# Hotspot Published articles for Hotspot. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Sunsetting spoton: Android 16 killed the hotspot toggle trick DevFeed: [Sunsetting spoton: Android 16 killed the hotspot toggle trick]() Original publisher: [Read original article]() Author: Marco Gomiero Published: 2025-12-16T00:00:00Z Content type: article Language: en Sources: [Posts on Marco Gomiero]() Topics: [Android](), [Wi-Fi](), [API]() Tags: [android](), [android-16](), [api](), [hotspot](), [wi-fi]() ### AI overview The author explains why the spoton Wear OS and companion phone app is being sunset. The app used reflection to call hidden Android tethering APIs and let users toggle a phone hotspot from a watch. Android 16 moved the relevant methods and added a permission limited to system apps, preventing the approach from working for a normal Play Store app. ### Source excerpt spoton is getting sunset. I started this project because I had a very specific (and very lazy) problem: I wanted to enable my phone hotspot without taking my phone out of my pocket. I do it often when I'm travelling or working somewhere without stable Wi-Fi, and every time it was the same ritual: unlock phone, quick settings, find the hotspot tile, toggle, put phone away. At some point, I thought: "This should be a button on my wrist." ## Consistent hashing algorithm DevFeed: [Consistent hashing algorithm]() Original publisher: [Read original article]() Author: NK Published: 2023-02-22T16:39:15Z Content type: tutorial Language: en Sources: [High Scalability](), [High Scalability]() Topics: [hashing](), [Algorithm](), [Cache](), [Scalability](), [distributed-systems](), [Software](), [Availability]() Tags: [algorithm](), [availability](), [cache](), [consistent-hashing](), [distributed-system](), [hashing](), [hotspot](), [load-balancing](), [low-latency](), [scalability](), [sharding](), [software-architecture]() ### AI overview A tutorial explaining consistent hashing: nodes and data keys are mapped onto a virtual hash ring, and clockwise traversal assigns data to nodes. It discusses terminology, cache-server scaling requirements, hotspot reduction, dynamic load, replication, availability, and latency. ### Source excerpt This is a guest article by NK. You can view the original article Consistent hashing explained on systemdesign.one website. How does consistent hashing work? At a high level, consistent hashing performs the following operations: The output of the hash function is placed on a virtual ring structure (known as the hash ring) The hashed IP addresses of the nodes are used to assign a position for the nodes on the hash ring The key of a data object is hashed using the same hash function to find the position of the key on the hash ring The hash ring is traversed in the clockwise direction starting from the position of the key until a node is found The data object is stored or retrieved from the node that was found Terminology ## Test React app on mobile without Wi-Fi DevFeed: [Test React app on mobile without Wi-Fi]() Original publisher: [Read original article]() Author: info@jeroenmols.com (Jeroen Mols) Published: 2022-11-19T00:00:00Z Content type: tutorial Language: en Sources: [Jeroen Mols]() Topics: [React](), [Mobile](), [Development](), [USB]() Tags: [android](), [blogs](), [development](), [hotspot](), [how-to](), [mobile](), [offline](), [react](), [tips](), [usb]() ### AI overview This quick tutorial explains how to access a React development server from an Android phone without Wi-Fi by connecting the phone to a laptop with USB tethering. ### Source excerpt Traveling by train or plane and want to test your react app on your mobile phone? This quick post explains how to access your react development server from your phone without a Wi-Fi connection. ## What's new in Figma: December 2021 DevFeed: [What's new in Figma: December 2021]() Original publisher: [Read original article]() Author: Sula Yang Published: 2021-12-16T00:00:00Z Content type: article Language: en Sources: [Figma Blog]() Topics: [Figma](), [Playback](), [App]() Tags: [collaboration](), [design](), [feature](), [features](), [figma](), [hotspot](), [inspiration](), [latest-release](), [media](), [mobile](), [music](), [playback](), [plugin](), [productivity](), [prototypes](), [release](), [updates](), [webcam](), [work]() ### AI overview Figma's December 2021 update added collaboration and media features across Figma and FigJam, including Vimeo and Spotify support, webcam and screen recording through a Vimeo plugin, new FigJam highlighting and erasing tools, and expanded mobile app support for prototypes, files, projects, teams, and workspaces. ### Source excerpt A round-up of new features, fixes, and capabilities that we've added to Figma and FigJam recently. ## Essential Technology for a Team Offsite DevFeed: [Essential Technology for a Team Offsite]() Original publisher: [Read original article]() Author: Fuzzygroup Published: 2019-10-30T00:00:00Z Content type: opinion Language: en Sources: [Scott Johnson]() Topics: [hdmi](), [USB](), [Chrome](), [Windows](), [dropbox](), [Google]() Tags: [battery](), [beats](), [cast](), [chrome](), [chrome-cast](), [connectivity](), [dropbox](), [hdmi](), [hotspot](), [ipad](), [mac](), [management](), [offsite](), [startup](), [team](), [technology](), [wifi](), [windows]() ### AI overview A personal checklist of technology to bring to a team offsite, based on difficulties connecting several devices to a Chromecast-equipped TV. The recommendations include cables, USB storage, power accessories, a hotspot, a Chromecast, and a USB speaker, with dongles suggested for newer MacBooks. ### Source excerpt I'm in the process of wrapping up a team offsite even though I was ostensibly the lead technologist present, I was not actually prepared in terms of bringing the right technology with me to facilitate the team's needs. The single worst omission was the lack of an HDMI cable without which, I saw three tech folk (me, other engineer #1, team coordinator) fail to be able to connect a Mac, an iPad and a Windows box to a Chrome Cast equipped TV. Here is my list of the technical stuff I will never again be without for a team meeting: A couple of USB sticks. Even today in the age of Google Drive and DropBox, USB sticks can still be more convenient An Anker USB battery just in case 2 lightning cables, at least one of which is 6 foot like this Amazon cable 1 6' USB type C cable 1 USB 2 cable 1 power strip with USB ports 1 extension cord with USB ports 1 Verizon Mifi Hotspot able to share connectivity if WiFi fails 1 ChromeCast 1 6' HDMI Cable 1 USB Speaker like a Beats Pill This is roughly enough technology to support a team offsite of 6 to 8 people (imho). Note: I use a MacBook 2015 classic so I still have real ports. If you are using newer MacBooks then you likely need dongles as well. ## Basics of Java Garbage Collection DevFeed: [Basics of Java Garbage Collection]() Original publisher: [Read original article]() Author: umer Published: 2017-08-06T00:00:00Z Content type: tutorial Language: en Sources: [Code Ahoy - Articles]() Topics: [Java](), [Algorithms](), [Concurrency](), [real-time]() Tags: [garbage-collection](), [garbage-collectors](), [gc](), [hotspot](), [java](), [jvm](), [latency](), [low-latency](), [memory](), [performance](), [real-time](), [threads](), [troubleshooting]() ### AI overview This tutorial provides a high-level overview of Java garbage collection, including collector algorithms, stop-the-world pauses, throughput and low-latency tradeoffs, JVM heap generations, and troubleshooting performance issues. ### Source excerpt Knock, knock. Who's there? ...long GC pause... Java. It's an old joke from the time when Java was new and slow compared to other languages. Over time, Java became a lot faster. Today it powers many real-time applications with hundreds of thousands of concurrent users. These days, the biggest impact on Java's performance comes from its garbage collection. Fortunately, in many cases, it can be tweaked and optimized to improve performance. For most applications, the default settings of the JVM work fine. But when you start noticing performance issues caused by garbage collection and giving more heap memory isn't possible, you need to tune and optimize the garbage collection. For most developers, it's a chore. It requires patience, good knowledge of how garbage collection works and an understanding of application's behavior. This post is a high-level overview of Java's garbage collection with some examples of troubleshooting performance issues. Let's get started. Java ships with several garbage collectors. More specifically, these are different algorithms that run in their own threads. Each works differently and has pros and cons. The most important thing to keep in mind is that all garbage collectors stop the world. That is, your application is put on hold or paused, as the garbage is collected and taken out. The main difference among the algorithms is how they stop the world. Some algorithms sit completely idle until the garbage collection is absolutely needed and then pause your application for a long period while others do most of their work concurrently with your application and thus need a shorter pause during stop the world phase. The best algorithm depends on your goals: are your optimizing for throughput where long pauses every now and then are tolerable or you are optimizing for low latency by spreading it out and having short pauses all along. To enhance the garbage collection process, Java (HotSpot JVM, more accurately) divides up the heap memory into two genera ## TIP: Use Tethering to Simulate Slow Network Connections DevFeed: [TIP: Use Tethering to Simulate Slow Network Connections]() Original publisher: [Read original article]() Author: Shai Almog Published: 2017-01-29T00:00:00Z Content type: tutorial Language: en Sources: [CodeName One]() Topics: [Android Studio](), [Mobile](), [debugging](), [Large Screen](), [Networks](), [ide]() Tags: [android](), [android-studio](), [debug](), [debugging](), [hotspot](), [laptop](), [mobile](), [mobile-apps](), [networking](), [performance](), [portable](), [simulator](), [wifi]() ### AI overview This article explains how to use phone tethering and a portable hotspot to simulate slow 3G or 2G network conditions for debugging and profiling mobile applications in the simulator or on a device. ### Source excerpt I recently had to debug some code on Android Studio and was reminded how awful that IDE really is. IntelliJ is a pretty good IDE but Android Studio is remarkably slow even for trivial projects... One of the things that make it slow (besides RAM usage) is the approach of downloading everything it needs dynamically. This might be unnoticeable on Google's fast networks where this probably runs instantly. But on my fast home network this was painfully slow. ## Java Garbage Collection Distilled DevFeed: [Java Garbage Collection Distilled]() Original publisher: [Read original article]() Author: Martin Thompson (noreply@blogger.com) Published: 2013-07-16T19:45:00Z Content type: tutorial Language: en Sources: [Mechanical Sympathy]() Topics: [Java](), [openjdk](), [Algorithms, Complexity](), [systems]() Tags: [algorithms](), [garbage-collection](), [guide](), [hotspot](), [java](), [jvm](), [latency](), [memory](), [openjdk](), [performance]() ### AI overview A guide to the tradeoffs involved in choosing and tuning Java garbage-collection algorithms for different workloads. It focuses on Oracle HotSpot and OpenJDK collectors and considers throughput, latency, and memory goals. ### Source excerpt Serial, Parallel, Concurrent, CMS, G1, Young Gen, New Gen, Old Gen, Perm Gen, Eden, Tenured, Survivor Spaces, Safepoints, and the hundreds of JVM startup flags. Does this all baffle you when trying to tune the garbage collector while trying to get the required throughput and latency from your Java application? If it does then do not worry, you are not alone. Documentation describing garbage collection feels like man pages for an aircraft. Every knob and dial is detailed and explained but nowhere can you find a guide on how to fly. This article will attempt to explain the tradeoffs when choosing and tuning garbage collection algorithms for a particular workload. The focus will be on Oracle Hotspot JVM and OpenJDK collectors as those are the ones in most common usage. Towards the end other commercial JVMs will be discussed to illustrate alternatives. The Tradeoffs Wise folk keep telling us, "You do not get something for nothing". When we get something we usually have to give up something in return. When it comes to garbage collection we play with 3 major variables that set targets for the collectors: Throughput: The amount of work done by an application as a ratio of time spent in GC. Target throughput with -XX:GCTimeRatio=99 ; 99 is the default equating to 1% GC time. Latency: The time taken by systems in responding to events which is impacted by pauses introduced by garbage collection. Target latency for GC pauses with -XX:MaxGCPauseMillis=. Memory: The amount of memory our systems use to store state, which is often copied and moved around when being managed. The set of active objects retained by the application at any point in time is known as the Live Set. Maximum heap size -Xmx is a tuning parameter for setting the heap size available to an application. Note: Often Hotspot cannot achieve these targets and will silently continue without warning, having missed its target by a great margin. Latency is a distribution across events. It may be acceptable to have ## Printing Generated Assembly Code From The Hotspot JIT Compiler DevFeed: [Printing Generated Assembly Code From The Hotspot JIT Compiler]() Original publisher: [Read original article]() Author: Martin Thompson (noreply@blogger.com) Published: 2013-06-27T19:24:00Z Content type: tutorial Language: en Sources: [Mechanical Sympathy]() Topics: [Java](), [JIT](), [Compiler](), [Assembly](), [Command-line interface](), [Linux](), [Concurrency]() Tags: [asm](), [assembly](), [command-line](), [compiler](), [concurrent](), [debugging](), [hotspot](), [java](), [jit](), [latency](), [linux]() ### AI overview A tutorial on installing the Hotspot Disassembler Plugin and using Java command-line options to print generated assembly code for a targeted method. It uses a concurrent two-thread latency test involving volatile fields and explains how to inspect JIT-generated output. ### Source excerpt Sometimes when profiling a Java application it is necessary to understand the assembly code generated by the Hotspot JIT compiler. This can be useful in determining what optimisation decisions have been made and how our code changes can affect the generated assembly code. It is also useful at times knowing what instructions are emitted when debugging a concurrent algorithm to ensure visibility rules have been applied as expected. I have found quite a few bugs in various JVMs this way. This blog illustrates how to install a Disassembler Plugin and provides command line options for targeting a particular method. Installation Previously it was necessary to obtain a debug build for printing the assembly code generated by the Hotspot JIT for the Oracle/SUN JVM. Since Java 7, it has been possible to print the generated assembly code if a Disassembler Plugin is installed in a standard Oracle Hotspot JVM. To install the plugin for 64-bit Linux follow the steps below: Download the appropriate binary, or build from source, from https://kenai.com/projects/base-hsdis/downloads On Linux rename linux-hsdis-amd64.so to libhsdis-amd64.so Copy the shared library to $JAVA_HOME/jre/lib/amd64/server You now have the plugin installed! Test Program To test the plugin we need some code that is both interesting to a programmer and executes sufficiently hot to be optimised by the JIT. Some details of when the JIT will optimise can be found here. The code below can be used to measure the average latency between two threads by reading and writing volatile fields. These volatile fields are interesting because they require associated hardware fences to honour the Java Memory Model. import static java.lang.System.out; public class InterThreadLatency { private static final int REPETITIONS = 100 * 1000 * 1000; private static volatile int ping = -1; private static volatile int pong = -1; public static void main(final String[] args) throws Exception { for (int i = 0; i < 5; i++) { final long duratio ## Listing HotSpot VM Flags and Their Default Values DevFeed: [Listing HotSpot VM Flags and Their Default Values]() Original publisher: [Read original article]() Author: Michael Barker (noreply@blogger.com) Published: 2011-08-18T09:58:00Z Content type: tutorial Language: en Sources: [Bad Concurrency]() Topics: [Java]() Tags: [hotspot](), [java]() ### AI overview A short tip showing how to list HotSpot VM flags and their default values using java -XX:+PrintFlagsFinal. ### Source excerpt Ever wanted to know what flags could be set and their default values for the Hotspot VM? Try this: java -XX:+PrintFlagsFinal