# Quotas Published articles for Quotas. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Vercel Sandbox now supports 10,000 concurrent sandboxes and 5,000 vCPUs per minute DevFeed: [Vercel Sandbox now supports 10,000 concurrent sandboxes and 5,000 vCPUs per minute]() Original publisher: [Read original article]() Author: Brandon Tuttle Published: 2026-08-05T00:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [Vercel]() Tags: [concurrent](), [enterprise](), [pricing](), [quotas](), [sales](), [sandbox](), [sandboxes](), [vercel]() ### AI overview Vercel Sandbox has increased its default quotas for Pro and Enterprise plans to support up to 10,000 concurrent sandboxes and 5,000 vCPUs per minute. ### Source excerpt We've increased the default quotas for Vercel Sandbox on Pro and Enterprise plans: Quota Before After Concurrent sandboxes 2,000 10,000 vCPUs allocation rate 200/min (Pro), 400/min (Enterprise) Up to 5,000/min The higher vCPU allocation rate is possible thanks to a new dynamic quota: instead of a fixed limit, the allowed rate now ramps with sustained usage: it starts at 150 vCPUs per minute and increases by 500 vCPUs per minute as you continue creating sandboxes, up to 5,000 vCPUs per minute The new quotas apply automatically to all Pro and Enterprise teams. If you need higher quotas, contact sales. Learn more about Sandbox pricing and dynamic quotas. Read more ## Inspect Volcano workloads faster with Headlamp DevFeed: [Inspect Volcano workloads faster with Headlamp]() Original publisher: [Read original article]() Author: Mahmoud Magdy Published: 2026-06-25T20:00:00Z Content type: article Language: en Sources: [Kubernetes Blog]() Topics: [Kubernetes](), [jobs](), [High-Performance Computing](), [Machine learning](), [Web](), [Command-line interface]() Tags: [ai-ml](), [cli](), [high-performance-computing](), [jobs](), [kubernetes](), [quotas](), [ui](), [workflow]() ### AI overview This article introduces the Volcano plugin for Headlamp, a Kubernetes web UI. The plugin brings Volcano jobs, queues, PodGroups, Pods, and events into a unified interface, helping teams inspect batch workloads, scheduling behavior, quotas, priorities, and gang scheduling for Kubernetes, AI/ML, and high-performance computing workloads. ### Source excerpt Volcano is a cloud native batch scheduler for Kubernetes, built for high-performance computing, AI/ML, and other batch workloads. Headlamp is an extensible Kubernetes web UI. With its plugin system, Headlamp can surface APIs and workflows beyond the built-in Kubernetes resources. The Volcano plugin brings core Volcano resources into Headlamp so you can inspect workload state, queue behavior, and gang scheduling details in one place. Kubernetes was originally designed around long-running services, where applications are expected to start and remain available over time. Batch, AI/ML, and HPC workloads often behave differently: jobs arrive dynamically, compete for limited resources, and may need multiple workers to start together before useful work can begin. Volcano extends Kubernetes with concepts such as queues, priorities, quotas, and gang scheduling. Instead of treating every Pod independently, Volcano schedules workloads with awareness of the job as a whole and the resources it needs to make progress. To make these workloads easier to operate and troubleshoot, the Volcano plugin brings that scheduling context directly into Headlamp. Watch this short walkthrough to see the Volcano plugin in Headlamp: Visual context helps teams understand Volcano jobs, queues, and PodGroups faster Working with Volcano often means moving across several related resources while trying to understand a batch workload. You might start with a Job, then look at the related PodGroup, inspect the Pods behind it, check the Queue, and finally return to the Job again. All of that is possible with CLI tools like kubectl and the Volcano CLI, but it can become fragmented very quickly. The Volcano plugin for Headlamp makes that workflow easier by bringing the key resources together in a single UI. Instead of reconstructing relationships manually, you can move directly between Jobs, Queues, PodGroups, Pods, and events from the same interface. Volcano introduces its own resources on top of core Kuber ## OpenAI Style Usage Limits: Implementing Customer Quotas in Your Product DevFeed: [OpenAI Style Usage Limits: Implementing Customer Quotas in Your Product]() Original publisher: [Read original article]() Author: Ayush Agarwal Published: 2026-05-20T00:00:00Z Content type: tutorial Language: en Sources: [Dodo Payments Blog]() Topics: [Artificial Intelligence](), [Software as a service](), [OpenAI]() Tags: [ai](), [architecture](), [bug](), [how-to](), [implement](), [openai](), [protection](), [quotas](), [real-time](), [retry](), [trust](), [usage-based-billing]() ### AI overview A tutorial on implementing customer-facing usage limits for AI and SaaS products. It explains soft limits with email alerts, hard limits that stop billable work, real-time usage aggregation, clear limit messaging, and the protection these controls provide to customers and sellers. ### Source excerpt How to implement customer facing usage limits and quotas in your AI product. Soft caps, hard caps, alerts, and the OpenAI style limit experience. ## Introducing no-cost trials for Data Connect DevFeed: [Introducing no-cost trials for Data Connect]() Original publisher: [Read original article]() Author: Cynthia Wang Published: 2026-03-12T00:00:00Z Content type: release Language: en Sources: [Firebase Blog]() Topics: [Firebase](), [PostgreSQL](), [Database](), [Cloud]() Tags: [billing](), [firebase](), [free](), [news](), [postgresql](), [quotas](), [sql-connect](), [ssd](), [storage](), [updates]() ### AI overview Firebase announces no-cost trials for Firebase Data Connect. Spark-plan projects can provision one PostgreSQL database instance for 90 days without a credit card, while Blaze-plan projects qualify for a no-cost Cloud SQL for PostgreSQL trial for three months. ### Source excerpt News, tutorials, and updates from the Firebase team. ## hybrid quota-linear rate limiter DevFeed: [hybrid quota-linear rate limiter]() Original publisher: [Read original article]() Published: 2026-01-13T00:12:01Z Content type: article Language: en Sources: [Tony Finch's blog]() Topics: [rate-limiting](), [Algorithms]() Tags: [algorithm](), [quotas](), [rate-limiting]() ### AI overview The article explores a hybrid quota-linear rate limiter intended to enforce request quotas more precisely within a time window while limiting storage costs and avoiding bursty client behavior. It compares linear rate limiting with fixed-window quota resets and notes trade-offs, including throttling response time and burstiness. ### Source excerpt A while back I wrote about the linear rate limit algorithms leaky bucket and GCRA. Since then I have been vexed by how common it is to implement rate limiting using complicated and wasteful algorithms (for example). But linear (and exponential) rate limiters have a disadvantage: they can be slow to throttle clients whose request rate is above the limit but not super fast. And I just realised that this disadvantage can be unacceptable in some situations, when it's imperative that no more than some quota of requests is accepted within a window of time. In this article I'll explore a way to enforce rate limit quotas more precisely, without undue storage costs, and without encouraging clients to oscillate between bursts and pauses. However I'm not sure it's a good idea. linear reaction time fixed window quota resets hybrid quota-linear algorithm discussion opinion linear reaction time How many requests does a linear rate limiter allow before throttling? The parameters for a rate limiter are: q, the permitted quota of requests w, the accounting time window So the maximum permitted rate is q/w. Let's consider a client whose rate is some multiple a > 1 of the permitted rate (a for abuse factor) c = a * q/w I'll model the rate limiter as a token bucket which starts off with q tokens at time 0. The bucket accumulates tokens at the permitted rate and the client consumes them at its request rate. (It is capped at q tokens but we can ignore that detail when a > 1.) b(t) = q + t*q/w - t*a*q/w The time taken for n requests is t(n) = n/c = (n*w) / (a*q) After n requests the bucket contains b(n) = q + n/a - n The rate limter throttles the client when the bucket is empty. b(t) = 0 = q + t * (1 - a) * q/w 0 = 1 - t * (a - 1) / w t = w / (a - 1) b(n) = 0 = q + n * (1/a - 1) 0 = q - n * (a - 1) / a n = q * a / (a - 1) For example, if the client is running at twice the permitted rate, a=2, they will be allowed q*2 requests within w seconds before they are throttled. That's a bit slow. T ## Neon's New Pricing, Explained: Usage-Based, No Minimum DevFeed: [Neon's New Pricing, Explained: Usage-Based, No Minimum]() Original publisher: [Read original article]() Author: Mike Jerome Published: 2025-08-14T13:03:58Z Content type: article Language: en Sources: [Blog -- Neon Docs]() Topics: [Databases](), [autoscaling](), [Serverless](), [data]() Tags: [autoscaling](), [billing](), [capacity](), [company](), [postgres](), [pricing](), [quotas](), [serverless](), [storage]() ### AI overview Neon explains its December 2025 pricing update, under which paid plans become fully usage-based with no quotas, overages, or monthly minimums. Billing is based on compute, storage, additional branches, and restore history, while the Free plan remains available with increased storage per project. ### Source excerpt We've just rolled out a major update to Neon's pricing. Starting today, our paid plans are fully usage-based. That means you only pay for what you use, with no quotas to manage, no overages to worry about, and no need to guess how much capacity you'll need upfront. We're only enf... ## Storage: 10x Larger Uploads, 3x Cheaper Cached Egress, and 2x Egress Quota DevFeed: [Storage: 10x Larger Uploads, 3x Cheaper Cached Egress, and 2x Egress Quota]() Original publisher: [Read original article]() Author: Inian Parameshwaran Published: 2025-07-18T07:00:00Z Content type: release Language: en Sources: [Supabase Blog]() Topics: [Supabase](), [Amazon API Gateway](), [Caching](), [Terraform]() Tags: [3d](), [api](), [api-gateway](), [applications](), [cache](), [cdn](), [media](), [pricing](), [quotas](), [s3](), [saas](), [storage]() ### AI overview Supabase announces 500 GB file uploads for paid plans, cheaper cached egress, and increased cached and uncached egress quotas. The changes support large media files, user-generated data, 3D models, and archival workloads. ### Source excerpt Upload files up to 500 GB with significant egress cost reductions. ## Organization-based Billing, Project Transfers, Team Plan DevFeed: [Organization-based Billing, Project Transfers, Team Plan]() Original publisher: [Read original article]() Author: Paul Copplestone; Kevin Grüneberg Published: 2023-08-31T07:00:00Z Content type: article Language: en Sources: [Supabase Blog]() Topics: [Supabase](), [Databases]() Tags: [add-ons](), [billing](), [can](), [community](), [cost](), [enterprise](), [features](), [free](), [launch](), [platform](), [pricing](), [projects](), [quotas](), [subscriptions](), [support](), [updates](), [upgrades]() ### AI overview Supabase is moving from project-based to organization-based billing. Each organization will have one subscription and plan, while project-level add-ons such as compute upgrades, custom domains, and PITR remain attached to the organization subscription. Quotas and usage will be aggregated across projects, with paid-plan benefits applying to every project in the organization. ### Source excerpt Introducing the new Organization-based Billing ## Tips for maximizing your Turso billing allowances DevFeed: [Tips for maximizing your Turso billing allowances]() Original publisher: [Read original article]() Author: Doug Stevenson Published: 2023-08-23T00:00:00Z Content type: article Language: en Sources: [Turso Blog]() Topics: [Turso](), [SQLite](), [SQL](), [Databases]() Tags: [billing](), [code](), [performance](), [quotas](), [software-engineering](), [sql](), [sqlite](), [turso]() ### AI overview This article explains how to maximize Turso usage allowances while improving SQLite query performance. It focuses on reducing row reads by avoiding full table scans, using indexes and triggers, and inspecting query plans with SQLite's EXPLAIN QUERY PLAN statement. It also discusses Turso's Starter and Scaler plans, quotas, and billing metrics. ### Source excerpt Make the most out of your Turso usage allowance, and boost the performance of your SQLite queries at the same time, using indexes and triggers. ## Setting the right requests and limits in Kubernetes DevFeed: [Setting the right requests and limits in Kubernetes]() Original publisher: [Read original article]() Author: Gulcan Topcu Published: 2020-09-02T00:00:00Z Content type: tutorial Language: en Sources: [Learnk8s]() Topics: [Kubernetes](), [cpu](), [Linux](), [autoscaling](), [configuration](), [YAML]() Tags: [autoscaling](), [cgroups](), [configuration](), [container](), [cpu](), [kubernetes](), [memory](), [quotas](), [resource](), [systems](), [yaml]() ### AI overview A tutorial explaining how Kubernetes CPU and memory requests and limits affect scheduling, Linux cgroups, resource contention, eviction, out-of-memory handling, and autoscaling. ### Source excerpt Learn how Kubernetes CPU and memory requests and limits control scheduling, cgroup weights and quotas, eviction, throttling, and OOM kills. ## Increase your Build Quotas DevFeed: [Increase your Build Quotas]() Original publisher: [Read original article]() Author: Shai Almog Published: 2018-07-24T00:00:00Z Content type: article Language: en Sources: [CodeName One]() Topics: [Open Source](), [Server]() Tags: [build](), [developers](), [open-source](), [quotas]() ### AI overview Codename One describes its open-source code and build-server quotas, then announces a referral program that permanently increases users' build credits and JAR size limits for each friend who joins, subject to a 15-friend cap and abuse restrictions. ### Source excerpt The most common question we get about Codename One is: "Is Codename One Free". The direct answer is "Yes" but we don't want to mislead. You can work with the open source code, which is just as free as any other project. But it's not for the faint of heart... The build servers have quotas so we won't go out of business. This is perceived by developers as "not free" but since no one else offers build servers I have an issue with that perception. To battle that perception we're increasing the build quotas. ## Backup your Win8 computer to your Synology NAS DevFeed: [Backup your Win8 computer to your Synology NAS]() Original publisher: [Read original article]() Published: 2015-01-17T00:00:00Z Content type: tutorial Language: en Sources: [Juri Strumpflohner]() Topics: [synology nas](), [Synology](), [Windows](), [configuration]() Tags: [backup](), [computer](), [configuration](), [dsm](), [files](), [interface](), [nas](), [quotas](), [synology](), [synology-nas](), [windows]() ### AI overview A tutorial explains how to back up a Windows 8 computer to a Synology NAS using Windows File History. It covers creating a shared backup folder, creating a dedicated backup user with access rights and a quota, and enabling File History. ### Source excerpt Lorem ipsum dolor sit amet