
Red Hat Developer
@rhdevelopers
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Red Hat Developer program provides no-cost software subscriptions, tutorials, and career insights to enterprise software developers and architects.
Joined June 2015
RT @natalevinto: Developer Day Milan happening now! Here's Roberto CarratalΓ fand Marco Caimi showing Llama Stack @vllm_project @_llm_d_ anβ¦.
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Integrate #OpenTelemetry on #OpenShift for efficient #cloudnative deployments with fast startup and low memory. π
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Create a Model-as-a-Service platform using @RedHat #OpenShift Container Platform and @openshift #AI. π
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RT @cedricclyburn: Happy Monday folks! Iβm inbound βοΈ to @dev_bcn where Iβll be speaking about my favorite open source projects @Podman_ioβ¦.
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Are you on the fence about #PodmanDesktop? Well, we have π reasons on why you should use it for your container development. Check them out! .π
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π₯ #RHEL is available for #Microsoft's Windows Subsystem for #Linux. Build Linux apps on a Windows machine, and then deploy on a RHEL environment for production to save significant time and resources - that's just the beginning. Check it out. π
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π΄ Tired of manual builds & deployments? Automate CI/CD for your container apps on @RedHat #OpenShift, and reduce mistakes, boost productivity, and test more thoroughly. Even better, it's ready to go in the #DeveloperSandbox!.π
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#RedHat @OpenShift #AI now includes LLM Compressor, part of the vLLM project for efficient serving of LLMsβhelping deliver faster, more cost-effective inference at scale. π Read: .βΆοΈ Watch:
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Understand how #HaProxy route settings, a default feature, influence your #JBossEAP, #Serverless, and Data Grid deployments. Master your OpenShift Ingress. π
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π£ Calling all #developers! Your ultimate learning and networking experience awaits at @WeAreDevs 2025, where you can get insights on #AI, cloud, #opensource, and more. Registration is still open!.π
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Improve #developer productivity and app #security while providing a foundation for #AI-enabled app development with @RedHat Advanced Developer Suite. π
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Unleash faster LLM inference and explore how #vLLM and speculative decoding are transforming the speed and efficiency of large language models. π
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