2026-09-15 13:17
π AI coding agents are transforming service development by generating entire services and scaffolding applications quickly. However, they may not align with your organizationβs specific compliance rules or existing services. Understanding these gaps is crucial to ensure compliance and efficiency. Explore how Red Hat Developer Hub addresses these challenges! #AICoding #Compliance #RedHat #SoftwareDevelopment #TechTrends
Source: Red Hat Developer Blog
Evan Shortiss, Ben Wilcock
2026-09-14 13:01
π Exciting progress in model quantization! The article discusses how the Llama 3.1 8B Instruct model was compressed from 14.9 GB to 8.0 GB using 8-bit integer (INT8) W8A8 quantization techniques, including SmoothQuant and GPTQ. This approach maintains accuracy while enhancing performance. #AI #Quantization #MachineLearning #DataScience #ModelOptimization
Source: Red Hat Developer Blog
Sana Fayyaz
2026-09-14 13:01
π Great news for developers! Python 3.14 is now available in a free-threaded build for Red Hat Enterprise Linux 9.8 and 10.2. This new version allows for full parallel CPU execution, enhancing performance. You can find both the standard and free-threaded variants in the Red Hat CodeReady Linux Builder repositories. This marks the first official support for the free-threaded build. #Python #RedHat #Development #RHEL #TechNews
Source: Red Hat Developer Blog
LumΓr Balhar
2026-09-11 13:01
π Is your encrypted server stuck in initramfs? This article explains how to unlock a LUKS root over SSH on Fedora and RHEL. It details three commands and a kernel argument that enable NetworkManager and sshd in the initramfs environment. This allows remote unlocking of your encrypted root, ensuring smoother server management. For more insights, check out the full post! #Linux #Fedora #RHEL #ServerManagement #Encryption
Source: Red Hat Developer Blog
Josephine Pfeiffer
2026-09-11 13:01
Unlock the potential of large language models (LLMs) with AutoRAG! These models rely on training data to understand context, including specific corporate jargon. Without the right data, they may misinterpret information, leading to inaccuracies. AutoRAG aims to enhance LLMs by providing tailored knowledge, improving their response quality. #AI #AutoRAG #LanguageModels #TechInnovation #DataScience π€π
Source: Red Hat Developer Blog
Diego Alvarez Ponce, Diego Garcia Perez
2026-09-11 13:01
Choosing the right edge platform is crucial for organizations. Options vary widely, from basic single-board computers to complex Kubernetes clusters with advanced features. Selecting an inadequate platform can lead to challenges as needs evolve. Understanding your requirements is key to making an informed decision. π§π»π #EdgeComputing #RedHat #Kubernetes #TechDecisions #CloudSolutions
Source: Red Hat Developer Blog
Daniel Froehlich
2026-09-10 13:01
AI implementation is proving costly for organizations, as many have opted to use external AI providers for their workflows. Initially, this approach seemed effective due to accessible APIs and reliable models. However, unexpected expenses have raised concerns among businesses. Exploring the shift from being token consumers to becoming token providers could help organizations manage costs better. ππ‘ #AI #BusinessStrategy #TechTrends #Innovation
Source: Red Hat Developer Blog
Markell Rawls
2026-09-09 15:05
In part 3 of the series on local guardrail development, the focus is on deploying NeMo Guardrails on Red Hat OpenShift AI. The previous articles covered designing guardrail configurations and conducting manual testing. The second part emphasized rigorous testing against large-scale risk datasets. This series offers valuable insights for developers. ππ§ #NeMoGuardrails #RedHat #OpenShiftAI #TechDevelopment #DataSafety
Source: Red Hat Developer Blog
Rob Geada
2026-09-09 14:01
Explore the benefits of using local and open source coding assistants! Many popular AI coding tools lack transparency or compromise your data privacy by relying on cloud processing. For those seeking alternatives, consider integrating an open coding assistant with an open source IDE. Stay in control of your projects while enhancing your coding experience! π»π #OpenSource #Coding #DataPrivacy #AI #DeveloperTools
Source: Red Hat Developer Blog
Seth Kenlon
2026-09-09 03:32
π A recent CSA Research survey highlights that 76% of consumers prefer to buy in their native language, and 40% wonβt purchase in another. This preference extends to how products communicate verbally. Explore how to personalize text-to-speech voices using Kubeflow Trainer on Red Hat OpenShift AI. #TextToSpeech #LanguagePreference #AI #RedHat #CustomerExperience
Source: Red Hat Developer Blog
Dmytro Hryshchenko, Abhijeet Dhumal
2026-09-08 14:20
Large language models (LLMs) face challenges with autoregressive decoding, as they rely heavily on memory bandwidth. Each token requires a full forward pass over billions of parameters, leading to inefficiencies. The article discusses the MTP training objective, which helps models like DeepSeek and Qwen predict multiple future tokens, enhancing data efficiency and quality. For more insights, check out the full article! ππ‘ #LLM #DataEfficiency #MachineLearning #FastMTP #RedHatDeveloper
Source: Red Hat Developer Blog
Rahul Tuli
2026-09-07 07:01
Large language models like Llama 3.1 8B require significant GPU memory, around 15 GB when using Bfloat16 (BF16) precision. This includes storage for 8 billion parameters and additional memory for key-value caches and activations during inference. W8A8 INT8 quantization offers a solution by reducing model size while maintaining performance and accuracy. ππ‘π #MachineLearning #AI #ModelOptimization #Quantization
Source: Red Hat Developer Blog
Sana Fayyaz
2026-09-07 07:01
π Red Hat Developer Hub offers a new approach to software template authoring with rhdh-templates. Platform engineers and developers often face challenges with Nunjucks syntax and locating YAML files. The process can lead to errors that are only identified after rendering in the developer portal. AI tools may assist with generic YAML, but they do not support the specific conventions of Red Hat Developer Hub and Backstage. #RedHat #DeveloperHub #YAML #SoftwareTemplates #TechNews
Source: Red Hat Developer Blog
Kashish Mittal
2026-09-07 03:00
π Red Hat Advanced Cluster Security for Kubernetes offers an image scanning API crucial for CI/CD pipelines assessing vulnerabilities. π« However, upgrades and restarts can cause downtime, disrupting essential build processes. This article outlines a reference architecture that resolves this issue by utilizing two Central service instances along with a client-side failover mechanism. #Kubernetes #RedHat #DevOps #Cybersecurity #HAScanning
Source: Red Hat Developer Blog
Johannes Malsam
2026-09-05 03:01
Unlocking the potential of AI in operations is crucial for effective incident management. In a recent article, a basic AIOps workflow was developed using AWS EC2, Red Hat Enterprise Linux, Red Hat Ansible Automation Platform, and Claude Code. The focus is on transforming insights from incidents into safe, repeatable actions. Explore how technology can streamline operations! ππ» #AIOps #RedHat #Automation #TechTrends #IncidentManagement
Source: Red Hat Developer Blog
Neha Chugh
2026-09-04 07:01
Unlock the power of automation with Ansible! πβ¨ The article discusses how to integrate AI-assisted workflows into firewall management. It highlights the ability to manage access requests, such as allowing app-client-01 to connect to the database on port 5432. Explore how Ansible can streamline these processes effectively. #Ansible #Automation #Cybersecurity #AI #FirewallManagement
Source: Red Hat Developer Blog
Michal Zdyb
2026-09-04 07:01
In shared AI and high-performance computing clusters, managing limited hardware resources like GPUs and CPUs is crucial for OpenShift platform engineers. The FIFO admission rule can lead to long wait times for later workloads, impacting service predictability. Red Hat build of Kueue 1.4 introduces two methods for ensuring fairness: fair sharing-based preemption and admission fair sharing. Learn more about optimizing resource management! ππ» #OpenShift #Kueue #ResourceManagement #AI...
Source: Red Hat Developer Blog
Maysa De Macedo Souza
2026-09-03 17:56
π Amazon has introduced P-EAGLE, a new speculative decoding algorithm designed to enhance LLM inference. This innovation builds on EAGLE-3 by incorporating parallel drafting, which aims to improve efficiency in processing. Discover how P-EAGLE is set to advance speculative decoding technology in the latest update. #TechInnovation #MachineLearning #Amazon #SpeculativeDecoding #AI
Source: Red Hat Developer Blog
Helen Zhao, Megan Flynn, Dipika Sikka
2026-09-03 16:58
In part 2 of the series on local guardrail development, the focus is on evaluating LLM guardrail configurations using EvalHub. The article expands on the design and development process discussed in the first part, emphasizing the importance of manual testing to ensure effectiveness. Stay tuned for further insights on enhancing local configurations! ππ» #EvalHub #LLM #GuardrailDevelopment #RedHat #TechInsights
Source: Red Hat Developer Blog
Rob Geada
2026-09-03 07:01
π Adopting eval-driven development is crucial for reliable AI agents. However, implementation can be challenging. Even agents that perform well in basic scenarios may face subtle issues in production. These include misusing tools, straying off-topic, or providing plausible but incorrect responses. Unit tests often miss these failures, highlighting the need for better evaluation methods. #AI #EvalDrivenDevelopment #IBM #OpenShift #TechInsights
Source: Red Hat Developer Blog
Hema Veeradhi, Surya Pathak
2026-09-03 03:01
π Migrating to Red Hat OpenShift Virtualization can modernize your infrastructure without disrupting existing network settings. However, traditional systems often face challenges in maintaining connectivity for imported VMs and ensuring multi-tenant isolation. The article highlights solutions using BGP and EVPN to streamline these processes. #RedHat #OpenShift #Virtualization #Networking #BGP #EVPN
Source: Red Hat Developer Blog
Miguel Duarte de Mora Barroso, Valentino Uberti
2026-09-02 07:01
A recent article discusses the risks associated with deploying productivity assistants in pharmaceutical research. A researcher utilized a trusted open-weight model, enhanced with a low-rank adaptation (LoRA) adapter for specific lab needs. While the main model is reliable, the adapter is often overlooked, raising concerns about potential vulnerabilities. OpenShift AI offers strategies to mitigate these risks and ensure safer implementation. ππ‘ #AI #Pharmaceuticals #Cybersecurity #OpenSource...
Source: Red Hat Developer Blog
Mike Hepburn
2026-09-02 03:16
π Model sizes are rapidly increasing, doubling each year, while GPU memory struggles to keep pace. π The article discusses LLM quantization, a technique that enables efficient deployment of large models on accessible hardware. This is essential for serving multiple users effectively. π‘ Learn how quantization can help in managing resource limitations while maximizing performance. #LLM #Quantization #MachineLearning #AI #TechTrends
Source: Red Hat Developer Blog
Cedric Clyburn
2026-09-01 07:01
Discover how to enhance your streaming retrieval-augmented generation (RAG) pipeline with OpenShift AI. The previous article outlined a single Ray Data script that handles parsing, chunking, embedding, and writing to Milvus. However, this monolithic approach has a drawback: if a parsing error occurs, you must restart the entire process. Learn more about optimizing your RAG workflow! ππ» #OpenShiftAI #DataPipeline #RAG #TechInnovation #RedHatDeveloper
Source: Red Hat Developer Blog
Ana Biazetti, Saad Zaher
2026-09-01 03:01
π Large language models (LLMs) offer great potential, but deploying them comes with risks like prompt injection and data leakage. π€ Red Hat has teamed up with NVIDIA to create NeMo Guardrails, an open source framework designed to add safety measures to LLM applications. π§ This solution enables developers to implement programmable guardrails, enhancing the security of their AI systems. #AI #MachineLearning #DataSecurity #NeMoGuardrails #OpenSource
Source: Red Hat Developer Blog
Rob Geada
2026-09-01 03:01
Discover the latest in Red Hat OpenShift scaling solutions! This article explores the MachineSet Autoscaler with KEDA, a metrics-driven method for scaling individual MachineSets based on external or custom signals. Previously, we discussed the Cluster Autoscaler, a built-in, Kubernetes-native approach. Learn how these options can enhance your compute infrastructure! π»π #RedHat #OpenShift #KEDA #Autoscaling #CloudComputing
Source: Red Hat Developer Blog
Ramon Gordillo Gutierrez, Jose Ortiz Padilla
2026-08-31 07:16
Managing large-scale Kubernetes environments presents significant challenges, especially in maintaining visibility and troubleshooting across multiple clusters. As the number of managed clusters increases, platform engineers face a higher cognitive load, which can slow response times during critical incidents. OpenShift Lightspeed and Red Hat Advanced Cluster Management offer solutions to help manage fleet health effectively. π§π»π #Kubernetes #OpenShift #RedHat #CloudManagement #TechSolutions
Source: Red Hat Developer Blog
Diego Alvarez Ponce, Luiz Bernardo Levenhagen
2026-08-31 03:01
Are idle GPUs costing you? π₯οΈπΈ In Kubernetes, wasted GPU resources can lead to significant expenses. Users often find GPUs allocated for days with minimal activity, resulting in unnecessary charges. The article introduces GPU-pruner, a tool designed to address this issue by optimizing GPU allocation. Learn more about how to manage your resources effectively! #Kubernetes #GPUManagement #CloudComputing #TechSolutions #ResourceOptimization
Source: Red Hat Developer Blog
Fahim Uddin
2026-08-28 08:16
Running a multi-tenant Red Hat OpenShift cluster can be challenging. Currently, every backup and restore with Velero needs cluster-admin privileges. This limits application teams from managing their own workloads effectively. They often rely on the platform team, creating delays and bottlenecks in the process. A new approach to self-service backup may help streamline these operations. ππ»π‘ #OpenShift #Backup #CloudComputing #DevOps #RedHat
Source: Red Hat Developer Blog
Michal Pryc, Shubham Dilip Pampattiwar
2026-08-28 03:01
π Building reliable notebook images for Open Data Hub and Red Hat OpenShift AI has been streamlined. Key to this process is the concept of hermetic builds, where nothing is downloaded during the build. Dependencies are pre-fetched and installed from a local cache, ensuring consistency and eliminating network issues. This approach works seamlessly across different environments, including laptops and GitHub Actions. π§π» #OpenDataHub #RedHat #DevOps #Containerization #AI
Source: Red Hat Developer Blog
Vath Sok
2026-08-27 03:01
π llm-d flow control introduces priority-aware admission and tenant fairness scheduling for GPUs. This enhancement allows platform teams to effectively manage mixed workloads on shared model pools. Now available in Red Hat AI Inference 3.5, this feature aims to optimize GPU resource utilization. #RedHat #AIInference #GPU #TechUpdates #MachineLearning
Source: Red Hat Developer Blog
Alexa Griffith, Rishabh Saini
2026-08-26 09:16
Understanding AI observability is crucial, especially since AI responses can be inaccurate. The article explores how MLflow is utilized to enhance AI observability, ensuring better monitoring and evaluation of AI models. For those interested in improving AI accuracy, this piece provides valuable insights. π€π #AI #MLflow #DataScience #TechInsights
Source: Red Hat Developer Blog
Cedric Clyburn
2026-08-26 07:01
π Red Hat's Ansible Automation Platform has enhanced its VS Code extension since 2021. Key features include automatic linting and simplified documentation access. A standout capability is the generation of Ansible playbooks and roles using AI language models. Explore the Ansible playbook generation lab with Gemini and OpenAI! #RedHat #Ansible #Automation #AI #VSCode
Source: Red Hat Developer Blog
clobner
2026-08-26 03:01
Discover a new method for automating Red Hat OpenShift AI installations using Helm and GitOps. This article builds on previous insights about managing OpenShift AI dependencies and presents a more streamlined approach for deployment. Learn how this can enhance your workflow! ππ§ #RedHat #OpenShiftAI #GitOps #Helm #Automation
Source: Red Hat Developer Blog
Davide Bianchi, Andrea Tarocchi
2026-08-26 03:00
Large language models are great for conversation, but enterprise needs often require structured reasoning, like generating SQL or JSON. Supervised fine-tuning improves these skills but can be costly and time-consuming to curate data. Explore how GRPO fine-tuning on Red Hat OpenShift AI addresses these challenges with reinforcement learning. #AI #RedHat #MachineLearning #DataScience #EnterpriseSolutions π€π
Source: Red Hat Developer Blog
Fiona Waters
2026-08-25 03:16
Explore the latest advancements in GRPO fine-tuning on Red Hat OpenShift AI. This article discusses how reinforcement learning can utilize verifiable rewards to enhance training efficiency. Key insights include the role of the Training Hub in facilitating this process and its implications for developers in AI. Stay informed about the future of AI development! π€π #RedHat #OpenShiftAI #ReinforcementLearning #AI #TrainingHub
Source: Red Hat Developer Blog
Fiona Waters
2026-08-25 03:16
π Explore the capabilities of the Red Hat OpenShift Cluster Autoscaler! This built-in tool automatically adjusts your cluster size based on workload demands. It integrates seamlessly with the Red Hat OpenShift machine API, using two key resources: ClusterAutoscalerAPI and MachineAutoscalerAPI. Learn how it handles scale-up and scale-down operations, ensuring efficient resource management. Check out the article for practical examples on Microsoft Azure! #RedHat #OpenShift #Autoscaler...
Source: Red Hat Developer Blog
Ramon Gordillo Gutierrez, Jose Ortiz Padilla
2026-08-24 07:01
π Ray is a powerful open-source framework for scaling AI workloads, now integrated into Red Hat OpenShift AI. With the inclusion of the Training Hub, users can easily fine-tune large language models using algorithms like LoRA, SFT, and GRPO without complex setup. π οΈ The article details how to run a LoRA fine-tuning job on Ray, focusing on SQL generation and model evaluation from a Jupyter notebook. A complete guide with examples is available in the Red Hat AI examples repository. π Ray offers...
Source: Red Hat Developer Blog
Fiona Waters
2026-08-21 13:18
π Red Hat introduces an event-driven automatic first information report (FIR) collector designed to enhance failure reporting in OpenShift. This tool captures critical system context immediately during incidents, ensuring logs aren't lost or overwritten. It monitors key events, triggers data collection automatically, and stores logs off-site temporarily. This innovation helps teams analyze incidents effectively, improving response times and customer trust. Explore the project and its...
Source: Red Hat Developer Blog
Periyamaruthu Mohanraj
2026-08-21 07:01
Red Hat introduces Ansible development workspaces, streamlining automation developer onboarding. π By utilizing OpenShift Dev Spaces, developers can quickly access a fully configured VS Code environment in the cloud, enhancing standardization and security. Key benefits include faster onboarding, consistent tools, and centralized control over development environments. ππ» This approach eliminates common issues like version mismatches and local setup complexities. #Ansible #OpenShift #Automation...
Source: Red Hat Developer Blog
Leonardo Gallego