Welcome to issue #171 January 6th, 2020

News

Start 2020 off right with these New Year’s tech resolutions - Cloud technology changes fast, and in 2020, there’s a lot to look forward to. Here are some cloud tips and tricks to use.

Getting started with new table formats on Dataproc - You can now use table format projects Apache Iceberg and Delta Lake with Google Cloud’s Dataproc, built to run Hadoop systems in the cloud.

GCP Inter-Region Latency - A website which displays heatmap of latencies between Google Cloud Compute instances in all available regions.

Create first GCP resource with Terraform - A brief tutorial which goes to the process of creating Cloud Storage bucket with Terraform.

The only correct way to setup a Google Kubernetes Engine - Some thoughts about security to consider when creating a GKE cluster.

The top 10 things to know about Firestore when choosing a database for your app - Firestore has many great qualities apps that need a cloud-hosted database. But you should know these 10 things before going all-in.

Intro to Transferring Files Between AWS S3 and GCS - Setting CLI to copy data between AWS S3 and Google Cloud Storage.

Migrating your App Engine app to Go 1.12+ - Example of code changes in the web app when updating from Go 1.11 to Go 1.12 to on Google App Engine.

Connecting to MS SQL on compute in GCP using Cloud IAP. - Connect to MS SQL on Google Compute Engine using your preferred SQL management software via Cloud Identity Aware Proxy.

Algorithmic Trading Automated in Python with Alpaca and Google Cloud - Example of using Cloud Scheduler and Cloud Functions to automate stock trading.

Multi-tenant applications with Firebase and Google Cloud - Using the Cloud Identity Platform to create multi-tenant applications in Firebase.

How to mount Cloud Storage bucket with GCP compute engine - Using gcsfuse to mount Cloud Storage bucket as a disk in Compute Engine instance.

Step-up your Developer skills with App Engine Part I - Create a twitter sentiment analyzing bot. Use Cloud NLP to analyze sentiment and use a corn Job to automate crawling and showing data.

Serverless ETL on Google Cloud, a case study: raw data into JSON Lines - Using Cloud Functions and Node.js client for Google Cloud Storage to transform server log data and save in another bucket in Cloud Storage.