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Products that do what duckkit.dev does
Kafka, rate limits, latency math & more, in your browser
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- 2KT
Hey HN, for those of you tired of running kafka-consumer-groups.sh and similar tools, here's a small real-time monitoring CLI tool for Apache Kafka, that displays consumer lag and event rates in a clean, top-like interface. You can quickly assess which consumers are lagging and when they will catch up. I've made this to quickly assess the health of remote on-premises clusters which most of the time lack proper monitoring. The tool can be found here: https://github.com/sivann/kafkatop I'd be very interested to hear your feedback or any features you think would add value to…
Sep 2025 · github.com
- 3DF
Hello Everyone! We built SQLFlow as a lightweight stream processing engine. We leverage DuckDB as the stream processing engine, which gives SQLFlow the ability to process 10's of thousands of messages a second using ~250MiB of memory! DuckDB also supports a rich ecosystem of sinks and connectors! https://sql-flow.com/docs/category/tutorials/ https://github.com/turbolytics/sql-flow We were tired of running JVM's for simple stream processing, and also of bespoke one off stream processors I would love your feedback, criticisms and/or…
Dec 2025 · sql-flow.com
- 4PS
Hey HN! Lev and Justin here, authors of PgDog (https://pgdog.dev/), a connection pooler, load balancer and database sharder for PostgreSQL. If you build apps with a lot of traffic, you know the first thing to break is the database. We are solving this with a network proxy that works without requiring application code changes or database migrations. Our post from last year: https://news.ycombinator.com/item?id=44099187 The most important update: we are in production. Sharding is used a lot, with direct-to-shard queries (one shard per query) working pretty much…
Feb 2026 · github.com
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- 6KA
2020 · github.com
- 7KS
2016 · github.com
- 8
- 9KA
A large part of our (Real Kinetic's) business is helping organizations implement platform engineering, but we've found the existing tooling to be lacking. For IaC, Terraform state becomes a pain because TF treats infrastructure as "one-shot" commands. The Kubernetes controller model provides a nicer approach to managing infrastructure, but the tooling here is also lacking. For configuration management, Helm just doesn't really scale with complexity, nor does Kustomize. For resource orchestration, Crossplane is a step in the right direction but still has challenges and limitations. As a…
2025 · koreo.dev
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- 11DR
Hi HN! I built a distributed rate limiter using the token bucket algorithm with Redis backing. Key highlights: • 50,000+ requests/second throughput with <2ms P95 latency • Redis-backed distributed state for multi-instance deployments • 18 REST API endpoints for rate limiting, config, and monitoring • 265+ tests including load tests and integration tests • Docker/Kubernetes ready with comprehensive documentation Built with Java 21 + Spring Boot. Perfect for protecting APIs, microservices, or SaaS platforms from abuse. The pain point I solved: existing solutions were either too…
Sep 2025 · github.com
- 12PP
Hey! I'm Andrei. I got frustrated by how people tend to build overcomplicated backend systems, being "motivated" by big tech case studies and popular books. So, I started exploring lean architecture, and building my digital garden of ideas, approaches and data that align with this direction. Here I want to present one of the tools – Sizing tool for PostgreSQL. I've benchmarked PostgreSQL on different EC2 instances and disks, with different initial data sets to see performance that these instances can give you. And I've built a tool to visualize this data, which I welcome you to explore. So,…
Jul 2026 · postgres.saneengineer.com
- 13GD
2017 · github.com
- 14AI
Hi HN, We are launching Denormalized (www.denormalized.io), a serverless real-time data platform built on Kafka and Pinot. We felt a bit burnt out by the sheer developer toil we faced when building application around the real-time data stack and set out to create a platform to allow small teams to be very productive with realtime data without having to glue together an elaborate system to serve real-time as well as time series queries. Here is our motivating post. Would appreciate any and all feedback.
2023 · teamdenormalized.substack.com
- 15IR
The Emotion Engine has 32 MB of RAM total, so the trick is streaming weights from CD-ROM one matrix at a time during the forward pass — only activations, KV cache and embeddings live in RAM. This means models bigger than the RAM can still run, they just read more from disc. Had to build a custom quantized format (PSNT), hack endianness, write a tokenizer pipeline, and most of the PS2 SDK from scratch (releasing that separately). The model itself is also custom — a 10M param Llama-style architecture I trained specifically for this. And it works. On real hardware.
Mar 2026 · github.com
- 16AU
I run 3mins.news (https://3mins.news), an AI news aggregator built entirely on Cloudflare Workers. The backend has 10+ cron triggers running every few minutes: RSS fetching, article clustering, LLM calls, email delivery. The problem: Workers Paid Plan has hard monthly limits (10M requests, 1M KV writes, 1M queue ops, etc.). There's no built-in "pause when you hit the limit", CF just starts billing overages. KV writes cost $5/M over the cap, so a retry loop bug can get expensive fast. AWS has Budget Alerts, but those are passive notifications, by the time you read the email,…
Mar 2026
- 17AB
2025 · github.com
- 18LA
A lightweight, keyboard-driven Kubernetes TUI for exploring and managing clusters from terminal.
May 2026 · github.com
- 19RT
We have been involved in a number of real time streaming projects using tools such as Flink, Spark Streams and Kafka Streams backed by "real time" databases such as Druid. We always found these projects quite complex to develop and run, with stream processing in particular being a bit of a dark art. A stream to stream join in Flink can get quite mind bending for instance. In 2020 we had the idea of building a low code SaaS product for real time streaming analytics. The first attempt failed due to being a little over-engineered and with too many changes of direction, but over the last few…
2021
- 20CA
I think agents should work like real teams, with independent, distinct roles, async communication, and the ability to onboard new teammates or tools without restructuring the whole org. I built backend systems at Yahoo and TikTok so event-driven agents felt obvious. But no agent SDKs were using this pattern, so I made Calfkit. Calfkit breaks down agents into independent services (LLM inference, tools, and routing) that communicate asynchronously through Kafka. Agents, tool services, and downstream consumers can be deployed, added-to, removed, and scaled independently. Check it out if this…
Feb 2026 · github.com
- 21KS
2020 · github.com
- 22MK
I built a Model Context Protocol server that allows users to interact with Kafka using natural language instead of complex CLIs. It uses LLMs to interpret commands in plain English and executes the corresponding Kafka operations. This makes Kafka more accessible to non-experts while maintaining its powerful functionality.
2025 · github.com
- 23AN
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
- 24KA
2020 · github.com
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