Tecnología

TeamCity 2026.2.2 and 2026.1.6 Updates

TeamCity On-Premises 2026.2.2 and 2026.1.6 bug-fix updates are now available. These updates resolve a significant number of issues, including security and performance issues, as well as the following bugs: As always, we strongly recommend installing these updates, as they address security vulnerabilities and help keep your TeamCity On-Premises instance protected against potential threats. See TeamCity […]

The JetBrains Blog · EN

The eMudhra Certificate Authority Compromise: What It Means for TeamCity

Summary In October 2026, the private keys of eight intermediate certificate authorities operated by eMudhra were found to be weak and recoverable from public data. According to eMudhra’s official statement, none of the affected intermediate CAs had issued end-entity (leaf) certificates, and eMudhra is not aware of evidence that the weak keys were recovered or exploited before the issue was disclosed. The […]

The JetBrains Blog · EN

Hear What Your IDE Is Doing: New Sound Cues in JetBrains IDEs

You can use the audio player below to listen to this blog post. With JetBrains IDEs 2026.3, we’re adding a new way to stay connected to your work: sound cues. A short sound can tell you if a build has finished successfully or failed, a breakpoint has been hit, or there’s something at the caret […]

The JetBrains Blog · EN

Use Your GitHub Copilot Plan in JetBrains Air – in Your IDE and in the Cloud

GitHub and JetBrains are bringing GitHub Copilot to JetBrains Air. Air lets you hand coding tasks to agents, run them in parallel, and review their changes in one place. You can now pick GitHub Copilot as the agent in Air – locally in your JetBrains IDE, and in the cloud with Air Teams. Tasks run […]

The JetBrains Blog · EN

Flexible Authentication: Reimagining authentication for millions of users at Airbnb

Rebuilding login and signup surfaced product insights, not just technical challenges. Here’s how we designed Flexible Authentication at the intersection of product intuition and technical architecture. By : Jose Santos , Mike Barry For Airbnb, logins at irregular intervals are normal. A guest books a trip in January and may not open the app again until summer. A host checks back only when a reservation comes in, and may be busy with other activities when it does. For a two-sided marketplace where a failed login means a lost booking, and lost revenue for both the guest and the host, long gaps b

The Airbnb Tech Blog - Medium · EN

How we knew COVID was over (and what our models had to unlearn)

When we retrain, when we rebuild, and when we leave a model alone. By: Harrison Katz A forecast that carries weight The Forecasting Data Science team at Airbnb produces many of the forecasts the rest of the company plans around: demand, bookings, cancellations, and a range of finer cuts by market and segment, refreshed continuously across thousands of markets. The targets differ, and the models differ, but they have one thing in common: Other teams build on top of them. This means a forecast that is casually wrong is not a clean miss, as it might be in an academic setting. That’s because a sma

The Airbnb Tech Blog - Medium · EN

Project Lighthouse — Part 3: Introducing project-lighthouse-anonymize

Project Lighthouse — Part 3: Introducing project-lighthouse-anonymize The data in Project Lighthouse is powered by privacy-preserving anonymization code. We’ve put this code into open source, and published two new technical papers detailing the scalable algorithms and data quality frameworks behind it. By: Adam Bloomston Introduction In 2020, we launched Project Lighthouse, which we developed in partnership with leading civil rights and privacy organizations. As our 2020 announcement details, Project Lighthouse enables us to measure potential disparities in user experiences. This work uses per

The Airbnb Tech Blog - Medium · EN

Beyond the model: Engineering AI infra with scientific judgement

How Airbnb’s agent harness transforms unstructured data exploration by encoding scientific methodology into scalable, reproducible, and audit-ready infrastructure. By : Wren Dougherty Ask a coding agent to analyze 100,000 customer support conversations and within minutes you’ll have a polished taxonomy, precise prevalence numbers, and an executive-ready summary. What you can’t see is the investigation that produced them: the methods it chose, the evidence it weighed, how much to trust it, or whether a second request would agree. All that reaches you is the polish. The model is undeniably intel

The Airbnb Tech Blog - Medium · EN

The guest journey, updated in real time: extending Airbnb’s sequence recommender with Chronon

How two new Chronon capabilities, Push Mode and NRT Model Transform, allows us to provide more relevant search results instantly as a guest explores, rather than waiting for the next batch run. By : Pengyu Hou , Yuli Han , Daochen Zha , Haozhen Ding , Xin Liu , Sophie Wang , Pallavi Adusumilli , Sherry Li , Henry Saputra , Chun How Tan , Huiji Gao , Yan Zhang , Stephanie Moyerman , Yi Li , and Sanjeev Katariya A guest’s interaction with Airbnb doesn’t pause to wait for a nightly batch job. Someone might browse a dozen listings on a Tuesday afternoon, run a new search that evening, and expect t

The Airbnb Tech Blog - Medium · EN

Personalization without user identity

How Airbnb uses proximity signals to personalize without relying on individual user history. By : Wei Jiang , Bin Xu , Bharathi Thangamani , Weiwei Guo , Sundar Srinivasavaradhan , Tracy Yu , Huiji Gao , Swapnil Ghike , Michael Kinoti Great personalization starts with knowing your user. But what happens when the user is a stranger? A significant share of Airbnb users arrive without a login, without a recent search history, or without any prior booking — especially those landing from paid advertising or organic search. For these users, the ML models that power search ranking, destination recomm

The Airbnb Tech Blog - Medium · EN

Beyond synthetic testing: Capturing and replaying real database workloads at Airbnb

How we capture real production database traffic at Airbnb and replay it offline to load-test, plan capacity, and de-risk upgrades. By: Zuofei Wang , Erluo Li Introduction At Airbnb, MySQL-compatible databases are a critical backbone of our online database infrastructure: a fleet of hundreds of clusters supporting thousands of use cases at millions of queries per second (QPS). Operating databases at scale brings hard problems, including sizing clusters for future growth, keeping behavior consistent across version upgrades and migrations, and reproducing production incidents well enough to debug

The Airbnb Tech Blog - Medium · EN

CASTLE: training natural language search before the first real query

How we addressed the cold-start problem for Airbnb’s natural language search by jointly generating synthetic training data — queries and relevance labels — from de-identified booking and search signals. By : Wendy Ran Wei , Hao Li , Weiwei Guo , Xiaowei Liu , Xueyin Chen , Chun How Tan , Malay Haldar , Soumyadip Banerjee , Kedar Bellare , Huiji Gao , Sanjeev Katariya , and Stephanie Moyerman Introduction Natural language search lets guests express intent in their own words, such as “romantic cabin near skiing” or “pet-friendly beach house that sleeps eight,” rather than navigating filters and

The Airbnb Tech Blog - Medium · EN

The Regression Tests Nobody Writes: Capturing How Software Actually Behaves

Founded in 2008, Stack Overflow’s public platform is used by nearly everyone who codes to learn, share their knowledge, collaborate, and build their careers.

Stack Overflow Blog · EN

Rumors of the SaaS demise are greatly exaggerated

Recorded on the floor of LDX3, Ryan chats with Nivia Henry, an engineering leader most recently at Netflix, about the reality of the supposed SaaS apocalypse, the complex calculus of the modern build-versus-buy decision in the era of AI, and the critical importance of understanding system architectures to manage long-term infrastructure costs.

Stack Overflow Blog · EN

Elevators, toasters, and the birth of Java

Ryan sits down with James Gosling, creator of Java at Sun Microsystems, to talk about the early networking friction that drove the need for interconnectedness, the stringent reliability requirements of consumer electronics companies that inspired the Java virtual machine, and the evolution of garbage collectors that allow Java to handle large-scale concurrent memory management.

Stack Overflow Blog · EN

Delivering controlled and concentrated context

Check out the new features and capabilities now available in Stack Internal and Stack Internal Community. Try Stack Internal for free by visiting stackinternal.com.

Stack Overflow Blog · EN

A JSON schema Is not an AI governance layer

The AI governance argument is happening one layer above the code that actually stops your agent.

Stack Overflow Blog · EN

The reports of Stack Overflow's death are greatly exaggerated

I’ve seen the recent predictions about Stack Overflow’s demise. They make for compelling headlines, but they confuse a change in how people access knowledge with the disappearance of the knowledge—and the company—behind it.

Stack Overflow Blog · EN

It’s ok that computers are (sometimes) better than us

Ryan is joined by Charity Majors, co-founder and CTO at Honeycomb, for a conversation about applying the concept of immutable infrastructure to software development to treat code like cattle instead of pets, shifting the paradigm of system specifications to accommodate the rapid influx of AI-generated code, and navigating the complex ethical boundaries between system observability and human surveillance in modern technology ecosystems.

Stack Overflow Blog · EN

Oh, your agents need OAuth2, too

Recorded at LDX3 by LeadDev, Ryan chats with Dan Moore, Senior Director of CIAM Strategy and Identity Standards at FusionAuth, about adapting established OAuth2 protocols for the agentic era, the security necessity of giving autonomous AI agents their own distinct identities, and how AI coding tools are shifting developers' focus toward solving core business problems.

Stack Overflow Blog · EN

What's on my plate

Atlantis is the new version of UserLand Frontier that runs on modern systems. As I've said earlier, I'm surprised how well we covered all the bases, it's reliable, it works like Frontier works with a couple of important exceptions which I've now had it start working on. First, the Find and Replace command has never worked properly in Atlantis and it's been a struggle to get Claude to fix the problems. I think the key was I didn't tell it to use the C kernel as the guide for how Find & Replace works. So it was trying to create a F&R that you would have in a text editor, not the object database

Scripting News · EN

Frontier's debugger is back

The Frontier debugger now works in Atlantis, the version of Frontier that runs on modern systems, the one I have been using for everyday work for a month or so. I write software in the debugger, testing each addition after writing it, to see that the input produces the expected output. I also use it to see why code that has worked for 10 years now doesn't produce the expected result, ie debugging. A UserTalk script, stopped at a breakpoint. Full size screen shot .

Scripting News · EN

Updating to .NET 8, updating to IHostBuilder, and running Playwright Tests within NUnit headless or headed on any OS

I've been doing not just Unit Testing for my sites but full on Integration Testing and Browser Automation Testing as early as 2007 with Selenium. Lately, however, I've been using the faster and generally more compatible Playwright . It has one API and can test on Windows, Linux, Mac, locally, in a container (headless), in my CI/CD pipeline, on Azure DevOps, or in GitHub Actions. For me, it's that last moment of truth to make sure that the site runs completely from end to end. I can write those Playwright tests in something like TypeScript, and I could launch them with node, but I like running

Scott Hanselman's Blog · EN

Open Sourcing DOS 4

See the canonical version of this blog post at the Microsoft Open Source Blog ! Ten years ago, Microsoft released the source for MS-DOS 1.25 and 2.0 to the Computer History Museum, and then later republished them for reference purposes. This code holds an important place in history and is a fascinating read of an operating system that was written entirely in 8086 assembly code nearly 45 years ago. Today, in partnership with IBM and in the spirit of open innovation, we're releasing the source code to MS-DOS 4.00 under the MIT license. There's a somewhat complex and fascinating history behind th

Scott Hanselman's Blog · EN