I did not see any point to listing out the cons as others have already done it a bunch of times. I was trying to focus on what moving to a monorepo solved for us (which was optics and poor ux).
The linked article talks about identification numbers that can be used to link a person. I am not a lawyer but the article specifically refers to one person.
By that logic, if the hash you generate cannot be linked to exactly one, specific person/request - you’re in the clear. I think ;)
> ‘personal data’ means any information relating to an identified or identifiable natural person (‘data subject’); an identifiable natural person is one who can be identified, directly or indirectly, in particular by reference to an identifier such as a name, an identification number, location data, an online identifier or to one or more factors specific to the physical, physiological, genetic, mental, economic, cultural or social identity of that natural person;
Re: docs - oops. We were frantically putting stuff together and linking before the docs were in that location - the link is supposed to be https://docs.streamdal.com/en/core-components/sdk/ . Fixed it in the readme.
re: libs vs sdk - we named it that in anticipation of exactly having to do some funky stuff. As it stands, we are already doing grpc, Protobuf, wasm and having it all interop across all languages is not easy - so having to introduce some sort of a “helper” binding/lib is not at all unlikely.
Besides that, the “tail” part is really a small part of the functionality - the overall idea is that the sdk/lib has access to most/all I/O of the app and is able to interact with the payload that the caller provides before it is sent on its way.
Traditional pipes aren’t really in the equation.
We went with calling it “tail” because it’s easier to explain instead of “it’s a lib that an app owner can wrap their i/o calls with to enable calling dynamic wasm”… and that’s still not the whole thing haha
Hmm good idea about the spark integration - integration is possible with basically anything that you’ve got code-level access to. I don’t know about messaging though - runtime data transformations for spark? I guess data folks would have no problem with that hmmm.
And re: emojis - we’ll tone it down - we were all working hard on docs late into the night and may have gotten a little wild with emojis haha :)
This is solid - thank you very much. We will do some more research but basically sounds like - go as low as possible, as long as the underlying libs support it.
And re: kotlin - I last worked/played with it in 2016 and recall that it was MUCH nicer to work in compared to Java.
I just did a quick cursory look and it seems like Kotlin only has slightly slower builds compared to Java and rest of perf is basically the same due to generating similar bytecode. Neat!
I know you kid - but the _data_ in this context is the data that the app is processing at runtime. Ie. If the app is reading from a DB - that’s what we are tailing.
I wonder if we screwed up by calling out “tail” - it is so much more then that - it executes wasm rules on the client that are pushed to it by the server AND because we have access to the data - we can expose a UI to see it flowing… like a “tail -f” - but that doesn’t quite flow off the tongue :)
I’d urge you to check out the live demo and “tail” an app at runtime - it might be able to explain what we we are doing better than I can.
And yep, you’re right - we are using protobuf to have a common schema between all SDKs, the server and UI.
Re: sdk implementation - it’s basically implementing grpc methods, knowing how to exec wasm and doing a couple of extra things at instantiation. In real terms - it took us about a week to implement the python SDK - that’s with learning how to do wasm, Protobuf and grpc in python + 1 week afterwards to iron out edge cases.
Re: Java - that was going to be the next sdk we do but we have no idea if it needs to be a specific Java version? Should we target lowest possible Java version? We need to have a solid wasm runtime support - so maybe that limits us to newer versions of Java. Is that a problem?
I did Java a looong time ago - so need some outside input at this point haha
Good news then :) Everything stays on your network. Actually, in most situations - everything stays completely client-side. Because the rules that the client executes are Wasm modules, all data inspections and transformations occur in the client itself.
There is a server component (that you host) - but it is only used for pushing rules/Wasm down to the SDKs and for facilitating tail - that's it.
Can you elaborate on the Sun comparison? I am a huge fan of Sun and what they did for computing at large - designing hardware, creating specs, their contributions to evolving unix and so on. I'm not sure how Oxide compares. Unless you're talking about "in the spirit of Sun".
What a great idea. He was part of the hacker subculture - regardless of what your opinion of him or his abilities is. This made me think of the takedown.com telnet transcripts - what a blast from the past.
Really sad day, RIP - will definitely have a drink for him tonight.
If you have a gRPC service, you'd use `grpcurl`. This one is for RESTish HTTP 1 API's where the req/resp body is protobuf - something that `grpcurl` can't handle. In other words, you'd use this if your API uses traditional HTTP methods and responds with binary encoded protobuf blobs. I would imagine this is extremely niche.
The "reimplementing" part resonates with me 100%. I've also reimplemented this solution many times and every time it has been a pain in the ass.
I built https://batch.sh specifically to address this - not having to reinvent the wheel for storage, search and replay.
For some cases, storing your events in a pg database is probably good enough - but if you're planning on storing billions of complex records AND fetching a particular group of them every now and then - it'll get rough and you need a more sophisticated storage system.
What storage mechanism did you use? And how did you choose which events to replay?
^ 100% this. Do not delete events. They are your source of truth - you shouldn't really even modify them but stripping out PII is "alright".
Re 24M+ records: create a batch runner that goes through "jobs" to perform stripping/cleaning tasks. To store state (and to organize cleaners), use a distributed store such as etcd - that way you can bookmark where you were at in the cleaning process.
Hi there, I started a company specifically centered around event sourcing - it's a saas platform for capturing all of your events, gaining the ability to granularly search them and then replay them to whatever destination.
I'd be happy to walk you through the platform - there's no lock-in, since we don't require the use of any SDK's, just run an event-relaying container which will pipe all of your events to our stores.
One big piece is that our platform is message bus agnostic meaning, we are able to hook into any message bus, be it kafka, rabbit, nats, etc.; same goes for replays - we can replay into any destination.
The relayer is open source - https://github.com/batchcorp/plumber - if anything, the relayer can also be used for working with message busses which could improve your dev workflow for reading/writing messages, etc.
I'm late to this party but I'll chime in anyway - I love event sourcing. So much so that I actually built a company around it (and got into YC S20) - https://batch.sh
Event sourcing is not easy but the benefits are huge - not only from a software architecture perspective but from a systems perspective - you gain a whole lot of additional platform reliability.
There are roughly 3 pillars to event sourcing that have to be built (most of the time) from scratch - storing events (forever), reading stored events, replaying stored events.
Those are the 3 things I've built at several companies and it is always a huge barrier to someone taking up the pattern. Of course there are more things under the hood, but those are foundational pieces that will make the whole experience much better.
Would love to chat with folks who want to nerd out over this stuff :-)
I did not see any point to listing out the cons as others have already done it a bunch of times. I was trying to focus on what moving to a monorepo solved for us (which was optics and poor ux).