Build #AI agents that actually remember with Hermes Agent on #RedHat#OpenShift AI. Deploy with KServe InferenceService, vLLM GPU acceleration, and persistent storage for skills and conversation history.
Complete deployment in under ๐ minutes.
https://t.co/WU3Z2IWkEp
This one has been in the works for a while. @cedricclyburn teaching LLM inference, compression, and benchmarking with @vllm_project -- free course with @DeepLearningAI. Proud of this one.
Reframe #AI optimization with eval-driven development. Define criteria before writing prompts, measure quality scores from 0-100, and iterate based on data, not intuition. Turn probabilistic systems into controlled experiments with measurable outcomes.
https://t.co/MbMvoSeXbT
๐ Improve routing accuracy from 80% to 98% with fine-tuned embedding models in vLLM Semantic Router. Reduce misrouting from 1 in 5 to 1 in 70 requests using contrastive learning on #RedHat#OpenShift#AI.
https://t.co/JaEdAkPxFj
Troubleshoot memory leaks and automate performance tests with #RedHat build of #Cryostat 4.2. Run SQL queries on JFR recordings, profile with async-profiler, and manage smart triggers from the web console.
https://t.co/cXJ69nRWAW
๐ ICYMI: Instruction-based malware is the new threat. โ ๏ธ 300+ malicious skills were recently found in the #OpenClaw marketplace. No bad code, just adversarial inputs.
Protect your stack from semantic malware with #RedHat's #AI security layers. #RHSummit
https://t.co/FG3h4vKAIk
Protect your #Kubernetes operators from memory exhaustion attacks. Any user with edit permissions can flood ConfigMaps and trigger OOMKilled crashes. Filter your informer caches, label your resources, and audit your ByObject configuration today.
https://t.co/9PmlLKHApL
๐ Master time synchronization challenges in #Kubernetes environments. The PTP operator now integrates containerized chronyd for seamless failover from GNSS to NTP, ensuring your system clock stays accurate even during signal loss.
https://t.co/XtuvWYwCFg
Improve node stability in #RedHat#OpenShift clusters with AutoSizingReserved and system-reserved-compressible enforcement. These features auto scale system reserves based on node capacity and enforce CPU limits on system daemons.
Read the full blog ๐ https://t.co/fhTVXlk1VV
Transform your #Go performance analysis workflow with #Claude. Analyze large CPU profiles, parse trace files, compare multiple benchmarks, and identify optimization opportunities in your applications without manual inspection overhead.
https://t.co/oN5mZdcIdX
Tackle production outages smarter with LogAn, an #opensource tool that extracts log templates and applies semantic classification. Get started with the CLI or run it as a #Podman container to analyze your logs today. https://t.co/uhTJvTKwN3
Upgrade your real-time #Linux monitoring with stalld's queue_track backend. Move from polling to event-driven detection using #BPF CO-RE. Experience reduced overhead, complete scheduler visibility, and robust performance across kernel versions.
https://t.co/WjZOKdA3V8
Optimize cost and performance for production #AI workloads. #RedHat and Rebellions bring ATOM NPUs to #OpenShift#AI, reinforcing our "any model, any accelerator, any cloud" strategy for enterprise inference infrastructure.
https://t.co/bP8DMeMHJi
๐ ICYMI: How do you give developers speed without compromising security? โ๏ธ Meet Janine (Dev) and Raj (OpSec). See how they use automation to deploy sensitive AI models into confidential environments with zero trust. #RHSummit
Read the guide โฌ๏ธ
https://t.co/vM3idNfKi5
Test against real dependencies, not simulations. Discover how @RedHat#OpenShift#AI replaced mocked unit tests with real Llama Stack integration, leveraged record-replay to eliminate LLM costs, and built a daily compatibility sentinel for early warnings.
https://t.co/wAU2hRyk1P
Validate your #AI agentic infrastructure by running end-to-end benchmarks like the Berkeley Function-Calling Leaderboard. Co-upgrade the Open GenAI Stack (OGX) and vLLM on #RedHat#OpenShift#AI 3.4 to prevent silent tool-calling accuracy regressions.
https://t.co/e9KWkE0M22
Analyze the performance and power trade-offs of a 32-core x64 system on 100 GbE workloads. Discover how increasing concurrency boosts system energy efficiency despite diminishing marginal throughput returns and hidden hardware bottlenecks.
https://t.co/c7bTOdHwPC
Secure GPU-accelerated workloads on #RedHat#OpenShift. Leverage sandboxed containers and the Red Hat build of Trustee to achieve dual CPU and GPU hardware attestation for confidential computing.
https://t.co/12uyeVgAvN
Simplify multi-model routing by decoupling provider integrations from your code.
Use #RedHat#OpenShift#AI 3.4โs built-in Models-as-a-Service capability or a LiteLLM proxy to orchestrate a single, unified gateway endpoint for all LLM inference. https://t.co/6z369jKPLJ