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Case Study

Building an Observable Platform for a Rapidly Scaling SaaS Business

Enabling Engineering Teams with End-to-End Observability Across Kubernetes, Cloud Infrastructure, and Applications

SaaS
200+ Employees
AWS
5 Weeks
78%
Reduction in MTTD
25 min
Mean Time to Resolution
(Previously 2.5 Hours)
65%
Reduction in Alert Noise
100%
Critical Service Visibility
99.95%
Production Availability
40%
Improvement in Engineering Productivity
Executive Summary

As the organization expanded its cloud-native platform, engineering teams struggled to maintain visibility into increasingly distributed services. Critical production incidents required engineers to manually inspect logs across multiple systems, correlate infrastructure metrics, and investigate application behavior independently.

The absence of centralized observability resulted in delayed incident detection, alert fatigue, inconsistent monitoring standards, and longer recovery times.

NirvahaTech designed and implemented a comprehensive observability platform based on open standards and cloud-native tooling. The solution unified metrics, logs, traces, dashboards, and intelligent alerting into a single engineering experience, enabling proactive monitoring and faster incident response.

Customer Profile
Industry
SaaS
Employees
200+
Engineering Team
45 Engineers
Cloud Provider
AWS
Platform
Kubernetes (Amazon EKS)
Deployment Model
Microservices
Production Regions
Multi-AZ
Business Challenge

Where they were stuck

Business Challenges
  • Production incidents required multiple engineering teams to investigate independently.
  • Monitoring tools operated in silos with no unified dashboard.
  • Alert fatigue caused important incidents to be overlooked.
  • Root cause analysis relied heavily on manual investigation.
  • Limited visibility into application performance affected customer experience.
Technical Challenges
  • Logs distributed across multiple systems
  • No centralized metrics collection
  • Lack of distributed tracing
  • Kubernetes cluster health difficult to monitor
  • Missing application-level observability
  • Excessive alert noise
  • No service-level objectives (SLOs)
  • Reactive incident management
Objectives
Centralize logs, metrics, and tracesStandardize monitoring practicesReduce incident response timeImprove production visibilityEnable proactive alertingDefine SLOs and SLIsImprove engineering confidenceSimplify troubleshooting
Solution Overview

NirvahaTech designed a cloud-native observability platform using open-source technologies integrated with AWS services. The implementation provided a single source of truth for engineering teams, enabling complete visibility across infrastructure, applications, and platform services.

OpenTelemetry instrumentation
Prometheus metrics collection
Grafana dashboards
Loki centralized logging
Tempo distributed tracing
Kubernetes monitoring
CloudWatch integration
Intelligent alert routing
Service health dashboards
SLO-based monitoring
Incident response workflows
Solution Architecture

How it all fits together

Applications
OpenTelemetry SDK
OpenTelemetry SDK
Amazon EKS Cluster
Amazon EKS Cluster
Node Exporter
Node Exporter
kube-state-metrics
kube-state-metrics
cAdvisor
cAdvisor
Prometheus
Prometheus
Loki
Loki
Tempo
Tempo
Grafana Dashboards
Grafana Dashboards
Amazon CloudWatch
Amazon CloudWatch
Alertmanager
Alertmanager
Slack Notifications
Slack Notifications
Engineering Team
Implementation Timeline

5 Weeks, start to go-live

1
Week 1
Discovery & Observability Assessment
2
Week 2
Architecture Design & Instrumentation Strategy
3
Week 3
Metrics, Logs & Traces Implementation
4
Week 4
Dashboard Creation & Alert Optimization
5
Week 5
SLO Definition, Testing & Production Rollout
Technology Stack

What was actually used

Cloud
AWS
AWS
Amazon EKS
Amazon EKS
Amazon CloudWatch
Amazon CloudWatch
IAM
IAM
Observability
OpenTelemetry
OpenTelemetry
Prometheus
Prometheus
Grafana
Grafana
Loki
Loki
Tempo
Tempo
Alertmanager
Alertmanager
Kubernetes
kube-state-metrics
kube-state-metrics
Node Exporter
Node Exporter
cAdvisor
Collaboration
Slack
Slack
GitHub Actions
GitHub Actions
Business Outcomes

Before vs. after

Mean Time to Detect
45 Minutes10 Minutes
Mean Time to Resolution
2.5 Hours25 Minutes
Alert Noise
HighReduced by 65%
Dashboard Coverage
Limited100% Critical Services
Production Visibility
FragmentedUnified
Incident Investigation
ManualCentralized
Engineering Highlights
End-to-End ObservabilityOpenTelemetry InstrumentationCentralized LoggingDistributed TracingKubernetes MonitoringSLO & SLI FrameworkIntelligent AlertingInfrastructure MonitoringApplication Performance MonitoringProduction ReadinessRoot Cause AnalysisIncident Response Optimization
Business Impact

The organization transitioned from reactive production support to a proactive engineering model driven by observability. Engineering teams gained real-time visibility into infrastructure health, application performance, and service dependencies through unified dashboards. Centralized telemetry and intelligent alerting significantly reduced investigation time, while distributed tracing enabled faster root cause analysis across microservices. The observability platform became a core component of the engineering ecosystem, supporting higher deployment confidence, improved customer experience, and scalable operations as the platform continued to grow.

The observability platform transformed how we operate in production. Instead of searching across multiple tools, our teams now have a single, reliable view of application health, enabling faster decisions and more confident releases.

Engineering Manager

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