Deploy a live sensor dashboard with TimescaleDB and Grafana on Google Cloud C4A
Introduction
Get started with TimescaleDB on Google Axion C4A
Create a firewall rule for Grafana/TimescaleDB
Create a Google Axion C4A Arm virtual machine on GCP
Set up TimescaleDB on Arm64
Ingest real-time sensor data on Arm64
Install Grafana and configure the TimescaleDB data source
Build a live sensor temperature dashboard
Next Steps

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About this Learning Path

Skill level:  Introductory
Reading time:  45 min
Last updated:  31 Jul 2026
Skill level:
  Introductory
Reading time:
  45 min
Last updated:
  31 Jul 2026
Author:Pareena Verma, Arm
Arm IP:Neoverse
Tags: Databases Google Cloud Linux TimescaleDB PostgreSQL Python Grafana psycopg2
Author:
  • Pareena Verma, Arm
Arm IP:
Neoverse
Tags:
Databases Google Cloud Linux TimescaleDB PostgreSQL Python Grafana psycopg2

Who is this for?

This is an introductory topic for DevOps engineers, database engineers, and software developers who want to deploy and operate TimescaleDB on SUSE Linux Enterprise Server (SLES) Arm64, ingest live time-series sensor data, and visualize it in Grafana.

What will you learn?

Upon completion of this Learning Path, you will be able to:

  • Install and configure TimescaleDB on Google Cloud C4A Axion processors by building from source for Arm64
  • Create a real-time sensor data ingestion pipeline using Python with hypertables, continuous aggregates, and retention policies
  • Build a live sensor dashboard with Grafana that automatically refreshes to display time-series data
  • Validate end-to-end data flow from ingestion through TimescaleDB to Grafana visualization

Prerequisites

Before starting, you will need the following:

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