Show HN: AI Configured Log Collection Agents
2 by stephenjcollins | 0 comments on Hacker News.
Long time reader, first time caller! I had what I thought was a common DevOps problem. My data collection agents had a centralized config registry but couldn't update their own configs. This was a nightmare for my dynamic environments where one-off deployments were common. Unable to find something that fit my needs, LogSail was born. My solution is an autonomous logging and monitoring platform that provides a reactive log layer. Once an agent deploys, it defines collection sources and starts reporting. The agent decides on its own what to check, as well as when and how to do it. It even works in the face of anomalies and other problems. Part of the logic lives in the agent, but I ended up designing a protocol for the agents to be more robust. This could make it useful for some scenarios where connectivity is iffy, too. By design, the log collection layer has started out agnostic of other upstream logging platforms. It turns out, this work also reduces centralized logging storage costs, network traffic, and enhances data quality. In early prototypes, my first customer saw a 30% drop in their Datadog bill. LogSail isn’t designed to replace the likes of Datadog or Splunk, but it lets you optimize your dollars with them. As an added bonus, real time control over agents via web-based console or API makes integration a snap. For my own needs, it was enough to store log data in a secure archive. The archive design had multi-tenancy and security in mind. Now that I have a few customers, they have all asked for event forwarding to Datadog, SumoLogic, and Splunk. At the link, I’ve included a quick video showing what agents are capable of finding, as well as the ease of deployment. Please feel free to try it out. There’s a free tier to make that easier and I welcome any feedback. Even if you don’t try it, I’d appreciate an opportunity to get your feedback about the idea and any pointers you might have based on your own experiences.
Wednesday, 16 August 2023
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Show HN: Yadget Synthetic Data Generation for Testing
2 by Renjit | 0 comments on Hacker News.
Yadget is an honest-to-goodness SaaS tool designed to generate Synthetic Data for testing. You can produce realistic, non-identifiable datasets to help you test and validate your products. Ideal for sw developers for data testing and validation processes. Right now the only differentiator is the number of free rows that it can develop but there is a roadmap IF people use it. Is this a good approach or a chicken and egg problem that we have set for ourselves?
2 by Renjit | 0 comments on Hacker News.
Yadget is an honest-to-goodness SaaS tool designed to generate Synthetic Data for testing. You can produce realistic, non-identifiable datasets to help you test and validate your products. Ideal for sw developers for data testing and validation processes. Right now the only differentiator is the number of free rows that it can develop but there is a roadmap IF people use it. Is this a good approach or a chicken and egg problem that we have set for ourselves?
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Show HN: Static_str_ops: &'static str and non-const operations in Rust
2 by sighingnow | 0 comments on Hacker News.
It is often asked by Rust programmer that how to create `&'static str` in Rust with non-const operations at runtime, e.g., returns the result of `format!()` as `&'static str`, rather than `String`. The crate static_str_ops addressed this issue, by allocating a hash set under the hood, and return the reference as the result. Along with this crate, a set of utilities are provided, including `static_format!`, `static_concat!`, and `staticize_once!` which can be used to initialize static strings with the `call_once` semantic.
2 by sighingnow | 0 comments on Hacker News.
It is often asked by Rust programmer that how to create `&'static str` in Rust with non-const operations at runtime, e.g., returns the result of `format!()` as `&'static str`, rather than `String`. The crate static_str_ops addressed this issue, by allocating a hash set under the hood, and return the reference as the result. Along with this crate, a set of utilities are provided, including `static_format!`, `static_concat!`, and `staticize_once!` which can be used to initialize static strings with the `call_once` semantic.
Tuesday, 15 August 2023
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Show HN: Exploring the design space of binary search trees
2 by rtheunissen | 0 comments on Hacker News.
2 by rtheunissen | 0 comments on Hacker News.
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Show HN: Layerform (YC S23) – Open-source dev environments using Terraform files
14 by lucas_vieira | 4 comments on Hacker News.
Hi HN, we're Lucas and Lucas, the authors of Layerform (https://ift.tt/nt1ZOaG). Layerform is an open-source tool for setting up development environments using plain .tf files. We allow each engineer to create their own "staging" environment and reuse infrastructure. Whenever engineers run layerform spawn, we use plain .tf files to give them their own "staging" environment that looks just like production. Many teams have a single (or too few) staging environments, which developers have to queue to use. This is particularly a problem when a system is large, because then engineers can't run it on their machines and cannot easily test their changes in a production-like environment. Often they end up with a cluttered Slack channel in which engineers wait for their turn to use staging. Sometimes, they don't even have that clunky channel and end up merging broken code or shipping bugs to production. Lucas and I decided to solve this because we previously suffered with shared staging environments. Layerform gives each developer their own production-like environment.This eliminates the bottleneck, increasing the number of deploys engineers make. Additionally, it reduces the amount of bugs and rework because developers have a production-like environment to develop and test against. They can just run "layerform spawn" and get their own staging. We wrap the MPL-licensed Terraform and allow engineers to encapsulate each part of their infrastructure into layers. They can then create multiple instances of a particular layer to create a development environment.The benefit of using layers instead of raw Terraform modules is that they're much easier to write and reuse, meaning multiple development environments can run on top of the same infrastructure. Layerform's environments are quick and cheap to spin up because they share core pieces of infrastructure. Additionally, Layerform can automatically tag components in each layer, making it easier for FinOps teams to manage costs and do chargebacks. For example: with Layerform, a product developer can spin up their own lambdas and pods for staging while still using a shared Kubernetes cluster and Kafka instance. That way, development environments are quicker to spin up and cheaper to maintain. Each developer's layer also gets a tag, meaning FinOps teams know how much each team's environments cost. For the sake of transparency, the way we intend to make money is by providing a managed service with governance, management, and cost-control features, including turning off environments automatically on inactivity or after business hours. The Layerform CLI itself will remain free and open. You can download the Layerform CLI right now and use it for free. Currently, all the state, permissions, and layer definitions stay in your cloud, under your control. After the whole license change thing, I think it's also worth mentioning we'll be building on top of the community's fork and will consider adding support for Pulumi too. We'd love your feedback on our solution to eliminate “the staging bottleneck". What do you think?
14 by lucas_vieira | 4 comments on Hacker News.
Hi HN, we're Lucas and Lucas, the authors of Layerform (https://ift.tt/nt1ZOaG). Layerform is an open-source tool for setting up development environments using plain .tf files. We allow each engineer to create their own "staging" environment and reuse infrastructure. Whenever engineers run layerform spawn, we use plain .tf files to give them their own "staging" environment that looks just like production. Many teams have a single (or too few) staging environments, which developers have to queue to use. This is particularly a problem when a system is large, because then engineers can't run it on their machines and cannot easily test their changes in a production-like environment. Often they end up with a cluttered Slack channel in which engineers wait for their turn to use staging. Sometimes, they don't even have that clunky channel and end up merging broken code or shipping bugs to production. Lucas and I decided to solve this because we previously suffered with shared staging environments. Layerform gives each developer their own production-like environment.This eliminates the bottleneck, increasing the number of deploys engineers make. Additionally, it reduces the amount of bugs and rework because developers have a production-like environment to develop and test against. They can just run "layerform spawn" and get their own staging. We wrap the MPL-licensed Terraform and allow engineers to encapsulate each part of their infrastructure into layers. They can then create multiple instances of a particular layer to create a development environment.The benefit of using layers instead of raw Terraform modules is that they're much easier to write and reuse, meaning multiple development environments can run on top of the same infrastructure. Layerform's environments are quick and cheap to spin up because they share core pieces of infrastructure. Additionally, Layerform can automatically tag components in each layer, making it easier for FinOps teams to manage costs and do chargebacks. For example: with Layerform, a product developer can spin up their own lambdas and pods for staging while still using a shared Kubernetes cluster and Kafka instance. That way, development environments are quicker to spin up and cheaper to maintain. Each developer's layer also gets a tag, meaning FinOps teams know how much each team's environments cost. For the sake of transparency, the way we intend to make money is by providing a managed service with governance, management, and cost-control features, including turning off environments automatically on inactivity or after business hours. The Layerform CLI itself will remain free and open. You can download the Layerform CLI right now and use it for free. Currently, all the state, permissions, and layer definitions stay in your cloud, under your control. After the whole license change thing, I think it's also worth mentioning we'll be building on top of the community's fork and will consider adding support for Pulumi too. We'd love your feedback on our solution to eliminate “the staging bottleneck". What do you think?
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Show HN: Portfolio/Resume website driven by GPT
3 by neighborlynook | 0 comments on Hacker News.
Decided to take a left turn in building a portfolio site for myself. So I fed ChatGPT my resume, came up with a prompt, and now will let ChatGPT be my advocate for my resume site. Github for the page: https://ift.tt/PcIxJHE
3 by neighborlynook | 0 comments on Hacker News.
Decided to take a left turn in building a portfolio site for myself. So I fed ChatGPT my resume, came up with a prompt, and now will let ChatGPT be my advocate for my resume site. Github for the page: https://ift.tt/PcIxJHE
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