Real-Time Anomaly Detection
Nikhil Singh
Real-Time Anomaly Detection
Stop AWS "Bill Shock" Before It Hits Your Bottom Line
Native AWS tools tell you what you spent yesterday. CloudInfix AI detects unusual spending patterns the moment they occur, identifying the root cause so you can act instantly.
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Why Reactive Monitoring Fails
Cloud Visibility Shouldn't Be a RetrospectiveTrap
In modern, auto-scaling cloud environments, a single rogue script, an unchecked dev environment, or a misconfigured Lambda function can destroy a quarterly budget in hours.
$1.50$1.25$1.00$0.75$0.502026-03-272026-03-282026-03-292026-03-30INITIAL SPARK
EC2 Service
ANOMALY DETECTED
+240% cost spike
(+18% over threshold)
BUDGET RISK ALERT Slack Notified
$24,300 Forecast
Prediction Confidence
94%
AI Confidence MODEL: LSTM-V4
PROJECTED SPEND
$24,30018% over budget
False Positive: Ignored Reason: Scheduled Load Test
ROOT CAUSE IDENTIFIED
Process: python3 data_pipeline.py
User: ubuntu@ip-10-0-12-45Trigger: Auto-scale job
CPU USAGE
92%
INSTANCES
12 → 36
Detect Issues Instantly
Identify cost spikes the moment they happen—not days later. Stay ahead of runaway resources and unexpected usage.
Predict Before You Overspend
Forecast future spend in real time and see budget risks before they hit. Make proactive decisions with confidence.
Understand the Root Cause
Instantly trace anomalies back to the exact service, user, or deployment—no more digging through logs.
Real-Time Detection
Catch Cost Spikes As They Happen
COST TRAJECTORY MATRIX
PROJECTED ANOMALY
⚠️ ANOMALY DETECTED2026-03-30 | 14:02 UTC
$1.2172
2026-03-272026-03-282026-03-292026-03-302026-03-31
24H HIGH
$1.2172 -22.3%
24H LOW
$0.4907 -04.2%
VIEW NODE DETAILSAUTOMATED MITIGATION
Most tools tell you what went wrong—hours later. Cloudinfix monitors your infrastructure in real time, detecting abnormal spend patterns instantly so you can respond before costs escalate.
Detect Spikes in Real Time — Detects cost spikes the moment they occur across your infrastructure.
Continuous Monitoring — Tracks spend patterns across services, teams, and workloads in real time.
Behavior Analysis — Identifies unusual spikes, drops, and irregular usage instantly.
Immediate Actionability — Enables teams to respond before costs escalate further.
Log-Linked Attribution (CORE USP)
From Spike to Root Cause — Instantly
Every anomaly is automatically mapped to its source. Cloudinfix surfaces Ubuntu syslogs and system activity in real time, so you know exactly which process, service, or user triggered the spike.
Source-Level Mapping — Links every anomaly to the exact service, process, or user.
Real-Time Log Correlation — Surfaces Ubuntu syslogs alongside cost spikes for instant context.
Zero Guesswork Debugging — Eliminates manual investigation with clear root cause visibility.
Faster Resolution — Helps teams fix issues quickly and reduce cost impact.
UBUNTU-SYSLOGS-NODE-04
Feb 14 09:12:01 node-04 systemd[1]: Starting Periodic Command Scheduler...
Feb 14 09:12:04 node-04 systemd[1]: Started Periodic Command Scheduler.
Feb 14 09:12:10 node-04 kernel: [4812.33] intel_pstate: HWP enabled
Feb 14 09:13:45 node-04 kubelet[1243]: I0214 09:13:45.340 pod_workers.go:1290] "Syncing pod" pod="kube-proxy-8x"
Feb 14 09:14:02 node-04 kube-proxy[24901]: CRITICAL resource exhaustion detected in iptables sync
Feb 14 09:14:03 node-04 kube-proxy[24901]: W0214 09:14:03.111 proxier.go:1538] Failed to update service endpoints
Feb 14 09:14:05 node-04 systemd[1]: compute-optimization.service: Main process exited, code=exited, status=1/FAILURE
Streaming logs in real-time...
Predictive Burn Alerts
Know Before You Overspend
Forecasting Engine
Refreshed: 14:00 UTC • Accuracy: 98.4%
ACTUAL PROJECTED
BUDGET THRESHOLD $11,500
DAY 01DAY 10CURRENTDAY 20DAY 30
MONTH-TO-DATE
$7,240.45
FORECASTED MONTH-END
$12,450.00
PREDICTED OVERRUN
+$950.00
Our machine learning engine forecasts your month-end cloud spend every hour. If your burn rate indicates a budget overrun, you’ll get proactive alerts via Slack or WhatsApp—before the cost hits.
Live Spend Forecasting — Predicts month-end cloud costs based on current usage trends.
Dynamic Projections — Continuously updates forecasts with real-time data.
Proactive Risk Alerts — Notifies teams before budgets are exceeded.
Early Decision Making — Enables timely actions to avoid cost overruns.
Anti-False Positive Engine
Alerts That Actually Matter
Cloudinfix understands your infrastructure behavior. It learns deployment cycles, scheduled jobs, and traffic patterns—so it won't trigger alerts during expected spikes like load tests or backups.
Behavior Learning — Understands deployment cycles, traffic patterns, and usage trends.
Context Awareness — Recognizes expected spikes like load tests and backups.
Noise Reduction — Filters out irrelevant alerts to reduce alert fatigue.
Actionable Signals Only — Ensures teams receive only meaningful, high-impact alerts
Intelligence Pulse FeedREAL-TIME STREAM
SUPPRESSED04:22:01 UTC
Spike in Network Ingress: US-EAST-1
Identified as Scheduled Load Test. Signature matches known pattern 2532.
DETECTED04:22:01 UTC
Unusual DB Write Pattern
Anomaly detected in RDS-Main. No matching suppression rules found.
SUPPRESSED04:22:01 UTC
Spike in Network Ingress: US-EAST-1
Identified as Scheduled Load Test. Signature matches known pattern 2532.
DETECTED04:22:01 UTC
Unusual DB Write Pattern
Anomaly detected in RDS-Main. No matching suppression rules found.
SUPPRESSED04:22:01 UTC
Spike in Network Ingress: US-EAST-1
Identified as Scheduled Load Test. Signature matches known pattern 2532.
DETECTED04:22:01 UTC
Unusual DB Write Pattern
Anomaly detected in RDS-Main. No matching suppression rules found.
Identified Patterns
Weekly DB Maintenance
Log Rotation Cluster-A
Configure Custom Rule
ACTIVE SUPPRESSION RULES
Production Load Test ACTIVE
API Doc Gen Task IDLE
How It Works
From Raw Cloud Data to Actionable Insights
A simple, automated pipeline that transforms complex AWS billing into clear, real-time decisions.
MONITOR
Continuously track cloud behavior
Stream AWS billing and usage data in real time
Establish baseline spending patterns automatically
Monitor across services, teams, and accounts
LIVE MONITORING
EC2 HEALTH99.8%
S3 STORAGE1.2 PB
42.5k /sec
LAMBDA THROUGHPUT
DETECT
Identify anomalies instantly
Detect unusual spikes, drops, or irregular patterns
Compare against historical trends and expected behavior
Catch misconfigurations, leaks, or unexpected traffic
SYSTEM LATENCY 1,402 ms
SPIKE DETECTED
DIAGNOSE
Understand the root cause
Pinpoint the exact service, team, or feature responsible
Correlate anomalies with deployments or usage changes
Get contextual insights, not just alerts
Spike caused by increased compute usage after deployment v2.4.1
ACT
Resolve before costs escalate
Get real-time alerts with actionable recommendations
Fix issues quickly and prevent recurrence
Optimize cloud usage and reduce unnecessary spend
ACTIONABLE RECOMMENDATIONS
Scale up EC2 instances
Deploy 4 additional t3.large...
Enable auto-scaling group
Automate instance management...
"Lozyy redefines the moving experience by ensuring your home accessories are handled with care and offering secure, temporary storage solutions for a seamless transition between locations."
Vikas Pilania
FOUNDER
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Posted Oct 28, 2026
Detects cost anomalies in real time, maps spikes to root causes via log correlation, and forecasts spend to prevent unexpected bill overruns.
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