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#

gcp-compute-engine

Here are 20 public repositories matching this topic...

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Terraform code to instantiate a Cloud Run V2 connected to a Postgres Cloud SQL, on which the pgvector extension will be enabled, with a connection to Redis and continuous deployment through the automatic trigger of Cloud Build.

  • UpdatedApr 9, 2024
  • HCL
sap-on-gcp-scripts

Sample flask app for demonstrating the continuous deployment to Google compute instances using GitHub workflows

  • UpdatedApr 20, 2023
  • Python
Machine-Learning-Prediction-of-California-House-Prices

The repository contains the California House Prices Prediction Project implemented with Machine Learning. The app was deployed on the Flask server, implemented End-to-End by developing a front end to consume the Machine Learning model, and deployed in Azure, Google Cloud Platform, and Heroku. Refer to README.md for demo and application link

  • UpdatedAug 1, 2021
  • Jupyter Notebook

BIAS Autoscaler leverages burstable instances for scaling Google Computer Engines

  • UpdatedNov 4, 2021
  • Java
alertIngress

Ingress alerts for the Pi Mask Detection project. Read records from a Kafka topic and persist them to a PostgreSQL database.

  • UpdatedOct 12, 2020
  • Go

Peace of Mind - BrainStation Capstone Project

  • UpdatedOct 6, 2025
  • JavaScript

DogBreedSpotter is a Python-based image classification project designed to identify and classify dog breeds in images. This project utilizes deep learning models, including convolutional neural networks (CNNs) such as VGG, AlexNet, and ResNet, to accurately detect whether an image contains a dog and, if so, determine the breed.

  • UpdatedSep 9, 2023
  • CSS

Build secure, scalable, lightweight, and hardened OS/machine images for cloud and on-premise hypervisors using Packer.

  • UpdatedNov 13, 2025
  • HCL

Automated TriMet ETL pipeline and visualization over GCP Pub/Sub

  • UpdatedJun 25, 2025
  • Python

This project presents an end-to-end cloud-based analytics solution for taxi trip data using Google Cloud Platform. It integrates GCP services such as Cloud Storage, Compute Engine, BigQuery, and Looker Studio alongside Python and the Mage data pipeline tool to automate data ingestion, processing, and visualization.

  • UpdatedSep 3, 2025
  • Jupyter Notebook

Simple Web Server using terraform as IaC

  • UpdatedDec 4, 2025
  • HCL

SECBridge is a high-performance financial data pipeline that automates the extraction, transformation, validation, and visualization of SEC financial statement data. Built with Snowflake, Apache Airflow, FastAPI, and Streamlit, it enables efficient ETL processing, structured data storage, and API-driven access for financial analysis.

  • UpdatedMar 19, 2025
  • Jupyter Notebook
Build-an-ETL-Pipeline-for-Financial-Data-Analytics-on-GCP-IaC

Springboot Backend Codes for 'All Ears'

  • UpdatedFeb 25, 2024
  • Java

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