Series B HR SaaS
- Challenge
- No distributed tracing; 4-hour MTTR on hiring API.
- Simplileap solution
- OpenTelemetry, Grafana SLOs, and error-budget alerts.
- Outcome
- MTTR 4h → 22 minutes.
// Scale
Monitoring & Analytics Services in Bangalore
APM, error tracking, uptime monitoring, user analytics, and custom dashboards. We instrument your application with the three pillars of observability, metrics, logs, and traces, so you can find and fix production issues before users report them.
// Services
Monitoring & analytics services
- Metrics, logs, and distributed traces
- Structured logging with correlation IDs
- SLO and error budget configuration
- Business and engineering dashboards
- Alert fatigue reduction and calibration
Application Performance Monitoring
APM with distributed tracing and latency analysis.
Error Tracking & Logging
Sentry and structured logging for fast error resolution.
Uptime & System Monitoring
Multi-location uptime checks with status page and alerting.
User Behaviour Analytics
Funnel analysis, session replay, and feature adoption tracking.
Custom Dashboards & Reporting
Grafana and Metabase dashboards for engineering and business.
// Standards
Observability engineering standards
Three pillars of observability
Metrics (numerical time-series), logs (structured event records), and traces (distributed request paths), all three required for production observability, not just metrics.
Alert fatigue prevention
Alerts calibrated against error rate significance, not arbitrary thresholds. Alerts that fire and resolve without action are investigated and removed, they erode on-call trust.
Structured logging
Logs emitted as structured JSON with consistent fields (request_id, user_id, duration, status_code) to enable filtering, aggregation, and correlation across services.
Distributed tracing
OpenTelemetry instrumentation provides end-to-end request tracing across service boundaries, essential for diagnosing latency issues in microservices architectures.
SLOs and error budgets
Service Level Objectives define acceptable reliability targets. Error budgets make the trade-off between reliability and feature velocity explicit and data-driven.
Business metrics alongside technical
Conversion rates, active users, and feature adoption tracked alongside infrastructure metrics. Business impact of incidents visible without switching to separate analytics tools.
// Technology
Monitoring & analytics toolstack
APM
Datadog APMNew RelicDynatraceElastic APMSentry PerformanceHoneycomb
Logging
Datadog LogsGrafana LokiAWS CloudWatch LogsElastic StackLogtailPapertrail
Metrics
PrometheusGrafanaDatadog MetricsInfluxDBOpenTelemetryStatsD
Error Tracking
SentryRollbarBugsnagDatadog Error TrackingHoneybadgerAirbrake
User Analytics
PostHogMixpanelAmplitudeFullStoryLogRocketMicrosoft Clarity
Alerting
PagerDutyOpsGenieDatadog AlertsGrafana AlertingBetter UptimeCheckly
// Process
From observability audit to production-grade visibility
01
Observability Audit
1–2 daysAssess current monitoring coverage, what is monitored, what is not, alert noise level, and MTTD (mean time to detect) for recent incidents. Identify coverage gaps.
// Stack & frameworks
Stack we use for this
Cloud
- AWS / GCP
- Auto-scaling
- Reserved instances
- Cost dashboards
DevOps
- GitHub Actions
- Terraform IaC
- Docker
- Blue-green deploys
Observability
- Datadog / Grafana
- Error tracking
- Uptime monitors
- Executive reporting
// Delivery
Simplileap execution framework
01
Architecture mapping
Dependencies, API contracts, compliance constraints, and performance budgets documented before sprint one.
02
Secure sprints
Two-week increments with GitHub access, demo recordings, and QA checkpoints, client visibility at every stage.
03
QA & handover
Automated tests on critical paths, security review, runbooks, and knowledge transfer to your team.
// Proof
Real deployments from Bangalore
Edtech platform
- Challenge
- GA4, Mixpanel, and warehouse reported conflicting activation metrics.
- Simplileap solution
- Event dictionary, RudderStack taxonomy, dbt models in Snowflake.
- Outcome
- Single KPI definition in QBR; experiment analysis 40% faster.
Healthcare marketing operator
- Challenge
- 47 GTM tags degraded INP to 480ms.
- Simplileap solution
- Tag governance and Consent Mode v2.
- Outcome
- INP p75 back to 188ms.
// Engagement models
How teams engage us
Currency
| Package | Ideal for | Investment | Includes |
|---|---|---|---|
| Managed services AMC | Post-launch platforms | ₹25K – ₹1.5L / month |
|
| DevOps transformation | Engineering teams | Project + retainer |
|
| SLO-backed operations | Revenue-critical apps | Scoped within AMC range |
|
// Company and service positioning
Company and Service positioning is reviewed for production delivery standards by Harsha Parthasarathy (Co-Founder, Strategy & Operations 24+ years IT veteran, IBM, Global Delivery, Program Management) and Keshav Sharma (Co-Founder, Engineering and Lead Architect, Full-stack engineering, product delivery and technical standards).
CIN
AAU-8582
Startup India
DIPP83124
Founded
November 2020
Office
Residency Rd, Bengaluru, India
// FAQ
Common questions about monitoring and analytics
What is the difference between monitoring and observability?+
Monitoring tracks known failure modes (is this specific thing working?). Observability allows you to understand unknown failure modes by interrogating system state through metrics, logs, and traces. You need both, monitoring for known patterns, observability for novel incidents.
Which APM tool do you recommend?+
Datadog for teams who want a comprehensive platform (APM, logs, metrics, alerting, dashboards in one place). Sentry for cost-effective error tracking with good developer experience. New Relic for existing New Relic users. OpenTelemetry for vendor-neutral instrumentation that works with any backend.
How do you design alerts that are not noisy?+
Alert on symptoms, not causes (alert on error rate increase, not CPU spike). Set thresholds based on historical percentiles, not round numbers. Track alert-to-action ratio, alerts that don't result in action are either misconfigured or should be notifications, not pages.
What are SLOs and error budgets?+
SLO (Service Level Objective) is a target reliability level (e.g. 99.9% uptime). Error budget is the allowed downtime per month (0.1% of 30 days = 43 minutes). When error budget is consumed, reliability work takes priority over feature work. This makes reliability trade-offs explicit.
Can you set up user behaviour analytics alongside technical monitoring?+
Yes, we implement PostHog or Mixpanel alongside technical APM so business metrics (feature adoption, funnel conversion) are visible in the same workflow as technical metrics. This makes the business impact of incidents immediately quantifiable.