hyperdx VS starter-workflows

Hi HN, Mike and Warren here! We’ve been building an open source local-dev-friendly mode for HyperDX (hyperdx.io). It's a single Docker container that lets you view logs, metrics, and traces for local development in a similar way you can use them for production (live tail, filter/correlate logs & spans, build charts, flamegraph, etc.) Basically, imagine you can run Datadog in a single container for local development. We does this by spinning up an OpenTelemetry collector, Clickhouse DB and HyperDX UI all in a single container - it only takes a few seconds to start and lets you start live tailing your local logs and traces immediately (and graph metrics of course).

README (w/ demo gif): https://github.com/hyperdxio/hyperdx/blob/main/LOCAL.md

We started building local mode as it became one of our most loved [1] community issue after sharing HyperDX. It made sense - as we constantly use HyperDX to debug our own issues locally, and have found it to be a huge productivity boost for things like…

1. Tailing multiple container logs (and grepping/isolating them) without a ton of different terminal splits open at the same time.

2. Be able to sensibly view structured logs and correlated traces to debug local issues (because you’re using structured logging and tracing right?) instead of adding ad-hoc console statements that print out exactly what I could’ve gotten from tracing.

3. Testing telemetry are actually emitting/correlating as expected, before shipping it all the way out to prod and realizing I accidentally created a very expensive high-cardinality metric or a span that has the wrong properties.

We spent some time packaging & tuning our existing OSS stack to run in a single container with less memory/space requirements by staring at `dive` to slim down the image and applied incantations from documentation until memory usage improved. Additionally we removed a few non-local-friendly things like authentication requirements and extraneous services.

It still has all the goodness you’d want - so you can full text search your logs/traces, live tail all your events, view spans correlated with logs (and vice versa), create dashboards based on logs, metrics, traces, and is fully OpenTelemetry compatible - just point your Otel SDK/collector to http://localhost:4318 (or 4317 for the grpc folks) and you’re already good to go.

I’m excited to share what we’ve been working on and would love to hear your feedback and opinions!

Spin up the container yourself to try it out:

docker run -p 8000:8000 -p 4318:4318 -p 4317:4317 -p 8080:8080 -p 8002:8002 hyperdx/hyperdx-local

Main Open Source Repo: https://github.com/hyperdxio/hyperdx

Hosted Demo (in case you want to play around in a cloud sandbox instead): https://api.hyperdx.io/login/demo

HyperDX Landing Page: https://hyperdx.io

[1]: https://github.com/hyperdxio/hyperdx/issues/7

ClickHouse also excels at storing and querying semi-structured data, like event logs. Previously, many engineering teams used Elasticsearch in a similar niche to ClickHouse, building applications like Kibana. Increasingly, developers are choosing ClickHouse over Elasticsearch for its unparalleled performance characteristics. For example, our friends at hyperdx.io are using ClickHouse to build an open-source OpenTelemetry provider!

HyperDX

Biased as a founder in the space [1] but I think with OpenTelemetry + OSS extensible observability tooling, the holy grail of one tool is more realizable than ever.

Vendor lock in with Otel now is hopefully a thing of the past - but now that more obs solutions are going open source, hopefully it's not necessarily true that one tool would be mediocre over all use cases (since DD and the likes are inherently limited by their own engineering teams, vs OSS products can have community/customer contributions to improve the surface area over time on top of the core maintainer's work).

[1] https://github.com/hyperdxio/hyperdx

HyperDX (YC S22) | Founding Engineer | SF Bay Area HQ | REMOTE

We're building an open source, dev friendly observability tool (think Datadog, but something developers actually love to use and companies can actually afford).

We're in the intersection of needing to build rock solid infrastructure ingesting TBs of data, searching it incredibly quickly and scalably, and layering on top a buttery smooth DX from our language-specific SDKs, APIs and web app.

We're super early and hiring our first founding engineer. We already have a cloud product customers pay for and love, loads of runway regardless of the wider economy, 5k+ Github stars weeks after our OSS launch, and tons of hard technical problems.

The vast majority of our work is open source, so you can get a sense of what you'd be working with here: https://github.com/hyperdxio/hyperdx

Our job listing is here as well: https://www.ycombinator.com/companies/hyperdx/jobs/zFXTbzl-f...

Come by our discord as well if you just want to talk shop: https://discord.gg/FErRRKU78j

I'm Mike, one of the cofounders. If you love shipping quickly and want to help us build from the ground up an open source developer tool (that devs won't hate when they're on-call), let me know! mike [at] hyperdx.io

Oh huh! What would you do with span start independent of stops?

A tangent on logcat - local observability to me is a really intriguing area, I think there's a story of Otel for local as well if someone can build a good enough local DX for consuming them (we've been told a number of times about this https://github.com/hyperdxio/hyperdx/issues/7 as an example)

Hi HN, Mike and Warren here! We’ve been building HyperDX (hyperdx.io). HyperDX allows you to easily search and correlate logs, traces, metrics (alpha), and session replays all in one place. For example, if a user reports a bug “this button doesn’t work," an engineer can play back what the user was doing in their browser and trace API calls back to the backend logs for that specific request, all from a single view. Github Repo: https://github.com/hyperdxio/hyperdx

We're building the OSS equivalent when it comes to the observability side of Splunk/DD, on Clickhouse naturally of course but believe in the same end goal of lowering cost via separation of compute and storage.

https://github.com/hyperdxio/hyperdx

GitHub, as one of the leading web-based Git repository hosting service, provides a powerful suite of CI/CD tools in the form of GitHub Actions. These are directly integrated into the platform which empowers developers to increase the speed, efficiency and reliability of delivering products. In this brief article, we will take a look at what CI/CD is, why we should use it, as well as some of its applications in my projects.

GitHub Actions is a modern CI/CD tool integrated natively on GitHub. Itenables the rapid automation of build, test, deployment, and other custom workflows on GitHub with no need for external tools.

GitHub Actions is GitHub's CI/CD solution. You can use it to run automated tasks each time you change your code. Although the platform lacks a built-in Kubernetes integration, third-party plugins such as Azure's Deploy to Kubernetes Cluster action can automate deployments and manage different rollout strategies.

GitHub Actions is a feature-rich CI/CD platform embedded within GitHub, enabling developers to automate, customize, and execute software development workflows directly in their repositories. An Action inside GitHub Actions is a discrete unit of automation that performs a specific task within a workflow. All the Actions are reusable, and there are many to choose from. You can even create your own reusable ones.

actions/starter-workflows

The real power of using PHP code-quality tools is when it’s added to your continuous integration process, which means it automatically checks the code every time someone makes a push or pull request to your project repo. In this section, we'll be looking at how to do just that. GitHub actions is available for free so we'll use it for demo purposes. Note that there are some limits to private repos, so set your test repo to public if you can.

You can even automate the running of this script — hence the directory name automation — to happen every time the data changes, using GitHub Actions.

# Based on https://github.com/actions/starter-workflows/blob/main/ci/node.js.yml name: CI on: pull_request: branches: - main jobs: ci: runs-on: ubuntu-latest steps: - uses: actions/checkout@v2 - uses: actions/setup-node@v2 with: node-version: lts/* cache: 'npm' - run: npm ci - run: npm run build --if-present - run: npm test

You might remember that I’ve been taking an interest in GitHub Actions for the last year or so (I even wrote a book on the subject). And at the Perl Conference in Toronto last summer I gave a talk called “GitHub Actions for Perl Development” (here are the slides and the video).