Edition 5a: AWS - AWS Well - Architected Framework
Sitaram Choudary Yarlagadda
Data Technology Architect and Engineer Capable of utilizing the People, Process, and Technology framework as well as the DAMA-DMBOK concepts to effectively create and manage mission-critical enterprise data platforms.
AWS Well Architected Framework
??????????? AWS Well-Architected framework assists cloud architects in constructing secure, high-performing, robust, and efficient infrastructure for diverse applications and workloads. Based on six core principles—operational excellence, security, reliability, performance efficiency, cost optimization, and sustainability—AWS Well-Architected framework offers a standardized method for customers and partners to assess architectural designs and create scalable solutions.
??????????? The AWS Well-Architected Framework provides a comprehensive guide on fundamental ideas, design principles, and optimal architectural techniques for effectively building and operating workloads in the cloud. By responding to a set of fundamental questions, you may ascertain the extent to which your architecture adheres to cloud best practices and get recommendations for enhancing it.
·?????? Operational Excellence Pillar: The operational excellence pillar is on the efficient management and oversight of systems, with a constant emphasis on enhancing processes and protocols. The main subjects covered are the automation of modifications, the handling of occurrences, and the establishment of guidelines for the management of everyday tasks.
·?????? Security Pillar: The security pillar is dedicated to safeguarding information and systems. The main subjects covered include data confidentiality and integrity, user authorization management, and the implementation of security measures to identify security incidents.
·?????? Reliability Pillar: The reliability pillar emphasizes the performance of workloads in fulfilling their intended functions and strategies for promptly recovering from failures to satisfy expectations. The main subjects covered include the design of distributed systems, planning for recovery, and adjusting to changing needs.
·?????? Performance Efficiency Pillar: The performance efficiency pillar emphasizes the systematic and efficient allocation of IT and computing resources. The key subjects covered are the careful selection of resource kinds and sizes that are best suited for the specific workload demands, the continuous monitoring of performance, and the ongoing maintenance of efficiency to adapt to changing business needs.
·?????? Cost Optimization Pillar: The cost optimization pillar is centered on the avoidance of superfluous expenses. Important subjects include comprehending expenditure patterns over time and managing the distribution of funds, choosing appropriate and sufficient resources, and expanding operations to fulfill corporate requirements without excessive spending.
·?????? Sustainability Pillar: The sustainability pillar focuses on minimizing the environmental impacts of running cloud workloads. Key topics include a shared responsibility model for sustainability, understanding impact, and maximizing utilization to minimize required resources and reduce downstream impacts.
??????????? The AWS Well-Architected Framework use the following terminology:
·?????? Component: A component refers to the combination of code, configuration, and AWS Resources that together fulfill a certain need. A component is often seen as the fundamental unit of technical ownership and is designed to be independent from other components.
·?????? Workload: The word workload refers to a collection of components that collaborate to provide business value. A workload often refers to the amount of information that is exchanged between business and technology executives.
·?????? Architecture: Architecture refers to the manner in which components collaborate within a task. The communication and interaction between components are often the central focus of architectural diagrams.
·?????? Milestones: Milestones signify significant transitions in your architecture as it progresses across the product lifecycle (including design, implementation, testing, deployment, and ongoing operation).
·?????? Level of Effort: The degree of effort refers to the quantification of the time, energy, and intricacy involved in carrying out an activity. To accurately classify the degree of effort required for a company, it is essential to take into account factors such as the team's size and competence, as well as the complexity of the assignment.
o?? High: The task may need many weeks or perhaps several months to complete. This might be divided into numerous narratives, publications, and assignments.
o?? Medium: The task may need many days or even weeks to complete. This might be divided into various releases and tasks.
o?? Low: The task may need many hours or several days to complete. This might be divided into many tasks.
The Well-Architected Framework establishes a collection of universal design principles that promote effective design in cloud computing:
·?????? Stop guessing your capacity needs: Failure to make an appropriate capacity choice while deploying a task may result in the wasteful use of costly idle resources or the negative consequences of insufficient capacity on performance. Cloud computing can eliminate these issues. You have the flexibility to use whatever amount of capacity that suits your requirements, and the ability to automatically adjust and adapt the capacity as needed.
·?????? Test systems at production scale: Within the cloud, you have the capability to promptly establish a test environment of significant size, carry out your testing, and thereafter dismantle the allocated resources. By only incurring charges for the test environment while it is active, you have the ability to replicate your real environment at a much-reduced cost compared to doing tests on-site.
·?????? Automate with architectural experimentation in mind: Automation enables you to generate and duplicate your tasks at a reduced cost and eliminate the need for human labor. You have the ability to monitor modifications to your automation, examine the consequences, and restore earlier settings if needed.
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·?????? Consider evolutionary architectures: In a conventional setting, architectural choices are often executed as fixed, singular occurrences, with a limited number of significant iterations of a system during its existence. As a company and its setting undergo continuous changes, these initial choices may impede the system's capacity to meet evolving business needs. Within the cloud environment, the ability to automate and test as needed reduces the potential negative consequences resulting from changes in design. This allows systems to gradually develop over time, enabling firms to readily benefit from new advancements as a customary procedure.
·?????? Drive architectures using data: Within the cloud environment, you have the capability to gather data pertaining to the impact of your architectural decisions on the performance of your workload. This enables you to make informed selections based on factual information about how to enhance your task. Since your cloud infrastructure is written as code, you can utilize this data to make informed decisions about your design and make continuous changes over time.
·?????? Improve through game days: Evaluate the performance of your architecture and processes by routinely organizing game days to imitate events that occur in a production environment. This will facilitate comprehension of areas for improvement and foster the accumulation of organizational expertise in managing events.
Developing a software system has a strong resemblance to erecting a physical structure. Insufficient foundation might compromise the structural stability and functionality of the structure. When designing technological solutions, failing to consider the six fundamental aspects of operational excellence, security, reliability, performance efficiency, cost optimization, and sustainability may make it difficult to create a system that meets your expectations and needs. By integrating these fundamental principles into your architectural design, you will be able to create robust and optimized systems. This will enable you to concentrate on the other aspects of design, such as the functional prerequisites.
?Bibliography
Acceldata. (2022, September 7). How to Architect a Data Platform. Retrieved from acceldata.io : https://www.acceldata.io/article/what-is-a-data-platform-architecture
Amazon Web Services. (n.d.). AWS Well Architected Framework. Retrieved from aws.amazon.com : https://aws.amazon.com/architecture/well-architected/?wa-lens-whitepapers.sort-by=item.additionalFields.sortDate&wa-lens-whitepapers.sort-order=desc&wa-guidance-whitepapers.sort-by=item.additionalFields.sortDate&wa-guidance-whitepapers.sort-order=desc
Amazon Web Services. (n.d.). What is AWS? Retrieved from aws.amazon.com : https://aws.amazon.com/what-is-aws/?nc1=f_cc
DAMA International. (2024). DAMA-DMBOK: Data Management Body of Knowledge: 2nd Edition, Revised. Los Angles: Technics Publications.
en.wikipedia.org . (n.d.). Data Management Association. Retrieved from en.wikipedia.org : https://en.wikipedia.org/wiki/Data_Management_Association
Groover, M. (2021). Speed of Advance. Lion Crest Publications.
Hiltbrand, T. (2024, May 9). From Data-Driven to Data-Centric: The Next Evolution in Business Strategy. Retrieved from tdwi.org : https://tdwi.org/Articles/2024/05/09/PPM-ALL-From-Data-Driven-to-Data-Centric-Next-Evolution-in-Business-Strategy.aspx
Intrepid Tech Ventures. (n.d.). Understand your data asset. Retrieved from theintrepidventures.com : https://theintrepidventures.com/value-proposition/understand-your-data-asset/
Khan, S. M. (2024, May 9). The data product lifecycle: Getting the most out of your data investments. Retrieved from starburst.io : https://www.starburst.io/blog/data-product-lifecycle/
Roberts, S. (2023, April 18). Understand the four Vs of Big Data. Retrieved from theknowledgeacademy.com : https://www.theknowledgeacademy.com/blog/4-vs-of-big-data/
Rowshankish, R. L. (2023, July 31). The evolution of the data-driven enterprise. Retrieved from mckinsey.com : https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/tech-forward/the-evolution-of-the-data-driven-enterprise
Simon, B. (2021, July 21). Complete Guide to PPT Framework | Smartsheet. Retrieved from smartsheet.com : https://www.smartsheet.com/content/people-process-technology#:~:text=for%20IT%20%26%20Ops-,What%20Is%20the%20People%2C%20Process%2C%20Technology%20Framework%3F,maintain%20good%20relationships%20among%20them .
Tharran, A. S. (2023, October 22). The Evolution of Data Science: Past, Present, and Future. Retrieved from linkedin.com : https://www.dhirubhai.net/pulse/evolution-data-science-past-present-future-aditya-singh-tharran-bmmre/
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