We design, implement, and operate cloud-native observability stacks using AWS-native tools and OpenTelemetry.
Traditional monitoring tells you when something is broken. Observability tells you why—and helps you find problems you didn't know to look for.
We build observability stacks that give you deep visibility into your AWS infrastructure using cloud-native tools: CloudWatch, X-Ray, Amazon Managed Prometheus, Amazon Managed Grafana, and OpenSearch.
The result: faster incident response, proactive problem detection, and the ability to answer questions about your system you've never asked before.
A four-phase approach to building world-class observability.
Audit existing monitoring, identify gaps, and understand your infrastructure landscape
Define SLAs, compliance needs, budget constraints, and team capabilities
Define SLIs and SLOs using the VALET framework with error budgets and burn rates
Design your observability stack with the right tools for your scale and needs
Deploy CloudWatch, X-Ray, AMP, AMG, and OpenSearch using Terraform or CDK
OpenTelemetry setup, CloudWatch Agent config, and application-level tracing
We use the VALET framework to define meaningful SLOs that actually reflect user experience:
Request throughput capacity. Can your system handle expected load?
Service uptime percentage. What ratio of requests succeed?
Response time at p50, p90, p99. How fast is fast enough?
Error rates by type. What's your acceptable failure rate?
Manual intervention count. How much operational toil exists?
AWS-native observability tools configured for your environment.
Metrics, logs, and alarms with anomaly detection. Custom dashboards and Contributor Insights for deep analysis.
Distributed tracing for microservices. Service maps, trace analysis, and latency insights across your architecture.
Scalable Prometheus-compatible metrics for container workloads. PromQL queries without the operational overhead.
Beautiful dashboards with enterprise features. SSO integration, alerting, and cross-account visibility.
Log analytics at scale. Full-text search, anomaly detection, and long-term retention for compliance.
Vendor-neutral instrumentation. Collect traces, metrics, and logs with ADOT (AWS Distro for OpenTelemetry).
Third-party observability tools are expensive—often costing more than the infrastructure they monitor. We help you migrate to AWS-native tooling without sacrificing capability.
Flexible models based on where you are in your observability journey.
Understand your current state and get a roadmap for observability excellence.
Full design and deployment of your AWS-native observability stack.
Move from Datadog, New Relic, or Splunk to AWS-native tooling.
Machine learning that delivers genuinely useful insights, not just dashboards.
ML models learn your system's normal behavior and alert on meaningful deviations—no more threshold tuning.
When incidents occur, AI traces causality across your infrastructure to identify the true root cause, not just symptoms.
Ask questions in plain English: "Why is my API slow?" or "What changed in the last hour?" and get relevant answers.
Identify trends that indicate impending issues—capacity exhaustion, performance degradation—before they impact users.
Automatically group related alerts into incidents, reducing noise and helping you focus on what matters.
AI-assisted creation of remediation runbooks based on incident patterns and resolution history.
Explore a sample VALET dashboard showing the metrics and visualizations we deploy for clients.
Let's discuss how AWS-native observability can give you deep visibility into your infrastructure.
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