# legacy An older computer system, programming language, or application still used instead of contemporary alternatives. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Accelerating Operational Efficiency in Modern Transportation DevFeed: [Accelerating Operational Efficiency in Modern Transportation]() Original publisher: [Read original article]() Author: Emily Kasman Published: 2026-09-17T13:30:51Z Content type: article Language: en Sources: [Cisco Blogs]() Topics: [Cisco](), [Network](), [Critical Infrastructure](), [legacy](), [Low Latency](), [Security](), [observability](), [Resilience]() Tags: [cisco](), [cisco-connected-rail](), [cisco-industrial-ethernet-switches](), [cisco-industrial-routers](), [cisco-industrial-security](), [connected-roadways](), [critical-infrastructure](), [industrial-ai](), [industrial-iot](), [legacy](), [low-latency](), [modernization](), [network](), [observability](), [resilience](), [security](), [transportation]() ### AI overview This Cisco article discusses how transit and roadway agencies can modernize legacy network infrastructure. It presents secure, low-latency connectivity, end-to-end operational visibility, and security-focused architecture as ways to support real-time processing, connected systems, and more resilient transportation operations. ### Source excerpt Learn how Cisco helps transit agencies overcome legacy network bottlenecks with secure, AI-ready connectivity, full visibility, and robust cyber resilience. ## Fedora 45 beta drags the Linux console into the 21st century (Register) DevFeed: [Fedora 45 beta drags the Linux console into the 21st century (Register)]() Original publisher: [Read original article]() Author: corbet Published: 2026-09-16T16:24:46Z Content type: news Language: en Sources: [LWN.net]() Topics: [Fedora](), [Linux](), [console](), [legacy](), [Terminal](), [Software]() Tags: [beta](), [console](), [development](), [legacy](), [linux](), [replacement](), [software](), [terminal]() ### AI overview The article reports that Fedora 45 beta replaces Linux's legacy in-kernel console with kmscon, a software-controlled userspace terminal emulator that has been in development for more than a decade. ### Source excerpt The Register looks forward to the upcoming Fedora 45 release. The biggest surprise is that Linux's legacy in-kernel console - the text-mode interface normally hidden beneath the GUI - has been replaced with a software-controlled alternative. The replacement is kmscon, a userspace terminal emulator that has been in development for more than a decade. ## Enterprises are sweating legacy IT assets as AI investment grows DevFeed: [Enterprises are sweating legacy IT assets as AI investment grows]() Original publisher: [Read original article]() Author: Dan Robinson Published: 2026-09-16T16:15:00Z Content type: article Language: en Sources: [www.theregister.com - Articles]() Topics: [legacy](), [Hardware](), [mainframes](), [data](), [business logic](), [Artificial Intelligence]() Tags: [ai](), [artificial-intelligence](), [business-logic](), [data](), [ensono](), [hardware](), [it-modernization](), [legacy](), [legacy-systems](), [mainframes](), [systems]() ### AI overview The article examines how enterprises are dealing with legacy IT assets as AI investment grows. It reports that mainframes and other hardware may contain the data and business logic needed to build AI services. ### Source excerpt Hardware such as mainframes found to hold the data and business logic needed to build those AI services ## Researchers link the RubyHack campaign to alleged OpenAI-connected agents, while RubyGems disputes key claims DevFeed: [Researchers link the RubyHack campaign to alleged OpenAI-connected agents, while RubyGems disputes key claims]() Original publisher: [Read original article]() Author: amaksimovv (CodeScoring) Published: 2026-09-16T15:08:49Z Content type: news Language: ru Sources: [Tagir Valeev]() Topics: [rubygems](), [Ruby](), [OpenAI](), [legacy](), [API]() Tags: [api](), [appsec](), [cdn](), [gemstuffer](), [legacy](), [load](), [openai](), [ruby](), [rubydoc](), [rubygems](), [rubyhack](), [tag-070ecaaf0eda](), [tag-64251c106897](), [yard]() ### AI overview Researchers from Nightingale Collective linked the RubyHack campaign in RubyGems to alleged internal OpenAI agents. The article describes malicious code executed during RubyDoc documentation builds, data collection from British municipal websites, attempts to obtain RubyGems API keys, and a caching flaw involving legacy keys. RubyGems said it could not independently identify the package creators and found no evidence that чужие keys were successfully obtained. ### Source excerpt 11 сентября исследователи Nightingale Collective опубликовали разбор RubyHack и связали майскую кампанию в RubyGems с внутренними агентами OpenAI. По их версии, скрипты внутри пакетов запускали код в инфраструктуре RubyDoc, собирали открытые данные с сайтов британских муниципалитетов и публиковали результаты обратно в реестр. В нескольких образцах исследователи также обнаружили попытки получить чужие API-ключи RubyGems. Команда RubyGems не смогла независимо установить, кем именно были созданы пакеты, и не нашла доказательств успешного получения чужих ключей. Во время майской кампании она отозвала вредоносные пакеты и на четыре дня остановила регистрацию новых пользователей. Одной из точек входа стала обычная сборка документации. В пакет добавляли .yardopts - файл параметров генератора YARD - с указанием загрузить Ruby-скрипт. Когда для пакета запрашивали документацию на RubyDoc, сборщик обрабатывал этот файл и запускал вложенный код. Такое поведение соответствует механике самого YARD: параметр --load загружает указанный Ruby-файл перед выполнением команды. Запущенный скрипт обращался к муниципальным сайтам, сохранял ответы, собирал из них новый .gem-архив и отправлял его в RubyGems со встроенным ключом. В результате реестр использовался как канал передачи и хранения собранных данных. Установка такого пакета множеством разработчиков для работы этой схемы не требовалась: достаточно было исполнения кода в сервисе сборки документации. Отдельные пакеты обращались к старому endpoint выдачи API-ключей. В нём действовала ошибка кэширования: при определённых условиях CDN мог сохранить ответ с legacy-ключом и до часа отдавать его следующим запросам на том же узле. RubyGems исправил проблему 9 июля, очистил кэш, отозвал legacy-ключи и затем отключил старый endpoint. Читать далее ## Lyft Moves Streaming Fleet to Apache Flink Kubernetes Operator DevFeed: [Lyft Moves Streaming Fleet to Apache Flink Kubernetes Operator]() Original publisher: [Read original article]() Author: Mark Silvester Published: 2026-09-16T11:00:00Z Content type: news Language: en Sources: [InfoQ]() Topics: [flink](), [apache-flink](), [Kubernetes](), [autoscaling](), [Deployment](), [legacy](), [Testing]() Tags: [apache-flink](), [architecture-design](), [autoscaling](), [deployment](), [development](), [devops](), [flink](), [kubernetes](), [kubernetes-operator](), [legacy](), [lyft-flink-k8s-operator](), [news](), [testing](), [upgrade]() ### AI overview Lyft moved hundreds of production Apache Flink jobs from its in-house Kubernetes operator to the Apache Flink Kubernetes Operator. The change enabled last-state upgrades, in-place autoscaling, and resource autotuning, while Lyft adapted legacy deployment specifications through its deploy API and contributed a fix for a configuration-renaming bug. ### Source excerpt Lyft has moved hundreds of production Flink jobs from a 2020 in-house Kubernetes operator to the Apache Flink Kubernetes Operator, unlocking last-state upgrades, in-place autoscaling and resource autotuning across the fleet. By Mark Silvester ## Using acceptance tests to catch regression bugs in legacy code before production DevFeed: [Using acceptance tests to catch regression bugs in legacy code before production]() Original publisher: [Read original article]() Author: Valentina Jemuović Published: 2026-09-16T07:33:58Z Content type: tutorial Language: en Sources: [Optivem Journal]() Topics: [Testing](), [Requirements](), [legacy]() Tags: [automated](), [bugs](), [e2e](), [legacy-code](), [regression](), [requirements](), [testing](), [ui](), [unit-tests]() ### AI overview This hands-on article explains why automated unit and end-to-end tests may still allow production bugs in legacy code. It presents acceptance test-driven development (ATDD), where requirements and tests describe the same observable behavior, making coverage clearer and reducing dependence on UI steps. ### Source excerpt You automated, and manual regression testing is still there. Those two facts have the same cause. ## Cisco UCS Manager: Celebrating the legacy, shaping the future with Cisco Intersight DevFeed: [Cisco UCS Manager: Celebrating the legacy, shaping the future with Cisco Intersight]() Original publisher: [Read original article]() Author: Jacob Van Ewyk Published: 2026-09-15T21:00:37Z Content type: opinion Language: en Sources: [Cisco Blogs]() Topics: [Cisco](), [Server](), [Automation](), [configuration](), [API](), [legacy]() Tags: [api](), [automation](), [cisco](), [data-center](), [end-of-life](), [eol](), [infrastructure](), [legacy](), [lifecycle](), [management](), [server]() ### AI overview Cisco describes the legacy of Cisco UCS Manager and positions Cisco Intersight as the strategic platform for future Cisco UCS software management. The article also outlines announced end-of-sale and end-of-life milestones, including a planned Last Date of Support of December 31, 2030, subject to applicable contracts and service terms. ### Source excerpt Cisco UCS Manager shaped 17 years of infrastructure management. Now, with its end-of-life announced, Cisco Intersight carries that foundation forward with centralized visibility, automation, and scale. Learn the key dates for the UCS Manager EOL. ## Community updates: taking time off, AI club, and next events 💬 DevFeed: [Community updates: taking time off, AI club, and next events 💬]() Original publisher: [Read original article]() Author: Luca Rossi Published: 2026-08-28T07:01:45Z Content type: article Language: en Sources: [Refactoring]() Topics: [sessions](), [Artificial Intelligence](), [Processes](), [legacy]() Tags: [ai](), [community](), [events](), [ownership](), [processes](), [projects](), [sessions](), [slack]() ### AI overview A community update recaps discussions from the August Mastermind and AI Club, including planning time off without disrupting team ownership, AI learning and legacy migrations, and upcoming events. ### Source excerpt A special edition focused on our community activities! ## Core Banking Modernization with Temenos Core and CockroachDB DevFeed: [Core Banking Modernization with Temenos Core and CockroachDB]() Original publisher: [Read original article]() Author: Nanda Badrappan,Muruga Balakrishnan Published: 2026-08-24T00:00:00Z Content type: article Language: en Sources: [Cockroach Labs]() Topics: [CockroachDB](), [Cockroach Labs](), [Data Infrastructure](), [Availability](), [real-time](), [Resilience](), [Transactions](), [legacy](), [SQL](), [Cloud](), [systems](), [on-prem]() Tags: [availability](), [cloud](), [cockroach-labs](), [cockroachdb](), [data-infrastructure](), [legacy](), [on-prem](), [real-time](), [resilience](), [sql](), [transactions]() ### AI overview This article explains why banks are modernizing legacy core banking infrastructure. It describes how Temenos Core and CockroachDB are positioned to support real-time transaction processing, continuous availability, distributed operations, resilience, and regulatory requirements. ### Source excerpt Banking has become an always-on business. Customers expect instant payments, accurate balances, and continuous access to financial services... ## Why agentic AI starts with legacy modernisation DevFeed: [Why agentic AI starts with legacy modernisation]() Original publisher: [Read original article]() Author: Suzanne Angell Published: 2026-08-21T09:33:00Z Content type: opinion Language: en Sources: [Scott Logic]() Topics: [Artificial Intelligence](), [AI Agent](), [legacy](), [legacy systems](), [data](), [Processes]() Tags: [agentic-ai](), [agents](), [ai-agents](), [artificial-intelligence](), [data](), [governance](), [integration](), [legacy](), [legacy-modernisation](), [operational-risk](), [processes](), [risk-management]() ### AI overview The article argues that organisations must address fragmented data, brittle processes, and outdated architectures before they can realise the full value of agentic AI. It explains that legacy systems may remain operationally critical, while accumulated technical, process, and organisational debt can prevent agents from accessing reliable information and executing workflows consistently. ### Source excerpt Organisations are increasingly excited by the potential of agentic AI, but many overlook the legacy obstacles that stand in the way. In this post, I explore why successful AI adoption depends on tackling fragmented data, brittle processes and outdated architectures, and why modernisation is often the most important step towards unlocking value from intelligent agents. ## How a Tech Lead Encouraged Testing in Legacy Code DevFeed: [How a Tech Lead Encouraged Testing in Legacy Code]() Original publisher: [Read original article]() Author: Valentina Jemuović Published: 2026-08-04T06:02:15Z Content type: opinion Language: en Sources: [Optivem Journal]() Topics: [Test-driven development](), [legacy](), [clean-code](), [Template](), [Software Engineering]() Tags: [clean-code](), [legacy-code](), [tdd](), [tech-lead](), [training](), [unit-tests]() ### AI overview This opinion article recounts how an engineering leader struggled to introduce testing and clean-code practices across multiple companies. As a Tech Lead, the author created a testable Clean Architecture template, recruited developers who valued quality, built an initial module, and trained the team to use the approach. ### Source excerpt "We don't have time to write the code twice." ## Four pillars of agentic AI success DevFeed: [Four pillars of agentic AI success]() Original publisher: [Read original article]() Author: Simon Sear Published: 2026-07-29T15:47:00Z Content type: article Language: en Sources: [Scott Logic]() Topics: [Artificial Intelligence](), [Software Engineering](), [data](), [legacy](), [systems](), [context]() Tags: [accessibility](), [agentic-ai](), [ai](), [ai-accelerated-development](), [ai-agents](), [architecture](), [artificial-intelligence](), [context](), [data](), [data-architecture](), [data-governance](), [data-strategy](), [delivery](), [engineering](), [governance](), [legacy](), [legacy-modernisation](), [software-engineering](), [systems]() ### AI overview This article argues that organizations need strong foundations before scaling agentic AI. It identifies four pillars: modernizing legacy systems, building reliable data foundations and architecture, managing governance and risk, and democratizing access to data. ### Source excerpt Everyone is talking about agentic AI. That's not surprising. The promise is huge: AI agents that can plan, reason, use tools, work across systems and get real work done. In software engineering, that could mean faster delivery and better quality. In operations, it could mean complex processes moving with less manual effort, fewer handovers and better decisions. ## Broken Systems Don't Need More Developers DevFeed: [Broken Systems Don't Need More Developers]() Original publisher: [Read original article]() Author: Valentina Jemuović Published: 2026-07-14T09:12:34Z Content type: opinion Language: en Sources: [Optivem Journal]() Topics: [systems](), [legacy](), [Back end](), [Test-driven development]() Tags: [architecture](), [code-reviews](), [developers](), [engineering](), [legacy](), [legacy-code](), [meetings](), [merge](), [onboarding]() ### AI overview Adding developers to a tightly coupled legacy system may slow progress because onboarding, interruptions, meetings, code reviews, and merge conflicts increase. The article argues that architecture, rather than team size, is the main bottleneck. ### Source excerpt If four developers aren't delivering fast enough, why not make it eight? ## Your Architecture Doesn't Rot Overnight DevFeed: [Your Architecture Doesn't Rot Overnight]() Original publisher: [Read original article]() Author: Valentina Jemuović Published: 2026-07-07T06:00:37Z Content type: opinion Language: en Sources: [Optivem Journal]() Topics: [legacy](), [systems](), [Software](), [Test-driven development]() Tags: [architecture](), [business-logic](), [code](), [dependency](), [legacy](), [refactor](), [requirements]() ### AI overview The article explains how repeated convenience-driven decisions gradually weaken boundaries between business logic and infrastructure. It argues that architectural decay often remains hidden while the application works and tests pass, eventually making seemingly simple changes difficult to locate and implement. ### Source excerpt As deadlines become tighter, convenience starts winning. ## TDD in Legacy Code - Maintainable Component Tests - Backend DevFeed: [TDD in Legacy Code - Maintainable Component Tests - Backend]() Original publisher: [Read original article]() Author: Valentina Jemuović Published: 2026-07-02T06:02:41Z Content type: tutorial Language: en Sources: [Optivem Journal]() Topics: [Back end](), [Test-driven development](), [legacy]() Tags: [api](), [backend](), [component](), [erp](), [legacy](), [legacy-code](), [refactor](), [tdd](), [tests]() ### AI overview A tutorial on refactoring brittle backend component tests that are coupled to a backend API and ERP system, with the goal of making them more maintainable. ### Source excerpt Many Backend Teams write unmaintainable Backend Component Tests - coupled to the Backend API and ERP. I'll show you how to refactor these brittle tests. ## Why Legacy Code Turns Small Changes Into Multi-Day Firefighting DevFeed: [Why Legacy Code Turns Small Changes Into Multi-Day Firefighting]() Original publisher: [Read original article]() Author: Valentina Jemuović Published: 2026-06-30T06:02:36Z Content type: opinion Language: en Sources: [Optivem Journal]() Topics: [legacy](), [Test-driven development](), [Development](), [Software]() Tags: [dev](), [engineering](), [legacy-code](), [tdd]() ### AI overview This commentary examines how legacy code can turn a small change into days of investigation and risk. It argues that tangled dependencies, missing tests, and outdated code prevent senior developers from improving architecture and make routine maintenance frustrating. ### Source excerpt The field took twenty minutes. Everything around it took three days. ## Community Comebacks, Angular 21.1 Features, and Smarter Signal Forms ⚡ DevFeed: [Community Comebacks, Angular 21.1 Features, and Smarter Signal Forms ⚡]() Original publisher: [Read original article]() Author: Angular Published: 2026-06-19T10:01:04Z Content type: article Language: en Sources: [Angular]() Topics: [Angular](), [Forms](), [async](), [Open Source](), [legacy](), [migration]() Tags: [angular](), [angular-newsletter](), [angular-release](), [angular-weekly](), [async](), [asynchronous](), [forms](), [legacy](), [migration](), [open-source]() ### AI overview This Angular community roundup covers podcast episodes about Angular 20 and developer career setbacks, a recap of Angular 21.1, Signal Forms techniques for asynchronous validators and debouncing, dynamic form lists, an interview about joining the Angular team, and migration to modern Control Flow syntax. ### Source excerpt The Angular community is about much more than just code -- it's about the people building it, their career journeys, and how we collaborate. This week's roundup features inspiring community stories alongside technical deep dives into the Angular 21.1 features and advanced form tuning. Tune into this week's excellent community resources The Dev Life Podcast: Inside Angular 20 & Navigating Layoffs Brooke Avery @JediBravery and Matthew Christiansen back-to-back drop two must-listen episodes of The Dev Life podcast. First, they sit down with Minko Gechev @mgechev to go inside the engineering decisions of Angular 20. Then, they host GDE Chris Perko for an incredibly timely, candid conversation about bouncing back from tech layoffs and turning career setbacks into massive opportunities. Listen to Ep. 3 (Inside Angular 20): https://www.youtube.com/watch?v=QhfXXXzOD6g Listen to Ep. 4 (Navigating Layoffs): https://www.youtube.com/watch?v=laYzvyEDtw8 What was new in Angular 21.1? Alain Chautard @AlainChautard provides a fantastic, concise recap of the January Angular release. If you want to know what minor features, bug fixes, and performance polishes landed in Angular 21.1, this is your go-to guide. Read the release recap: https://blog.angulartraining.com/whats-new-in-angular-21-1-7454f699104f Stop Wasting API Calls! Async Validators & Debouncing Fanis Prodromou @prodromouf tackles a massive real-world performance issue in form handling. Learn how to combine asynchronous validators with debouncing in the Signal Forms API to keep your backend from being overwhelmed by unnecessary API requests. Watch the tutorial: https://youtu.be/R10dQ4zlWs0 Dynamic Lists & Joining the Angular Team (French) Modeste Assiongbon @rblmdst shares two incredible French-language videos this week. Dive into a technical walkthrough on handling dynamic field lists using Signal Forms. Then, catch an inspiring interview with Matthieu Riegler @Jean_Meche, tracking his journey from a casual open-source cont ## Cockroach Labs and Netlution Partner to Accelerate Database Modernization in Germany DevFeed: [Cockroach Labs and Netlution Partner to Accelerate Database Modernization in Germany]() Original publisher: [Read original article]() Author: Tushar Ghotikar Published: 2026-04-06T00:00:00Z Content type: article Language: en Sources: [Cockroach Labs]() Topics: [Cockroach Labs](), [CockroachDB](), [digital sovereignty](), [legacy](), [Cloud](), [implementation]() Tags: [cockroach-labs](), [cockroachdb](), [digital-sovereignty](), [digital-transformation](), [germany](), [implementation](), [legacy](), [modernization](), [partner]() ### AI overview Cockroach Labs and Germany-based IT consulting firm Netlution have entered a strategic partnership to help enterprises in EMEA adopt resilient, distributed SQL for mission-critical applications. The collaboration combines CockroachDB's cloud-native architecture with Netlution's local delivery expertise to support database modernization, data sovereignty, compliance, and legacy-system transformation. ### Source excerpt The data landscape for European enterprises is shifting, shaped by an intersection of technological ambition and a sophisticated regulatory environment. ## Building Resilient Fintech Infrastructure for Scale DevFeed: [Building Resilient Fintech Infrastructure for Scale]() Original publisher: [Read original article]() Author: David Weiss Published: 2026-04-02T00:00:00Z Content type: article Language: en Sources: [Cockroach Labs]() Topics: [Resilience](), [Data Infrastructure](), [Database](), [CockroachDB](), [legacy]() Tags: [cockroach-labs](), [cockroachdb](), [compliance](), [fintech](), [fraud-detection](), [infrastructure](), [legacy](), [outages](), [postgresql](), [resilience](), [uptime]() ### AI overview The article argues that fintech and quant firms need resilient data infrastructure to handle growth, real-time payments, instant settlement, AI-driven fraud detection, and cross-border compliance. It describes the limits of legacy database architectures and presents SumUp's migration from PostgreSQL to CockroachDB as an example of improved resilience and near-zero downtime. ### Source excerpt The fintech companies and quant firms that define the next decade aren't just building better products. They're succeeding with more resilient fintech infrastructure. ## Revamping Myntra App Analytics persistence with KMP and SQLite DevFeed: [Revamping Myntra App Analytics persistence with KMP and SQLite]() Original publisher: [Read original article]() Author: Kartik Sharma Published: 2026-03-31T13:01:09Z Content type: article Language: en Sources: [Myntra]() Topics: [App](), [SQLite](), [Persistence](), [SDK](), [Databases](), [legacy](), [Error Handling]() Tags: [android](), [app](), [databases](), [error-handling](), [ios](), [kotlin-multiplatform](), [legacy](), [mobile-app-development](), [persistence](), [sdk](), [sqlite]() ### AI overview This engineering post describes Myntra's effort to re-architect the persistence layer of its app analytics SDK. It explains how a legacy Android pipeline using in-memory queues and SharedPreferences created performance and data-reliability bottlenecks as event volume grew, and introduces a SQLite-backed persistence engine intended to improve app stability and data integrity. ### Source excerpt Introduction In the dynamic landscape of e-commerce, data is the bedrock of decision-making, and app stability is the foundation of user experience. At Myntra, where millions of users engage with our platform daily, ensuring the reliability of both is paramount. This necessity drove us to re-architect a critical piece of our infrastructure: the persistence layer of the Myntra app's analytics SDK. This post details our journey of augmenting our legacy analytics SDK with a robust new persistence engine backed by SQLite[1], achieving significant gains in app stability and data integrity. Background: The Limits of the Legacy Pipeline For years, our legacy in-house analytics SDK was the workhorse for collecting user interaction data. However, as our app's event volume grew, the SDK's aging persistence and processing logic created significant bottlenecks that led to degraded app performance and compromised the reliability of analytics data our product teams depended on. On Android: The Legacy Pipeline and its Limits On Android, the legacy analytics pipeline followed a straightforward event processing model: Capture, Persist & Batch: Events generated by used actions were held in an in-memory queue and then serialized into a persistent queue backed by SharedPreferences[2]. Once a batch threshold was met (typically 10 events), the batch was dispatched to the server. Background Flushing: Periodic background jobs flushed unsent events and retried failed batches. Error Handling: Failed batches were pushed to a separate retry queue, with older events silently purged if the queue hit its cap. High level overview of legacy android pipeline At the time of the initial implementation, SharedPreferences was a pragmatic choice to prioritize velocity. The ecosystem for local databases on Android was still maturing, and raw SQLite often required significant boilerplate compared to the simplicity of a key-value store. However, SharedPreferences is architecturally limited for high-throughp ## Choose Boring Technology and Innovative Practices DevFeed: [Choose Boring Technology and Innovative Practices]() Original publisher: [Read original article]() Author: Hillel Wayne Published: 2026-03-24T14:38:06Z Content type: opinion Language: en Sources: [Newsletter feed for Hillel Wayne's Newsletter]() Topics: [maintenance](), [legacy](), [Software](), [The Julia Language](), [Databases]() Tags: [innovation](), [legacy](), [maintenance](), [technology](), [time]() ### AI overview The article argues that innovative technology carries unknown risks and long-term maintenance costs, while practices can be changed more easily. It recommends being conservative about business-critical software and more willing to innovate in development practices and tools. ### Source excerpt The famous article Choose Boring Technology lists two problems with using innovative technology: There are too many "unknown unknowns" in a new technology, whereas in boring technology the pitfalls are already well-known. Shiny tech has a maintenance burden that persist long after everybody has gotten bored with it. Both of these tie back to the idea that the main cost of technology is maintenance. Even if something is easy to build with, it might not be as easy to keep running. We cannot "abandon" mission-critical technology. Say my team builds a new service on Julia, and 2 years later decides it was the wrong choice. We're stuck with either the (expensive) process of migrating all our data to Postgres code to Java or the (expensive) process of keeping it running anyway. Either way, the company needs to spend resources keeping engineers trained on the tech instead of other useful things, like how to mine crypto in their heads. Tech is slow to change. Not as slow to change as, say, a bridge, but still pretty slow. Now say at the same time as Julia, we also decided to start practicing test && commit || revert (TCR). After two years, we get sick of that, too. To deal with this, we can simply... not do TCR anymore. There is no "legacy practice" we need to support, no maintenance burden to dropping a process. It is much easier to adopt and abandon practices than it is to adopt and abandon technology. This means while we should be conservative in the software we use, we can be more freely innovative in how we use it. If we get three innovation tokens for technology, we get like six or seven for practices. And we can trade in our practices to get those tokens back. (The flip side of this is that social processes are less "stable" than technology and take more work to keep running. This is why "engineering controls" are considered more effective as reducing accidents than administrative controls.) Choose Boring Material and Innovative Tools Pushing this argument further, w ## What Database Modernization Means in the Cloud Era DevFeed: [What Database Modernization Means in the Cloud Era]() Original publisher: [Read original article]() Author: David Weiss Published: 2026-02-09T00:00:00Z Content type: article Language: en Sources: [Cockroach Labs]() Topics: [Databases](), [Cloud](), [cloud-infrastructure](), [Resilience](), [legacy](), [SQL](), [consistency]() Tags: [2026](), [cloud](), [cloud-infrastructure](), [cloud-native](), [consistency](), [databases](), [distributed](), [failover](), [infrastructure](), [legacy](), [modernization](), [operational](), [outages](), [patterns](), [performance](), [resilience](), [scale](), [schema](), [sql](), [systems]() ### AI overview This article explains database modernization in cloud environments, emphasizing architectures that scale horizontally, tolerate infrastructure failures, support global access, preserve transactional consistency, and reduce operational risk. It presents distributed SQL as an approach for incremental modernization. ### Source excerpt Database modernization is a priority for many enterprises in 2026, as pressure builds for applications to grow more distributed, failure-tolerant, and globally accessible. Increasing cloud deployments may seem like a quick cure... ## Why Software Migration Requires Continuous Adaptation DevFeed: [Why Software Migration Requires Continuous Adaptation]() Original publisher: [Read original article]() Author: hi@swizec.com (Swizec Teller) Published: 2026-01-31T00:00:00Z Content type: opinion Language: en Sources: [Swizec Teller]() Topics: [migration](), [Software Engineering](), [Refactoring](), [legacy]() Tags: [legacy](), [migration](), [software-development](), [software-engineering]() ### AI overview This opinion article argues that production software is always undergoing migration as requirements, teams, and systems change. It explains that migration must account for legacy behavior, accumulated knowledge, edge cases, and persistent data, making incremental adaptation a central part of software engineering. ### Source excerpt Your code becomes legacy software when it works. You build something to solve a problem, then the problem changes. Or best practices evolve. Or you hire team members with more experience. Or the world changes. Or you have more people touching the same code and your beautiful architectural vision didn't translate. ## Refining SQL Data Models Without Breaking Legacy Code DevFeed: [Refining SQL Data Models Without Breaking Legacy Code]() Original publisher: [Read original article]() Author: Hillel Wayne Published: 2026-01-20T17:49:07Z Content type: article Language: en Sources: [Newsletter feed for Hillel Wayne's Newsletter]() Topics: [SQL](), [Databases](), [legacy]() Tags: [database](), [event-sourcing](), [legacy-code](), [sql](), [sql-database]() ### AI overview This article explains how refinement mappings can support SQL schema changes while preserving compatibility with existing code. It applies the approach to migrating a boolean column to a timestamp, then to an event-sourcing-like model, and examines how mutability constraints affect whether the refinement remains valid. ### Source excerpt Imagine we have a SQL database with a user table, and users have a non-nullable is_activated boolean column. Having read That Boolean Should Probably Be Something else, you decide to migrate it to a nullable activated_at column. You can change any of the SQL queries that read/update the user table but not any of the code that uses the results of these queries. Can we make this change in a way that preserves all external properties? Yes. If an update would set is_activated to true, instead set it to the current date. Now define the refinement mapping that takes a new_user and returns an old_user. All columns will be unchanged except is_activated, which will be f(new_user).is_activated = if new_user.activated_at == NULL then FALSE else TRUE Now new code can use new_user directly while legacy code can use f(new_user) instead, which will behave indistinguishably from the old_user. A little more time passes and you decide to switch to an event sourcing-like model. So instead of an activated_at column, you have a user_events table, where every record is (user_id, timestamp, event). So adding an activate event will activate the user, adding a deactivate event will deactivate the user. Once again, we can update the queries but not any of the code that uses the results of these queries. Can we make a change that preserves all external properties? Yes. If an update would change is_activated, instead have it add an appropriate record to the event table. Now, define the refinement mapping that takes newer_user and returns new_user. The activated_at field will be computed like this: g(newer_user).activated_at = # last_activated_event let lae = newer_user.events .filter(event = "activate" | "deactivate") .last, in if lae.event == "activate" then lae.timestamp else NULL Now new code can use newer_user directly while old code can use g(newer_user) and the really old code can use f(g(newer_user)). Mutability constraints I said "these preserve all external properties" and that was a [Next page]()