Alternatives
Products that do what Stacktical, a scalability prediction platform does
Hi guys, we're Wilhem from Paris and Jean-Daniel from Tokyo, software engineers with a passion for all things cloud (IaaS, PaaS, SaaS). We recently decided to tackle the problem of Capacity Planning with Stacktical, a Scalability Prediction service (https://stacktical.com). For a decade, we've been observing our clients and colleagues trying to nail down their strategy using repeated cycles of defining, collecting and interpreting load testing campaigns. It's funny how most people don't realize how demanding the work of infrastructure managers and their teams really is... While…
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2014 · stackshare.io
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Hi HN, I’m Sean, the founder of Ascend.io (https://www.ascend.io). I’m really excited to post here and announce the launch of Ascend.io, a radical new way of designing, scaling, and automating data pipelines. Ascend is the result of nearly 4 years of development effort for a team that is now 30-strong, and I would love for you to give it a test drive and let me what you think. I’ve felt this pain since I wrote my first MapReduce in 2004 (using Sawzall @ Google), and in the 15 years since, things have not improved at the pace of other parts of the technology ecosystem. When I went…
2019
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2017 · elasticbyte.net
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I've been working on a platform that uses LLMs to build maintain and manage k8s clusters on any cloud. The system writes infra as code to your Github repos and automatically containerizes and scales any services (public or private). The goal is to give your average engineer a vercel-like deployment experience for any service in any language at minimal cost. We have humans involved at the moment auditing LLM outputs and keeping an eye on clusters. We are looking for folks who may be thinking about their first infra/devops hire. Just connect your github and your cloud provider. The system…
2024 · milkinfrastructure.com
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2021 · github.com
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Hi HN, I previously wore SWE/SRE hats on GCP. Later, I was on the other side, managing thousands of machines. The friction points of onboarding and operating cloud systems are personal problems to me. I’ve found it hard to keep track of all the random cloud resources floating around, especially as my team’s assets proliferated. Occasionally, there is a resource affecting an outage but no one remembers where it is. I am constantly frustrated by existing tooling. APIs can work, after you’ve navigated the byzantine documentation, but I often find myself doing ad-hoc tasks which are best…
2022 · listvms.com
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Heya! We're longtime lurkers and do sometimes post, today however I want to present to you with the fruits of almost 4 years of work, hacking, designing, physically building (for the record: 2 years full time). We'd love to get some feedback from you guys and feel free to give us any hints on what we could/should change, or any opinion on whether you think that'd be something you'd use. protonet.info So here's our rough plan: We love the web and the possibilities it gives us, we also love the way the cloud allows us instant and ubiquitous access to our data and apps. Now what we don't like…
2012
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2021 · beta.rocketcompute.com
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Frustrated by the complexity and resource drain of multi service monitoring stacks, I built Simon. I wanted a single, lightweight dashboard to replace the heavy stack and the constant need for an SSH client for routine tasks. The result is a resource efficient dashboard in a single Rust binary, just a couple of megabytes in size. Its support for various architectures on Linux also makes it ideal for embedded systems and lightweight SBCs. It integrates: Comprehensive Monitoring: Realtime and historical metrics for the host system and Docker containers (CPU, memory, disk usage, and network…
Nov 2025 · github.com
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Kimi K3 has 2.78 trillion parameters and ships as 1.42 TB of weights. It clearly does not fit in the memory of a laptop. But K3 is a Mixture-of-Experts model. For each token, only a small fraction of its 896 experts per layer is activated. That changes the problem: the entire model does not need to be resident in RAM, as long as the weights required by each token can be reached quickly enough. We built WASTE — the Weight-Aware Streaming Tensor Engine — to explore that idea. WASTE keeps the dense, repeatedly used part of the model resident in memory, stores the routed experts in an…
Jul 2026
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Hi everyone, it’s Alex, Simon, Felipe and the team from Unikraft.io We have built kraft.cloud, a millisecond cloud platform, where apps and services cold start, scale to zero and autoscale in milliseconds, ensuring you never pay for idle, can efficiently cope with traffic peaks, and don’t have to deal with complex cold start issues. As of today we are now in open early access! The platform (and we) come from research in the area of lightweight virtualization — trying to ask the question of how efficient cloud platforms could (or should) be while still retaining strong, hardware-level…
2024 · kraft.cloud
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It's free servers monitoring and centralized cloud management app. We're hoping to lunch anytime soon. What do you think? Thanks.
2013 · cloudiff.com
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Hello HN, Lucas here. I’ve been working with BigQuery for ~5 years, mostly in large (petabyte-scale) environments. Over time we ended up spending a lot of money and engineering effort just trying to understand where costs were coming from, why and how to optimize them. At some point we decided to stop, leverage all our past experience and spend a full cycle building tooling focused on cost visibility and optimization. The main goal was to regain ownership of cost data and make it possible to understand our cost structure in under a minute, while aligning the views of engineering and FinOps…
Jan 2026 · cloudclerk.ai
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Hey HN, We’re the developers of Chonkie, a powerful and easy-to-use chunking library. Last November, we introduced Chonkie OSS here on HN (https://news.ycombinator.com/item?id=42100819) and got some fantastic feedback. Today, we’re excited to share Chonkie Cloud, a fully hosted service for chunking, along with new tools to make building and debugging RAG systems easier than ever. --- A quick recap for context: We launched Chonkie as an open-source project late last year. A few weeks ago, we decided to go full-time on it. Unfortunately, this shift wasn’t as smooth as we had…
2025 · cloud.chonkie.ai
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I'd like to share a project I've been working on for the past few months. It's a distributed workflow engine written entirely in Go. Some highlights: * Tasks are executed in a Docker container * Can run stand-alone or distributed * Highly extensible * Able to enforce limits (CPU/RAM) per task * Web UI Would love the get your feedback on it, and find out if this could be useful.
2023 · github.com
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2020 · ebbflow.io
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I wanted to share something I've been working on recently: Statum, a handy web analytics tool. https://github.com/extractumio/statum The journey began when I found myself frequently needing simple web analytics for my projects. I tried Google Analytics, especially GA4, and realized it was quite complex and, at times, not very accurate, especially when I wanted to view stats for the current day or recent hours. Then I tested a few fancy startup solution but ended up with way too expensive plans the expect me to subscribe (I'm not that rich to pay $99/month for every…
2023 · github.com
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We’re building an open-source language layer on top of Go, designed specifically for COBOL-style workloads: Native decimal arithmetic (COBOL-accurate) Record structures and copybook compatibility Batch jobs and transactional orchestration as first-class constructs Sequential / indexed file I/O baked into the runtime Compiles through Go for speed, concurrency, and cloud deployability Think of it as Kotlin for COBOL, or “COBOL on Go” familiar to mainframe engineers, powerful for modern developers. Test Results so far: NIST COBOL-85 validation: 77.61% overall (305/393 tests) NC…
Nov 2025 · github.com
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2021 · github.com
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