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On this page
  • About OpenTelemetry
  • Advanced Observability Suite Use Cases
  • Real-Time Monitoring and Observability
  • End-to-End Tracing and Dependency Mapping
  • Performance Optimization
  • Alerting and Incident Management
  • User Experience Insights
  • Custom Business and Operational Metrics
  • Other Duplo-Specific Use Cases
  • Additional Functions

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  1. Observability

Advanced Observability Suite

DuploCloud's Advanced Observability Suite Add-on

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Last updated 1 month ago

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DuploCloud's Advanced Observability Suite (AOS) is an add-on service to boost your monitoring and troubleshooting abilities. Built on OpenTelemetry, our AOS leverages CloudWatch, LGTM (Loki, Grafana, Tempo and Mimir), and Pyroscope to deliver robust observability for your cloud infrastructure. It includes real-time anomaly detection and customizable alerts and unifies metrics, traces, logs, and profiles to track all aspects of your environment easily.

The Grafana-powered dashboards spotlight key metrics and visualize trends in real-time, empowering swift, data-driven decisions. Additionally, AOS leverages object storage solutions like S3, GCS, and Storage Accounts, making it extremely cost-effective. Overall DuploCloud’s AOS simplifies troubleshooting and enhances system health by providing a holistic view of your application and infrastructure performance.

About OpenTelemetry

a project under the Cloud Native Computing Foundation (CNCF), supports multiple programming languages and environments and provides a flexible, vendor-neutral framework for monitoring and analyzing application performance. Designed for high scalability and ideal for distributed applications, OpenTelemetry is the industry standard for observability. See the for more.

Advanced Observability Suite Use Cases

Real-Time Monitoring and Observability

  • System Health Check: Track real-time metrics like CPU usage, memory consumption, network traffic, and error rates across services to ensure that applications are healthy.

  • Latency Tracking: Monitor request latencies to identify performance bottlenecks, particularly in services where latency spikes might indicate an issue. Easily drill down to the traces and determine which specific module is the cause for latency, or switch to profile view for deeper utilization visibility.

  • Error Rate Analysis: Track error counts and types to ensure services operate as expected and identify critical failure points. Drill down to the traces with just a click to determine where the error occurs.

End-to-End Tracing and Dependency Mapping

  • Request Flow Visualization: Visualize the path of requests through different services to understand interdependencies and identify which services may contribute to slowdowns or failures.

  • Service Dependency Mapping: See which services interact with each other, allowing for a clear view of critical service dependencies and helping identify potential cascading failures.

  • Root Cause Analysis (RCA): Trace issues back to the source by identifying slow, failed, or error-prone transactions and drilling down to pinpoint problematic services or infrastructure.

Performance Optimization

  • Identify Performance Bottlenecks: Detect slow components, such as long-running queries, network delays, or overloaded services, and make data-driven decisions to optimize them.

  • Capacity Planning: Use metrics to analyze usage patterns, forecast demand, and optimize resource allocation, helping avoid over-provisioning or under-resourcing.

  • Compare Release Impact: Measure the impact of new releases on system performance by comparing metrics before and after deployments.

Alerting and Incident Management

  • Set Alerts for Key Metrics: Define thresholds and set alerts for anomalies in critical metrics, such as high error rates or slow response times, so that teams can act quickly.

  • Incident Response and Remediation: Enable responders to access context-specific insights that accelerate incident response, diagnostics, and resolution times.

User Experience Insights

  • Track User Journey Metrics: Analyze performance metrics specific to different user journeys (e.g., checkout flows) to understand the impact of backend performance on user experience.

  • End-to-End Latency Perceptions: Collect latency and success metrics for critical user actions to help understand where improvements could enhance user satisfaction.

Custom Business and Operational Metrics

  • Monitor Business KPIs: Track custom metrics like transaction success rates, revenue per minute, or user engagement rates to tie technical performance to business outcomes.

  • Cost Optimization: Identify underused resources or inefficient services to optimize operational costs and improve infrastructure utilization.

Other Duplo-Specific Use Cases

  • Request new capabilities via DuploCloud/Using the OpenTelemetry open-source API.

Additional Functions

From the Grafana console, you can perform various tasks to customize your observability experience and proactively manage system health. For additional information, see the .

OpenTelemetry,
OpenTelemetry documentation
Grafana documentation