In part one of this series, we covered how you could limit deployments to Platform.sh only when a tag is pushed/created, focusing primarily on using GitHub and the GitHub Actions platform to accomplish this goal. But we’re a polyglot PaaS and strive to be agnostic in our users’ source code management terms of the service. With that in mind, let’s look at how we can accomplish the same goal using GitLab and your CI/CD system. Just like last time, there are some assumptions to consider.

StackState had a blast at this year's KubeCon + CloudNativeCon gathering in Paris! The discussions were in-depth, covering a wide array of topics and lasting much longer than in the past. This year, attendees seemed to have a considerably deeper understanding of the cloud-native ecosystem, probably attributed to its rapid growth. We also noticed a pretty dramatic evolutionary shift in the vendors at the expo hall, who were showcasing some truly progressive specialized solutions.

If there's one thing almost every developer has done in their life, it's deploy an application to Heroku. From their launch in 2007, Heroku dominated PaaS and caught the attention of Salesforce who acquired them in 2010. They had the first managed Postgres service in 2011, an easy to use CLI, and, last but not least, it was free to get started which led to a big uptick in initial popularity. Every side project from here to the moon went to Heroku.

Is your Azure spend management getting out of control? You’re not alone. Countless businesses struggle with the exact problem, often lacking clarity on the reasons behind the cost spike. Especially within larger organizations, where multiple teams deploy Azure resources, the Azure costs can quickly get out of control without the necessary tools to effectively track the spending and evaluate monthly Azure spend against their business needs.

Ensuring efficient deployment and management of containerized applications is critical to development teams across all possible industries in today’s cloud-native world. A standout service for many has been AWS Elastic Container Service (ECS), which has proven to be scalable and easy to use while integrated into one of the largest cloud ecosystems out there. However, one size does not fit all.

Tidal Accelerator has recently made its powerful Business Analytics feature generally available across all existing and new workspaces, as discussed in our previous article. This game-changing capability empowers organizations to make data-driven decisions throughout their migration and modernization journeys. In this article, we’ll dive deeper into four key areas where Tidal Accelerator’s advanced analytics provide invaluable insights.

As businesses increasingly move their workloads to the cloud, managing cloud costs has become a critical concern. At Tidal.Cloud, with the roll-out of new features such as Tidal Accelerator’s Business Analytics, we recently realized that our AWS costs were steadily increasing, and we needed to take action to optimize our cloud spending.

From its initial appearance in the dev-tools space, GenAI has had an outsized impact on how developers approach day-to-day tasks (just ask any developer about when they first started using GitHub’s copilot). While any risks are still being evaluated—like potential for introducing anti-patterns or inadvertently running afoul of compliance requirements, many engineering teams have successfully implemented GenAI with measurable gains in collaboration and productivity.

This blog post explores the technical and strategic benefits of deploying open-source AI models on Ubuntu. We’ll highlight why it makes sense to use Ubuntu with open-source AI models, and outline the deployment process on Azure.

Friends of this blog know that I am a big fan of building internal tools, or as we call them, "tools that help scale people". As the name suggests, internal tools are used, well, internally and as such usually will require their access to be restricted to the company's staff and network. In the past, I've written about how to use Tailscale for authentication of internal tools using HTTP. In this post, I will show you how to use Tailscale for gRPC authentication in Golang.