AI - Powered Cloud Workload Cost Estimator
Finitizer AI Powered Cloud Workload Cost Estimator free tool helps you estimate the cost of your cloud workload across Google Cloud, AWS, and Microsoft Azure. Whether you’re evaluating your current workload cost or planning a future deployment, this estimator provides AI-powered review of your total cost and helps you compare providers side-by-side — all without needing to sign in.
Finitizer AI-powered Cloud Workload Cost Estimator
Enter your cloud workload information below to see the costs. You can estimate cloud workload costs either for your current workload or a task you are planning for the future. You can See the samples below to get an idea of what to enter. You can also pick your current cloud provider or pick any / all of them to get the cost estimate.
See samples below to enter information — either as a descriptive text as in Sample 1 or provide detailed information as in Sample 2
Sample 1 (Descriptive text of your cloud workload)
We run a combination of production and development workloads. Our production compute consists of around 40 virtual machines (n2-standard-8 type), operating continuously in the us-central1 region. In addition, we operate 10 smaller VMs for development and testing on weekdays, with limited daily uptime. For storage, we use Nearline and Coldline tiers for long-term retention and frequent access data, totaling around 30 TB spread across us-central1 and europe-west4. Attached to our production VMs are about 500 GB of persistent SSD storage.
Networking involves approximately 7 TB of egress traffic to Asia and about 2 TB of inter-region transfers within the U.S. On the analytics side, we process 2 TB of query data daily using a flat-rate slot-based model and store around 5 TB of data actively. In terms of serverless workloads, we execute about 10 million Cloud Function invocations monthly and publish/pull about 2 million messages via Pub/Sub each month.
Sample 2 (Detailed description of your cloud workload)
Compute: - 15 × AWS m5.2xlarge in US East - 20 × Azure D8s v4 for development (18 hours/day) Storage: - 10 TB AWS S3 Standard-IA - 12 TB Azure Blob Cool Networking: - 5 TB egress to Europe - 3 TB inter-region egress Analytics: - 3 TB/day Redshift RA3 equivalent - 4 TB managed Synapse warehouse Serverless & Messaging: - 5M Lambda invocations/mo (512MB) - 1M SNS/SQS messages