Scheduled serverless dbt + BigQuery service

My colleague Felipe Hoffa recently published a blog post titled Get started with BigQuery and dbt, the easy way. More specifically, he showed how to install dbt in Google Cloud Shell, configure it and manually run it to create a temporary dataset in BigQuery. This is great for testing dbt + BigQuery but how do you run this kind of setup in production? dbt documentation states that Running dbt in production simply means setting up a system to run a dbt job on a schedule, rather than running dbt commands manually from the command line. [Read More]

Knative v0.16.0 update

I finally got around to updating my Knative Tutorial from Knative v0.14.0 to the latest Knative v0.16.0 release. Since I skipped v0.15.0, I’m not sure which changes are due to v0.15.0 vs. v0.16.0. Regardless, there have been some notable changes that I want to outline in this blog post. This is not meant to be an exhaustive list. Feel free to let me know in the comments if there are other notable changes that I should be aware of. [Read More]

Google Cloud Functions on .NET

.NET for Google Cloud Functions (Alpha) I spoke at many .NET conferences over the last 3-4 years and one of the top requests I always received was: When will .NET be supported on Cloud Functions? Unfortunately, I didn’t have a good answer for a while. That all changed last month with the following tweet from Jon Skeet from our C# team: I'm thrilled that .NET support is coming to Google Cloud Functions, along with the . [Read More]

.NET Core 3.1 updates in Cloud Shell and App Engine flexible environment

.NET Core 3.1 updates on Google Cloud .NET Core 3.1 was released on December 3rd, 2019 and is a LTS release, supported for three years. In Google Cloud, you could already deploy .NET Core 3.1 containers in Cloud Run (see cloud-run-dotnetcore-31) and also in App Engine flexible environment with a custom runtime. We recently extended .NET Core 3.1 support in a couple of ways: Cloud Shell now supports . [Read More]

Daily COVID-19 cases notification Pipeline with Knative Eventing, BigQuery, Matplotlib and SendGrid

Motivation When I started working from home in mid-March, I was totally obsessed with COVID-19 news. I was constantly checking number of cases and news from the UK (where I currently live) and from Cyprus (where I’m originally from). It took me a couple of weeks to realize how unproductive this was. I started limiting myself to check for news once a day. This definitely helped me to regain sanity and productivity but it was manual. [Read More]

Event-Driven Image Processing Pipeline with Knative Eventing

In this post, I want to talk about an event-driven image processing pipeline that I built recently using Knative Eventing. Along the way, I’ll tell you about event sources, custom events and other components provided by Knative that simply development of event-driven architectures. Requirements Let’s first talk about the basic requirements I had for the image processing pipeline: Users upload files to an input bucket and get processed images in an output bucket. [Read More]

Workload Identity Authentication for Knative v0.14.0 on GKE

If you ever used Knative on Google Cloud, you must have heard of Knative-GCP project. As the name suggests, Knative-GCP project provides a number of sources such as CloudPubSubSource, CloudStorageSource, CloudSchedulerSource and more to help reading various Google Cloud sources into your Knative cluster. I recently updated my Knative Tutorial to use the latest Knative Eventing release v0.14.2 and its corresponding Knative-GCP release v0.14.0. I ran into a weird authentication problem that I want to outline here. [Read More]

Knative Eventing Delivery Methods

Knative Eventing docs are a little confusing when it comes to different event delivery methods it supports. It talks about event brokers and triggers and it also talks about sources, services, channels, and subscriptions. What to use and when? It’s not clear. Let’s break it down. Delivery methods There are 3 distinct methods in Knative: Simple delivery Complex delivery with optional reply Broker and Trigger delivery Broker and Trigger delivery is what you should care about most of the time. [Read More]

An app modernization story — Part 4 (Serverless Microservices)

In part 3 of the blog series, I talked about how we transformed our Windows-only .NET Framework app to a containerized multi-platform .NET Core app. This removed our dependency on Windows and enabled us to deploy to Linux-based platforms such as App Engine (Flex). On the other hand, the app still ran on VMs, it was billed per second even if nobody used it, deployments were slow and most importantly, it was a single monolith that was deployed and scaled as a single unit. [Read More]

An app modernization story — Part 3 (Containerize & Redeploy)

In part 1, I talked about the initial app and its challenges. In part 2, I talked about the lift & shift to the cloud with some unexpected benefits. In this part 3 of the series, I’ll talk about how we transformed our Windows-only .NET Framework app to a containerized multi-platform .NET Core app and the huge benefits we got along the way. Why? The initial Windows VM based cloud setup served us well with minimal issues about roughly 2 years (from early 2017 to early 2019). [Read More]