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LedgerOS

Cloud cost intelligence that turns infrastructure spend into a strategic advantage — not a monthly surprise.

Next.jsFinOps2024SaaS
DB spend +23% WoW — 2 services flaggedReview
LEDGER OSCloud Cost Analytics
PERIODDec 2024
$84,392total spend 2.1%
vs last month +$9,204
services 47+3
anomalies 3
COST TREND6 months
$84.4k
AugSepOctNovDecJan
SERVICE BREAKDOWN
SERVICE% OF SPENDCOSTΔ MOM
Compute
54.3%
$38,204
+6.2%
Storage
21%
$18,020
+15.1%
Network
14.7%
$16,100
-3.2%
Database
12%
$10,800
+23.4%
CDN
8.2%
$6,920
+2.8%
Lambda
5.1%
$4,310
-8.5%
Cache
3.8%
$3,210
+18.9%
Other
0.9%
$738
-1.2%
RECENT ANOMALIES
Database
Spike detected: +23.4% WoW, 8 slow queries
Cache
Eviction rate 18% above baseline
Storage
Increased I/O ops, replication lag +15%

Real-time cost analytics, anomaly detection, and per-team attribution — delivered before the monthly bill arrives, not after.

01

Cloud spend growing undetected

AWS spend was climbing 30% month-over-month with no clear explanation. Finance and engineering were pointing fingers with nothing actionable in between.

02

Spikes caught at billing time

No anomaly detection meant overruns went unnoticed until the bill arrived. Post-mortems on damage already done, every month.

03

No team-level accountability

Without per-team attribution, no one owned their cost footprint. Engineering had no visibility, finance had no leverage.

Solution

Cost visibility before the damage is done.

Real-time anomaly detection

Statistical deviation thresholds tuned to each team's spend baseline. Alerts fire within hours of a spike — not at the end of the billing cycle.

Per-team attribution

Every team sees their cost footprint broken down by service. Accountability shifts from a finance problem to an engineering culture.

Trend forecasting

Service-level trend forecasting lets teams anticipate spend before it compounds. Decisions made on current data, not last month's.

Stack
Next.jsAWS Cost Explorer APIRechartsTypeScriptVercel
Impact

Engineering teams now own their cost footprint. Anomalies caught in hours, not billing cycles. The monthly review went from post-mortem to forward-looking strategy.

0
reduction in wasted cloud spend within 60 days
0
in annual savings identified from first cost audit
0
anomaly detection — was days of manual review

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