Quick share. Been running into this enough times across NetSapiens deployments that it's worth flagging. Scenario: Call gets placed or transferred between two domains on the same NetSapiens platform. The call connects fine. Audio works. But the caller ID showing up on the receiving side is wrong. It's showing the local extension or domain user instead of the actual originating caller. If you check the NetSapiens Known Issues page, this maps to NMS-2518. It shows up specifically when calls cross domain boundaries during hold or transfer. The fallout is mostly cosmetic but it matters for anyone running multi-tenant reseller deployments. Your customer sees the wrong name in their call history. Voicemail attribution gets weird. Inter-domain analytics show calls from the wrong source. A few patterns I've seen work around it: Configure SIP header rewriting at the SBC layer to preserve the original From URI across domain hops For softphones that pull call history from NetSapiens API directly, verify which field the client is actually displaying. Some pull from orig_user , others from local_user . The discrepancy shows up clearer than you'd expect. If you're running a mobile softphone client, check whether the client is caching contact info locally and overriding what NetSapiens returns. A lot of "wrong caller ID" reports turn out to be client-side caching bugs, not platform bugs. The deeper fix is platform-side and depends on what NetSapiens version you're running. The cleaner softphone integrations route call history through the NetSapiens API rather than building it locally on the device, which sidesteps the worst of this behavior. White-label softphones that integrate natively with NetSapiens handle this more consistently than generic SIP clients. Tragofone is one example where the call history syncs through the NetSapiens softphone integration layer directly, so inter-domain caller ID is consistent with what the platform actually has. Other native integrations handle t

Se você já fez algum front-end interativo, já tem 80% do que precisa pra fazer um jogo simples. Game jams como a June Solstice são desculpa perfeita pra testar isso — três semanas, tema aberto, e você descobre que canvas + requestAnimationFrame levam longe. Por Que Desenvolvedores Web Deviam Fazer Game Jams A maioria dos devs que conheço nunca tentou fazer um jogo porque acha que precisa aprender Unity ou Unreal. Mas se você já mexeu com animações CSS, state management ou physics simulators básicos pra UI, você já cruzou metade da ponte. Game jams forçam escopo pequeno — você não vai fazer Elden Ring em três semanas, vai fazer um Snake com twist. E isso cabe perfeitamente no que o browser oferece. Além disso, jogos web rodam em qualquer lugar. Sem instalador, sem App Store review, sem build pra cinco plataformas. Você manda um link e qualquer um joga. Pra um jam onde o pessoal precisa testar dezenas de jogos rápido, isso importa. Canvas API: Seu Motor Gráfico Embutido O <canvas> existe desde 2010 e faz exatamente o que você precisa: desenhar pixels, shapes e imagens num loop de 60fps. A estrutura básica de qualquer jogo 2D cabe em 30 linhas: const canvas = document . querySelector ( ' canvas ' ); const ctx = canvas . getContext ( ' 2d ' ); const gameState = { player : { x : 50 , y : 50 , speed : 2 }, enemies : [] }; function update ( deltaTime ) { // Input handling if ( keys [ ' ArrowRight ' ]) gameState . player . x += gameState . player . speed ; if ( keys [ ' ArrowLeft ' ]) gameState . player . x -= gameState . player . speed ; // Game logic gameState . enemies . forEach ( enemy => { enemy . x += Math . sin ( Date . now () / 1000 ) * 0.5 ; }); } function render () { ctx . clearRect ( 0 , 0 , canvas . width , canvas . height ); // Draw player ctx . fillStyle = ' #00ff00 ' ; ctx . fillRect ( gameState . player . x , gameState . player . y , 20 , 20 ); // Draw enemies gameState . enemies . forEach ( enemy => { ctx . fillStyle = ' #ff0000 ' ; ctx . fillRect ( enemy .

I've started a series of short blog posts about hot path optimizations. This first one covers a counterintuitive optimization: replacing integer division ( IDIVQ ) with floating-point division ( DIVSD ). submitted by /u/watman12 [link] [留言]

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