InfoQ Homepage Operating Systems Content on InfoQ
-
/articles/android-beat-aligned-mobile-audio-streaming/en/smallimage/android-beat-aligned-mobile-audio-streaming-thumbnail-1783408153943.jpg)
Beat-Aligned Mobile Audio Streaming with Virtual Chunks and Native Playback
In this article, I describe the challenges and the design of a React Native real-time mobile beat-aligned playback system for iOS and Android. The system combines personalization with low-latency, and seamless navigation and was the result of careful analysis and experimentation to address strict mobile and network constraints as well as meet user expectations.
-
/articles/rdla-offline-first-reactive-android-data-layer/en/smallimage/rdla-offline-first-reactive-android-data-layer-thumbnail-1781776366032.jpg)
Beyond CLEAN and MVP: Architecting an Offline-First Reactive Data Layer in Android
With the Reactive Data Layer Architecture (RDLA), you establish a clear boundary between public data APIs and private, framework-specific data-source implementations. Your presentation layer operates in a purely reactive manner, observing data changes rather than procedurally querying them. RDLA also simplifies testing by encouraging you to program to interfaces and use clean seeding patterns.
-
/articles/ebpf-for-security-observability/en/smallimage/ebpf-for-security-observability-thumbnail-1778674557176.jpg)
Kernel-Level Ground Truth: Why eBPF is Replacing User-Space Agents for Security Observability
eBPF is emerging as a preferred method for security observability over traditional user-space agents. By attaching probes directly to the Linux kernel's syscall interface, it provides consistent visibility even during container-level compromises. eBPF reduces security-related CPU consumption and limits data volume by performing filtering at the kernel level, enhancing operational efficiency.
-
/articles/metrics-driven-approach-ios-performance/en/smallimage/metrics-driven-approach-ios-performance-thumbnail-1777624958302.jpg)
Beyond the Benchmark: a Metrics-Driven Approach to Sustained iOS Performance on Real Devices
iOS performance engineering often defaults to a mental model where performance is a property of a component. Performance is instead an emergent behavior of the interaction between application code, device hardware, OS resource management, network conditions, and user behavior patterns over time. This article gives a direct, first-party path to capturing performance issues using Xcode Instruments.
-
/articles/adopting-swiftui-at-scale/en/smallimage/swiftui-at-consumer-scale-lessons-from-adopting-it-with-50-million-users-thumb-1773911055159.jpg)
Lessons from Adopting SwiftUI in an App with 50 Million Users
Most SwiftUI educational content focuses on small projects and sample apps that do not explain what it means to adopt it in a 50 million user app developed by a team of 20+ iOS engineers. This article will attempt to fill this gap. and show how to succeed without breaking your team, your app, or your users' trust along the way.
-
/articles/kotlin-scalable-swiftui-patterns/en/smallimage/thumbnail-kotlin-scalable-swiftui-patterns-1771922819056.jpg)
Borrowing from Kotlin/Android to Architect Scalable iOS Apps in SwiftUI
Building iOS apps can feel like stitching together guidance from blog posts and Apple samples, which are rarely representative of how production architectures grow and survive. In contrast, the Kotlin/Android ecosystem has converged on well-documented, real-world patterns. This article explores how those approaches can be translated into Swift/SwiftUI to create maintainable, scalable iOS apps.
-
/articles/kotlin-multiplatform-evaluation/en/smallimage/kotlin-multiplatform-evaluation-thumbnail-1756451872984.jpg)
Evaluating Kotlin Multiplatform: Benefits and Trade-Offs in Cross-Platform Development
KMP is emerging as an alternative for cross-platform development, offering a path to share code without sacrificing the performance and feel of a native application. KMP comes with its own set of trade-offs and this article dives deep into those. While it focuses primarily on Android and iOS, KMP can be used to build desktop, web, and server-side applications, all from the same shared logic.
-
/articles/ceph-rbd-open-source/en/smallimage/ceph-rbd-open-source-thumbnail-1751612399293.jpg)
Ceph RBD Turns 15: a Story of Open Source Creation
Fifteen years ago, Ceph RBD began as a community-driven idea that grew into essential infrastructure powering today's cloud platforms. This insider story from Yehuda Sadeh-Weinraub reveals how two developers started a distributed storage that now supports OpenStack and Kubernetes through transparent, collaborative development.
-
/articles/securing-linux-applications/en/smallimage/proactive-approaches-security-linux-logo-small-1727870445556.jpg)
Proactive Approaches to Securing Linux Systems and Engineering Applications
Maintaining a strong security posture is challenging, especially with Linux. An effective approach is proactive and includes patch management, optimized resource allocation, and effective alerting.
-
/articles/benchmark-profile-ebpf-code/en/smallimage/GettyImages-1460473661-small-1718285327503.jpg)
Zero to Performance Hero: How to Benchmark and Profile Your eBPF Code in Rust
In this article, we will walk through creating a basic eBPF program in Rust. We will intentionally include a performance regression and then use profilers to locate and fix the bug. We will also create benchmarks and track them using a continuous benchmarking tool for CI.
-
/articles/dfs-architecture-comparison/en/smallimage/comparative-analysis-GFS-Tectonic-JuiceFS-small-1687347930445.jpg)
Comparative Analysis of Major Distributed File System Architectures: GFS vs. Tectonic vs. JuiceFS
As storage needs continue to grow, traditional disk file systems have revealed their limitations. To address the growing storage demands, distributed file systems have emerged as dynamic and scalable solutions. In this article, we explore the design principles, innovations, and challenges addressed by three representative distributed file systems: Google File System (GFS), Tectonic, and JuiceFS.
-
/articles/debugging-production-ebpf-chaos/en/smallimage/debugging-production-eBPF-chaos-small-1686746361099.jpg)
Debugging Production: eBPF Chaos
This article shares insights into learning eBPF as a new cloud-native technology which aims to improve Observability and Security workflows. You’ll learn how chaos engineering can help, and get an insight into eBPF based observability and security use cases. Breaking them in a professional way also inspires new ideas for chaos engineering itself.