🌥️ A lightweight data pipeline based on Google Cloud's Storage, Functions, Tasks and Scheduler.
-
Updated
Jun 9, 2023 - HCL
Google Cloud Platform, offered by Google, is a suite of cloud computing services. It provides Infrastructure as a Service, Platform as a Service, and serverless computing environments. Alongside a set of management tools, it provides a series of modular cloud services including computing, data storage, data analytics and machine learning.
🌥️ A lightweight data pipeline based on Google Cloud's Storage, Functions, Tasks and Scheduler.
A python script for upload Online File to Google Cloud Storage (GCS) built on Docker
This repository is for sharing knowledge, thoughts and approaches to multi-cloud and best-practice ways of working.
Stream CSV data from Google Cloud Storage to BigQuery using Apache Beam Dataflow, featuring dynamic schema detection and flexible runner options.
Terragrunt Infrastructure for a project called Crypto4All
An example how to use custom metrics in GKE
Data engineering project for TLC taxi Parquet data following an ELT model (extraction, load, transform)
Kogito Serverless Workflow Google GCP example
Analysis of NYC's citibike data. Technologies: Python , Prefect, dbt, Terraform , Looker data studio
A reference implementation of Vertex Pipelines for creating a production-ready MLOps solution on Google Cloud.
Apache Beam pipeline to analyze London bicycle hiring dataset with GCP Dataflow
Entire ETL pipeline project from data ingestion, transformation and finally analytics with Google Looker Studio
An experimental project using Pulumi and Golang to deploy a serverless use-case to Google Cloud Platform ☁️
Released April 7, 2008