Systems | Development | Analytics | API | Testing

ClearML

ClearML + Nutanix: The Deep-Dive Guide to a Turnkey Enterprise AI Stack

Apr 7, 2026 By ClearML In ClearML
Enterprise AI teams are laboring under two key pressures: 1) squeeze maximum value out of expensive GPUs and 2) deliver new GenAI experiences faster than competitors. Too often, their ability to deliver is blocked by: The new ClearML running on the Nutanix Kubernetes Platform (NKP) solution is designed to tackle every one of these headaches. Below, we unpack each layer of the stack and explain what it is, why it matters, and how it helps you ship AI both quickly and with cost efficiency.
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bitrise

GitHub Actions macOS runner alternative: M4 Pro with 54GB RAM and same-day Xcode

Apr 7, 2026 By Catherine Doyle In Bitrise
Bitrise Build Hub is a vertically integrated mobile CI/CD infrastructure layer that drops into GitHub Actions with one line of YAML. GitHub Actions runs your CI, but its Mac runners are holding your mobile builds back. Limited M1/M2 hardware, stale Xcode, no cache co-location, no macOS uptime SLA. The infrastructure wasn't built for mobile. Build Hub was. Build Hub upgrades the runner layer underneath.
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appsignal

Monitoring Express Route Performance with AppSignal

Apr 7, 2026 By Dimitrije Stamenić In AppSignal
Slow Express routes rarely look broken in logs. They just feel sluggish to users. With AppSignal, though, you can quickly identify which endpoints are the slowest, gain insight into each request, and find out if the latency is related to any errors or slow queries. In this guide, you'll set up a mock Express application, create a load, and use AppSignal to analyze a route's performance as if you were working through a live incident.
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InsightSoftware

SQL Query Optimization: How Driver Architecture Shapes Database Performance

Apr 7, 2026 By InsightSoftware In InsightSoftware
When it comes to database performance, most focus on writing better SQL or tuning database parameters. Both matter. But there’s a third layer that’s crucial to consider: the driver sitting between your application and your data source. Drivers decide where query operations actually execute. Some operations get pushed down to the data source, a fast process. Others get processed in the driver layer itself, which takes more time.
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zymr

AI for Treatment Personalization: Use Cases, Benefits, and Implementation Guide (2026)

Apr 7, 2026 By Suhas Phartale In Zymr
Healthcare still runs on generalized treatment protocols, even though every patient is biologically and clinically different. Clinicians often make decisions under time pressure using fragmented data from EHRs, labs, and patient history. That leads to gaps such as delayed diagnoses, trial-and-error treatments, and inconsistent outcomes. At the same time, expectations have changed. Patients now expect healthcare to be as personalized as the rest of their digital experiences.
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bugfender

iOS App Clips: What They Are and How to Create One

Apr 7, 2026 By Aleix Ventayol In Bugfender
App Clips are one of the most under-appreciated parts of the iOS universe. Introduced with iOS 14 back in 2020, they allow users to sample the best features of an app without having to download it in full. Users explore the Apple ecosystem. Developers broaden their audience. Win-win, right? Well, bizarrely few devs are actually using App Clips right now. A lot of folks think they’re going to be overly complex and full of friction.
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speedscale

From Datadog to CI Tests: Catch Regressions Before Deploy

Apr 6, 2026 By Ken Ahrens In Speedscale
I worked in observability for years, and the same pattern showed up across teams. An alert fired, the on-call rotation scrambled, and everyone did what they had to do to stabilize production. Then came the retrospective. Once the immediate pressure was gone, the conversation shifted to one question: how do we make sure this never happens again? My friend Jade Rubick coined a name for that principle: DRI, “don’t repeat the incident”.
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Hevo's Next Evolution

Apr 6, 2026 By Hevo Data In Hevo
Every company has an AI roadmap. Very few have the data infrastructure to execute it. At Hevo Data, we've spent 8 years building pipelines that are reliable, simple, and transparent so 2,000+ data teams can build without second-guessing their data. We sat down with Manish Jethani, Amit Gupta, and Scott Husband to talk about what comes next. If your data isn't AI-ready, your roadmap stays a roadmap. We've re-engineered the platform to serve as the context engine your AI vision actually runs on. Because the models are only as good as the data underneath them.
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keploy

API Testing Strategies: A Complete Guide (2026)

Apr 6, 2026 By Keploy In Keploy
API testing strategies directly impact your release cycle. With 83% of web traffic flowing through APIs, even a single failure can break payments, dashboards, and user experience. Teams that invest in automated API testing do not slow down, they ship faster with confidence. A strong strategy goes beyond checklists. It defines what success looks like, where tests run, how data stays consistent, and how testing fits into CI/CD.
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