Well-Architected: 5-Wk custom Assessment

Consid AB

Azure Well-Architected Assessment Report - Findings and Recommendations for Areas of Improvement

The Consid Azure Well-Architected Assessment is an expert analysis and assessment of your existing architecture to benchmark and discover focus areas for improvement according to the five pillars in the Azure Well-Architected Framework. The outcome is a structured report pointing out areas for improvement when compared to standards and recommendations in the Azure Well-Architectured Framework. 5 weeks is an estimation but is dependant on what the customer want to include in the assessment. Please use the Contact me button to get in touch for scoping discussions and a quote.

Why? A good architecture contributes to and increases the likelihood of business success. Consid’s Azure Well-Architected assessment provides a report covering areas for improvement including potential outcomes and priorities in a suggested roadmap. As a starting point for this journey Consid offers an assessment of your architecture focussing on gaps compared to established practices from Azure WAF in combination with our experience

How? Consid’s assessment highlights strenghts, weaknesses and deviations from the Azure Well-Architected Framework and presents the result in a structured report containing met requirement, deficiencies, and recommended mitigations. Our experts will assess and evaluate the suitability of the architecture from the perspectives of operational excellence, security, reliability, performance efficience and cost optimization.

https://store-images.s-microsoft.com/image/apps.38178.4eee7462-539e-4008-8998-deb18bc224e2.6d46d55b-fe5f-42ce-8b8f-5ccea5658d39.ac3b9266-6066-4900-b8bc-2f7913e9a68c
https://store-images.s-microsoft.com/image/apps.38178.4eee7462-539e-4008-8998-deb18bc224e2.6d46d55b-fe5f-42ce-8b8f-5ccea5658d39.ac3b9266-6066-4900-b8bc-2f7913e9a68c
https://store-images.s-microsoft.com/image/apps.27338.4eee7462-539e-4008-8998-deb18bc224e2.6d46d55b-fe5f-42ce-8b8f-5ccea5658d39.742ff61e-ee2d-4fdb-8a64-175d9c05321a