Know what is broken before your users do.
Discovering problems through user reports is not an operating model. Dashboards built after the first incident detect the second. We instrument systems from day one — metrics, logs and alerts configured before the first user hits production.
What the problem costs you.
Most infrastructure problems are not caused by the tools chosen. They are caused by how infrastructure is provisioned and managed over time.
Discovering failures through user reports
The first indication of a problem is a support ticket. By the time the team investigates, the blast radius has already expanded.
Dashboards built after incidents
Monitoring that covers what broke last time misses what will break next time. Reactive observability is not observability.
Alerting on the wrong signals
CPU and memory thresholds alert on causes, not symptoms. Teams spend time investigating non-events while real failures go undetected.
No SLIs or error budgets
Without defined service level indicators, every incident is equally urgent. No error budget means no rational basis for prioritizing reliability work.
The observability stack we deliver.
Three pillars — metrics, logs and alerting — configured before the first workload reaches production.
Metrics Collection
Prometheus · ServiceMonitors · PodMonitors · kube-state-metricsPrometheus scrapes workload and cluster metrics from deployment day. Custom metrics exposed via standard /metrics endpoints. No vendor lock-in.
Visualization
Grafana · Pre-built dashboards · Infrastructure + application panelsGrafana dashboards covering Kubernetes cluster health, workload performance and application-level metrics in a single view.
Cloud Monitoring
CloudWatch · Container Insights · Log Insights · AlarmsCloudWatch Container Insights for EKS and ECS workloads. Alarms on latency, error rates and queue depth — not raw CPU.
Alerting
Alertmanager · PagerDuty · Slack · Routing rulesAlert routing by severity and team. On-call receives actionable alerts with runbook links, not raw metric dumps.
SLIs and SLOs
Error budgets · Burn rate alerts · Multi-window alertingService level indicators defined at design time. Error budget burn rate alerts before the budget is exhausted, not after.
Log Management
Structured JSON logs · CloudWatch Logs · Log Insights queriesStructured logging from application startup. Log Insights queries pre-built for the most common failure modes.
How we implement it.
Observability audit
Review what is currently instrumented, what is missing and what alert fatigue exists before adding more noise.
SLI definition
Define service level indicators for each workload — availability, latency, error rate — before writing a single alert rule.
Instrumentation rollout
Deploy Prometheus, configure ServiceMonitors and validate metric collection in staging before production.
Alerting and runbooks
Configure alert routing, build Grafana dashboards and write runbooks for the top failure modes before go-live.
What changes when this is delivered.
Failures detected before user reports
alerting on symptoms, not thresholds
SLIs tracked from day one
not added after the first SLA breach
Mean time to detect reduced
from hours to minutes
On-call receives actionable alerts
with runbook links, not raw metrics
Error budgets defined
rational basis for reliability prioritization
Infrastructure and application in one view
single Grafana instance, no context switching
Observability across cloud and Kubernetes
CloudWatch + CloudTrail on AWS. Prometheus + Grafana + Alertmanager on Kubernetes.
gitops-stack — Cloud observability
- • CloudWatch Logs + Metrics — application and infrastructure
- • CloudTrail — every AWS API call logged and queryable
- • Full audit trail: commit → pipeline → pod → API call
- • Zero static credentials — IAM roles throughout
k8s-devops-platform — Kubernetes observability
- • Prometheus — metrics collection from day one
- • Grafana — dashboards and visualization
- • Alertmanager — alert routing and notification
- • Deployed as part of the initial platform — not added later
Start with an observability review.
Bring your current monitoring setup. We identify what is missing, what is generating noise and what would actually detect your next outage before your users do.