Enterprise Observability Infrastructure

Show us your SIEM bill. We'll show you where to cut 25%+.

Filter and route logs at the source. Cut 50-70% of volume, halve query times, make your existing stack perform.

Representative Savings Model

Model: $2.02M Annual Savings

150+ microservices | 8TB/day logs | 68% cost reduction, 16× faster queries

Before Expanso

Centralized SIEM

Monthly Cost $240,000
SIEM Ingest: $180,000 Compute: $20,000 Storage (SIEM Hot Index): $35,000 Networking: $5,000 Total: $240,000
Query Latency 45s
Daily Log Volume 8 TB/day
Indexed Events 500M/day
With Expanso

Distributed Edge Processing

Monthly Cost $71,000
SIEM Ingest: $57,600 Edge Compute (Reuse Existing): $0 Storage (S3): $12,400 Networking (Reduced Volume): $1,000 Total: $71,000
Query Latency 2.8s
Daily Log Volume 2.6 TB/day
Indexed Events 160M/day
$2,028,000/year
72% cost reduction | 68% less data | 16× faster queries
The Challenge

The Log Management Tax

💸

Wasted SIEM Spend

Paying to ingest data you'll never search.

$180K/month on unsearched logs

60-70% of logs are debug-level noise that ages out unsearched. But you're paying to ingest, index, and store all of it.

Large enterprises: $10K-$50K/month wasted

Exponential scaling costs

Each new microservice adds 50-100GB of daily logs. Volume doubles every 18 months, costs triple.

Log volume doubles every 18 months, costs triple
🐌

Slow Queries

High-cardinality fields make dashboards unusable.

45-second query timeouts

SREs wait 45+ seconds for incident dashboards during outages. High-cardinality fields (user IDs, trace IDs) make queries crawl.

Typical centralized latency: 45+ seconds

2-3 weeks per service onboarding

Each microservice needs custom parsing, field extraction, and routing. Platform teams become bottlenecks.

Average: 2-3 weeks per service
🔒

Compliance Gaps

PII crossing jurisdictions creates regulatory risk.

Data sovereignty violations

EU logs with PII flowing to US systems create GDPR risk. Regulations require local processing.

GDPR fines: €20M or 4% revenue

No filtering audit trail

Manual log filtering lacks lineage tracking. Audits can't prove what was filtered, when, or why.

Creates SOC 2 / ISO 27001 gaps

Centralized Architectures
Process Everything

Every debug log sent to central SIEM

Ingest costs scale with volume growth

Query performance degrades with event count

You pay for all of it

Centralized Challenge
Distributed Processing
Ingest Everything, Filter Later
Filter at source before ingest charges
Manual Parsing Per Service
Policy-driven enrichment for all services
Query Timeouts on High-Cardinality Data
Pre-aggregate metrics, index actionable events only
Limited Data Lineage
Full audit trail from source to destination
Complex Multi-Region Routing
Jurisdiction-aware routing, automatic compliance

Expanso vs Traditional Solutions

Traditional Stack
The Expanso Advantage
Data Noise Reduction
Minimal or Manual Filtering
Checkmark Built-in, Automated Filtering
Time to Insights
Slow
Checkmark Real-Time
Stack Flexibility
Rigid, Vendor-Locked
Checkmark Flexible, works with nearly every vendor
Cost Efficiency
Increases rapidly with the amount of stored data
Checkmark Up to 80% Cost Reduction

Data Noise Reduction

Traditional Stack:
Minimal or Manual Filtering
Expanso:
Checkmark Built-in, Automated Filtering

Time to Insights

Traditional Stack:
Slow
Expanso:
Checkmark Real-Time

Stack Flexibility

Traditional Stack:
Rigid, Vendor-Locked
Expanso:
Checkmark Flexible, works with nearly every vendor

Cost Efficiency

Traditional Stack:
Increases rapidly with the amount of stored data
Expanso:
Checkmark Up to 80% Cost Reduction

Use Cases Across Industries

Where Expanso Helps
Multi-Region Retail
Process POS logs locally, route per jurisdiction
Financial Services
Filter PII/PCI at edge, maintain audit trails
Healthcare
Process HIPAA logs locally, mask PHI
Manufacturing & IIoT
Analyze production logs per facility
Telecommunications
Process CDRs regionally, filter noise
IoT Fleet Management
Filter telemetry at edge, route alerts

Better Observability, Lower Costs

Benefit

  • 50-70% Volume Reduction
    50-70% Volume Reduction
  • 16× Faster Queries
    16× Faster Queries
  • 50% Faster Onboarding
    50% Faster Onboarding

What You Get

  • Filter at source before ingest charges
    Filter at source before ingest charges
  • Policy-driven-new services inherit rules
    Policy-driven-new services inherit rules
  • Works with Splunk, Datadog, Elastic, New Relic
    Works with Splunk, Datadog, Elastic, New Relic
Background

Show us your observability stack

We'll show you how to cut SIEM costs 50-70%, improve query times 16×, and process logs at the source-enhancing your existing platforms.