<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Cloud Run on Atamel.Dev</title><link>https://atamel.dev/tags/cloud-run/</link><description>Recent content in Cloud Run on Atamel.Dev</description><generator>Hugo</generator><language>en</language><managingEditor>atamel@gmail.com (Mete Atamel)</managingEditor><webMaster>atamel@gmail.com (Mete Atamel)</webMaster><lastBuildDate>Fri, 21 Nov 2025 11:03:22 +0000</lastBuildDate><atom:link href="https://atamel.dev/tags/cloud-run/index.xml" rel="self" type="application/rss+xml"/><item><title>Extending Cloud Code with custom templates</title><link>https://atamel.dev/posts/2023/03-18_extending_cloudcode_with_custom_templates/</link><pubDate>Sat, 18 Mar 2023 00:00:00 +0000</pubDate><author>atamel@gmail.com (Mete Atamel)</author><guid>https://atamel.dev/posts/2023/03-18_extending_cloudcode_with_custom_templates/</guid><description>&lt;p&gt;&lt;a href="https://cloud.google.com/code"&gt;Cloud Code&lt;/a&gt; is a set of IDE plugins for popular IDEs that make it easier to create, deploy and integrate applications with Google Cloud. Cloud Code provides an excellent extension mechanism through custom templates. In this post, I show you how you can create and use your own custom templates to add some features beyond those supported natively in Cloud Code, such as .NET functions, event triggered functions and more. &lt;/p&gt;</description></item><item><title>.NET 7 on Cloud Run</title><link>https://atamel.dev/posts/2022/11-11_dotnet7_cloud_run/</link><pubDate>Fri, 11 Nov 2022 00:00:00 +0000</pubDate><author>atamel@gmail.com (Mete Atamel)</author><guid>https://atamel.dev/posts/2022/11-11_dotnet7_cloud_run/</guid><description>&lt;p&gt;&lt;figure&gt;
 &lt;img src="https://atamel.dev/img/2022/dotnet7oncloudrun.png" alt=".NET 7 on Cloud Run" /&gt;
 
 &lt;figcaption&gt;.NET 7 on Cloud Run&lt;/figcaption&gt;
 
&lt;/figure&gt;&lt;/p&gt;
&lt;p&gt;.NET 7 was
&lt;a href="https://devblogs.microsoft.com/dotnet/announcing-dotnet-7/"&gt;released&lt;/a&gt; a few
days ago with new features and performance improvements and it&amp;rsquo;s already
supported on Cloud Run on Google Cloud!&lt;/p&gt;
&lt;p&gt;In this short blog post, I show you how to deploy a .NET 7 web app to Cloud Run.&lt;/p&gt;
&lt;h2 id="create-a-net-7-web-app"&gt;Create a .NET 7 web app&lt;/h2&gt;
&lt;p&gt;First, make sure you&amp;rsquo;re on .NET 7:&lt;/p&gt;
&lt;div class="highlight"&gt;&lt;pre tabindex="0" class="chroma"&gt;&lt;code class="language-sh" data-lang="sh"&gt;&lt;span class="line"&gt;&lt;span class="cl"&gt;dotnet --version
&lt;/span&gt;&lt;/span&gt;&lt;span class="line"&gt;&lt;span class="cl"&gt;7.0.100
&lt;/span&gt;&lt;/span&gt;&lt;/code&gt;&lt;/pre&gt;&lt;/div&gt;&lt;p&gt;Create a simple web app:&lt;/p&gt;</description></item><item><title>Taking screenshots of web pages with Cloud Run jobs, Workflows, and Eventarc</title><link>https://atamel.dev/posts/2022/06-16_taking-screenshots-web-pages-cloud-run-jobs-workflows-and-eventarc/</link><pubDate>Thu, 16 Jun 2022 00:00:00 +0000</pubDate><author>atamel@gmail.com (Mete Atamel)</author><guid>https://atamel.dev/posts/2022/06-16_taking-screenshots-web-pages-cloud-run-jobs-workflows-and-eventarc/</guid><description>&lt;p&gt;At Google Cloud I/O, we announced the public preview of Cloud Run jobs. Unlike Cloud Run services that run continuously to respond to web requests or events, Cloud Run jobs run code that performs some work and quits when the work is done. Cloud Run jobs are a good fit for administrative tasks such as database migration, scheduled work like nightly reports, or doing batch data transformation.&lt;/p&gt;
&lt;p&gt;In this post, I show you a fully serverless, event-driven application to take screenshots of web pages, powered by Cloud Run jobs, Workflows, and Eventarc.&lt;/p&gt;</description></item><item><title>Trying out source-based deployment in Cloud Run</title><link>https://atamel.dev/posts/2021/10-19_trying-out-source-based-deployment-cloud-run/</link><pubDate>Tue, 19 Oct 2021 00:00:00 +0000</pubDate><author>atamel@gmail.com (Mete Atamel)</author><guid>https://atamel.dev/posts/2021/10-19_trying-out-source-based-deployment-cloud-run/</guid><description>&lt;p&gt;Until recently, this is how you deployed code to Cloud Run:&lt;/p&gt;
&lt;p&gt;Define your container-based app with a Dockerfile.
Build the container image and push it to the Container Registry (typically with Cloud Build).
Deploy the container image to Cloud Run.
Back in December, we announced the beta release of source-based deployments for Cloud Run. This combines steps 2 and 3 above into a single command. Perhaps more importantly, it also eliminates the need for a Dockerfile for supported language versions.&lt;/p&gt;</description></item><item><title>Three ways of receiving events in Cloud Run</title><link>https://atamel.dev/posts/2021/03-12_three-ways-receiving-events-cloud-run/</link><pubDate>Fri, 12 Mar 2021 00:00:00 +0000</pubDate><author>atamel@gmail.com (Mete Atamel)</author><guid>https://atamel.dev/posts/2021/03-12_three-ways-receiving-events-cloud-run/</guid><description>&lt;p&gt;Cloud Run and Eventarc is a great combination for building event-driven services with different event routing options. There are two trigger types (Audit Logs and Pub/Sub) to choose from in Eventarc. Eventarc uses Pub/Sub as its underlying transport layer and provides convenience and standardization on top of it. If you wanted to, you could skip Eventarc and read messages directly from Pub/Sub in Cloud Run.&lt;/p&gt;
&lt;p&gt;This blog post details three ways of receiving events in Cloud Run and provides a decision framework on how to choose.&lt;/p&gt;</description></item><item><title>Events for Cloud Run for Anthos &gt;= Knative Eventing on Kubernetes</title><link>https://atamel.dev/posts/2020/10-09_events_cloud_run_anthos_knative_eventing/</link><pubDate>Thu, 08 Oct 2020 00:00:00 +0000</pubDate><author>atamel@gmail.com (Mete Atamel)</author><guid>https://atamel.dev/posts/2020/10-09_events_cloud_run_anthos_knative_eventing/</guid><description>&lt;h2 id="introduction"&gt;Introduction&lt;/h2&gt;
&lt;p&gt;We recently
&lt;a href="https://cloud.google.com/blog/products/serverless/cloud-run-for-anthos-adds-events"&gt;announced&lt;/a&gt;
a new feature, &lt;em&gt;Events for Cloud Run for Anthos&lt;/em&gt;, to build event driven systems on
Google Kubernetes Engine (GKE). In the announcement, we also stated that the
solution is based on open-source &lt;a href="https://knative.dev/"&gt;Knative&lt;/a&gt;.&lt;/p&gt;
&lt;p&gt;In this blog post, I want to further explain the relationship between this new
feature and Knative. I also want to convince you that our solution is an easier
way to deploy Knative compliant event consuming services on Google Cloud.&lt;/p&gt;</description></item><item><title>Cloud Run for Anthos brings eventing to your Kubernetes microservices</title><link>https://atamel.dev/posts/2020/09-24_cloud-run-for-anthos-adds-events/</link><pubDate>Thu, 24 Sep 2020 00:00:00 +0000</pubDate><author>atamel@gmail.com (Mete Atamel)</author><guid>https://atamel.dev/posts/2020/09-24_cloud-run-for-anthos-adds-events/</guid><description>&lt;p&gt;Building microservices on Google Kubernetes Engine (GKE) provides you with maximum flexibility to build your applications, while still benefiting from the scale and toolset that Google Cloud has to offer. But with great flexibility comes great responsibility. Orchestrating microservices can be difficult, requiring non-trivial implementation, customization, and maintenance of messaging systems.&lt;/p&gt;
&lt;p&gt;Cloud Run for Anthos now includes an events feature that allows you to easily build event-driven systems on Google Cloud. Now in beta, Cloud Run for Anthos’ event feature assumes responsibility for the implementation and management of eventing infrastructure, so you don’t have to.&lt;/p&gt;</description></item><item><title>A first look at serverless orchestration with Workflows</title><link>https://atamel.dev/posts/2020/09-08_first_look_at_workflows/</link><pubDate>Tue, 08 Sep 2020 00:00:00 +0000</pubDate><author>atamel@gmail.com (Mete Atamel)</author><guid>https://atamel.dev/posts/2020/09-08_first_look_at_workflows/</guid><description>&lt;h2 id="challenges-in-connecting-services"&gt;Challenges in connecting services&lt;/h2&gt;
&lt;p&gt;When I think about my recent projects, I probably spent half of my time coding
new services and the other half in connecting services. Service A calling
Service B, or Service C calling an external service and using the result to feed
into another Service D.&lt;/p&gt;
&lt;p&gt;Connecting services is one of those things that &amp;lsquo;should be easy&amp;rsquo; but in reality,
it takes a lot of time and effort. You need to figure out a common
connection format for services to use, make the connection, parse the results,
and pass the results on. I&amp;rsquo;m not even mentioning error handling, retries and
all those production readiness type features that you ultimately need to do.&lt;/p&gt;</description></item><item><title>Scheduled serverless dbt + BigQuery service</title><link>https://atamel.dev/posts/2020/07-29_scheduled_serverless_dbt_with_bigquery/</link><pubDate>Wed, 29 Jul 2020 00:00:00 +0000</pubDate><author>atamel@gmail.com (Mete Atamel)</author><guid>https://atamel.dev/posts/2020/07-29_scheduled_serverless_dbt_with_bigquery/</guid><description>&lt;p&gt;My colleague &lt;a href="https://twitter.com/felipehoffa"&gt;Felipe Hoffa&lt;/a&gt; recently published a
blog post titled &lt;a href="https://medium.com/@hoffa/get-started-with-bigquery-and-dbt-the-easy-way-36b9d9735e35"&gt;Get started with BigQuery and dbt, the easy
way&lt;/a&gt;.
More specifically, he showed how to install &lt;a href="https://getdbt.com/"&gt;dbt&lt;/a&gt; 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?&lt;/p&gt;
&lt;p&gt;&lt;a href="https://docs.getdbt.com/docs/running-a-dbt-project/running-dbt-in-production/"&gt;dbt
documentation&lt;/a&gt;
states that &lt;strong&gt;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.&lt;/strong&gt;&lt;/p&gt;</description></item></channel></rss>