ClickStack

ing open source, more performant, and doesn’t require extensive culling of retention limits and sampling rates - ClickStack gives a batteries-included way of starting that migration journey. For those that aren’t familiar with ClickHouse, it’s a high performance database that has already been used by companies such as Anthropic, Cloudflare, and DoorDash to power their core observability at scale due to its flexibility, ease of use, and cost effectiveness. However, this required teams to dedicate engineers to building a custom observability stack, where it’s difficult to not only get their telemetry data easily into ClickHouse but also struggling without a native UI experience. That’s why we’re building ClickStack - we wanted to bundle an easy way to get started ingesting your telemetry data whether it’s logs & traces from Node.js or Ruby to metrics from Kubernetes or your bare metal infrastructure. Just as important we wanted our users to enjoy a visualization experience that allowed users to quickly search using a familiar lucene-like search syntax (similar to what you’d use in Google!). We recognise though, that a SQL mode is needed for the most complex of queries. We've also added high cardinality outlier analysis by charting the delta between outlier and inlier events - which we've found really helpful in narrowing down causes of regressions/anomalies in our traces as well as log patterns to condense down clusters of similar logs. We’re really excited about the roadmap ahead in terms of improving ClickStack as a product and the ClickHouse core database to improve observability. Would love to hear everyone’s feedback and what they think! Spinning up a container is pretty simple: `docker run -p 8080:8080 -p 4317:4317 -p 4318:4318 docker.hyperdx.io/hyperdx/hyperdx-all-in-one` In browser live demo (no sign ups or anything silly, it runs fully in your browser!): https://play.hyperdx.io/ Landing Page: https://clickhouse.com/o11y Github Repo: https://github.com/hyperdxio/hyperdx Discord community: https://hyperdx.io/discord Docs: https://clickhouse.com/docs/use-cases/observability/clicksta...

ing open source, more performant, and doesn’t require extensive culling of retention limits and sampling rates - ClickStack gives a batteries-included way of starting that migration journey. For those that aren’t familiar with ClickHouse, it’s a high performance database that has already been used by companies such as Anthropic, Cloudflare, and DoorDash to power their core observability at scale due to its flexibility, ease of use, and cost effectiveness. However, this required teams to dedicate engineers to building a custom observability stack, where it’s difficult to not only get their telemetry data easily into ClickHouse but also struggling without a native UI experience. That’s why we’re building ClickStack - we wanted to bundle an easy way to get started ingesting your telemetry data whether it’s logs & traces from Node.js or Ruby to metrics from Kubernetes or your bare metal infrastructure. Just as important we wanted our users to enjoy a visualization experience that allowed users to quickly search using a familiar lucene-like search syntax (similar to what you’d use in Google!). We recognise though, that a SQL mode is needed for the most complex of queries. We've also added high cardinality outlier analysis by charting the delta between outlier and inlier events - which we've found really helpful in narrowing down causes of regressions/anomalies in our traces as well as log patterns to condense down clusters of similar logs. We’re really excited about the roadmap ahead in terms of improving ClickStack as a product and the ClickHouse core database to improve observability. Would love to hear everyone’s feedback and what they think! In browser live demo (no sign ups or anything silly, it runs fully in your browser!): https://play.hyperdx.io/ Landing Page: https://clickhouse.com/o11y Github Repo: https://github.com/hyperdxio/hyperdx Discord community: https://hyperdx.io/discord Docs: https://clickhouse.com/docs/use-cases/observability/clicksta...

or too tied to a specific ingestion architecture to scale to every use case (we used to be in this category!). For companies that needed more flexibility in how their data is ingested and stored (usually due to running at a large scale), there's really no good options for a developer experience (DX) focused observability layer on top of Clickhouse (Shopify spent 3 years building it in-house!) Our current release works completely in the browser - and it does this by building on top of Clickhouse's HTTP interface, which our React app can directly talk to. This means you can actually try HyperDX in your browser on your own Clickhouse with no installation! This was fortunately easy for us to accomplish due to being full stack Typescript, making it incredibly easy to shift between server and client code. On top of this we've been spending time baking in performance optimizations to ensure that HyperDX can continue to leverage Clickhouse efficiently at larger data volumes. We do a few tricks like only fetching columns that are needed for the current search, and re-querying to expand the entire row if needed to fully leverage Clickhouse's columnar nature (40% faster, ymmv!) - or rewriting queries to use materialized columns to speed up Map column access when available (10x faster!). On the DX side: we support querying using both Lucene (ex. `fullText property:value`) and SQL syntax. We've found the former to be our favorite for how concise it is. Similarly for charts, our chart builder has been upgraded to accept SQL expressions as well, so you can leverage the full power of SQL, while avoiding typing paragraphs of boilerplate SQL for time series data. We also make it easy to switch between UTC/local timestamps! Lastly, we've added high cardinality outlier analysis by charting the delta between outlier and inlier events (a la bubble up) - which we've found really helpful in narrowing down causes of regressions/anomalies in our traces. We have a lot more planned for the full release - but wanted to get this out early to hear your feedback and opinions! In Browser Live Demo: https://play.hyperdx.io/search Github Repo: https://github.com/hyperdxio/hyperdx/tree/v2 Landing Page: https://hyperdx.io/v2 [1]: https://www.uber.com/blog/logging/ [2]: https://blog.cloudflare.com/log-analytics-using-clickhouse/ [3]: https://www.youtube.com/watch?v=LDj3_jMsCXg&list=PLvQF73bM4-...

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

al/pull/43 - https://github.com/jxnl/instructor/pull/467 - https://github.com/ion-design/numi/pull/1 You can also tag @ellipsis-dev in a comment and ask it for a re-review or to answer a question about the PR. You’ll get a new review for every commit that’s pushed to the PR branch. Our docs (https://docs.ellipsis.dev/review) have more info. Today, 17 companies, including PromptLayer and Warp (W23) are using Ellipsis. We’re working on the code generation component (ex: tag Ellipsis to fix bugs), but that’s still in a public beta. Ellipsis doesn’t store or train models on your code. Ask: Try it out, it takes 2 clicks to install at https://www.ellipsis.dev. Feedback? team@ellipsis.dev

ting is here as well: https://www.ycombinator.com/companies/hyperdx/jobs/1Ja2psR-f... Come by our discord as well if you just want to talk shop: https://hyperdx.io/discord 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

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

verall doesn't seem like the right tradeoff. Imo the real concern as someone that personally owns too many tiny VM instances is resource footprint - which can be tuned down to ~1GB of memory for us (depending on server load). Feel free to open an issue too if you think there's something we can adjust there as well. [1] https://github.com/hyperdxio/hyperdx