Overview
GrafLI is a cloud-native monitoring and visualization platform developed by LinkedIn to enhance the developer experience and increase engineering velocity in Azure environments. It automates dashboard creation and leverages Azure's native monitoring stack, providing real-time visualization capabilities for both Azure and on-premises services.
What You'll Learn
1
How to leverage Azure Resource Graph for efficient resource monitoring
2
Why automated dashboard generation is crucial for scaling Azure monitoring
3
How to implement Infrastructure as Code (IaC) for consistent Azure deployments
Prerequisites & Requirements
- Understanding of Azure services and monitoring concepts
- Familiarity with Azure DevOps or GitHub for CI/CD(optional)
Key Questions Answered
What are the key features of GrafLI?
GrafLI offers dynamic dashboard generation, enhanced discoverability through Azure Resource Graph queries, and consolidated monitoring dashboards that compile metrics from various sources. These features enable real-time visualization and efficient monitoring across Azure and on-premises services.
How does GrafLI automate monitoring and visualization?
GrafLI automates monitoring by integrating with Azure's native monitoring stack, utilizing Infrastructure as Code (IaC) for resource provisioning, and leveraging Kusto Query Language (KQL) for querying metrics. This approach allows for real-time dashboard updates and efficient data visualization.
What is the impact of GrafLI on developer productivity?
GrafLI significantly enhances developer productivity by providing a multifaceted view of Azure and hybrid environments, allowing for quick analysis of application performance and infrastructure health. This leads to improved resource utilization and faster responses to monitoring needs.
Key Statistics & Figures
Number of dashboards created
1500+
GrafLI encompasses over 1500 dashboards, providing insights across 800+ distinct services deployed in Azure.
Access to Azure resources
~100K
GrafLI provides access to approximately 100,000 Azure resources and their corresponding metrics.
Technologies & Tools
Backend
Azure Resource Graph
Used for querying and discovering Azure resources efficiently.
Query Language
Kusto Query Language (kql)
Utilized for executing queries against Azure Monitor and Log Analytics.
Frontend
Chartjs
Employed for generating dynamic visualizations in GrafLI.
Frontend
D3.js
Used for advanced data visualization capabilities within GrafLI.
Key Actionable Insights
1Implement GrafLI to automate your Azure monitoring processes.This will reduce the time spent on manual dashboard creation and allow your team to focus on more strategic tasks, enhancing overall productivity.
2Utilize Kusto Query Language (KQL) for efficient data querying.KQL enables complex queries across Azure resources, providing deeper insights into application performance and health.
3Adopt Infrastructure as Code (IaC) practices for consistent deployments.IaC ensures that your Azure resources are provisioned consistently, reducing errors and improving the reliability of your monitoring setup.
Common Pitfalls
1
Failing to adhere to naming conventions and resource tagging during Azure deployments.
This can lead to difficulties in resource discoverability and management, making it harder to monitor and visualize metrics effectively.
Related Concepts
Infrastructure As Code (iac)
Azure Monitoring Best Practices
Kusto Query Language (kql) Usage