AWS Well-Architected Framework Review

Build better on AWS with confidence. Our full AWS Well-Architected Framework Review provides a comprehensive evaluation of your workloads against AWS best practices, helping you reduce risk, improve efficiency, and align your cloud strategy with business outcomes.

What is it? This in-depth review assesses your workloads using the six pillars of the AWS Well-Architected Framework:

• Operational Excellence
• Security
• Reliability
• Performance Efficiency
• Cost Optimization
• Sustainability

Using a structured approach with over 60 detailed questions, our AWS-certified architects work closely with your technical and business stakeholders to identify key risks, gaps, and opportunities for improvement across your architecture, processes, and governance.

It’s not just a checkbox exercise; it’s a powerful method to ensure your cloud infrastructure is resilient, scalable, and optimised.

Why choose the full review?

• Comprehensive coverage: Deep dive into all six pillars across your workload lifecycle
• Risk-focused: Uncover and prioritise the most critical issues to address
• Expert-led: Delivered by experienced AWS-certified professionals
• Actionable outcomes: Includes detailed improvement plans tailored to your context
• AWS-aligned: Leverages AWS tools and may qualify for AWS funding incentives

Who is it for? This offering is perfect for:

• Organisations with production workloads on AWS
• Teams preparing for scale, migration, or modernisation
• Businesses seeking to formalise their cloud governance or compliance posture
• Anyone looking to validate, improve, or benchmark their use of AWS against best practices

What you get: At the end of the engagement, you’ll receive:

• A full report covering findings for each Well-Architected pillar
• Detailed risk assessment and priority recommendations
• A remediation plan aligned to your goals and timelines
• Optional AWS funding to support improvement activities (subject to AWS approval)
• A clear path forward for optimising your workload