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AWS Cost Optimization for SaaS Companies

We optimize AWS costs for SaaS companies by connecting infrastructure spend to business metrics — per-tenant cost attribution, tier profitability analysis, and architecture changes that improve unit economics without reducing performance.

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Summary

Optimize AWS costs for SaaS platforms with per-tenant cost attribution, unprofitable tier identification, and DynamoDB cost controls. Align cloud spend with SaaS unit economics.

Key Facts

  • • Optimize AWS costs for SaaS platforms with per-tenant cost attribution, unprofitable tier identification, and DynamoDB cost controls
  • • Per-Tenant Cost Attribution: SaaS unit economics require knowing the AWS cost per tenant
  • • Without cost attribution, you cannot identify unprofitable tenants, optimize tier pricing, or project infrastructure costs at scale
  • • DynamoDB Cost Spikes: DynamoDB on-demand mode can produce unexpected cost spikes when tenants generate hot partitions or write bursts
  • • Multi-Tenant Resource Efficiency: Shared infrastructure serving many small tenants has different optimization levers than dedicated tenant infrastructure

Entity Definitions

Bedrock
Bedrock is an AWS service relevant to aws cost optimization for saas companies.
SageMaker
SageMaker is an AWS service relevant to aws cost optimization for saas companies.
Lambda
Lambda is an AWS service relevant to aws cost optimization for saas companies.
S3
S3 is an AWS service relevant to aws cost optimization for saas companies.
RDS
RDS is an AWS service relevant to aws cost optimization for saas companies.
DynamoDB
DynamoDB is an AWS service relevant to aws cost optimization for saas companies.
CloudWatch
CloudWatch is an AWS service relevant to aws cost optimization for saas companies.
multi-tenant
multi-tenant is a cloud computing concept relevant to aws cost optimization for saas companies.

Frequently Asked Questions

How do you calculate the AWS cost per tenant in a multi-tenant SaaS?

We implement a three-tier attribution model: (1) directly attributable costs tagged with tenant-ID (DynamoDB tables, S3 buckets, Lambda functions per tenant), (2) proportionally allocated costs based on usage metrics (shared RDS CPU time by query count), and (3) overhead costs allocated equally or by plan tier. This produces a cost-per-tenant P&L that connects to your SaaS pricing model.

How much can SaaS companies typically save on AWS costs?

SaaS companies typically achieve 25-40% cost reduction through: rightsizing compute (often 20-30% savings), moving steady-state workloads to Compute Savings Plans (20% savings), eliminating idle resources in staging environments, and optimizing data transfer between AWS services. The largest single savings opportunity varies by architecture — database and compute are usually the biggest levers.

When should a SaaS company move from DynamoDB on-demand to provisioned capacity?

Switch to provisioned capacity when a table has consistent, predictable traffic patterns — typically when monthly WCU/RCU consumption is stable within ±20% for 3+ months. Provisioned capacity is 20-40% cheaper than on-demand at consistent utilization. Keep on-demand for tables with spiky or unpredictable access patterns.

Related Content

Key Challenges We Solve

Per-Tenant Cost Attribution

SaaS unit economics require knowing the AWS cost per tenant. Without cost attribution, you cannot identify unprofitable tenants, optimize tier pricing, or project infrastructure costs at scale.

DynamoDB Cost Spikes

DynamoDB on-demand mode can produce unexpected cost spikes when tenants generate hot partitions or write bursts. Without monitoring, a single misconfigured tenant integration can double your database bill.

Multi-Tenant Resource Efficiency

Shared infrastructure serving many small tenants has different optimization levers than dedicated tenant infrastructure. Noisy-neighbor mitigation, connection pooling, and compute right-sizing require SaaS-specific approaches.

Cost Impact of AI Features

Adding Bedrock, SageMaker, or other AI capabilities to SaaS products creates unpredictable per-tenant AI costs that must be monitored and controlled to maintain healthy margins.

Our Approach

Per-Tenant Cost Attribution System

AWS resource tagging strategy with tenant-ID tags, Tag Editor automation for consistent tagging, Cost Explorer reports by tenant tag, and a monthly profitability dashboard showing AWS cost vs. plan revenue per tenant.

DynamoDB Cost Controls

CloudWatch alarms on DynamoDB consumed capacity, automated alerts for hot partition detection, capacity mode analysis (on-demand vs. provisioned crossover point per table), and DAX evaluation for read-heavy tables.

AI Feature Cost Metering

Token usage tracking per tenant for Bedrock features, SageMaker inference cost attribution, and automated budget alerts when any tenant's AI cost exceeds defined thresholds.

Frequently Asked Questions

How do you calculate the AWS cost per tenant in a multi-tenant SaaS?
We implement a three-tier attribution model: (1) directly attributable costs tagged with tenant-ID (DynamoDB tables, S3 buckets, Lambda functions per tenant), (2) proportionally allocated costs based on usage metrics (shared RDS CPU time by query count), and (3) overhead costs allocated equally or by plan tier. This produces a cost-per-tenant P&L that connects to your SaaS pricing model.
How much can SaaS companies typically save on AWS costs?
SaaS companies typically achieve 25-40% cost reduction through: rightsizing compute (often 20-30% savings), moving steady-state workloads to Compute Savings Plans (20% savings), eliminating idle resources in staging environments, and optimizing data transfer between AWS services. The largest single savings opportunity varies by architecture — database and compute are usually the biggest levers.
When should a SaaS company move from DynamoDB on-demand to provisioned capacity?
Switch to provisioned capacity when a table has consistent, predictable traffic patterns — typically when monthly WCU/RCU consumption is stable within ±20% for 3+ months. Provisioned capacity is 20-40% cheaper than on-demand at consistent utilization. Keep on-demand for tables with spiky or unpredictable access patterns.

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