Daily archive

Refresh calendar

Pick a day and revisit the stories TechEveryday saved for you.

Artificial Intelligence / Machine Learning · 5

Automation / Agentic Systems · 5

Research Papers · 5

Embedded Systems · 5

Computer Systems · 5

Developer Tools / Open Source · 5

Cloud / Infrastructure · 5

Archived section

Artificial Intelligence / Machine Learning · 5

Artificial Intelligence / Machine Learning
arXiv7/30/2026
Recently

AISPA: User-Centric System Prompt Auditing for Large Language Model Applications

System prompts are instructions configured by developers to govern the behaviors of foundation models in AI applications. They are used throughout commercial AI products, but are rarely disclosed to the public or regulators, creating a serious trust and accountability gap in the wide deployment of AI systems. In this paper, we introduce Artificial Intelligence System Prompt Assurance (AISPA), a user-centric framework for systematically auditing system prompts in AI systems. Authors: Xiangning Lin, Shenzhe Zhu, Shu Yang.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: System prompts are instructions configured by developers to govern the behaviors of foundation models in AI applications.

Primary paperarxivcs.AI
Original
Artificial Intelligence / Machine Learning
arXiv7/28/2026
Recently

Large Language Model for Operations Research Formulation Selection in Multi-Warehouse Inventory Allocation

Multi-warehouse inventory allocation is typically formulated as a mixed-integer programming (MIP) problem, yet no single formulation consistently matches heterogeneous instance-level regimes induced by demand concentration, inventory imbalance, replenishment scale, service constraints, and forecast volatility. We study this issue as instance-wise operations research (OR) formulation selection, where each allocation instance is assigned to a solver-executable formulation from a candidate OR expert library. We propose a solver-guided large language model (LLM) framework for OR formulation selection, in which each OR expert corresponds to a MIP formulation encoding a distinct allocation priority. Authors: Jintao Xu, Yingzheng Ma, Jiong Dong.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: Multi-warehouse inventory allocation is typically formulated as a mixed-integer programming (MIP) problem, yet no single formulation consistently matches heterogeneous instance-level regimes induced by demand concentration, inventory imbalance, replenishment scale, service constraints, and forecast volatility.

Primary paperarxivcs.AI
Original
Artificial Intelligence / Machine Learning
arXiv7/29/2026
Recently

MMAC: A Massive Multi-dimensional Benchmark for Audio Captioning

With the development of audio large language models (AudioLLMs), audio captioning needs to move from brief descriptions toward open-ended and fine-grained free-form descriptions. Existing evaluations often focus on generation quality or task performance, making it difficult to diagnose information coverage and description reliability. We propose MMAC, a Massive Multi-dimensional benchmark for Audio Captioning. Authors: Weijie Wu, Junbo Li, Lin Li.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: With the development of audio large language models (AudioLLMs), audio captioning needs to move from brief descriptions toward open-ended and fine-grained free-form descriptions.

Primary paperarxivcs.SD
Original
Artificial Intelligence / Machine Learning
arXiv7/28/2026
Recently

Empirical Evaluation of Out-Of-Distribution Performance of Tabular Foundation Models

Tabular Foundation Models (TFMs) have emerged as novel approaches for tabular predictive tasks, demonstrating competitive predictive performance to ensemble tree-based models. Most TFMs are trained and evaluated on independent and identically distributed data, but this assumption changes in real-world scenarios due to distribution shifts, which compromise the robustness of models. Limited research has been conducted of TFMs under distribution shifts. Authors: Malena Loza, David Chushig-Muzo, Eva Milara.

Why it matters

Read this for the paper's specific claim in Artificial Intelligence / Machine Learning: Tabular Foundation Models (TFMs) have emerged as novel approaches for tabular predictive tasks, demonstrating competitive predictive performance to ensemble tree-based models.

Primary paperarxivcs.LG
Original
Artificial Intelligence / Machine Learning
Microsoft Research Blog7/30/2026
Recently

Echoverse: Deep, evolving environments for computer-use agents

Computer-use AI agents struggle with multi-step workflows like email and customer support. Echoverse trains agents in realistic environments rather than simply providing more training tasks, helping them improve as the tasks, tests, and environments evolve. The post Echoverse: Deep, evolving environments for computer-use agents appeared first on Microsoft Research.

Why it matters

Read this for the official technical update in Artificial Intelligence / Machine Learning: Computer-use AI agents struggle with multi-step workflows like email and customer support.

Official sourceResearch Blog
Original

Archived section

Automation / Agentic Systems · 5

Automation / Agentic Systems
arXiv7/30/2026
Recently

Change2Task: From Repository Changes to Executable Coding Agent Tasks and Environments

Scaling coding agents requires a continuing supply of executable data for training, benchmarking, and continuous evaluation. Each task must couple a realistic software state with a specification, development tools, and reliable verification. To expand this supply, we present Change2Task, a system grounded in repository history that converts merged pull requests into verified tasks on healthy modern revisions of the same repository. Authors: Haomin Qi, Xingliang Wang, Xuanqi Gao.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: Scaling coding agents requires a continuing supply of executable data for training, benchmarking, and continuous evaluation.

Primary paperarxivcs.SE
Original
Automation / Agentic Systems
arXiv7/30/2026
Recently

ORCA-bench: How Ready Are Language Model Agents for Oncall?

Large language models can write, patch, and search code, but oncall root cause analysis (RCA) demands something different: reasoning over noisy metrics, logs, traces, and source code, starting from ambiguous user-facing reports, often hours after the incident began. We introduce ORCA-bench, a benchmark that puts general-purpose coding agents in a production-fidelity oncall setting. ORCA-bench pairs a live OpenTelemetry-instrumented microservice system--exposing six days of metrics, logs, and traces through real telemetry interfaces (Prometheus, Jaeger, and OpenSearch via Grafana) and full source-code access--with 1,079 RCA tasks that systematically vary report specificity, time-to-detection, and co-occurring fault scenarios. Authors: Albert Gong, Kyuseong Choi, Abhineet Agarwal.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: Large language models can write, patch, and search code, but oncall root cause analysis (RCA) demands something different: reasoning over noisy metrics, logs, traces, and source code, starting from ambiguous user-facing reports, often hours after the incident began.

Primary paperarxivcs.CL
Original
Automation / Agentic Systems
arXiv7/30/2026
Recently

Frontis-MA1: Training an AI4AI Model towards Recursive Self-Improvement in Machine Learning Engineering

, AI4AI); machine learning engineering (MLE) offers a concrete, executable testbed for studying this capability. We introduce OpenMLE, an open full-stack system for RSI research in MLE, spanning verifiable task environments with execution feedback (OpenMLE-Gym), operator learning (OpenMLE-RL), and long-horizon search (OpenMLE-Evo). On this stack we post-train Frontis-MA1 (35B) as a meta-evolution agent for MLE, aligning post-training and inference around four atomic program-evolution operators (Draft, Improve, Debug, Crossover): the same operators are trained via execution-grounded SFT and RL on data deduplicated against all evaluation benchmarks, then composed into long-horizon search, coupling learning and evolution in a single loop. Authors: Junlin Yang, Che Jiang, Yu Fu.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: , AI4AI); machine learning engineering (MLE) offers a concrete, executable testbed for studying this capability.

Primary paperarxivcs.CL
Original
Automation / Agentic Systems
arXiv7/30/2026
Recently

AskChem: Claim-Centered Infrastructure for Chemistry Literature Synthesis

Chemistry literature synthesis often requires assembling specific findings scattered across many publications, yet existing literature-search systems primarily return ranked document lists. As a result, scientists and AI agents need to locate relevant information, verify their provenance, and assemble cross-paper answers manually. We present AskChem, a claim-centered infrastructure for cross-paper chemistry search. Authors: Bing Yan, Gregory Wolfe, Stefano Martiniani.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: Chemistry literature synthesis often requires assembling specific findings scattered across many publications, yet existing literature-search systems primarily return ranked document lists.

Primary paperarxivcs.CL
Original
Automation / Agentic Systems
arXiv7/30/2026
Recently

OSReward: Instituting Standardized Evaluation for Cross-Platform Computer-Use Reward Models

Computer-using agents (CUAs) are advancing rapidly across the digital world. A CUA trajectory records the agent's actions, states, and reasoning. Verifying whether it fulfilled the task instruction is central to CUA evaluation, data curation, and reinforcement learning. Authors: Qiushi Sun, Kanzhi Cheng, Yian Wang.

Why it matters

Read this for the paper's specific claim in Automation / Agentic Systems: Computer-using agents (CUAs) are advancing rapidly across the digital world.

Primary paperarxivcs.AI
Original

Archived section

Research Papers · 5

Research Papers
arXiv7/29/2026
Recently

TactiPlay: Multi-Granularity Tactical Parsing and Video-Anchored Match Review for Amateur Badminton Players

Amateur badminton players increasingly record matches, yet existing tools provide only aggregate statistics or generic summaries, leaving most unable to extract tactical insights without expert guidance. A formative study (N=8) reveals the need for multi-granularity, video-anchored tactical analysis centered on rallies. We derive a taxonomy of performance issues from national-level athletes' annotations and present TactiPlay, an interactive system that instantiates an expert-taxonomy-guided, rally-level, video-anchored review workflow. Authors: Qiaoyi Chen, Yuheng Liu, Xinzhuang Xiong.

Why it matters

Read this for the paper's specific claim in Research Papers: Amateur badminton players increasingly record matches, yet existing tools provide only aggregate statistics or generic summaries, leaving most unable to extract tactical insights without expert guidance.

Primary paperarxivcs.HC
Original
Research Papers
arXiv7/29/2026
Recently

GraphQAG: A Knowledge-Graph-Guided Visual Analytics Framework for Question-Answer Pairs Generation

Question-answer (QA) pairs are widely used in knowledge base construction, question-answering systems, and the post-training of large language models (LLMs). However, important knowledge in long documents is often distributed across multiple paragraphs and connected through complex entity relationships. Such fragmented and relational knowledge poses substantial challenges for existing QA generation methods, which often fail to adequately cover core document content, cross-paragraph semantic connections, and multi-entity relationships. Authors: Yize Li, Ruiqi Yu, Tianya Pan.

Why it matters

Read this for the paper's specific claim in Research Papers: Question-answer (QA) pairs are widely used in knowledge base construction, question-answering systems, and the post-training of large language models (LLMs).

Primary paperarxivcs.HC
Original
Research Papers
arXiv7/30/2026
Recently

Effects of Auditory Information for People With Visual Impairments in Highly Automated Vehicles

Automated vehicles promise to improve accessibility and access to personal mobility for everyone. However, their design and current research trends in visualizing relevant information do not reflect this commitment to accessibility for users with visual impairments. Therefore, we designed and implemented a visual and auditory communication concept for people with visual impairments seated inside fully automated vehicles. Authors: Mark Colley, Tobias Aescht, Omid Rajabi.

Why it matters

Read this for the paper's specific claim in Research Papers: Automated vehicles promise to improve accessibility and access to personal mobility for everyone.

Primary paperarxivcs.HC
Original
Research Papers
arXiv7/30/2026
Recently

Formalization of security

Proof assistants are often used to validate that designs and implementations meet their expected security properties. A further motivation for using proof assistants is to support certification. This chapter focuses on their applications to system security, language-based security, secure compilation, and cryptography. Authors: Gilles Barthe.

Why it matters

Read this for the paper's specific claim in Research Papers: Proof assistants are often used to validate that designs and implementations meet their expected security properties.

Primary paperarxivcs.CR
Original
Research Papers
arXiv7/30/2026
Recently

Implementing Homomorphic Encryption-Based Logic Locking in System-on-Chip Designs

This study presents a logic locking scheme based on the binary Ring Learning With Errors algorithm, implemented in a RISC-V System-on-Chip design. Unlike traditional logic locking methods that require providing users with raw locking parameters, the proposed approach secures critical logic paths in the privilege switching process without exposing these sensitive parameters. 9% in Registers compared to the baseline system. Authors: Ye Ziyang, Makoto Ikeda.

Why it matters

Read this for the paper's specific claim in Research Papers: This study presents a logic locking scheme based on the binary Ring Learning With Errors algorithm, implemented in a RISC-V System-on-Chip design.

Primary paperarxivcs.CR
Original

Archived section

Embedded Systems · 5

Embedded Systems
arXiv7/30/2026
Recently

A subspace approach to data-driven predictive control for linear parameter-varying systems

This paper presents a subspace data-driven predictive control method for linear parameter-varying (LPV) systems. Starting from an affine LPV state-space model in innovation form, we derive a multi-step predictor that separates the effects of past data, future inputs, scheduling trajectories, and innovations. By projecting this representation onto the row span of lifted input-output-scheduling data, we obtain an asymptotically unbiased data-driven predictor that can be embedded directly in a receding-horizon control problem, without explicitly identifying an LPV model. Authors: Federico Porcari, Chris Verhoek, Valentina Breschi.

Why it matters

Read this for the paper's specific claim in Embedded Systems: presents a subspace data-driven predictive control method for linear parameter-varying (LPV) systems.

Primary paperarxiveess.SY
Original
Embedded Systems
arXiv7/30/2026
Recently

On the Implementation of Two-Parameter Stabilizing Controllers Using Stable-Block Input-Output Feedback Structures

This paper a universal implementation method for continuous- and discrete-time two-parameter (2-DOF) stabilizing controllers using exclusively stable constituent blocks. The framework is valid for all regular SISO and MIMO plants, particularly those failing to satisfy the parity interlacing property where unstable controllers are unavoidable. Unlike existing algebraic approaches that compromise parametric design freedom to force sub-block stability, the proposed method preserves design precedence. Authors: Fernando di Sciascio.

Why it matters

Read this for the paper's specific claim in Embedded Systems: a universal implementation method for continuous- and discrete-time two-parameter (2-DOF) stabilizing controllers using exclusively stable constituent blocks.

Primary paperarxiveess.SY
Original
Embedded Systems
arXiv7/30/2026
Recently

X-NavDP: Generalizing Navigation Diffusion Policy to Novel Behavior and Embodiments with Group Q-score Reweighted Matching

Pretraining navigation diffusion policies rely on large-scale expert demonstrations. These data are typically generated by a fully-informed oracle planner suited to a single nominal robot., escaping dead ends or detouring long obstacles) that demand diverse local reactive behaviors with only onboard local observations. Authors: Tianyu Yang, Yiming Zeng, Wenzhe Cai.

Why it matters

Read this for the paper's specific claim in Embedded Systems: Pretraining navigation diffusion policies rely on large-scale expert demonstrations.

Primary paperarxivcs.RO
Original
Embedded Systems
Hackster.io7/30/2026
Recently

A Full-Stack Platform for Wearable Development

In the world of wearable technology, getting from an idea to a working prototype usually means designing custom hardware, writing firmware, building a companion app, and creating software to collect and analyze sensor data. SensWear was designed to remove much of that overhead by providing an open source platform that covers the entire wearable development stack, giving researchers and developers a flexible foundation for everything from smart rings to health-monitoring patches. Designed around Nordic Semiconductor's nRF54L15 wireless SoC, SensWear is a modular wearable development platform that combines flexible hardware, embedded software, mobile applications, and developer tools into a single ecosystem.

Why it matters

Read this for the engineering context in Embedded Systems: In the world of wearable technology, getting from an idea to a working prototype usually means designing custom hardware, writing firmware, building a companion app, and creating software to collect and analyze sensor data.

Trusted source
Original
Embedded Systems
Hackster.io7/29/2026
Recently

Brain-Inspired Chip Cures AI's Memory Problem

" Train an AI model to perform a new task, and it often loses part or all of what it previously learned. That limitation makes it difficult to build edge AI systems that can adapt throughout their lifetime without repeatedly retraining in the cloud. Researchers at The University of Texas at San Antonio believe they have taken a significant step toward solving that problem with a new neuromorphic chip called Genesis.

Why it matters

Read this for the engineering context in Embedded Systems: " Train an AI model to perform a new task, and it often loses part or all of what it previously learned.

Trusted source
Original

Archived section

Computer Systems · 5

Computer Systems
arXiv7/30/2026
Recently

Quantum Fidelity-per-Cost: A Metric for Evaluation of Quantum Computing Systems

Cloud-accessible quantum computing has made hardware comparison not only a physics benchmark but also a practical purchasing decision. Cost-aware comparison of quantum computers remains underexplored and is difficult to do under the heterogeneous billing models offered by various cloud-based quantum computing providers. This paper makes two main contributions to enable price-aware comparison of quantum computers. Authors: Siddarth Shinde, Jakub Szefer.

Why it matters

Read this for the paper's specific claim in Computer Systems: Cloud-accessible quantum computing has made hardware comparison not only a physics benchmark but also a practical purchasing decision.

Primary paperarxivquant-ph
Original
Computer Systems
Kubernetes Blog7/29/2026
Recently

How the controller-runtime Cache Actually Works, and Why Your Controller Does Not Crash the API Server

Caution: Some of the technical detail in this article is not accurate. We are reviewing it and preparing corrections. Until then, check what you read here against the controller-runtime documentation.

Why it matters

Read this for the official technical update in Computer Systems: Caution: Some of the technical detail in this article is not accurate.

Official source
Original
Computer Systems
CNCF Blog7/31/2026
Recently

Scaling Kubernetes pods with KEDA based on Amazon SQS queue depth

In event-driven Kubernetes architectures, CPU and memory utilization often fail to reflect real system pressure. A worker pod may sit idle from a CPU perspective while thousands of messages pile up in an Amazon SQS queue...

Why it matters

Read this for the official technical update in Computer Systems: In event-driven Kubernetes architectures, CPU and memory utilization often fail to reflect real system pressure.

Official sourceBlog
Original
Computer Systems
arXiv7/29/2026
Recently

A Photonic-CXL Memory Appliance for Scalable KV Cache Management in LLM Inference

LLM inference at scale faces a memory wall. The KV cache demands tens of terabytes at hundreds of gigabytes per second, yet no current memory tier delivers both at once. Characterization across multi-generation GPU systems with various LLaMA models shows host memory retrieval achieves up to 100x speedup over re-computation but supports only tens of concurrent long-context users. Authors: Jing Ding, Yash Nishant, Chandrish Ambati.

Why it matters

Read this for the paper's specific claim in Computer Systems: The KV cache demands tens of terabytes at hundreds of gigabytes per second, yet no current memory tier delivers both at once.

Primary paperarxivcs.PF
Original
Computer Systems
arXiv7/29/2026
Recently

InferScale: GPU-Native KV Injection for Personalized LLM Serving

Large language models are increasingly deployed with persistent personalized context, such as accumulated memory profiles or long conversation histories, that is shared across a user's many requests., Mem0, MemGPT, and Zep) retrieve a relevant subset of this memory and inject it into the prompt, forcing the serving engine to repeatedly prefill the same content. As the retrieval budget grows, time-to-first-token (TTFT) increases even though the underlying memory is reused across requests. Authors: Peter Li, Prashant Pandey.

Why it matters

Read this for the paper's specific claim in Computer Systems: , Mem0, MemGPT, and Zep) retrieve a relevant subset of this memory and inject it into the prompt, forcing the serving engine to repeatedly prefill the same content.

Primary paperarxivcs.DC
Original

Archived section

Developer Tools / Open Source · 5

Developer Tools / Open Source
Docker Blog7/30/2026
Recently

The Future of Agentic AI Depends on Openness and Trust. That's Why Docker Is Joining Nvidia's Open Secure AI Alliance.

Docker joins NVIDIA's Open Secure AI Alliance to help build the security, governance, and trust frameworks that agentic AI systems demand.

Why it matters

Read this for the official technical update in Developer Tools / Open Source: Docker joins NVIDIA's Open Secure AI Alliance to help build the security, governance, and trust frameworks that agentic AI systems demand.

Official sourceCommunityCompany
Original
Developer Tools / Open Source
Vercel Blog7/28/2026
Recently

Additional custom environments can now be purchased

Pro and Enterprise teams can now purchase additional custom environment capacity without contacting sales. Custom environments let you model your team's release process on Vercel. stagingqapreviewproduction You can purchase or adjust capacity from the dashboard, API, or CLI.

Why it matters

Read this for the official technical update in Developer Tools / Open Source: Pro and Enterprise teams can now purchase additional custom environment capacity without contacting sales.

Official source
Original
Developer Tools / Open Source
Vercel Blog7/30/2026
Recently

Shopify and Vercel are rebuilding Hydrogen for faster storefronts

Shopify and Vercel Open source and runtime agnostic, runs anywhere JavaScript does Standard Actions brings agentic commerce to every storefront Feature development cut from months to a week for retailers like Global Retail Brands powers commerce for millions of merchants worldwide, and Hydrogen is its framework for building headless storefronts. The Shopify team is partnering with Vercel to rebuild Hydrogen from the ground up. js, Nuxt, Svelte, or any framework they choose.

Why it matters

Read this for the official technical update in Developer Tools / Open Source: Shopify and Vercel Open source and runtime agnostic, runs anywhere JavaScript does Standard Actions brings agentic commerce to every storefront Feature development cut from months to a week for retailers like Global Retail Brands powers commerce for millions of merchants worldwide, and Hydrogen is its framework for building headless storefronts.

Official source
Original
Developer Tools / Open Source
Hackster.io7/29/2026
Recently

InMachines Launches Their Open Source Piccola Desktop CNC Mill

I buy, repair, and sell industrial equipment, including CNC mills, and if there is one thing I've learned, it is that proprietary systems often become paperweights once they reach EoL (end-of-life). Manufacturers of old machines — if they're even still in business — have little interest in continuing support in the long term and so machines that cost tens (or hundreds) of thousands of dollars when new become literal scrap. The new Piccola desktop CNC mill, from InMachines, is different because it is open source.

Why it matters

Read this for the engineering context in Developer Tools / Open Source: I buy, repair, and sell industrial equipment, including CNC mills, and if there is one thing I've learned, it is that proprietary systems often become paperweights once they reach EoL (end-of-life).

Trusted source
Original
Developer Tools / Open Source
GitHub Blog7/30/2026
Recently

Stacked sessions and pull requests in the GitHub Copilot app

Learn how I modernized an old codebase of mine using stacked sessions and pull requests in the GitHub Copilot app. The post Stacked sessions and pull requests in the GitHub Copilot app appeared first on The GitHub Blog.

Why it matters

Read this for the official technical update in Developer Tools / Open Source: Learn how I modernized an old codebase of mine using stacked sessions and pull requests in the GitHub Copilot app.

Official sourceAI & MLCollaboration
Original

Archived section

Cloud / Infrastructure · 5

Cloud / Infrastructure
Cloudflare Blog7/30/2026
Recently

Dogfooding at scale: migrating cdnjs to Cloudflare's Developer Platform

We moved cdnjs, serving 9 billion requests a day, entirely onto Cloudflare's Developer Platform. That means we're running one of the Internet's busiest open-source CDNs on our own building blocks, and we pushed Workflows and Workers limits higher for everyone.

Why it matters

Read this for the official technical update in Cloud / Infrastructure: We moved cdnjs, serving 9 billion requests a day, entirely onto Cloudflare's Developer Platform.

Official sourceCacheCDNJS
Original
Cloud / Infrastructure
CNCF Blog7/28/2026
Recently

Subaru Wins CNCF End User Case Study Contest for Accelerating AI Development with Cloud Native Infrastructure

New architecture reduced AI container image pull times by 60x while automating workflows for next-generation driver assistance systems Key Highlights YOKOHAMA – KUBECON + CLOUDNATIVECON JAPAN — July 29, 2026 — The Cloud Native Computing Foundation®...

Why it matters

Read this for the official technical update in Cloud / Infrastructure: New architecture reduced AI container image pull times by 60x while automating workflows for next-generation driver assistance systems Key Highlights YOKOHAMA – KUBECON + CLOUDNATIVECON JAPAN — July 29, 2026 — The Cloud Native Computing Foundation®...

Official sourceAnnouncements
Original
Cloud / Infrastructure
CNCF Blog7/29/2026
Recently

Your Kubernetes health checks are accidentally waking your services. Here's the fix.

Scale-to-zero breaks when health checks scale you back up. Learn how KubeElasti's ProbeResponse lets Kubernetes services stay genuinely idle — while keeping load balancers and uptime monitors happy. Scale-to-zero sounds perfect on paper.

Why it matters

Read this for the official technical update in Cloud / Infrastructure: Scale-to-zero breaks when health checks scale you back up.

Official sourceBlog
Original
Cloud / Infrastructure
Cloudflare Blog7/29/2026
Recently

Post-quantum authentication to origins is now supported

Cloudflare now supports post-quantum (PQ) authentication when connecting to customer origin servers via Authenticated Origin Pulls and Custom Origin Trust Store. This is the first step towards providing PQ authentication for all Cloudflare products.

Why it matters

Read this for the official technical update in Cloud / Infrastructure: Cloudflare now supports post-quantum (PQ) authentication when connecting to customer origin servers via Authenticated Origin Pulls and Custom Origin Trust Store.

Official sourceCryptographyPost-Quantum
Original
Cloud / Infrastructure
Cloudflare Blog7/28/2026
Recently

Natural disasters and government interference: examining Q2 2026's major Internet disruption events

Cloudflare Radar tracked Internet disruptions driven by natural disasters, government-mandated shutdowns, and DNSSEC key rollovers over the last quarter. This post analyzes traffic telemetry to explain how these events impacted global connectivity.

Why it matters

Read this for the official technical update in Cloud / Infrastructure: Cloudflare Radar tracked Internet disruptions driven by natural disasters, government-mandated shutdowns, and DNSSEC key rollovers over the last quarter.

Official sourceAWSInternet Shutdown
Original