Inspect CPU and RAM usage
Diagnosing resource pressure
Neon · Const
Neon’s Monitoring dashboard in the Console presents system and database metrics as graphs. Choose a branch and compute, then use the Postgres, Storage, or Functions tabs to inspect the relevant data.
Neon’s Monitoring dashboard is a console-based view of system and database health. Select a project branch and compute, then inspect categorized graphs and refresh the displayed data when needed.
const monitoringUrl = "https://console.neon.tech";
console.log("Open Neon Console, select a project, then choose Monitoring.", monitoringUrl);Open the Neon Console, select a project, and access Monitoring from the sidebar to inspect metrics for a selected branch and compute.
Diagnosing resource pressure
Investigating database connectivity
Checking database behavior
The Monitoring dashboard is accessed from the Neon Console sidebar. It organizes observability data into Postgres, Storage, and Functions tabs and displays metrics for a selected branch and compute.
Follow-up: How would you change the scope of the displayed data? Select another branch from the project/branch menu and switch computes with the Compute drop-down.
The dashboard provides graphs for system and database metrics, including RAM, CPU, connection counts, database size, deadlocks, row changes, replication delay, and cache hit rate. These metrics help investigate resource use and database behavior.
Follow-up: Which metric would help investigate connection saturation? Inspect the Postgres connections count graph, which separates idle, active, and total direct connections.
The Postgres connections count graph reports idle, active, and total connections directly to the Postgres database over time for the selected compute. This distinguishes connection state while examining connection usage.
Follow-up: How can the displayed connection data be brought up to date? Press the dashboard’s Refresh button after selecting the required scope.
Postgres connections countRAMDeadlocksQuery performanceActive QueriesMetrics and logs reference