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Show HN: Alaz: Open-Source, Self-Hosted, eBPF-Based K8s Monitoring

Hello Everyone,<p>I'm excited to introduce a new open-source observability platform and would love to hear your feedback.<p>We are aware that there are lots of open-source/commercial tools out there. However, we believe that monitoring the clusters and extracting actionable insights requires deep know-how about the tools/domain. We mainly focused on this problem.<p>- Alaz is an eBPF agent installed on your K8s cluster as DaemonSet. Thanks to eBPF, Alaz collects traces directly from Linux kernels. This means there's no need for sidecars, instrumentations, or service restarts.<p>- The UI not only visualizes data but also provides actionable insights. Using the Service Map, you can:<p><pre><code> - View latencies and RPS between services. - Detect zombie services and underperforming SQL queries. - Monitor golden signals, such as 5xx status codes. </code></pre> In addition, Alaz can capture system resources like CPU, Memory, Disk, and Network through the Prometheus Node Exporter, which is embedded in the agent.<p>Setting up is straightforward: just install Alaz as a DaemonSet, and the platform will handle the rest.<p>Finally, the combination of Alaz and Ddosify Performance Testing makes it possible to do load testing and simultaneously monitor the system to find bottlenecks instantly.<p>For those interested, check out Alaz on GitHub: <a href="https://github.com/ddosify/alaz">https://github.com/ddosify/alaz</a><p>Your feedback would be greatly appreciated!

Show HN: Alaz: Open-Source, Self-Hosted, eBPF-Based K8s Monitoring

Hello Everyone,<p>I'm excited to introduce a new open-source observability platform and would love to hear your feedback.<p>We are aware that there are lots of open-source/commercial tools out there. However, we believe that monitoring the clusters and extracting actionable insights requires deep know-how about the tools/domain. We mainly focused on this problem.<p>- Alaz is an eBPF agent installed on your K8s cluster as DaemonSet. Thanks to eBPF, Alaz collects traces directly from Linux kernels. This means there's no need for sidecars, instrumentations, or service restarts.<p>- The UI not only visualizes data but also provides actionable insights. Using the Service Map, you can:<p><pre><code> - View latencies and RPS between services. - Detect zombie services and underperforming SQL queries. - Monitor golden signals, such as 5xx status codes. </code></pre> In addition, Alaz can capture system resources like CPU, Memory, Disk, and Network through the Prometheus Node Exporter, which is embedded in the agent.<p>Setting up is straightforward: just install Alaz as a DaemonSet, and the platform will handle the rest.<p>Finally, the combination of Alaz and Ddosify Performance Testing makes it possible to do load testing and simultaneously monitor the system to find bottlenecks instantly.<p>For those interested, check out Alaz on GitHub: <a href="https://github.com/ddosify/alaz">https://github.com/ddosify/alaz</a><p>Your feedback would be greatly appreciated!

Show HN: Fully client-side GPT2 prediction visualizer

Hi HN! I've found this visualization tool immensely helpful over the years for getting an intuition for how an LLM "sees" some piece of text, and with a bit of elbow grease decided to move all compute to client side so I could make it publicly available.<p>I've found it particularly useful for<p>- Understanding exactly how repetition and patterns affect a small LM's ability to predict correctly<p>- Understanding different tokenization patterns and how it affects model output<p>- Getting a general sense of how "hard" different prediction tasks are for GPT-style models<p>Known problems (that I probably won't fix, since this was a kind of one-off project)<p>- Doesn't work well with Unicode grapheme clusters that are multiple GPT-2 tokens (e.g. emoji, smart quotes)<p>- Support for other models (maybe later?)

Show HN: Fully client-side GPT2 prediction visualizer

Hi HN! I've found this visualization tool immensely helpful over the years for getting an intuition for how an LLM "sees" some piece of text, and with a bit of elbow grease decided to move all compute to client side so I could make it publicly available.<p>I've found it particularly useful for<p>- Understanding exactly how repetition and patterns affect a small LM's ability to predict correctly<p>- Understanding different tokenization patterns and how it affects model output<p>- Getting a general sense of how "hard" different prediction tasks are for GPT-style models<p>Known problems (that I probably won't fix, since this was a kind of one-off project)<p>- Doesn't work well with Unicode grapheme clusters that are multiple GPT-2 tokens (e.g. emoji, smart quotes)<p>- Support for other models (maybe later?)

Show HN: A better way to read blogs

Hey HN, maker here. It was a serious 4-6 months of effort to build this. I have never poured as much love, attention and detail into a project before. So I really appreciate you having a looksie!<p>The homepage has a fresh list of articles every hour and is open to all. Still, I recommend signing up so you can add stuff to your reading list and follow blogs.<p>My initial plan was to monetize this with subtle ads, but that didn't work out as the traffic to the site isn't nearly enough for that. That said, I have a fair bit invested in this and I need your help figuring out a way to make this sustainability profitable. If this was yours, what bits would you charge for? Are there any features I could add to a "pro" subscription?<p>Appreciate any help and support!

Show HN: A better way to read blogs

Hey HN, maker here. It was a serious 4-6 months of effort to build this. I have never poured as much love, attention and detail into a project before. So I really appreciate you having a looksie!<p>The homepage has a fresh list of articles every hour and is open to all. Still, I recommend signing up so you can add stuff to your reading list and follow blogs.<p>My initial plan was to monetize this with subtle ads, but that didn't work out as the traffic to the site isn't nearly enough for that. That said, I have a fair bit invested in this and I need your help figuring out a way to make this sustainability profitable. If this was yours, what bits would you charge for? Are there any features I could add to a "pro" subscription?<p>Appreciate any help and support!

Show HN: Nix Snapshotter – Native understanding of Nix packages for containerd

Hello! This is Edgar and Robbie and we built nix-snapshotter. nix-snapshotter brings native understanding of Nix packages to containerd.<p>We built this because Nix is a great fit for making efficient containers. They don't need an OS because Nix captures all dependencies exactly. However, the current process of creating Nix images is subpar because one needs to transform Nix packages into a format that container runtimes understand.<p>Using nix-snapshotter, instead of downloading image layers, packages come directly from the Nix store. Packages can be fetched from a binary cache or built on the fly if necessary. All existing non-Nix images continue to be supported, and Nix layers can be interleaved with normal layers.<p>nix-snapshotter also provides a CRI image service, which allows Kubernetes to resolve image manifests from Nix directly too. This enables for the first time, fully declarative Kubernetes resources, all the way down to the image specification and its contents. With this, you can even run pure Nix images without a Docker Registry at all, if you wish.<p>We'd love for you to try it out, there is a one-liner for Nix users to boot a VM with everything pre-configured: <a href="https://github.com/pdtpartners/nix-snapshotter">https://github.com/pdtpartners/nix-snapshotter</a>

Show HN: Nix Snapshotter – Native understanding of Nix packages for containerd

Hello! This is Edgar and Robbie and we built nix-snapshotter. nix-snapshotter brings native understanding of Nix packages to containerd.<p>We built this because Nix is a great fit for making efficient containers. They don't need an OS because Nix captures all dependencies exactly. However, the current process of creating Nix images is subpar because one needs to transform Nix packages into a format that container runtimes understand.<p>Using nix-snapshotter, instead of downloading image layers, packages come directly from the Nix store. Packages can be fetched from a binary cache or built on the fly if necessary. All existing non-Nix images continue to be supported, and Nix layers can be interleaved with normal layers.<p>nix-snapshotter also provides a CRI image service, which allows Kubernetes to resolve image manifests from Nix directly too. This enables for the first time, fully declarative Kubernetes resources, all the way down to the image specification and its contents. With this, you can even run pure Nix images without a Docker Registry at all, if you wish.<p>We'd love for you to try it out, there is a one-liner for Nix users to boot a VM with everything pre-configured: <a href="https://github.com/pdtpartners/nix-snapshotter">https://github.com/pdtpartners/nix-snapshotter</a>

Show HN: Nix Snapshotter – Native understanding of Nix packages for containerd

Hello! This is Edgar and Robbie and we built nix-snapshotter. nix-snapshotter brings native understanding of Nix packages to containerd.<p>We built this because Nix is a great fit for making efficient containers. They don't need an OS because Nix captures all dependencies exactly. However, the current process of creating Nix images is subpar because one needs to transform Nix packages into a format that container runtimes understand.<p>Using nix-snapshotter, instead of downloading image layers, packages come directly from the Nix store. Packages can be fetched from a binary cache or built on the fly if necessary. All existing non-Nix images continue to be supported, and Nix layers can be interleaved with normal layers.<p>nix-snapshotter also provides a CRI image service, which allows Kubernetes to resolve image manifests from Nix directly too. This enables for the first time, fully declarative Kubernetes resources, all the way down to the image specification and its contents. With this, you can even run pure Nix images without a Docker Registry at all, if you wish.<p>We'd love for you to try it out, there is a one-liner for Nix users to boot a VM with everything pre-configured: <a href="https://github.com/pdtpartners/nix-snapshotter">https://github.com/pdtpartners/nix-snapshotter</a>

Show HN: Host a Website in the URL

I wrote this silly thing a couple of weeks ago. It's absolutely useless but it's a fun tech demo for my web server library. Enjoy!

Show HN: Host a Website in the URL

I wrote this silly thing a couple of weeks ago. It's absolutely useless but it's a fun tech demo for my web server library. Enjoy!

Show HN: Host a Website in the URL

I wrote this silly thing a couple of weeks ago. It's absolutely useless but it's a fun tech demo for my web server library. Enjoy!

Show HN: Host a Website in the URL

I wrote this silly thing a couple of weeks ago. It's absolutely useless but it's a fun tech demo for my web server library. Enjoy!

Show HN: Transform any website or eBook into a research paper (no LLM required)

Show HN: Transform any website or eBook into a research paper (no LLM required)

Show HN: Pgs.sh – A zero-dependency static site hosting service for hackers

Hey all<p>I wanted to show a sneak peak of something I've been working on the for the past few months.<p>I build a lot of projects that involve static hosting and became frustrated by how complicated it is in 2023. All I need to do is move files from my CI onto a server that can serve the files. It shouldn't be as complicated as it is on GCP, AWS, etc. And the ones that are marketed as easy (e.g. Cloudflare Pages, surge.sh) still require the end-user to install a tool first.<p>With pgs.sh the user doesn't need to install anything. Signup is as simple as SSHing into pgs.sh and creating an account. Creating new static sites is as easy as copying files to pgs.sh.<p>To go even further, we have added features like instant promotion and rollback to make it easier to manage deployments safely.<p>The entire service can be managed via SSH commands. Pasted below is our help SSH command: <a href="https://erock.pastes.sh/pgs-cmds.md" rel="nofollow noreferrer">https://erock.pastes.sh/pgs-cmds.md</a><p>This service is in closed beta, but if you join our irc channel #pico.sh @ libera.chat we will invite you to test it out.<p>I'd love to read some feedback on this service, thanks!

Show HN: Bedframe – open-source Browser Extension Development framework

Show HN: Bedframe – open-source Browser Extension Development framework

Show HN: Keep – GitHub Actions for your monitoring tools

Hi Hacker News! Shahar and Tal from Keep here.<p>A few months ago, we introduced here at HN (<a href="https://news.ycombinator.com/item?id=34806482">https://news.ycombinator.com/item?id=34806482</a>) Keep as an “open source alerting CLI” and got some interesting feedback - mainly around UI, automation, and supporting more tools. We were VERY early back then, and we understood that although the current DX around creating alerts is not great, it's not that critical and developers don’t need another tool just for that.<p>But we did find something else.<p>While talking to developers and devops, we found that a lot of companies use many tools that generate alerts - from Cloudwatch, Prometheus, Grafana, and Datadog to tools such as Zabbix or Nagios. We definitely agree consolidation in the observability space is a real thing, but while talking to those companies we feel that there are still real use cases for having more than one tool (and for example, according to Grafana’s 2023 observability survey, 52% of the companies uses more than 6 observability tools <a href="https://grafana.com/observability-survey-2023/" rel="nofollow noreferrer">https://grafana.com/observability-survey-2023/</a>).<p>So we that in mind, we rebuilt Keep with a simple mindset: (1) Integrate with every tool that triggers alerts - it can be either pushing alerts to Keep via webhooks or routing policies or Keep to pull alerts via the tools API. (2) Create a simple abstraction layer to run workflows on top of these alerts. (3) Maintain a great developer experience - open source, API-first, workflows as code and generally having a developer mindset while building Keep.<p>During the time we rebuilt Keep, Datadog released their workflow automation tool (<a href="https://docs.datadoghq.com/service_management/workflows/" rel="nofollow noreferrer">https://docs.datadoghq.com/service_management/workflows/</a>) which led us to the understanding that's exactly what we solve - but for everyone who uses tools other than Datadog.<p>A short demo of Keep with a simple use case: <a href="https://www.youtube.com/watch?v=FPMRCZM8ZYg">https://www.youtube.com/watch?v=FPMRCZM8ZYg</a><p>You can try it yourself by signing into <a href="https://platform.keephq.dev">https://platform.keephq.dev</a><p>Like always - we invite you to try Keep and we are eager to hear any feedback.

Show HN: Keep – GitHub Actions for your monitoring tools

Hi Hacker News! Shahar and Tal from Keep here.<p>A few months ago, we introduced here at HN (<a href="https://news.ycombinator.com/item?id=34806482">https://news.ycombinator.com/item?id=34806482</a>) Keep as an “open source alerting CLI” and got some interesting feedback - mainly around UI, automation, and supporting more tools. We were VERY early back then, and we understood that although the current DX around creating alerts is not great, it's not that critical and developers don’t need another tool just for that.<p>But we did find something else.<p>While talking to developers and devops, we found that a lot of companies use many tools that generate alerts - from Cloudwatch, Prometheus, Grafana, and Datadog to tools such as Zabbix or Nagios. We definitely agree consolidation in the observability space is a real thing, but while talking to those companies we feel that there are still real use cases for having more than one tool (and for example, according to Grafana’s 2023 observability survey, 52% of the companies uses more than 6 observability tools <a href="https://grafana.com/observability-survey-2023/" rel="nofollow noreferrer">https://grafana.com/observability-survey-2023/</a>).<p>So we that in mind, we rebuilt Keep with a simple mindset: (1) Integrate with every tool that triggers alerts - it can be either pushing alerts to Keep via webhooks or routing policies or Keep to pull alerts via the tools API. (2) Create a simple abstraction layer to run workflows on top of these alerts. (3) Maintain a great developer experience - open source, API-first, workflows as code and generally having a developer mindset while building Keep.<p>During the time we rebuilt Keep, Datadog released their workflow automation tool (<a href="https://docs.datadoghq.com/service_management/workflows/" rel="nofollow noreferrer">https://docs.datadoghq.com/service_management/workflows/</a>) which led us to the understanding that's exactly what we solve - but for everyone who uses tools other than Datadog.<p>A short demo of Keep with a simple use case: <a href="https://www.youtube.com/watch?v=FPMRCZM8ZYg">https://www.youtube.com/watch?v=FPMRCZM8ZYg</a><p>You can try it yourself by signing into <a href="https://platform.keephq.dev">https://platform.keephq.dev</a><p>Like always - we invite you to try Keep and we are eager to hear any feedback.