See Everything Happening Across Your Applications, Infrastructure, and Cloud
Cloud observability brings your metrics, logs, and traces into one place, so your team knows what's wrong before customers tell you. We help you monitor applications, infrastructure, and cloud services end to end, and get to the root cause fast when something breaks.
What Is Cloud Observability?
Cloud observability is the ability to understand what's happening inside your systems by examining what they output — metrics, logs, and traces — rather than guessing from the outside. Monitoring tells you something is wrong. Observability tells you why. A well-built observability practice covers all three at once.
Metrics
Numerical signals over time — CPU, memory, request rate, error rate — that show trends and trigger alerts.
Logs
Detailed, timestamped records of what actually happened inside an application or system.
Traces
The path a single request takes across services, showing exactly where time is spent and where it breaks.
Why Cloud Observability, Not Just Monitoring
Native cloud dashboards tell you about one provider. Real operations run across several — and across the boundary is exactly where visibility usually breaks down.
One View, Every Cloud
Whether your workloads run on a single cloud or span AWS, Azure, and GCP, we bring the telemetry into one place instead of leaving your team tabbing between provider consoles.
Built on What You Already Run
We work with your existing cloud-native tooling — CloudWatch, Azure Monitor, Cloud Monitoring — and layer Prometheus, Grafana, and OpenTelemetry on top where it adds real value.
Visibility That Scales With You
As you add accounts, regions, and services, your observability setup keeps up — cost-aware retention and label hygiene from day one, not a rebuild eighteen months in.
Full-Stack Monitoring Across Everything You Run
From a single application to a distributed multi-cloud environment, we build monitoring and observability services around what you actually run, not a generic template.
Application Monitoring
Application performance monitoring (APM) for response times, error rates, throughput, and user-facing performance.
Infrastructure Monitoring
Servers, containers, storage, and networking — resource utilization and health across your full infrastructure footprint.
Kubernetes Observability
Cluster, node, pod, and workload-level visibility for Kubernetes environments — see our Kubernetes page for platform-level depth.
Cloud Service Monitoring
Native visibility into managed cloud services — databases, queues, serverless functions, and storage.
Database Monitoring
Query performance, connection pools, replication lag, and resource utilization across your database layer.
Network Monitoring
Latency, packet loss, and connectivity across services, regions, and cloud providers.
The Three Pillars, Working Together
Metrics, logs, and traces mean the most when they're connected, not scattered across separate tools with no way to jump from one to another.
Metrics Monitoring
Collect and visualize system and application metrics in real time, with thresholds and trends that matter to your workloads.
Centralized Logging
Centralized logging across applications, infrastructure, and containers into one searchable, correlated view.
Distributed Tracing
Distributed tracing across microservices to follow a single request end to end and see exactly where latency or failures occur.
OpenTelemetry & Standardization
Standardize telemetry collection using open instrumentation so you're not locked into a single vendor's data format.
Alerts That Matter, Not Alerts That Overwhelm
The point of alerting isn't more alerts — it's the right alert, to the right person, with enough context to act on it immediately.
uptime.check · 30s interval
24/7 Monitoring
Continuous monitoring across applications and infrastructure, not just during business hours.
alertmanager · dedup + route
Intelligent Alerting
Alert routing and thresholds tuned to reduce noise, so teams respond to genuine issues instead of chasing false positives.
raw signals
actionable
aiops.model · anomaly score
AI-Powered Anomaly Detection
AIOps and AI-powered observability to catch unusual patterns automatically, before they cross a manually defined threshold.
grafana.dash · role-based
Dashboards & Visualization
Role-specific dashboards so engineers, platform teams, and leadership each see the view that matters to them.
Find the Root Cause, Not Just the Symptom
Go beyond alerts to understand why an issue occurred. Correlate telemetry across applications, infrastructure, services, and dependencies to quickly identify the source of performance degradation or failures.
Dependency Mapping
Understand how applications, APIs, services, databases, and infrastructure components are connected.
Issue Correlation
Connect related metrics, logs, traces, and alerts to identify patterns behind an incident.
Application Troubleshooting
Investigate slow requests, errors, failed transactions, and application troubleshooting for performance issues.
Infrastructure Troubleshooting
Identify resource bottlenecks, network issues, capacity constraints, and infrastructure failures.
Service-Level Analysis
Trace issues across interconnected services to determine where a failure originates and how it impacts the wider environment.
Faster Resolution
Give engineering teams the context needed to move from detection to diagnosis and resolution with less manual investigation.
topology.map
trace_id: a91f2 · 4 spans
One View, Regardless of Where Your Workloads Run
Multi-cloud observability matters most when it matters least to notice — when an incident spans more than one environment and your team doesn't have to guess where to look first.
// Native and third-party observability tooling across all three major cloud providers, correlated into one view.
// Consistent visibility across on-premises infrastructure and cloud environments, without a blind spot at the boundary.
// Track requests and dependencies that span providers, so a cross-cloud issue doesn't fall into a gap between two separate toolsets.
// Observability data that feeds directly into recovery decisions — see our Disaster Recovery Services page for the broader recovery strategy this supports.
From Blind Spots to Full Visibility
A structured path to observability, not a tool dropped in and left to figure itself out.
Discover
Map applications, infrastructure, and existing monitoring tools to identify coverage gaps.
Instrument
Deploy metrics, logging, and tracing instrumentation across applications and infrastructure.
Centralize
Bring telemetry into a unified platform so teams stop switching between disconnected tools.
Alert
Configure alerting thresholds and routing tuned to your actual operational priorities.
Analyze
Establish root cause analysis workflows and dashboards for ongoing use.
Optimize
Continuously refine signal quality, alert thresholds, and coverage as your environment evolves.
Observability Data Should Save You Money, Not Just Explain Outages
The same telemetry that helps you troubleshoot an incident also tells you exactly where you're overprovisioned — observability cost optimization turns monitoring data into a capacity planning and cost-reduction tool, not just an incident-response one.
~35%
lower observability run-rate
Capacity Planning
Use real utilization trends to forecast infrastructure needs instead of guessing at headroom.
Performance Optimization
Identify slow queries, inefficient code paths, and resource contention before they become customer-facing problems.
Cost-Aware Observability
Right-size monitoring coverage and retention so observability tooling itself doesn't become a line-item cost problem — see our AWS Cost Optimization and FinOps pages for the broader cost picture.
What Better Observability Actually Delivers
Faster Incident Resolution
Cut the time from alert to root cause by correlating signals instead of searching multiple tools manually.
Fewer Customer-Facing Outages
Catch degradation before it becomes a full outage, using trend data and anomaly detection.
Lower Monitoring Tool Sprawl
Consolidate fragmented dashboards and logging tools into one coherent observability practice.
Better Capacity Decisions
Make infrastructure sizing and scaling decisions based on real data, not guesswork.
Reduced On-Call Fatigue
Fewer, better-targeted alerts mean engineers get paged for things that actually need attention.
Clearer Reporting for Leadership
Translate technical reliability data into business-relevant uptime and performance reporting.
Cloud Observability Services
From a single unified dashboard to full observability engineering across your cloud estate.
Unified Observability
Bring application, infrastructure, Kubernetes, and cloud telemetry into one unified platform, giving your teams a complete view of system health and performance.
Proactive Reliability Monitoring
Move beyond reactive troubleshooting with continuous monitoring and intelligent signals that flag performance degradation, failures, and reliability risks before they become major incidents.
Application & Infrastructure Visibility
Monitor critical applications, services, infrastructure, and dependencies across every cloud you run on, so a change in one layer doesn't surprise you in another.
Observability Engineering
Cloud observability consulting and implementation services that design telemetry, dashboards, alerts, and workflows around your business-critical workloads.
Trusted by forward-thinking teams
Ready for One View Across
Every Cloud?
Talk to our SRE team about unifying observability across AWS, Azure, GCP, or your hybrid environment.