be utilized on-premises for solving the problems related to the cloud deployment.

b. Prerequisites

It must be initiated through signing up for the AWS account, creation of IAM user within the AWS account and giving access to the IAM users for accessing AWS OpsWorks Stacks. The different prerequisites that will be considered in this are provided below:

To assign up for the AWS account

If user does not have AWS account then these steps must consider here. The amazon portal must be opened, and adhere to the online instructions. Here, the user must enter the verification details to ensure their identity.

Creating IAM User

Here, the AWS account must be utilized for creation of the AWS IAM (Identity and access management) user. IAM user can be utilized for accessing the AWS OpsWorks Stacks directly. Conducting this is not secured and it makes it complex for troubleshooting the issues related to the service access.

Assigning service access permissions

The IAM user can be set up that allow to give access for the AWS OpsWorks Stacks service and related services. For assigning the service access permissions for the IAM user, the managed policies must be considered (Baset et al., 2017). Here, AmazonS3FullAccess and AWSOpsWorks_FullAccess policies can be utilized for user that have been created within the previous step or for the existent IAM user that has to be utilised.

Application Server Stack

Application server stack comprises single instance of the application server that have relevant IP address for receiving the user requests. Here, application code and other associated files will be stored within the separate repository that will be further deployed with the server. The stack will have different components, these are a layer that will illustrate the group of instances and how these can be configured. For example, it can be the group of IIS instances. Another component is instance that will illustrate Amazon EC2 instance. Here, the layer will be configured that will be the single instance for executing IIS and layers will possess distinct instances. There will be an app that comprises information needed for installation of the application as an instance (Aiftimiei et al., 2017). A cookbook comprises custom Chef recipes that is liable for supporting the custom IIS layer. The app code and cookbook are stored within the remote repositories like an archive file within the Git repository or Amazon S3 bucket. The one windows stack cam be deployed within the stack for the online applications of the organization.

The OpsWork assist is relevant for the application server stack as it assists in management of the supplication with the identical permissions that can be modelled with the assistance of diverse layers. AWS Opsworks stack assists in load balancing and the characteristic of the automatic scaling assists in management of the diverse resources under the databases, and Amazon services. Here, the preset schedules will be applied for the incoming traffic levels that will illustrate the better cloud deployment. The application server can utilize any of the application in case they tend to make use of AWS services. The server stack is programmable that will enable storage of the data files. It is scalable through the usage of the PowerShell scripts. The key benefit that can be attained through this server is that it supports diverse kind of architects that are needed for handling web application and they possess complex software. There is a need of the server for cloud deployment that can stack the information on the different layers and AWS is the critical action. It assists to defined the new configuration for the system, version and environment that will assist in maintaining it through the assistance of the source code (Linthicum, 2017). The server possesses inclined features for usage of the layers and stacks that furnish inclined outcome for the cloud deployment strategies. The server is liable for providing the tags that can be further utilized for the monitoring purposes and cost allocation. The server stack is acceptable as the layer is liable for supporting the configuration that are connected through the OpsWork tool. Another element depicts the instance that will be further connected with OpsWork stack tool and last section of the server depicts application that needs server to store the application.

Recommendations for cloud deployment scalability

For executing the applications efficiently, the different practices are recommended for matching the servers with the current request volume. The three ways are provided for the management of the server instances, it includes 24/7 instances are initiated manually and it will be executed it until manual implementation stops by itself. Here, the time-based instance will be initiated automatically and these will be stopped through AWS OpsWorks Stacks for the user-specified scheduled. The load-based instances will be initiated automatically and will be stopped through the AWS OpsWorks Stacks when the threshold for the user-specified load metrics is crossed such as memory utilization or CPU.

It is recommended that in case stack will have over few application server instances then three kind of instances must be utilised. The stack must have relevant load-based instances so that when the load will cross the specified metrics then it will be initiated automatically. The cost for the non-executing instances is kept minimal through the usage of instance store-baked or Amazon EBS-backed instances. Recommended practices are efficient for creation of the enough for handling inclined request volumes. For instance, the three load-based instances must be possessed by the stack.

Conclusion

From above, it can be concluded that programmatic cloud deployment approach illustrates the modern technique for cloud services or applications and their deployment. It has declined the work for the dev ops and administrators so that the tasks might be automated effectively. The critical advantage that can be attained through this is that it can be scales down and up based on the applications environment for adjusting to the application nodes load and availability.

References

Aiftimiei, D.C., Fattibene, E., Gargana, R., Panella, M. and Salomoni, D., 2017, October. Abstracting application deployment on Cloud infrastructures. In Journal of Physics: Conference Series (Vol. 898, No. 8, p. 082053). IOP Publishing.

Baset, S., Suneja, S., Bila, N., Tuncer, O. and Isci, C., 2017, December. Usable declarative configuration specification and validation for applications, systems, and cloud. In Proceedings of the 18th ACM/IFIP/USENIX Middleware Conference: Industrial Track (pp. 29-35).

Chang, R.I., Lee, C.Y. and Hung, Y.H., 2021. Cloud-based analytics module for predictive maintenance of the textile manufacturing process. Applied Sciences, 11(21), p.9945.

Davatz, C., Inzinger, C., Scheuner, J. and Leitner, P., 2017, May. An approach and case study of cloud instance type selection for multi-tier web applications. In 2017 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGRID) (pp. 534-543). IEEE.

Eck, B., Fusco, F., Gormally, R., Purcell, M. and Tirupathi, S., 2020. Scalable deployment of AI time-series models for IoT. arXiv preprint arXiv:2003.12141.

Foresta, F., Cerroni, W., Foschini, L., Davoli, G., Contoli, C., Corradi, A. and Callegati, F., 2018, May. Improving OpenStack networking: Advantages and performance of native SDN integration. In 2018 IEEE international conference on communications (ICC) (pp. 1-6). IEEE.

Halpern, M., Boroujerdian, B., Mummert, T., Duesterwald, E. and Reddi, V.J., 2019. One size does not fit all: Quantifying and exposing the accuracy-latency trade-off in machine learning cloud service apis via tolerance tiers. arXiv preprint arXiv:1906.11307.

Kritikos, K., Kirkham, T., Kryza, B. and Massonet, P., 2017. Towards a security-enhanced PaaS platform for multi-cloud applications. Future Generation Computer Systems, 67, pp.206-226.

Linthicum, D.S., 2017. Cloud computing changes data integration forever: what's needed right now. IEEE Cloud Computing, 4(3), pp.50-53.

Štefanič, P., Cigale, M., Jones, A.C., Knight, L., Taylor, I., Istrate, C., Suciu, G., Ulisses, A., Stankovski, V., Taherizadeh, S. and Salado, G.F., 2019. SWITCH workbench: A novel approach for the development and deployment of time-critical microservice-based cloud-native applications. Future Generation Computer Systems, 99, pp.197-212.

Sturzinger, E.M., Lowrance, C.J., Faber, I.J., Choi, J.J. and MacCalman, A.D., 2021, April. Improving the performance of AI models in tactical environments using a hybrid cloud architecture. In Artificial Intelligence and Machine Learning for Multi-Domain Operations Applications III (Vol. 11746, pp. 18-32). SPIE.

Wurster, M., Breitenbücher, U., Brogi, A., Harzenetter, L., Leymann, F. and Soldani, J., 2020. Technology-agnostic declarative deployment automation of cloud applications. In Service-Oriented and Cloud Computing: 8th IFIP WG 2.14 European Conference, ESOCC 2020, Heraklion, Crete, Greece, September 28–30, 2020, Proceedings 8 (pp. 97-112). Springer International Publishing.

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