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One of the most useful questions in network troubleshooting is also one of the simplest: Does it fail from another machine too? If a website will not load on my laptop, trying it from another computer can immediately change the investigation. If it works there, the service probably is not down. Something about my machine, DNS configuration, VPN, firewall, route, or network path is different. If it fails there too, the problem may be farther upstream. I wanted Network Doctor to be able to ask that question directly. So I added remote diagnosis over SSH. netdoc --via ideapad github.com Instead of running the diagnosis locally, Network Doctor connects to ideapad , runs the checks there, and reports the result back on my machine. Why another vantage point matters A network failure is always observed from somewhere. Suppose github.com is unreachable from my workstation. I can test DNS: dig github.com Then TCP: nc -vz github.com 443 Then TLS: openssl s_client -connect github.com:443 Maybe I inspect my routes, VPN, proxy settings, or firewall. Those tests are useful, but they all share one property: they are observing the network from the same machine. Trying the same destination from another machine gives me a new piece of evidence. Imagine this: Thelio: DNS PASS TCP 443 FAIL Ideapad: DNS PASS TCP 443 PASS TLS PASS HTTPS PASS That difference is interesting. GitHub clearly is not universally unreachable. The second machine just reached it. Now I have a much smaller problem to investigate: what is different about the path from Thelio? That is often more useful than running another five commands on Thelio. Turning that into a command Network Doctor already runs network checks as a dependency graph. For an HTTPS target, for example, it can test things such as the local interface, DNS resolution, TCP connectivity, TLS, HTTP, routing, and path MTU. Normally: netdoc github.com means: Diagnose github.com from this machine. With --via : netdoc --via ideapad github.com it becomes:

It's conference season! I already had to sit at home jealous while friends had fun at Render ATL, but it's my turn soon with Commit Your Code next week in Plano, TX. It boasts a banger lineup of speakers, which got me thinking: how do you get the absolute most out of an event like this? The number one rule is determining your goal before you step through the doors. Are you going to hang out with friends, meet new people, or hunt for a job? Each objective requires a completely different approach, prep strategy, and attire. 1. Hanging Out with Friends This is the easiest path. Wear whatever keeps you comfortable while looking relatively professional. Meet up with your crew, enjoy the sessions, and have fun. You done did it. 2. Networking and Meeting New People This is my primary goal for CYC this year. I'll fill you in on my plan. To keep from getting overwhelmed, I built a tracking spreadsheet for everyone I want to connect with. It might sound clinical, but it ensures no follow-up slips through the cracks. Here is my process: Pre-Conference Research: First, I reviewed the talk schedule and logged the speakers and session titles that caught my eye. Initial Outreach: I added columns for sending an intro message and a LinkedIn connection request. Then I sat down and message every single one of them. I had a bit of a template, but mostly just told people why their talk sounded interesting or exciting to me. It's hard to have writers block when you have a genuine interest in something. Some of them replied, some didn't, but I already feel like I have a foot in the door heading into the conference. During & After the Event: My spreadsheet includes columns for attending their talk, taking photos (speakers always need good photos of themselves on stage), posting on social media, and sending a post-event follow-up. Sounds like a lot? Because it is! Which is why its in a spreadsheet and not my pasta strainer brain. But it's about intent, respect, and appreciating someone else

Meta has detailed MTIA 300, its first in-house accelerator optimized for training ranking and recommendation models. By Matt Foster

If you've provisioned a VPC from a Terraform module without fully internalising what each piece is doing, that's fine — right up until something breaks. An instance that should be reachable isn't. A private instance can't pull a package update. And you're left checking five different resources with no clear mental model of how they connect. This post builds that mental model from the ground up. Not just definitions — the why behind each piece, so troubleshooting becomes deduction instead of guesswork. CIDR math you actually need A CIDR block is IP address / prefix length . The prefix length fixes the network portion; the remaining bits are your host space. Formula: 2^(32 - prefix) = total addresses . AWS reserves 5 per subnet (network address, VPC router, DNS, reserved, broadcast). CIDR Total addresses Usable /16 65,536 65,531 /20 4,096 4,091 /24 256 251 /28 16 11 To reverse-engineer a prefix from a required host count: round up to the next power of two, subtract the exponent from 32. Need 300 hosts? Next power of two is 512 (2⁹), so prefix = 32 - 9 = /23 . Run this before sizing any subnet that will host an autoscaling group or EKS node group. Start with /16 for the VPC itself. VPC CIDR is difficult to resize after the fact — once you have subnets, peering connections, or Transit Gateway attachments built against it, renumbering becomes a migration project. /16 costs nothing up front and avoids that corner. Subnet allocation: carving up the VPC A practical three-AZ production layout from 10.0.0.0/16 : Tier AZ-a AZ-b AZ-c Size Typical use Public 10.0.0.0/24 10.0.1.0/24 10.0.2.0/24 /24 ALB, NAT gateway, bastion Private/app 10.0.16.0/20 10.0.32.0/20 10.0.48.0/20 /20 EKS nodes, ECS, EC2 Data 10.0.64.0/24 10.0.65.0/24 10.0.66.0/24 /24 RDS, ElastiCache Reserved 10.0.128.0/17 /17 Future tiers, Transit Gateway, VPN The jump from /24 in the public tier to /20 in the app tier is intentional. ALBs and NAT gateways consume very few IPs; the app tier is where consumption scales

After a 10-week hiatus since the last batch of Spring ecosystem releases, there was a flurry of activity during the week of August 17th, 2026, highlighting first milestone releases of: Spring Boot, Spring Framework, Spring Data, Spring Security, Spring Integration, Spring HATEOAS, Spring Modulith, Spring Batch, Spring AMQP and Spring for Apache Kafka. By Michael Redlich

Coates said in a LinkedIn post that the company is not trying to recreate Twitter.

Your datacenter needs to talk to Azure. You can send that traffic through an encrypted tunnel over the public internet, or over a private circuit that never touches it. That single choice — shared road or private rail — decides cost, speed, and reliability. Almost every organization moving to Azure keeps something on-premises, and those two worlds have to connect privately. Azure gives you two hybrid-connectivity options, and they take opposite routes to the same destination: VPN Gateway and ExpressRoute . Understanding them is really understanding one question — does your traffic ride the public internet, protected by encryption, or a dedicated line that bypasses it entirely? VPN Gateway: an encrypted tunnel over the internet Microsoft's description is exact: Azure VPN Gateway "can be used to send encrypted traffic between an Azure virtual network and on-premises locations over the public Internet." Your traffic still travels the ordinary internet, but inside an IPsec/IKE tunnel, so it is private even though the road is shared. It comes in a few shapes: site-to-site (your datacenter's VPN device to Azure), point-to-site (an individual remote worker to the VNet), and VNet-to-VNet . It is quick to stand up, needs no third party, and is inexpensive — the pragmatic default for dev/test and small-to-medium production links. ExpressRoute: a private, dedicated circuit ExpressRoute takes the other road entirely. It "lets you extend your on-premises networks into the Microsoft cloud over a private connection with the help of a connectivity provider." The defining fact: because ExpressRoute connections do not go over the public internet , they offer "more reliability, faster speeds, consistent latencies, and higher security than typical connections over the internet." You are not tunnelling through shared roads; you have a private rail line into Microsoft's network, arranged through a connectivity provider. That extra reliability and consistency costs more and takes longer t

The most common documentation failure is not a weak prompt or a lazy writer; it is the absence of a clear boundary between machine-draftable content and human-owned claims. A pipeline that drafts reference sections with free-tier model access and then verifies them with a symbol drift check turns docs into a testable artifact instead of a trust exercise. The model writes the inventory, and the human owns the promises. Why documentation rots inside a healthy CI pipeline Documentation bugs share a distinctive property: they are usually discovered by the people who consume the API, not by the pipeline that builds it. A function renamed in the last refactor stays documented under its old name until a user files an issue, and a newly added flag never appears in the docs at all. The root cause is structural, because nothing in the merge pipeline compares the documented surface against the actual code surface. A prompt cannot know what changed inside a pull request, so the fix has to live in the pipeline around the model. The workflow drafts reference material, validates that every documented symbol still exists, and routes the remaining claims to a human reviewer. That division of labor is the entire design, and each step has a concrete tool. The ownership boundary: what a model may draft The first step is to separate documentation into two classes by asking a single question: can this statement be verified against the codebase alone? If the answer is yes, a model may draft it, and if the answer is no, a human must own it. The table below applies that test to the statement types that appear in most API docs. The model may draft A human must own Function and class inventories Behavioral guarantees CLI flags and their defaults Security and authentication properties Config keys and their types Compatibility and support promises Error codes and exit statuses Deprecation timelines Compilable usage examples Performance or cost claims Parameter descriptions from signatures Ratio

Bluesky's new 10-minute video support includes faster upload speeds, too.

I maintain gumdrop , an async, non-blocking Java server framework. Last year I wanted to add HTTP/3 support, and ran into a wall: the Java ecosystem essentially doesn't have QUIC. The JDK's own experimental support (JEP 517) is client-only. Netty gets HTTP/3 by shelling out to quiche + BoringSSL over JNI — which works, but you're back to native builds, platform-specific binaries, and a C library sitting underneath your "pure Java" framework. I used that approach first. It was clumsy enough that I went looking for a pure-Java alternative. There's exactly one: Kwik. But Kwik is blocking per connection — one thread per QUIC connection. That's a non-starter for a framework built around single-threaded selector loops handling tens of thousands of concurrent connections. So I wrote a QUIC implementation from scratch: packet protection, loss detection and NewReno congestion control, connection migration, 0-RTT, QPACK, an HTTP/3 client and server — all driven by the same non-blocking event loop as everything else in gumdrop. Collaboration note: TLS 1.3 comes from Agent15 — also from Kwik's author, Peter Doornbosch, but just the handshake layer, not the connection model. We're currently working together on making PQC — hybrid key exchange and signatures — the default there. Why the thread model matters The reason this mattered beyond HTTP/3: gumdrop isn't a web framework with QUIC bolted on, it's a general async I/O framework, and QUIC is just a transport. One thread per connection is exactly the model gumdrop exists to avoid — it caps concurrency at your thread pool, not your file descriptors, and it's the reason a "just use Kwik" fix was never really on the table. The same QUIC stack backs DNS-over-QUIC (DoQ) as a first-class DNS transport alongside DoT, DoH, UDP, and TCP — and the DNS resolver itself is fully async, with no blocking InetAddress.getByName() anywhere in the I/O path, which is its own small miracle in Java. HTTP, SMTP, IMAP, POP3, FTP, MQTT, SOCKS — it's the

Seri: Proxmox VE Cluster ve Corosync | Hafta 5 Serinin adı "Cluster ve Corosync"; ama dört modüldür ağırlık HA Manager, resource affinity ve CRS'teydi, Corosync'in kendisine (redundant link'ler, izleme araçları) hiç dönmemiştim. Bu modülde iki konuyu birleştirip derinlemesine işledim: birden fazla corosync link'i tanımlayıp gerçekten birini kesip diğerinin devralmasını kanıtlamak, ve günlük operasyonda kullanılacak izleme araçlarını tek tek denemek. İkisi de planladığımdan çok daha fazla soru açtı; biri yanlış bir config anahtarı yüzünden saatler süren bir araştırmaya dönüştü, diğeri ise hiç beklemediğim bir kilitlenme keşfiyle bitti. Bölüm 1: Redundant Corosync Links Kurulum: İkinci Link'i Eklemek Şu ana kadar cluster'ımızda tek bir corosync link'i vardı ( link1 , izole corosync-net ağı). Management ağını ( 192.168.122.x ) link0 olarak ekleyip gerçek bir yedeklilik kurdum; /etc/pve/corosync.conf 'u kopyalayıp düzenleyip atomik olarak yerine taşıdım: cp /etc/pve/corosync.conf /etc/pve/corosync.conf.new # nodelist'teki her node'a ring0_addr ekledim, totem'e ikinci bir interface bloğu ekledim mv /etc/pve/corosync.conf.new /etc/pve/corosync.conf Doğrulama: corosync-cfgtool -s LINK ID 0 udp addr = 192.168.122.11 status: ... connected ... connected LINK ID 1 udp addr = 10.10.10.11 status: ... connected ... connected Teknik olarak başarılı; iki link de bağlı. Ama log'a dikkatlice bakınca, mimarimizin niyetini tersine çeviren bir şey oldu: [KNET ] rx: host: 3 link: 0 is up [KNET ] host: host: 3 (passive) best link: 0 (pri: 1) link_mode: passive modunda, öncelik eşitken düşük numaralı link kazanıyor . link0 'ı sonradan eklediğim için, o Corosync'in asıl trafiğini üstlenmiş; Modül 0'da özellikle izole ettiğimiz corosync-net ( link1 ) sessizce yedek konuma düşmüştü. Yanlış Anahtar, Saatler Süren Bir Araştırma Bunu düzeltmek için link1 'e daha yüksek öncelik vermeye çalıştım: interface { linknumber : 0 priority : 5 } interface { linknumber : 1 priority : 10 } İşe yaramadı. cor

The social app founded by Bonobos co-founder Andy Dunn is expanding beyond events with new digital homes for groups to connect, organize, and make plans.

The blunt tool is still in a lot of GRUB files: GRUB_CMDLINE_LINUX_DEFAULT = "isolcpus=0,1" Then update-grub (or grub2-mkconfig ) and reboot. Userspace tasks stop landing on CPU0/1. That is all most people verify — they fire a few busy loops and top looks empty on those cores. IRQs do not care. isolcpus is a scheduler isolation hint. Hardware interrupts can still fire on the "isolated" CPUs. I watched seven tight loops leave 0/1 idle for processes while /proc/interrupts still ticked on those cores. If you wanted a CPU for DPDK, a user-space NIC, or a cycle-accurate loop, scheduler isolation is necessary and not sufficient . Lab notes (English original is short; this write-up is the missing IRQ half): https://sunshout.tistory.com/1620 How to see what you actually isolated After reboot: cat /proc/cmdline # isolcpus=0,1 must be there grep PREEMPT /boot/config- $( uname -r ) || true taskset -cp 1 # pick a known userspace pid; it should not be 0,1 watch -n1 'grep "^ *[0-9]" /proc/interrupts | head' If IRQs still increment on CPU0/1, isolation is incomplete. That is expected with classic isolcpus= . On newer kernels the story split: isolcpus=domain / cpusets / cgroup cpuset — userspace isolcpus=managed_irq or manual irqaffinity / /proc/irq/*/smp_affinity — interrupts nohz_full= — tick reduction, another knob, not a substitute isolcpus is also marked deprecated in some trees in favor of cpusets. The IRQ caveat did not go away when the docs changed the preferred interface. Moving IRQs by hand Find the noisy ones ( eth0 , NVMe, GPU): grep -E 'eth|nvme|enp' /proc/interrupts # smp_affinity is a hex CPU mask. CPU2 only → 4 echo 4 > /proc/irq/IRQNUM/smp_affinity Or set the default affinity so new IRQs skip 0/1: irqaffinity=2-7 in the same GRUB line (adjust to your CPU count). Some devices ignore this (managed IRQs, VFIO). Then you isolate at the driver: bind the NIC to vfio-pci and poll from a pinned thread. When this shows up next to SR-IOV Passing a VF into KVM does not pin ho

Networking terms can feel like alphabet soup when you're starting out — Hub, Switch, Router, MAC address, IP address, Subnet Mask — thrown at you all at once, usually with zero real-world context. Here's how I finally made sense of it, using something a lot more familiar: cricket. The Cricket Analogy Imagine a cricket team with three players: a hub , a switch , and a router . All three are part of the same game, but each has a completely different job — one's a batsman, one's a bowler, one's a fielder. Networking devices work the same way: they're all part of one network, but each does something distinct. Hub — The One Who Shouts to Everyone A hub is the simplest of the three. If only two devices need to talk, you don't even need one — but the moment more than two devices are connected, a hub becomes necessary to relay traffic between them. Here's the catch: a hub has no idea who's talking to whom. If Device A wants to send data to Device B, it sends that data to the hub — and since the hub doesn't know which device Device A actually wants to reach, it just broadcasts the data to every single connected device. So a hub's "functionality" is really a lack of intelligence — it doesn't figure out who wants to speak with whom; it just floods the message everywhere and lets the devices sort it out. Switch — The One Who Knows Everyone by Name A switch does the same basic job as a hub — moving data between connected devices — but with one major upgrade: it actually knows who's who. Instead of blindly broadcasting to every device, a switch keeps a table of each connected device's MAC address , so it can send data directly to the right recipient. What Is a MAC Address? Every device that connects to a network — a laptop, phone, router, anything — has a Network Interface Card (NIC) . That NIC comes with a MAC address : a permanent ID burned in by the manufacturer. If your laptop has an Ethernet port, the NIC lives right behind it. If you're connecting over Wi-Fi instead, the NI

Opinion: Your Tests Can't See What a Migration Destroys — Dry-Run It on a Clone A green test suite is the wrong tool for judging an AI-generated migration, because tests run against the post-migration schema and never observe the intermediate states where data disappears. The up migration is the visible artifact that gets reviewed, while the down migration is treated as an afterthought even though it is the only safety net when the deployment goes wrong. Free model access makes the problem structural: generation cost drops to zero, so migration volume rises, and every additional migration multiplies the surface for unreviewed data loss. Disclosure: This article was prepared as part of MonkeyCode's product outreach. Tests validate the destination, not the journey When a test suite runs against a migrated database, it confirms that the application can read the new schema, but it cannot confirm that the migration preserved the data it was supposed to preserve. The test runner connects after the migration has executed, so it never sees the moment when a column is dropped, a table is renamed, or a constraint is silently relaxed. A migration that passes every test can still destroy production data, because the tests were designed to validate application behavior, not migration safety. The standard mitigation is a staging database, but staging is a poor substitute for a dry run because it has different data, different volume, and different usage patterns. The dry run I recommend uses a clone of the production schema with a representative data sample, and it exercises both directions of the migration with data integrity checks at every step. The clone does not need to be large; a few thousand rows per table is enough to expose most destructive patterns. The dry-run workflow in five steps The workflow is deliberately mechanical, because the goal is to remove judgment from the verification process and reserve human attention for the migration's intent: Clone the schema and lo

The organizations embracing hybrid agile models aren't making a principled methodological choice — most of them are just formalizing the mess they were already living in. Picture a delivery team at a mid-sized European bank. They run two-week Scrum sprints — daily standups, sprint reviews, the whole ceremony. They use Jira boards. They call themselves agile. And then, every quarter, a Release Approval Board convenes to review a 47-page change documentation package before anything goes to production. The sprints are agile theater. The real schedule is a Gantt chart that lives in somebody's SharePoint. Nobody says this out loud in the all-hands. They don't need to. This scenario — the sprint-shaped container wrapped around predictive, gate-controlled delivery — has quietly become the dominant operating model in software delivery. According to the 18th State of Agile Report, 74% of organizations now report using hybrid or homegrown models, mixing and matching agile with whatever else their org chart demands. The consulting firms have a polished name for it: hybrid delivery. The people living it often have a less flattering one. Here's the uncomfortable argument worth making: the rise of hybrid agile isn't evidence that organizations have matured past ideological purity. For many of them, it's evidence that they never committed to anything in the first place — and now have a framework-shaped fig leaf to cover that fact. The hybrid model is legitimate. Claiming you've adopted one when you've actually just left the org chart untouched while duct-taping Scrum on top? That's a different animal entirely. How We Got Here The path from "pure agile" to hybrid wasn't a straight line. It started with a real problem. As organizations tried to scale agile beyond small teams, limitations became visible — among them, agile's tendency to underweight documentation and its friction with physical product iteration cycles, both of which created compliance and maintenance headaches in regu

tailscale up --tun=userspace-networking gets you a green dot in the admin console and almost nothing else. The node appears in your tailnet, tailscale status looks healthy, and then you try to SSH into that container from your laptop and the connection hangs until TCP gives up. Two lines in the LXC config file fix it, and the container stays unprivileged. That's the whole post, really. But those two lines only make sense once you understand why every guide pushes you toward userspace mode in the first place, and what you're giving up by staying there. Who should care Anyone running services in unprivileged LXC containers on Proxmox who wants those containers to be real tailnet members with their own 100.64.0.0/10 address. Not reachable through something else. Reachable directly, over WireGuard, with a kernel network interface that ip addr can see. If you're already routing everything through a subnet router, you have a working setup and this is an optional upgrade. I covered that pattern in Tailscale Subnet Routers . Treat this as the next rung on the ladder: instead of one node advertising routes on behalf of everyone else, each container carries its own identity, its own ACL surface, and its own direct path to peers. What userspace networking actually costs you Every LXC-and-Tailscale guide I've read lands on the same instruction: pass --tun=userspace-networking and move on. It works because it sidesteps the problem entirely. Rather than asking the kernel for a TUN device, tailscaled runs a userspace TCP/IP stack (gVisor's netstack) inside its own process and never opens /dev/net/tun . Those costs stay invisible until you trip over one. Outbound traffic needs a proxy. In userspace mode, tailscaled exposes SOCKS5 and HTTP proxies on a local port. Nothing on the system routes to 100.64.0.0/10 automatically, because there is no interface and no route. Every client has to be told about the proxy: # userspace mode: this is the only way out export ALL_PROXY = socks5://l

Cloudflare, Astro, AI agents, GitHub Actions, issue triage, agentic AI, software architecture, open source, developer tools, AI automation, automated testing, human in the loop, agent workflows, GitHub, software engineering, AI software development, bug triage, continuous integration, developer productivity, autonomous agents, AI coding, Cloudflare Workers, Flue, triagebot By Leela Kumili

Technical Reconstruction of Toxic Work Culture Mechanisms Mechanisms and Their Impact Chains The evolution of workplace dynamics in large organizations has been marked by a pronounced shift from collaborative ecosystems to competitive arenas. This transformation is driven by specific mechanisms that, while often implemented with the intent to enhance productivity, inadvertently foster toxicity. Below, we dissect these mechanisms, their internal processes, and the observable effects they precipitate, elucidating the causal pathways that undermine organizational health. Performance Evaluation Systems Impact : Stackranking, hidden metrics, and PR/LoC counts incentivize individual competition, distorting the focus from collective goals to personal advancement. Internal Process : Employees, driven by survival instincts, prioritize outperforming peers over collaborative problem-solving, eroding the foundation of trust. Observable Effect : The erosion of trust and reduced team synergy directly correlate with diminished project outcomes and increased interpersonal conflicts. PIP Processes Impact : When PIP (Performance Improvement Plan) systems are weaponized punitively rather than utilized developmentally, they become tools of fear rather than growth. Internal Process : Employees perceive PIPs as existential threats, triggering stress responses that manifest as defensiveness and reduced engagement. Observable Effect : The resultant demoralization accelerates turnover rates, exacerbating recruitment costs and depleting institutional knowledge. Time Tracking Systems Impact : An overemphasis on quantifiable hours worked relegates quality and innovation to secondary priorities, fostering a culture of compliance over excellence. Internal Process : Employees, incentivized by logged hours, allocate effort disproportionately to tasks that maximize visibility rather than impact. Observable Effect : Despite inflated time logs, overall productivity declines as creative and strategic

VRP Is Ready for External Validation — Who Will Be the First to Pilot It? My name is Vitalijus Riabovas. I am the independent architect and creator of VRP — Veil Routing Protocol . VRP is a continuity-first networking architecture built around a simple principle: A logical session should not have to die simply because the network underneath it changed. Wi-Fi → LTE/5G. IP mutation. NAT / CGNAT churn. Temporary blackout. Path failure. Recovery. Replay attempts. Stale authority. Duplicate execution. For a long time, VRP was primarily architecture, runtime engineering and internal validation. That stage has changed. The public validation boundary exists now. And I am inviting serious engineers and organisations to test it. DON'T TRUST MY CLAIMS. TEST THEM. I am not asking the networking industry to believe a presentation. I built the measurement boundary. The public VRP Validation Kit provides engineers with an environment for evaluating observable behaviour independently. You can: clone the repository; run the Docker scenarios; inspect generated evidence; verify manifests and hashes; attack the evidence; delete events; duplicate events; reorder events; attempt replay; introduce stale conditions; corrupt artifacts; run the verifier; reproduce PASS / REJECT / INCOMPLETE outcomes. If you believe something is wrong, try to produce a reproducible contradiction. Give me: environment → scenario → commands → evidence → result That is useful engineering. WHAT HAS BEEN BUILT? VRP has moved far beyond an architectural diagram. The project now includes multiple engineering layers. Continuity architecture Logical session identity is designed to survive changes in the underlying network path. The architecture is being developed around continuity rather than assuming that transport identity and logical session identity must always be the same thing. Runtime The protected runtime implements the private VRP mechanisms. That implementation is not public . State and transition handling T