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The latest News and Information on DevOps, CI/CD, Automation and related technologies.

Scaling faster and predictable cloud bills with Civo's FlexCore

How does Defense.com scale its SaaS security platform while keeping costs predictable? CEO Oliver Pinson-Roxburgh explains why Civo’s FlexCore was the only choice. FlexCore is engineered to deliver massive scalability and high performance, as milliseconds matter for real-time threat analysis, while ensuring UK Data Sovereignty and Compliance (ISO 27001). Crucially, FlexCore offers predictable pricing, eliminating the sudden, massive bills of larger providers. FlexCore delivers on-prem performance with public cloud scaling and simplicity.

Cloud Cost Optimization Services Beyond Tools: Building A Sustainable Operating Model

If you’ve already worked through cloud cost optimization strategies, the fundamentals aren’t new. CloudZero’s State of Cloud Cost report shows that cloud cost optimization is now a priority for most organizations. We’ve also covered these foundations in depth, including how cloud cost optimization works in practice and how FinOps teams approach cost accountability. What’s less discussed is what happens next. Cloud environments don’t stand still. Architectures change.

Understanding Cloud Cost Elasticity: Aligning Spend With Value

In the cloud computing industry, we hear the word “scaling” a lot. We talk about scaling up resources to meet demand, scaling our teams, and scaling our platforms. What tends to get lost is whether your costs are scaling in proportion to the value you’re delivering. If those two metrics don’t move in tandem, it’s likely you’re leaving money on the table. It’s not enough to simply use the cloud.

Friends of GNOME | Ubuntu Summit 25.10 | Lightning talk

In this talk, Cassidy gives us a look into GNOME, the open source desktop environment project. Cassidy explains how GNOME has developed over time, the support provided by donations, and what could come next for the project. About Cassidy Cassiy James Blaede is a GNOME Foundation Director, Flathub Contributor, and Co-founder & CXO of Elementary. Ubuntu Summit 25.10 is a showcase for the innovative and the ambitious.

GUI testing using YARF | Ubuntu Summit 25.10 | Lightning talk

What do Ubuntu Engineers use to test things? In this talk, Tim Anderrson provides a closer look at YARF, a new internal tool used in Ubuntu Engineering for testing the desktop installer alongside other desktop applications. Tim shares a bit about how YARF works, what the Ubuntu Engineering team plan to use it for from an overarching perspective, and how they plan to integrate this tool with the community.

How Enterprises Modernize and Migrate to the Cloud Safely with Harness Automation

Cloud migration is a multi-layer transformation involving infrastructure, CI/CD, governance, security, and cost management—not just application movement. Enterprises face unique migration challenges due to complex systems, parallel cloud operations, compliance requirements, and tool sprawl. Automation and standardization are critical to reducing risk, manual effort, and operational inconsistency during cloud-to-cloud migrations.

Knowledge Graph + RAG: A Unified Approach to DevOps Intelligence

Knowledge graphs and RAG (Retrieval-Augmented Generation) are complementary techniques for enhancing large language models with external knowledge, and each brings unique strengths for DevOps use cases. While they are often mentioned together, they are fundamentally different systems, and combining them delivers far better outcomes than relying on either approach alone.

The 2025 Year in Review (and what's coming soon)

Every year is a big year for Bitbucket, but in 2025, we delivered transformative changes that cap off years of work to make Bitbucket Cloud the secure, scalable, cloud-first standard for large engineering teams around the world. Today, 15M developers build on Bitbucket, including all of Atlassian’s 10,000-strong engineering organization, and Bitbucket Pipelines runs more than 1 billion build minutes per month.

A framework for measuring effective AI adoption in engineering

These days, engineering leaders find themselves caught between a rock and a hard place. On paper, AI adoption looks like an unqualified success. Developers are shipping more code faster than ever, pull request volumes are up, and teams report feeling more productive. Their leaders rush to LinkedIn to share their plans to scale adoption because their teams are just so much more efficient. But then, the incidents and bug reports start piling up.