Multi Cloud Monitoring
Unified observability platform across AWS, Azure, and GCP — centralised dashboards, cross-cloud alerting, distributed tracing, log aggregation, and performance monitoring for multi-cloud environments.
Why Businesses Need This Service
Multi-cloud environments generate siloed observability data — CloudWatch in AWS, Azure Monitor in Azure, Cloud Monitoring in GCP. Teams switch between consoles, miss cross-cloud performance correlations, and lose critical context during incidents. Unified multi-cloud monitoring eliminates these silos with a single pane of glass, consistent alerting, and the distributed tracing needed to diagnose incidents that span cloud boundaries.
Key Capabilities
Comprehensive capabilities to address your cloud needs
Unified observability platform deployment (Datadog, Grafana, New Relic) across all cloud providers
Cross-cloud centralised logging with ELK Stack or cloud-native log aggregation
Distributed tracing implementation with OpenTelemetry across multi-cloud services
Intelligent alerting with cross-cloud correlation rules and noise reduction
Infrastructure-as-Code monitoring: Terraform-provisioned dashboards and alert policies
SLO/SLI framework design and error budget tracking across cloud environments
Technologies & Platforms
Industry-leading tools and platforms we use to deliver exceptional results
Technologies
Platforms
Business Outcomes
Measurable results that drive business value
Single pane of glass for all cloud environments — no console switching during incidents
Mean time to detect (MTTD) reduced by 60–80% with intelligent cross-cloud alerting
Mean time to resolve (MTTR) reduced by 40–60% with correlated observability data
Proactive capacity alerts prevent performance degradation before it impacts customers
SLO tracking with automated error budget burn-rate alerts
Common Use Cases
Real-world scenarios where this cloud service delivers value
Unified monitoring platform for multi-cloud enterprise environments
Cross-cloud incident detection and correlation with automated alert routing
Distributed tracing for microservices spanning AWS and Azure
Centralised log management for compliance and security analytics
SLO/SLI framework implementation for reliability engineering
Kubernetes multi-cluster observability across EKS, AKS, and GKE
Typical Architecture
Key components and layers in a typical cloud architecture
Metrics Aggregation Layer
Centralised Log Store
Distributed Trace Collector
Alert Manager
Unified Dashboard Layer
On-call & Incident Management
Our Implementation Process
A systematic approach that ensures timely delivery and exceeds expectations
Observability Assessment
Audit current monitoring coverage across all clouds, identify blind spots, assess alerting quality (noise vs. signal), and map the monitoring gaps causing MTTD/MTTR issues.
Platform Design
Select the right observability platform for your environment, design the metrics hierarchy, log schema, and tracing instrumentation strategy across services.
Instrumentation
Deploy monitoring agents and collectors across all cloud environments, implement OpenTelemetry instrumentation in applications, and establish consistent metric and log naming conventions.
Dashboard & Alerting
Build unified dashboards covering all cloud infrastructure and application performance, design intelligent alert policies with proper thresholds and routing to reduce noise.
SLO Implementation
Define SLIs and SLOs for critical services, implement error budget tracking, set burn-rate alerts, and establish the on-call processes to act on reliability data.
Industries We Serve
Our cloud services deliver value across diverse industries
SaaS Platforms
Fintech
Healthcare
Ecommerce
Media
AI / Data Platforms
Cloud Platforms & Tools
Industry-leading platforms and tools we leverage to deliver exceptional results
Technologies
Platforms
Example Success Story
See how we've helped businesses achieve success with cloud solutions
Client Challenge
A SaaS platform running across AWS (primary) and Azure (DR) had no unified monitoring. Teams used CloudWatch and Azure Monitor separately. Cross-cloud incidents took 45+ minutes to diagnose because engineers lacked context about which cloud was the failure source.
Cloud Solution Implemented
We deployed Datadog as the unified observability platform, integrated all AWS and Azure services, implemented distributed tracing with OpenTelemetry across 35 microservices, designed correlated dashboards, and established SLOs with error budget tracking for 12 critical user journeys.
Business Results
MTTD reduced from 45 minutes to 8 minutes
MTTR reduced from 3.2 hours to 52 minutes
Alert noise reduced by 73% with correlation rules
100% trace coverage across all services
12 critical SLOs defined and tracked with error budgets
Frequently Asked Questions
Common questions about Multi Cloud Monitoring
Multi-cloud monitoring provides unified observability across multiple cloud providers — typically AWS, Azure, and GCP. It consolidates metrics, logs, and traces from all environments into a single platform, enabling consistent alerting, faster incident response, and cross-cloud performance analysis.
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