[doctor_eval]

> Thin Events add coupling

That’s not my experience. In fact I’d say fat events add coupling because they create an invisible (from the emitter) dependency on the event body, which becomes ossified.

So I’d say the opposite: thin events reduce coupling. Sure, the receiver might call an API and that creates coupling with the API. But receivers are also free to call or not call any other API they want. What if they don’t care about the body of the object?

So I’m on team thin. Every time I’ve been tempted by the other team, I’ve regretted it. It’s also in my experience a lot more difficult to version events than it is to version APIs, so reducing their surface area also solves other problems.

[SideburnsOfDoom]

> thin events reduce coupling. Sure, the receiver might call an API and that creates coupling with the API.

You make a statement in the first sentence, and in the next sentence produce evidence ... that the statement is wrong. And, YMMV.

It is my experience that thin events add coupling. If service B receives an event, and wants to process it ASAP (i.e. near real time) and so calls back over http to Service A for the details, then

a) there is additional latency for a http call. And time variance - Even if the average latency of a http request round-trip is fine, the P99 might be bad.

b) You're asking for occasional "eventual consistency" trouble when A's state lags or has moved on ahead of the event

c) Worst of all: When service A is down or unreachable, Service B is unable to do work: Service B uptime must be <= Service A uptime. You have coupled their reliability, and if Service B is identified as mission-critical, then you have the choice of either making Service A equally critical, or decoupling them e.g. with "fat events".

I don't believe that it's accurate to say "receivers are also free to call or not call..." it's not choosing a flavor of ice-cream, you do the calls that the work at hand _needs_.

If you find that you never need to call back to service A then yes, "thin events" would suit your case better. That has not been my experience.

It's fair that event data format versioning is a lot of work with fat events - nothing is without downside. But in your case, do you have "dependency on the event body" ? All of it? If a thin event is all that you need, then you depend on a couple of ids in the event body, and not the rest. Json reading is very forgiving of added / removed fields, you can ignore the parts of a fat event that you don't care about.

[doctor_eval]

> You make a statement in the first sentence, and in the next sentence produce evidence ... that the statement is wrong.

My first sentence was quoting from the article, then I refute the article. Sorry if that wasn’t clear.

Re your point a), yes I agree in this case you’d send the contents in the body, but then I’d tend to call it stream processing rather than event processing - I admit this might seem like splitting hairs, but I do feel that there’s a difference between events and data distribution. And I personally find the data distribution pattern tends to be a lot more specialised.

Re b), it’s just an assumption that the receiver needs the version of data in the message, rather than the latest version. So I don’t think this is a strong argument for fat events.

Re c), again, it’s an assumption that the receiver needs the exact data provided in the event body; but I’ve found that, except in very simple cases, it’s very difficult to efficiently create event bodies that contain everything that all receivers are going to need. Maybe the receiver needs to collate a bunch more data, in which case the problem persists regardless of fat or thin, or maybe it just clears a local cache, in which case the problem is deferred until the data is needed and you probably have other things to worry about then anyway.

> I don't believe that it's accurate to say "receivers are also free to call or not call..." it's not choosing a flavor of ice-cream, you do the calls that the work at hand _needs_.

Sure, and the calls you make depend on the context, and if there is enough data in the event body to avoid making any calls at all. And I’m saying that in my experience that’s not generally the case. What I’ve seen is that the sender composes some event body and sends it, and the receivers end up needing to call APIs anyway.

In which case, the sender may as well have not gone to the trouble, hence my preference for thin events.

> But in your case, do you have "dependency on the event body" ? All of it?

From a maintenance perspective, the sender doesn’t know what the receivers depend on, so even if all your receivers only depend on the IDs, there is no way to find out. Because of this, it’s really easy to add fields to an event message, but really dangerous to remove them, because you can’t easily tell what receivers depend on the thing you’re removing. This is why I said that fat events create more coupling than thin events.

Of course as with most things there are always exceptions. Maybe I should have said, “I’m on team thin by default. But of course some use cases require fat messages, in which case proceed with great care”.

[SideburnsOfDoom]

I think it's a straw man to say "we couldn't eliminate all API calls, so fat events are useless" - even removing 1 dependency at a time is a win. In my experience, you generally can do this, and that was the approach taken for reliability improvement.

> it’s very difficult to efficiently create event bodies that contain everything that all receivers are going to need.

"everything that all receivers need" seems like another straw man, a "you won't get it perfect so don't try to improve". I've seen it work well enough to be worthwhile.

> From a maintenance perspective, the sender doesn’t know what the receivers depend on

At a glance, no. But it's not imponderable, assuming a limited number of in-house consumers. The absolute statement about it isn't accurate.

> it’s just an assumption that the receiver needs the version of data in the message, rather than the latest version. So I don’t think this is a strong argument for fat events.

I've seen it cause a severe and hard-to-diagnose failure, when system A lags enough, so I think it is a strong argument.

> Maybe I should have said, “I’m on team thin by default.

Sure. I'm on team "fat events" by default because it can solve more issues than it creates. If it turns out that 90% of the event gets ignored, with no issues or http call-backs, then this might be a case for thin events.

[doctor_eval]

> I think it's a straw man to say "we couldn't eliminate all API calls, so fat events are useless"

Well, yes it is a straw man, because I never said that.

> At a glance, no. But it's not imponderable, assuming a limited number of in-house consumers. The absolute statement about it isn't accurate.

That’s a pretty huge assumption. Especially when one of the advantages of pub/sub is supposed to be decoupling.

Anyway, we clearly have had different experiences, and there is no silver bullet.

[delusional]

b) You're asking for occasional "eventual consistency" trouble when A's state lags or has moved on ahead of the event

If you allow A's state to lag behind it's own events, then how are you ever going to create a sane system? Surely A either has to be ahead or at the state that caused the event to emit, or events are pointless.

[SideburnsOfDoom]

> A's state to lag behind it's own events,

Real systems don't have just 2 services. There can be 100s and the "own events" assumption may not hold.

[delusional]

Sure, but in a thin events model someone would "own" the events since otherwise the subscriber wouldn't know where to query the actual data. What would you even do with an event saying a customer changes address if querying that address then produces the old one.

I'm genuinely curious how such an architecture would work. You don't have to respond directly here, but if you have any reference to further reading, I'd appreciate it.

[SideburnsOfDoom]

> I'm genuinely curious how such an architecture would work.

Complex systems are the way that they are because they got that way over time. It is not my goal to defend or even characterise a system that I did not create.

I am here telling you the issue that I saw: one event consumer, at an edge case, ran substantially behind another, and when they attempted to co-ordinate over http, this failed. And how it was successfully resolved: fatter events removed the need for co-ordination between these two altogether. This was IMHO a more elegant design - it avoided he issues of the the thin events.

[delusional]

Ah, so A and C where both subscribed to B, but during A's processing of the event it assumed C had already processed it and tried to look up some state. Is that correctly understood?

This sounds more like an architectural deficiency (as you say probably from architectural decay) than a systematic design edge case. I can't quite understand what information A would need to get from C that could be included in the fat event but not simply queried from B.

[tremon]

If you allow A's state to lag behind it's own events

That's a mischaracterization. A's state is not lagging its emitted events; instead, A's state may have been changed at the time A's event is processed.

[SideburnsOfDoom]

The "own events" was the faulty assumption. it's not always the same service that both emits the events, and is the place to go to over http for data. It "seems logical" to also build that store from listening to events, but it can cause issues as mentioned.

[delusional]

The comment I quoted says:

> when A's state lags or has moved on ahead of the event

That sounds like it can EITHER be ahead or behind. Specifically, I do not understand it as A's state can either lag OR be ahead, not that "lags" is a synonym for "moved ahead"

[FeepingCreature]

> b) You're asking for occasional "eventual consistency" trouble when A's state lags or has moved on ahead of the event

To be noted that this is the default if B is recovering after an outage.

Personally, I consider events to be insane. "We create an immutable database so that the state of the system is always recoverable." Okay, cool, very functional programming of you. "But then to actually work with the event from the immutable database, you have to query a stateful service." ??? What? And even fat events only go so far to get you out of that. So with a stream of n events, you don't have n states that the application can be in, but n times the product of all possible states of every other service that you query. How does this help?!

[PaulRobinson]

The bit you seem to be missing is the events are the source of truth, not the databases.

Lose your database? Roll up all the events. Got a lot of them? Take snapshots and then roll up from the last trusted snapshot.

In true event sourced systems, the databases and stateful systems are artefacts that can be thrown away and rebuilt. The event log is the actual “true” database.

Once you design around that, your objections melt away.

And if you think this is some faddish trend, this is how finance has worked since the invention of book keeping and how your databases under your stateful services are working under the hood.

[FeepingCreature]

This only works if your events are in a single globally ordered stream or all your code is eventually consistent over every stream it consumes. Specifically, you cannot do the "query a service for the aggregate state" thing this article espouses for thin events, ever.

[insanitybit]

You can achieve strong eventual consistency with this system.

[paphillips]

I also disagree with the article - thin events don't always result in more coupling, and I'll add that thin events can remove temporal or state coupling as illustrated below. However, the caveat is: as with many things I think choosing one team or the other has nuance and depends on the specific scenario.

An example: I'm using thin events in a master data application integration scenario to send a 'sync this record' type of command message into a queue. The message body does not have the record details, only the basic information to uniquely identify the record. It also doesn't identify the type of change except for a flag to identify deletes. The 'sync' message is generalized to work for all entities and systems, so routing, logging, and other functions preceding the mapping and target operation have no coupling to any system or entity and can expect a fixed message format that will probably never change. Thus versioning isn't a concern.

Choosing team 'thin event' does result in an extra read of the target system, but that is a feature for this scenario and what I want to enforce. I can't assume a target system is in any particular state, and the operation to be performed will be determined from the target system at whatever point in time a message is processed, which could be more than once. If the message ended up in a dead letter queue, it can be reprocessed later without issue. If one production system's data is cloned down to a lower environment, the integrations continue to work even if the source and target environment data is mismatched. No state is stored or depended upon from either system and the design is idempotent (ignoring a target system's business rules that may constrain valid operations over time).

In contrast, other scenarios may benefit from or require a fat event. I've never used event sourcing, but as others mention, if current state can be built from all previous events 'rolled forward' or 'replayed', then each event must be a stand-alone immutable record with all information - thin events cannot be used. Or, if a scenario requires high performance we might need to use a fat event to eliminate the extra read, and then compensate for the other consequences that arise.

[avereveard]

assume the data format changes, it would change in the called api as well. as long as the fat event sends data that it's in the same format that the api would return, you'd have the same level of coupling.

I think fat vs thin is more about how much other services the event have to travel, because thin event would multiply reads by a fair factor, with the tradeoff being the performance hit for the queue system to store and ship large events

[doctor_eval]

With an API you can publish a new endpoint (/v1, /v2 etc). It’s normally reasonably easy to maintain an old API even while you add features to the new API, and the runtime penalty is minimal because clients would be expected to call just one version of the API for any given event. (You can also see who’s calling the old API and ask them to change)

But this is not true for events. If you change the body such that you now need to maintain two versions of an event, then you have to publish both events simultaneously, which means double the server side effort, storage etc for each event version. It’s pretty inefficient, and painful. You can work out who subscribes to the old event but there is still a big efficiency hit.

You might be right about many reads per event in a simplistic way; if you have a lot of clients then it could be expensive if you don’t have a server side cache. But there would typically be a lot of temporality in such a system so it seems like an easy problem to solve for most use cases; you don’t have to cache for long, but caches are of course tricky if your use case is not very simple. That said, if there is already a HTTP connection open then the additional latency and bandwidth hit cause by this events are going to be minimal in most cases, and probably drowned out entirely if you need to push multiple versions.

As I said in another thread, I should have said that thin is my default. There are cases when fat makes more sense, but normally I’d start with thin and see if I need to flesh it out. Whenever I’ve started fat I’ve ended up reverting.

[manfre]

Supporting multiple versions of an event schema is a solved problem. Apache Avro with a published schema hash in a message header is one solution.

https://avro.apache.org/

[morelisp]

This lets you identify the version but it doesn't let old clients read the new messages. (Well, for avro and others they still can if the new fields aren't important or the old fields aren't required - but if you can do that you also don't really have a new incompatible version and you don't need the schema hash to begin with.)

The point is that with a pull-based API, I have a fixed number of requests. As clients migrate from /v1 to /v2, load on /v1 goes down and /v2 goes up, and I can adjust resource allocations accordingly to keep the total requirements relatively constant. I can even reimplement /v1 in terms of /v2 internally in many cases and have ~0 operational overhead.

But for an evented system, as soon as just a single client wants v2 I need to publish that, and as long as any client wants v1 I need to publish that. So my outbound "work" (at the very least i/o but probably also DTO conversions and god help you if it's any kind of storage or business logic) is doubled immediately and remains doubled until everything is migrated.

[avereveard]

API versioning is more for external users, not internal. if your api is versioned, your events should be versioned as well tho, so we're at square one, as in, you're manufacturing a scenario where one approach is advantageous, and I agree your approach works in that scenario, but that is different than saying that one approach is advantageous at priori

[drewcoo]

Thank you. Came here to say that.

When I've seen this fat event pattern it's been because different services' responsibilities were not fully separated. And that's tight coupling. Fat events imply tight coupling.

The "thin" pattern described in the article goes like this:

1) service FOO gets an event

2) FOO then has to query BAR (and maybe BAZ and QUUX) to determine the overall state of everything to determine what to do next

And #2 means all of that is kind of "thin" is tightly coupled, too.

I've also personally seen thin events that are not the article's thin strawman.

I sometimes wonder if people understand coupling or design.