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Flowtopia Live 2026: Engineering the Frictionfree Enterprise

If your goals are accelerating flow and maximizing value in your organization, consider grabbing yourself a ticket to this year’s Flowtopia Live on Wednesday, June 24th. Flowtopia is a community of value stream practitioners, and this is our annual online jamboree where we gather to share, learn, and celebrate all things flow-related. Over 12 hours, we are featuring 50 live and interactive sessions with an incredible line-up of speakers, including transformational leaders from enterprises including Axians, Caisse des dépôts, Delta Airlines, Deutsche Telekom, Genomics England, Metlife, Parchment, Paymentology, Nationwide, NHS, Raytheon, RELEX Solutions, Sky, WIN Brands, Zayo, and many more! What’s on What’s in it for you 50 Live Sessions Direct interaction with leaders from Delta, Sky, and the NHS. 3 Parallel Tracks Specialized content for Product, Engineering, and Leadership. 3 Hands-on Workshops Practical skills in AI-driven models, VSRAs, and Lean m...
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Broadcom Aims to Better Secure Spring Applications in the AI Era

Broadcom today released a raft of updates to the open source Spring framework for building Java applications to primarily address a wave of vulnerabilities discovered by researchers using artificial intelligence (AI) tools. At the same time, Broadcom is also adding a managed service through which organizations can secure thousands of Spring dependencies for organizations building applications using its distribution of the Spring framework. That service is based on the Bitnami clean room technology that Broadcom uses to create secure images and Tanzu Buildpacks that automatically convert source code into images based on the Open Container Image (OCI) format. Broadcom gained access to that platform as part of its acquisition of VMware, with the Spring framework now part of the Tanzu division of Broadcom, which focuses on Java application development and the open source Cloud Foundry platform-as-a-service (PaaS) environment through which Buildpacks were first developed. Kevin Strohmey...
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The Hidden Cost of AI Code: Keeping Quality Up With Production 

AI maturity is fundamentally about expanding the delegation boundary. You start by letting AI assist with code completion, then with features. Eventually, agents write pull requests from requirements with minimal human involvement. Each step hands more responsibility to machines.   But here’s what people skip over: Tests are the primary mechanism for making that delegation safe.   You can’t let agents operate autonomously if you can’t verify what they produce. Low test coverage is the single biggest barrier to advancing along the AI maturity curve and most organizations haven’t come to terms with that. They want the AI productivity gains without doing the unglamorous work of building test infrastructure to make those gains trustworthy.   Coding assistants make delivery so fast that most QA organizations are underwater. Teams face a choice nobody wants to make: Attempt ten times the testing work, or test selectively and accept less certainty about whether what...
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Why the Software Development Tools you Choose Directly Affect Your CI/CD Reliability 

Most conversations about CI/CD reliability start in the wrong place. Teams debug flaky pipelines, investigate intermittent failures, tune alerting thresholds and optimize build times. All of that work is legitimate. However, the decisions that most directly determine whether a CI/CD pipeline is reliable or not were made months or years earlier, during tool selection. By the time teams are debugging pipeline reliability, they are usually dealing with the downstream consequences of upstream decisions that seemed reasonable at the time.   The software development tools a team chooses shape their CI/CD pipeline in ways that are not always visible during evaluation. Understanding those connections is the most practical starting point for teams that want reliable pipelines rather than better pipeline firefighting.   The Integration Surface Problem   Every tool in a software development stack creates an integration surface. Integration surface is the set of connections a tool has with oth...
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The Death of the Four Golden Signals: Designing Telemetry for Non-Deterministic Infrastructure 

In complex software systems, our traditional definition of operational health has always been comfortably binary. For over a decade, site reliability engineering (SRE) teams have relied on the industry-standard ‘Four Golden Signals’ — latency, traffic, errors and saturation — as the ultimate truth of platform stability. If our API-response times are hovering at sub-100 ms, network throughput is steady, CPU cores aren’t pegged and the HTTP 500 error rate is flatlined at zero, we sleep soundly. We check our Grafana dashboards, see an entirely green pasture and assume that our platform is delivering flawless value to the business.   Then came production AI.   With organizations rapidly transitioning from deterministic, code-driven microservices to   non-deterministic, LLM-powered applications, this foundational telemetry framework is facing a quiet crisis. In an AI-driven ecosystem, a system can be structurally flawless while failing functionally. An API gateway can return a crisp ...
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Harness Acquires Codecov to Identify Untested Code

Harness this week acquired Codecov , a provider of a platform that analyzes the percentage of a codebase that has been tested, from Sentry. Brad Rydzewski, a senior vice president and general manager for Harness, said Codecov makes it simpler for DevOps teams to track testing coverage at a time when the volume of code being created in the age of artificial intelligence is exponentially increasing. Codecov is already widely used by enterprises and maintainers to automatically run tests on any code that for one reason or another was not tested earlier in the software development lifecycle (SDLC). Going forward, Harness plans to integrate the data that Codecov generates in real time with the Harness Software Delivery Knowledge Graph to provide deeper insights across DevSecOps workflows as AI agents are integrated into workflows. Ultimately, the goal is to automate testing as much as possible while maintaining separation of duties between AI agents that write code and AI agents that te...
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Latest OpenTofu Release Simplifies Configuration Updates

The latest update to the OpenTofu infrastructure-as-code (IaC) tool is making it simpler to update and refactor configurations without having to rework the entire codebase. Version 1.12.0 of OpenTofu has added a destroy = false lifecycle option that enables DevOps engineers to drop an object from state without issuing a destroy application programming interface (API) call. Previously, any time a resource was updated or added an API call would try to destroy the actual infrastructure behind it. While DevOps teams could work around that issue by carefully maintaining state, the chances that something could go awry were fairly high. Now OpenTofu 1.12.0 allows DevOps teams to tie prevent_destroy to an input variable within the same module. Once set to default, the API call to destroy the IT infrastructure environment is overwritten. That per-stack variable configuration means DevOps teams can define the safety behavior once per environment and have it stay consistent across every run. ...
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