Well-Architected Review of Cloud Applications

Yes! We run Well-Architected Reviews for any cloud-based application, regardless of provider.

While the term “Well-Architected Review” was first used by the Amazon Web Services team to name an assessment for AWS-based applications, other cloud providers have since implemented analogous practices.

DataArt’s teams know the best practices for designing, implementing, and supporting applications in different cloud environments and apply a review process for measuring cloud architectures. As part of this process, we can also assess whether your environment is ready to integrate AI workloads, ensuring that infrastructure, data pipelines, and governance models can support intelligent automation and future AI adoption.

The AWS WAR Tool is optimized for recurrent evaluation of your application's state against the cloud best practices. The tool is good for tracking your improvement over time — quarterly, semi-annually, or annually — for a specific workload or pillar.

However, the questions you find in the Tool are quite broad and abstract. When DataArt’s cloud experts run a WAR, they narrow the questions to your specific architecture. They try to figure out why certain architectural decisions had been made, and why features are implemented in a particular way. They also consider your cloud architecture and check whether it is future-proof.

Furthermore, the AWS Tool’s post-review report only outlines the issues that need to be fixed. DataArt’s detailed post-review contains a list of application-specific issues that need to be fixed (in the order of priority), with a detailed description of risk mitigation measures and a roadmap for fixing the problems. Our reviews also highlight where AI can improve resilience, automate monitoring, or reduce costs, giving you practical, forward-looking recommendations that extend beyond standard cloud compliance.

The time it takes the DataArt team to run a Well-Architected Review depends on the cloud project size and complexity. Small and mid-sized projects can usually be assessed over a few one-hour sessions. Large projects require more time.

Other factors that matter are the complexity of running cloud workloads, and the number and availability of the key project stakeholders. In many cases, AI-assisted tools help us accelerate the analysis of logs, configurations, and performance metrics, shortening timelines while increasing accuracy.

To review the cloud application in-depth and from multiple angles, DataArt’s experts recommend that you involve key technical and business stakeholders. These usually include solution architect, technical team lead, product owner as well as stakeholders in charge of operations, security and finance. When AI-readiness is in scope, data owners and analytics leaders should also participate, since successful AI adoption depends on both cloud infrastructure and high-quality, well-governed data.

We'd advise achieving a balance between the pillars. Shoring up just one pillar will almost always increase costs and decrease business value. The wisest strategy is to invest in security first, then performance, then reliability. If you consider these pillars, your application will become sustainable.

Operational excellence can increase or decrease costs. At the same time, cost optimization will always be important for any organization in the public cloud, but it does not stand alone. Increasingly, organizations are also evaluating how each pillar supports AI adoption, for example, ensuring data security for AI models, reliable infrastructure for continuous AI training, and cost optimization for high-volume AI workloads.

The cost of a Well-Arch Review depends on the size and complexity of your cloud project as well as the time DataArt experts will spend reviewing it. Once your project stakeholders review the final report and findings, the decision about the implementation strategy and roadmap will be required. Reviews that include AI-readiness assessments provide an added layer of strategic value, helping you prioritize investments for today’s cloud, and for tomorrow’s AI-driven workloads.