What is the Cloud Recommendation Engine?
Cloud Recommendation Engine is a powerful feature that can provide you with exactly the details you need to plan your next cloud migration, compare costs between AWS and Microsoft Azure clouds, and right-size your next cloud deployment.
Find the Cloud Recommendation Engine (CRE) under Reports > Cloud Recommendation Engine menu, and get clear recommendations for sizing cloud instances to suit your physical or virtual workloads.
CRE feature overview:
- Cloud Recommendation Engine leverages Device42’s industry-leading auto-discovery and resource utilization data to understand your workloads
- Cloud instance recommendations are provided for your choice of AWS or Microsoft Azure cloud platforms (instance sizes + pricing info)
Instance recommendations are calculated based on a combination of your observed workloads, resource utilization if available, PLUS a user-selected “Safety Factor” via the slider. e.g. if your current instance peaks at 4GB RAM usage, and you chose 50% safety factor, CRE will size cloud instance at 6GB:
How Cloud Recommendation Engine Works:
- A summary of CPU, memory, and OS info is created based on auto-discovered inventory data
- If you have the resource utilization feature enabled, peak CPU and memory usage over the last month is factored in
- When you click the “Send to Cloud and Analyze Data” button, Device42 anonymizes your data and sends it to our cloud servers, finding matching AWS or Azure workloads
- Device42’s bots do the hard work, returning workload recommendations that have been best-matched each particular device to your main appliance. The anonymized data is then re-matched with your actual device names, and an output sheet is generated that contains both your device names and matched workloads for following 4 scenarios:
- AWS based on Resource Utilization
- AWS based on Inventory Data
- Azure based on Resource Utilization
- Azure based on Inventory Data
Downloaded Data Sample:
![Sample downloaded data](/media/images/reports/cloud-recommendation-engine/Sample of downloaded data.png)
AWS based on RU Sample:
![AWS based on RU sample output](/media/images/reports/cloud-recommendation-engine/AWS based on RU data.png)
Azure based on Inventory Sample:
![Azure based on Inventory Sample output](/media/images/reports/cloud-recommendation-engine/Azure based on inventory.png)