# technology investments Published articles for technology investments. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## The Most Expensive Milliseconds Are Unmeasured DevFeed: [The Most Expensive Milliseconds Are Unmeasured]() Original publisher: [Read original article]() Author: Divya Gupta Arora Published: 2026-06-03T17:11:58Z Content type: article Language: en Sources: [Expedia]() Topics: [Mobile](), [render](), [ui]() Tags: [case-study](), [devops](), [engineering](), [login](), [mobile](), [mobile-apps](), [mobile-performance](), [observability](), [performance](), [release](), [software-engineering](), [technology-investments](), [time-to-interactive](), [ui](), [visibility]() ### AI overview This Expedia Group engineering case study describes extending Native Time to Interactive across mobile login screens. The metric was used to evaluate technology investments, compare platform behavior, and detect performance regressions that existing system-health signals did not reveal. ### Source excerpt Expedia Group Technology -- EngineeringHow a screen-level performance metric reshaped platform decisions, engineering ownership, and release disciplinePhoto by Pietro De Grandi on Unsplash For the last few years, my responsibility has been straightforward to state but hard to execute -- owning the traveler login experience across mobile platforms. Not just whether a feature works, but whether it feels responsive, predictable, and trustworthy in the moments that matter most. During login, those moments are unforgiving: if a login screen hesitates travelers don't interpret it as 'a slow render', they interpret it as risk. And when the majority of travelers interact through our mobile apps, performance stops being a technical concern and becomes a product promise. This post is a case study of how, within Expedia Group™'s login domain, we extended Native Time to Interactive (NTTI) across login screens -- moving performance from a late-stage check to a first-class signal we can use to validate technology investments, compare platform behavior, and prevent silent regressions as we ship. The Problem: Mobile reliability rarely fails loudly Mobile performance rarely breaks with a crash. It usually degrades quietly, a button takes a beat longer to respond a screen looks ready, but taps don't register the UI stutters just enough to feel "off" Those are the expensive milliseconds -- because they erode trust without triggering obvious alarms. In our login flows, we were shipping consistently, evolving a major part of our stack, and supporting increasing product complexity. Yet we didn't have a consistent way to answer the user's real question -- "When can I actually use this screen?" Why our existing signals failed We were not blind. We tracked many useful things, crashes and ANRs backend latency and service SLIs some component-level timing signals limited Time to Interactive tracking on onboarding and initial login But we had a gap -- we had visibility into system health, not screen ## How CTOs Can Justify Technology Investments to the Board DevFeed: [How CTOs Can Justify Technology Investments to the Board]() Original publisher: [Read original article]() Published: 2025-09-15T00:00:00Z Content type: article Language: en Sources: [Chainguard: Unchained]() Topics: [DevOps](), [Cloud](), [migration](), [Automation]() Tags: [automation](), [boardroom-advice](), [business](), [chainguard](), [chief-technical-officer](), [cloud](), [cloud-native](), [cost](), [cto](), [devops](), [digital-products](), [efficiency](), [executive](), [head-of-engineering](), [infrastructure](), [innovation](), [metrics](), [migration](), [teams](), [technology-investments](), [technology-procurement]() ### AI overview The article explains how CTOs and engineering leaders can justify technology investments by connecting initiatives to measurable business outcomes such as revenue growth, faster innovation, lower costs, and reduced risk. It emphasizes using a small set of clear, baselined, trackable metrics and illustrates how cloud-native migration, containerized workloads, automation, and DevOps metrics can support efficiency and savings. ### Source excerpt Learn how CTOs can tie technology investments to increasing revenue, speeding innovation, and reducing risk and cost to drive positive business outcomes. ## Planning in Bets: Risk Mitigation at Scale DevFeed: [Planning in Bets: Risk Mitigation at Scale]() Original publisher: [Read original article]() Author: Kathryn Tang Published: 2022-12-06T22:07:13Z Content type: article Language: en Sources: [Shopify Engineering](), [Shopify Engineering - Shopify Engineering]() Topics: [Shopify](), [Network](), [Internet]() Tags: [business](), [infrastructure](), [network](), [operational](), [scale](), [shopify](), [technology-investments]() ### AI overview This Shopify Engineering article presents a high-level risk mitigation process for large-scale infrastructure and high-traffic events such as Black Friday Cyber Monday. It explains how teams identify risks through broad input and "what could go wrong" exercises, prioritize risks according to business importance, likelihood, and severity, assign ownership, and empower appropriate decision makers. ### Source excerpt What do you do with a finite amount of time to deal with an infinite number of things that can go wrong? This post breaks down a high-level risk mitigation process into four questions that can be applied to nearly any scenario in order to help you make the best use of your time and resources available.