Passkey vs. password: What's the difference and which is better?
Passwords are less secure than passkeys, even if you use a password manager. Here's why and how to get started with passkeys.
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Passwords are less secure than passkeys, even if you use a password manager. Here's why and how to get started with passkeys.
Starlink is an attractive option for those who live in remote areas or travel frequently, but the Mini isn't ideal for residential use.
A bug in macOS screen sharing lets attackers view your screen, open files and do just about anything else they want.
The program makes upgrading your hardware incredibly convenient, but weigh your options.
If you want the best quality out of your Bluetooth audio, it's worth reviewing some settings.
While there have been many twists and turns in the company's evolution, it remains one of the biggest names in the telecommunications industry.
If your internet has been slower than usual lately, your router might need a reset. Here are some things you can try.
Cloud computing is a fundamental pillar of modern network architecture, shifting infrastructure management from physical data centers to flexible, virtualized environments. This guide breaks down core cloud concepts, architecture models, service types, and operational characteristics aligned with CompTIA Network+ objectives. Virtualization and Network FoundationsNetwork Functions Virtualization (NFV)NFV replaces dedicated, proprietary hardware appliances (such as firewalls, load balancers, and routers) with virtual appliances running on standard servers. This decouples network functions from physical hardware, allowing for rapid deployment, easier scaling, and reduced capital expenditure.Virtual Private Cloud (VPC)A Virtual Private Cloud (VPC) provides an isolated, private cloud environment dedicated to a single customer within a shared public cloud infrastructure.Resource Separation: Uses subnets, VLANs, and tunneling to isolate compute, storage, and networking resources.Control: Customers have full administrative control over their network configuration, IP address ranges, and routing tables.Security: Regulated via Network Security Groups (NSGs) and Access Control Lists (ACLs) to govern traffic entering and leaving subnets.Cloud Gateways & Connection MethodsCloud gateways serve as translation points or secure entryways between on-premises networks and cloud environments. Organizations connect to cloud resources using several methods:Site-to-Site VPNs: Encrypted tunnels over the public internet connecting an on-premises office or data center to a VPC.Dedicated Interconnects (e.g., AWS Direct Connect, Azure ExpressRoute): High-speed, private, dedicated circuits that bypass the public internet for enhanced security, lower latency, and predictable performance. Cloud Deployment ModelsCloud architecture defines where infrastructure is hosted and who manages the underlying hardware.ModelCharacteristicsBest Suited ForPublic CloudOwned and operated by a third-party provide
Cloudflare recently introduced Cache Response Rules, a rules engine that operates after an origin server responds but before content is written to Cloudflare's cache. Previously, Cache Rules operated only on request attributes. Cache Response Rules add a response phase that evaluates origin responses before they are cached. By Renato Losio
Google has launched Gemini 3.7 Flash, providing significant updates for coding, automation, and the development of autonomous agents. The company reduced production pricing to help businesses deploy these tools more affordably. This release comes only three weeks after the previous version, signaling a faster pace for developer-focused updates. Accelerated development cycles and cost reduction strategies The introduction of Gemini 3.7 Flash highlights a shift in how technology providers manage their product lineups. Google is prioritizing rapid iteration for its Flash series, which serves as a high-speed tool for developers. This latest version arrived less than a month after its predecessor, showing the company responds quickly to user feedback. Engineers designed this model to handle software engineering tasks and complex, multi-step workflows with higher precision. Pricing for the new model sits at $0.75 per million input tokens and $3.75 per million output tokens. This represents a reduction of approximately fifty percent compared to the prior version. By lowering the financial barrier, Google aims to make large-scale production deployments more sustainable for businesses. The company describes this version as a reliable workhorse capable of following instructions with greater accuracy than previous iterations. While the Flash series moves quickly, the more advanced Pro models follow a different path. These high-end models, designed for the most difficult reasoning tasks, see less frequent updates. During recent financial discussions, leadership at the company did not provide a specific timeline for the next Pro release. This indicates a growing gap between fast, cost-effective models and the slower development of premium intelligence tiers. Industry trends in model tiering Other companies in the industry are following similar patterns by separating their offerings into distinct categories. For example, some competitors have launched high-end variants alongside
Quantum computing has alternated between breakthrough darling and overhyped promise in technology circles. Its powerful new capabilities come with a threat to break current cryptography, but for business leaders navigating the noise, the signal should be clear: post-quantum cryptography (PQC) is a manageable evolution, not a crisis. The mathematics behind today’s encrypted digital transactions may…
Get familiar with easy methods to elevate your photos and make them look crisp, clean, and visually appealing without diving into complicated software.
A Cambridge Student Writes an Operating System In the late 1970s, a Cambridge computer science student named Tim King needed an operating system for the Cambridge LISP machine. What he built instead was Tripos — a preemptive multitasking operating system written in BCPL that would, improbably, end up powering one of the most beloved home computers of the 1980s. King earned his Ph.D. at Cambridge in 1979. Tripos wasn't a university project exactly — it was born of necessity, the kind of system building that Cambridge encouraged. It was compact, fast, and remarkably capable for something written by a single person. It had a kernel, file system, windowing system, and a command-line interpreter, all in BCPL. What made Tripos special wasn't just that it worked — it was that it worked well . Preemptive multitasking in the 1970s was serious engineering. Most personal computers of the era couldn't do it at all. The Amiga wouldn't ship for another six years, and when it did, Tripos would be at its core. From Cambridge to MetaComco In 1984, King joined MetaComCo, a software company based in Bristol. He brought Tripos with him. The timing was perfect — Commodore was developing the Amiga, and they needed an operating system. The hardware was revolutionary: custom chips for graphics and sound, a Motorola 68000 CPU, and multitasking capabilities that put other home computers to shame. But the software wasn't ready. Tripos became the foundation of AmigaDOS. It wasn't a port in the traditional sense — the BCPL-based Tripos was adapted and integrated into the Amiga's environment, creating a hybrid system that combined the Amiga's custom hardware capabilities with Tripos's mature OS architecture. The result was a computer that could multitask in 1985, years before Windows or Mac OS could do the same. The Amiga shipped in 1985. AmigaDOS gave it a command-line interface, file system, and process management that were years ahead of anything else in the consumer market. The Amiga became
I spend most of my time building evidence layers for AI agents. The reflex in that work is to reach for a signature. Something happened, sign the record, hand it to the auditor, done. Three things from the last five months say that reflex is wrong, or at least badly incomplete. One is a governance draft that never asks for a signature at all. One is a CVE where the signature verified correctly and the client still ended up talking to an attacker. One is a limit in a spec I wrote myself. Read together they point at the same thing. A signature is a statement about an object. Almost every security question you actually care about is a statement about a relationship. Case one: the requirement that is not there The Open Secure AI Alliance published its Shared AI Findings Exchange draft on GitHub on August 3. It is an incident-reporting compact for AI agents. Members agree to report when an agent they operate accesses or disrupts a third-party system without authorization, and to do it on a clock: notify the affected organisation as soon as possible, notify customers with credible exposure within 72 hours, file a confidential report within four business days. The clock is well specified. So is the evidence. Members must preserve and provide affected organisations with "prompts, traces, tool calls, logs, configurations, model and safeguard versions and third-party dependencies", plus agent and workload identities, permissions and credentials available during the run, human approval events, and a complete incident timeline. That is a good list. It is close to the one I would have written. Now search the draft for signing. It appears exactly once, in a list of example recommendations that incident reviews might produce: "signed evaluation manifests". The draft also asks, in its review framework, whether "data boundaries [were] independently verified". Both of those are about keeping an agent inside its box. Neither applies to the record of what happened when it got out. The
InfoQ editorial staff and friends of InfoQ are discussing the current trends in the domain of Cloud and DevOps as part of the process of creating our annual 2026 trends report. By Steef-Jan Wiggers, Matt Saunders, Shweta Vohra, Daniel Bryant, Mark Silvester
Wireless connectivity comes in many different flavors, here's how they differ.
This is good : Post-quantum cryptography is now one pip-install away for the entire Python ecosystem. With funding from the Sovereign Tech Agency , we implemented support for ML-KEM, the NIST-standard key-establishment primitive, and ML-DSA, the NIST-standard digital-signature primitive, in pyca/cryptography. Remember, the reason to do this now is because there’s no emergency. And because you will make your systems crypto agile, which is always a good idea.
Cloud Native Buildpacks, which graduated within the CNCF in July 2026, move base image choice out of per-service Dockerfiles into a single builder owned by platform engineering, enabling fleet-wide patching. BellSoft's hardened Paketo builder is the latest sign that vendors now treat the builder, not the Dockerfile, as the container security control point. By Mark Silvester
Framework's customer database was accessed, but no payment info was released.
Introduction: Cloud computing has transformed the way individuals, businesses, educational institutions, and governments store, manage, and access data and applications. Rather than relying solely on physical servers and local infrastructure, cloud computing allows users to access computing resources over the internet on demand. Popular cloud service providers such as Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform offer scalable, secure, and cost-effective solutions that support everything from email services to artificial intelligence and big data analytics. Although cloud computing offers numerous benefits, it also presents certain challenges that organizations should consider before adopting cloud-based solutions. Understanding both the advantages and disadvantages helps businesses make informed decisions that align with their operational and strategic goals. What is Cloud Computing? Cloud computing is the delivery of computing services—including servers, storage, databases, networking, software, analytics, and artificial intelligence—over the internet ("the cloud"). Instead of purchasing and maintaining expensive hardware, users pay only for the resources they consume, making cloud computing flexible and cost-efficient. Advantages of Cloud Computing: Cost Savings One of the greatest advantages of cloud computing is its ability to reduce IT costs. Organizations no longer need to invest heavily in purchasing servers, networking equipment, and data centers. Cloud providers also handle hardware maintenance and software updates, reducing operational expenses. Scalability and Flexibility Cloud computing enables organizations to scale resources up or down depending on demand. Businesses experiencing seasonal spikes can quickly allocate additional computing resources without purchasing new hardware. High Availability and Reliability Leading cloud providers maintain multiple geographically distributed data centers. This redundancy ensures high avai