Tech leaders invest in new startup building billing software for data centers

Summary:

Prominent tech investors including AWS and Microsoft veterans funded DataBill, a startup developing AI-powered billing solutions for hyperscale data centers. The move addresses growing financial waste caused by outdated per-machine billing models failing to track dynamic cloud resources. Triggers include rising cloud adoption (Flexera 2023 reports 82% of enterprises face billing surprises), containerization complexity, and green computing initiatives requiring granular energy cost tracking.

What This Means for You:

• Impact: Overpaying 22-35% on underutilized resources (IDC 2022 data) due to legacy billing systems
• Fix: Audit usage patterns with aws ce get-cost-and-usage --time-period Start=2023-10-01,End=2023-10-15 --granularity DAILY --metrics "BlendedCost"
• Security: Billing systems are top ransomware targets – ensure access logs
• Warning: Vendor lock-in risks if billing tools don’t support multi-cloud

Solutions:

Solution 1: Real-Time Resource Tagging

Implement mandatory tagging policies across Kubernetes clusters and VM deployments. DataBill’s approach uses NLP to auto-generate tags from deployment tickets.

Enforce tagging compliance with AWS Config rules:

aws configservice put-config-rule --config-rule '{"ConfigRuleName": "ec2-tag-required", "Source": {"Owner": "AWS", "SourceIdentifier": "REQUIRED_TAGS"}, "InputParameters": "{"tag1Key":"Environment", "tag2Key":"Project"}"}'

Solution 2: Predictive Burst Billing

Traditional reserved instances fail for short-term workloads. DataBill’s ML models analyze historical patterns to purchase optimal spot instances automatically.

Test predictive capacity with AWS Forecast:

aws forecast create-dataset-import-job --dataset-arn arn:aws:forecast:us-east-1:123456789012:dataset/DATASET_NAME --data-source '{"S3Config": {"Path": "s3://bucket/training-data.csv"}}'

Solution 3: Carbon Cost Allocation

New SEC climate rules require tracking energy expenditures per workload. DataBill integrates power usage effectiveness (PUE) metrics directly into invoices.

Extract DC energy data via SDKs:

import boto3
ce = boto3.client('ce')
print(ce.get_cost_and_usage(TimePeriod={'Start': '2023-10-01', 'End': '2023-10-15'}, Granularity='DAILY', Filter={'Dimensions': {'Key': 'RECORD_TYPE','Values': ['Credit']}}))

Solution 4: Cross-Cloud Normalization

Convert AWS CU/hour, Azure DTUs, and GCP SUDs into standardized compute units for true cost comparison. Startup’s patent-pending algorithm accounts for regional energy costs.

Normalize costs manually with:

aws ce get-cost-forecast --metric "NORMALIZED_USAGE_AMOUNT" --time-period Start=2023-11-01,End=2023-11-30 --granularity MONTHLY

People Also Ask:

• Q: Why are investors targeting billing software now? A: Hybrid infrastructure creates billing blind spots
• Q: How does this affect cloud migration decisions? A: Enables precise TCO comparisons
• Q: Is traditional DCIM software obsolete? A: Only for financial ops – still needed for physical layer
• Q: What compliance risks does this solve? A: SOX/GDPR requires accurate cost allocation

Protect Yourself:

• Enable AWS Cost Anomaly Detection weekly
• Demand hourly billing increments from providers
• Isolate billing IAM roles with MFA
• Audit 3rd-party billing tool API permissions quarterly

Expert Take:

“Granular billing isn’t about cost-cutting – it’s the new control plane. When you can attribute expenses to individual microservices, infrastructure becomes a profit center.” – Lena K., ex-Azure Billing Architect

Tags:

• Data Center Billing Software Solutions
• AI for Cloud Cost Optimization
• Multi-cloud Chargeback Systems
• Hyperscale DC Financial Operations
• Carbon Accounting in Data Centers
• Startup Investment Trends in Cloud Tech

*Featured image via source

Edited by 4idiotz Editorial System