Data Analytics

Announcing the AWS Well-Architected Data Analytics Lens


We are delighted to announce the release of the Data Analytics Lens. The lens consists of a lens whitepaper and an AWS-created lens available in the Lens Catalog of the AWS Well-Architected Tool. The AWS Well-Architected Framework provides a consistent approach to evaluate architectures and implement scalable designs. With the AWS Well-Architected Framework, cloud architects, system architects, engineers, and developers can build secure, high-performance, resilient, and efficient infrastructure for their applications and workloads.

Using the Lens in the Tool’s Lens Catalog, you can directly assess your Analytics workload in the console, and produce a set of actionable results for customized improvement plans recommended by the Tool.

The updated Data Analytics Lens outlines the most up-to-date steps for performing an AWS Well-Architected review that empowers you to assess and identify technical risks of your data analytics platforms. The new whitepaper and Lens cover multiple analytics use cases and scenarios, and provide comprehensive guidance to help you design your analytics applications in accordance with AWS best practices.

The new Data Analytics Lens offers implementation guidance you can use to deliver secure, high performance and reliable workloads, all with an eye toward maintaining cost-effectiveness and sustainability.

For more information on AWS Well-Architected Lenses, refer to AWS Well-Architected.

What’s new in the Data Analytics Lens?

The Data Analytics Lens is a collection of customer-proven design principles, best practices, and prescriptive guidance to help you adopt a cloud-centered approach to running analytics on AWS. These recommendations are based on insights that AWS has gathered from customers, AWS Partners, the field, and our own analytics technical specialist communities.

This version covers the following topics:

  • New Lens for the Well-Architected Tool in the Lens Catalog
  • New Data Mesh analytics user scenario
  • Included guidance on building ACID compliant data lakes using Iceberg
  • Included guidance on adding business context to your data catalog to improve searchability and access
  • How best to leverage Serverless to build sustainable data pipelines
  • Expanded advanced performance tuning techniques
  • Additional content for analytics scenario use cases
  • Links to updated blogs and product documentation, partner solutions, training content, and how-to videos

The lens highlights some of the most common areas for assessment and improvement. It’s designed to align with and provide insights across the six pillars of the AWS Well-Architected Framework:

  • Operational excellence – Includes the ability to support development and run workloads effectively, gain insight into your operations, and continually improve supporting processes and procedures to deliver business value.
  • Security – Includes the ability to protect data, systems, and assets to take advantage of cloud technologies to improve your security.
  • Reliability – Includes the ability of a system to automatically recover from infrastructure or service disruptions, dynamically acquire computing resources to meet demand, and mitigate disruptions such as misconfiguration or transient network issues.
  • Performance efficiency – Includes the efficient use of computing resources to meet requirements and the maintenance of that efficiency as demand changes and technologies evolve.
  • Cost optimization – Includes the continual process of system refinement and improvement over the entire lifecycle to optimize cost, from the initial design of your first proof of concept to the ongoing operation of production workloads.
  • Sustainability – Includes minimizing the environmental impacts of running cloud workloads. Topics including benchmarking, trading data accuracy for carbon, encouraging a data minimization culture, implementing data retention processes, optimizing data modeling, preventing unnecessary data movement, and efficiently managing analytics infrastructure.

The new Data Analytics Lens provides guidance that can help you make appropriate design decisions in line with your business requirements. By applying the techniques detailed in this lens to your architecture, you can validate the resiliency and efficiency of your design. This lens also provides recommendations to address any gaps you may identify.

Who should use the Data Analytics Lens?

The Data Analytics Lens is intended for all AWS customers who use analytics processes to run their workloads.

We believe that the lens will be valuable regardless of your stage of cloud adoption: whether you’re launching your first analytics workloads on AWS, migrating existing services to the cloud, or working to extend and improve existing AWS analytics workloads.

The material is intended to support customers in roles such as architects, developers, and operations team members.

Conclusion

Applying the Data Analytics Lens to your existing architectures can validate the stability and efficiency of your design and provide recommendations to address identified gaps.

For more information about building your own Well-Architected systems using the Data Analytics Lens, see the Data Analytics Lens whitepaper. For information about on the new Lens, please see the Well Architected Tool and Lens Catalog briefs. If you require additional expert guidance, contact your AWS account team to engage a Specialist Solutions Architect.

To learn more about supported analytics solutions, customer case studies, and additional resources, refer to Architecture Best Practices for Analytics & Big Data.


About the authors

Russell Jackson is a Senior Solutions Architect at AWS based in the UK. Russell has over 15 years of analytics experience and is passionate about Big Data, event driven-architectures and building environmentally sustainable data pipelines. Outside of work, Russell enjoys road cycling, wild swimming and traveling.

Theo Tolv is a Senior Analytics Architect based in Stockholm, Sweden. He’s worked with small and big data for most of his career, and has built applications running on AWS since 2008. In his spare time he likes to tinker with electronics and read space opera.

Bruce Ross is a Senior Solutions Architect at AWS in the New York Area. Bruce is the Lens Leader for the Well-Architected Framework. He has been involved in IT and Content Development for over 20 years. He is an avid sailor and angler, and enjoys R&B, jazz, and classical music.

Dhiraj Thakur is a Solutions Architect with Amazon Web Services. He works with AWS customers and partners to provide guidance on enterprise cloud adoption, migration, and strategy. He is passionate about technology and enjoys building and experimenting in the analytics and AI/ML space.

Pragnesh Shah is a Solutions Architect in the Partner Organisation. He is specialist in migration, modernisation, Cloud strategy, designing and delivering data and analytics capabilities. Outside of work, he spends time with family and nature. He likes to record nature sound and practice Zen meditation.



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