DevOps & Cloud

You're flying blind — finding out about outages from customers instead of your monitoring

We deploy comprehensive infrastructure monitoring with Prometheus, Grafana dashboards, and PagerDuty-integrated alerting so your team knows about problems before users do.

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The challenges you're facing

No monitoring in place — learning about server failures when customers complain or services stop responding

Basic uptime checks that don't catch performance degradation before it becomes a user-visible outage

Alert noise so high from misconfigured monitoring that engineers ignore everything — including real incidents

Production-Grade Monitoring with Meaningful, Actionable Alerts

We deploy a complete monitoring stack: Prometheus for metrics collection, Grafana for dashboards, Alertmanager for alert routing, Loki for log aggregation, and synthetic monitoring for external endpoint validation. Alerts are tuned to alert on symptoms that affect users (not just noisy system metrics) and routed to the right people with the right priority at the right time.

What you get

Monitoring Requirements Scoping

Define what to monitor (services, SLOs, infrastructure), who to alert, and how to classify alert severity.

Prometheus & Exporters Deployment

Deploy Prometheus with appropriate exporters for servers, containers, databases, and cloud resources.

Grafana Dashboard Build

Build service-specific and infrastructure dashboards: RED method for services, USE method for infrastructure.

Alert Configuration & Tuning

Configure Alertmanager with routing, on-call schedules, and alert tuning to achieve low false positive rate.

Technologies & tools

PrometheusGrafanaAlertmanagerLokiPagerDutyBlackbox ExporterNode ExporterOpenTelemetry

Case study — anonymised

E-commerce Platform — AWS Infrastructure

Before

No monitoring beyond basic CloudWatch. 3 production incidents in 2 months discovered by customers. Average time-to-detection: 23 minutes. No performance baseline existed.

After

Full Prometheus/Grafana/Loki stack deployed. SLO-based alerting with PagerDuty integration. Synthetic monitoring from 5 global regions.

Mean time to detect reduced from 23 minutes to 2 minutes, 95% of incidents detected by monitoring before any customer impact, false positive alert rate under 5%

Frequently Asked Questions

Common questions from enterprise and mid-market teams across India and internationally.

Should we use Prometheus/Grafana or a managed service like Datadog or New Relic?

Open-source (Prometheus/Grafana) is free to run and fully controllable — ideal if you have engineers to operate it. Managed services (Datadog, New Relic, Grafana Cloud) are higher cost but zero operational overhead. For teams without dedicated SRE capacity, managed services are often more cost-effective at scale despite higher tool costs.

What are SLOs and should we implement them?

Service Level Objectives (SLOs) are availability and performance targets for your services (e.g., '99.9% of requests complete in under 200ms'). Alerting on SLO burn rate is far more meaningful than alerting on raw CPU percentage — because it directly correlates to user experience. We recommend implementing SLOs from the start.

How do you prevent alert fatigue?

Alert fatigue comes from alerting on the wrong things. We follow Google SRE principles: only alert on things that require human action, page only for things that are urgent AND user-impacting, and send everything else to a ticket or log. We tune alert thresholds based on 2–4 weeks of baseline data after deployment.

Can monitoring detect performance degradation before an outage?

Yes. This is the core value of proper monitoring. By alerting on SLO burn rate, request error rate increases, and response time p99 degradation, you typically have 30–120 minutes of warning before a degradation becomes a full outage. Reactive monitoring (uptime checks) catches outages. Proactive monitoring catches the problems before they become outages.

Ready to get started?

Tell us about your situation and we'll respond with a tailored assessment within one business day.