Grafana

Grafana is used as a core observability layer for understanding system behavior across applications, infrastructure, and machine learning workloads.

Rather than treating monitoring as an afterthought, Grafana is positioned as a decision-support tool, enabling teams to diagnose issues, track performance, and operate systems with confidence.

Key Capabilities

• Operational Dashboards
  Enables clear, actionable visualizations for system health, performance, and capacity.

• Alerting & Signal Definition
  Supports flexible alert rules that focus on meaningful signals rather than raw noise.

• Multi-Source Observability
  Integrates metrics, logs, and traces from multiple backends into a unified view.

• Extensible Architecture
  Allows customization and extension through plugins and data source integrations.

• Cross-Cutting Visibility
  Provides a shared operational view across application, platform, and ML layers.

Experience & Platform Contribution

Designed and maintained observability dashboards and alerting strategies as part of a shared platform, supporting application services, data pipelines, and ML systems in production.

Key contributions included:

• Defining service-level and platform-level dashboards focused on actionable insights
• Implementing alerting patterns that reduced noise while improving incident response
• Visualizing performance characteristics of ML inference and data processing workflows
• Enabling teams to self-serve operational insight without deep platform knowledge
• Advising teams on observability best practices and signal selection

Grafana acted as a critical feedback loop within the platform, helping teams move from reactive monitoring to informed operational decision-making.