Cloud functions allow you to run single-purpose functions without having to manage instances in Google Cloud. Cloud SQL is Google Cloud’s managed SQL service. For better security, it’s best practice to disable public IP in Cloud SQL. In terraform, the…

Semios is a Vancouver-based data analytics company for growers of high-value crops such as almonds and apples. It uses a combination of machine learning, in-crop wireless networks and half a million IoT sensors across 80,000 acres to offer real-time monitoring…

Good news! Cloud Data Fusion is now GA. Announced at Google Next ‘19 UK on November 21, 2019, Cloud Data Fusion is a fully managed, cloud-native, enterprise data integration service for quickly building and managing data pipelines. Cloud Data Fusion…

This blog post describes how to enable roll-your-own Disaster Recovery in GCP Cloud SQL. This process is automated and will save money. However, recovery is manual. Introduction One of the benefits of using the cloud is the ability to track…

More than half a year ago, Google announced a truly hybrid cloud solution – Anthos. It’s time to recap and see how exactly Anthos has changed the perception of the hybrid cloud, what types of customers are benefiting from it…

Often we get involved in projects where there are all sorts of stringent security requirements. In this post, I will share a few of the methods used to meet these security requirements within Google Cloud Platform (GCP), while still allowing…

Cloud migration is hot nowadays. Enterprises are considering options to migrate on-premises data and applications to cloud (AWS/GCP/Azure) to get the benefits of quick deployments, pay-per-use models and flexibility. Recently, I got a chance to work on data migration from…

ProxySQL is a great tool. It’s one of the most recommended technologies in our Open Source Database practice. Many of our clients are running it or are migrating towards it, but we’ve seen that it is pretty CPU-intensive. We’ve also…

Creating deep learning models using Keras is pretty straightforward, which is why Keras is often used for prototyping and creating proof-of-concept products. But when it comes to using it for training bigger models or using very big datasets, we need…