Observability built for clear signals and incident response.
Alert fatigue and blind spots are two sides of the same failure. CirOps builds observability stacks that surface what matters, silence what does not, and give your engineering team the signal they need to respond, not react.
Full-stack
Metrics, logs & traces unified
Incident signals
Aligned to service objectives
AI-assisted
Root cause analysis
The Problem
The two ways monitoring fails
Monitoring gaps usually appear as one of two operating conditions.
Alert Fatigue
High alert volume dominated by noise. On-call engineers mute channels. PagerDuty pages that everyone has learned to dismiss. When everything is urgent, nothing is. The real incident is buried under the routine ones, and nobody sees it until a customer does.
Blind Spots
The opposite problem: monitoring that never fires until something is catastrophically wrong. No trace of the latency spike that was degrading checkout for forty minutes before conversions dropped. No visibility into which service is leaking memory. The first signal is a spike in support tickets.
Both failure modes share a root cause: instrumentation without strategy. Metrics collected but not mapped to outcomes. Alerts configured once and never tuned. Dashboards built for demos, not for the engineer who is paged at 2 a.m.
CirOps designs observability from the on-call perspective, what does the engineer need to see, in what order, to diagnose and resolve an incident quickly.
Capabilities
What CirOps delivers
We engineer the full observability stack, metrics, logs, and distributed tracing, and align it to your system's SLOs.
Metrics Collection & Aggregation
Infrastructure, application, and business metrics unified in a single view.
Structured Logging
Log pipeline design, centralized ingestion, and log-based alerting for events that metrics miss.
Distributed Tracing
End-to-end trace instrumentation with OpenTelemetry, surfacing latency and error patterns across service boundaries.
AWS CloudWatch
Native AWS telemetry tuned and organized, not left in default chaos.
Grafana Dashboards
SLO-aligned dashboards built for operational use, not stakeholder presentations.
SigNoz
Our preferred open-source APM: APM, infra metrics, logs, and distributed traces in one unified interface.
Alerting Strategy
Alert design by severity, routing by role, and suppression logic to reduce noise.
Incident Alerting
PagerDuty / Opsgenie integration, escalation policy design, and runbook linking.
Open-Source First
Why we lead with SigNoz
Commercial observability platforms and self-managed stacks have different cost, retention, and operating tradeoffs. We compare those tradeoffs against your telemetry volume, team capacity, existing commitments, and required service integrations.
SigNoz is an open-source, OpenTelemetry-native observability platform that can run in your cloud environment. It delivers APM, distributed tracing, log management, and infrastructure metrics in a single interface, the same capabilities that drive the cost of commercial platforms up. You own the data, control the retention policy, and pay for compute resources you already manage.
If you are committed to Datadog, Grafana Cloud, or another commercial platform, we work with that stack too. The recommendation follows the audit, not the other way around.
Who It's For
Built for teams that need clearer operational signals
SaaS Platforms
Distributed tracing across microservices, SLO-aligned alerting, and clearer context when service behaviour degrades.
Ecommerce & D2C Teams
Uptime and latency visibility during traffic spikes and peak sale periods, with retention and capacity planned for expected telemetry volume.
Startups & Scale-ups
Teams that have outgrown CloudWatch defaults but have not yet built a coherent observability practice - or are paying for a commercial APM they are barely using.
Our Process
How we build your observability stack
Observability Audit
We review what exists: current metrics, logging setup, alerting configuration, and gaps in coverage. We map the output against your services, SLOs, and on-call workflow. Output: a prioritized instrumentation plan.
Instrumentation Design
We design the observability architecture - which signals to collect, how to structure logs, where to instrument for distributed traces, and how to connect it all to your incident response workflow. OpenTelemetry as the instrumentation layer where applicable.
Stack Implementation
We deploy and configure the full stack: SigNoz or Grafana for visualization, CloudWatch for native AWS telemetry, log pipeline setup, and distributed tracing across your services. Everything is implemented as code - repeatable, version-controlled, and reproducible.
Alert Tuning + Dashboard Build
We build SLO-aligned dashboards and tune alerts to actionable thresholds. Suppression rules reduce recurring noise. Escalation policies route alerts according to the agreed response model. Runbooks are linked directly from alerts so the on-call engineer has context, not just a notification.
AI-Augmented Operations
AI-assisted observability, standard practice
CirOps engineers apply AI-assisted analysis as standard practice across observability engagements. This includes AI-assisted log pattern analysis that surfaces anomalies rule-based alerting would miss, ML-based anomaly detection integrated into CloudWatch and SigNoz alert pipelines, and AI-assisted noise reduction that distinguishes signal from the constant alert volume that causes fatigue.
The result: fewer pages, faster diagnosis, and on-call engineers who trust their alerts.
See how AI-augmented operations work at CirOps →Operating principles
Observability designed for accountable operations
CirOps engineers observability around service objectives, clear alert ownership, and actionable runbooks. Customer outcomes vary by workload and are documented separately when evidence and permission are available.
See our full credentials and proof →FAQ
Frequently asked questions
Start with a clear view of your observability gaps
The free Architecture Review includes your current monitoring and alerting setup - what is instrumented, what is missing, and where the blind spots are. You leave with a concrete observability plan, not a generic report.