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Our Golang Stack in 2025
In our Go projects, we rely on a consistent and battle-tested stack of libraries that help us build reliable, maintainable, and scalable systems. We started using Go in our stack many years ago (before Go v1) and therefore many of our choices have changed over the years. Here in this post, I wanted to share some of the libraries we use regularly to power our Go apps.
Anbox Cloud 1.26.0: what's new?
In this video, Anbox team covers new features and changes in Anbox Cloud 1.26.0 release: Deployment and operations Instance management Logging Dashboard enhancements Images Streaming CVEs What is Anbox Cloud? Anbox Cloud lets you run virtualized Android environments securely, at any scale, to any device letting you focus on your use case. Run Android in system containers, not emulators, on AWS, OCI, Azure, GCP or your private cloud with ultra low streaming latency.
An Introduction to Bitbucket Pipelines
This video provides a 90-second introduction to Bitbucket Pipelines to help you get started with CI/CD in Bitbucket. Bitbucket pipes, which are reusable pipeline steps, are introduced. About Atlassian: Behind every great human achievement, there is a team. From medicine and space travel to disaster response and pizza deliveries, we help teams all over the planet advance humanity through the power of software. Our mission is to help unleash the potential of every team.
DevEx Unpacked 004 - Scaling Startups, Blockchain & Developer Culture with Jack Spargo
Episode 004: In this episode of DevEx Unpacked, Alan Carson chats with Jack Spargo, CTO of Control Alt, about his fascinating career journey from aerospace engineering to leading blockchain-powered investment platforms. Jack shares lessons from being acquired overnight, the challenges of building a platform from scratch, and why he’s betting big on junior engineers and AI augmentation. They explore the realities of compliance, software supply chain security, and why Northern Ireland is fast becoming a serious start-up hub.
2025 Cloud Pricing Comparison: An In-Depth Guide
Over $44.5 billion in cloud spend goes to waste annually, per the FinOps Foundation. No wonder reducing unnecessary costs is critical to protecting your margins. A logical place to start? Cloud service pricing. Providers like AWS, Azure, and Google Cloud continue to evolve their pricing models. They are offering new discounts, regional rates, and shifting commitments. All to win your business. Yet, a cloud pricing comparison alone doesn’t give you a complete picture.
How to test your systems for scalability and redundancy with fault injection
Part of the Gremlin Office Hours series: A monthly deep dive with Gremlin experts. Do you know if your services can tolerate losing a node? What about an entire availability zone? Or a region? Large-scale outages aren’t unheard of. When you’re running critical services, it’s vital that those services can keep running even if an AZ or region fails. In addition to failing over, these services also need to scale quickly so traffic shifts don’t overwhelm your systems. How do you prove that a service is both scalable and redundant? The answer is with Fault Injection.
Celebrating a Decade of GitKraken
As I sit down to write this, I can’t help but feel a wave of nostalgia wash over me. I’m Sara Stamas, VP of Marketing at GitKraken, and I’ve had the incredible privilege of being part of this company for over a decade (yes, before GitKraken was even a twinkle in an Axosoft developer’s eye).
How to be prepared for cloud provider outages
GCP’s recent outage on June 12th was a reminder of just how interconnected modern architectures are. The 2 hour and 28 minute outage affected dozens of companies and spanned 80+ Google services and products. But what was really illuminating was just how far the outage spread due to hidden dependency risks. Many companies that don’t run on GCP were startled to find their services suddenly affected because they had dependencies or depended on vendors that did use GCP.
Automating machine learning security checks using CI/CD
Machine learning (ML) pipelines are increasingly being treated like software; built, tested, deployed, and monitored using automated tooling. But while infrastructure as code and microservices have matured with security best practices, ML systems often lag behind. The truth is, your ML pipeline is part of your software supply chain and it is vulnerable.