OTel isn't going well (and I made a spreadsheet about it)(matduggan.com) |
OTel isn't going well (and I made a spreadsheet about it)(matduggan.com) |
For example, if I look at a graph in monitoring dashboard and see something suspicious, I’d like to say: “The next time something like this occurs again, please save me a trace.” I should be able to just do that with a single mouse click.
I remember them releasing the tracing spec/SDKs and saying “now let’s move on to metrics/logs.” That never sat right with me.
What I’m suggesting is that your apps by default only send metrics to your monitoring system, but that the monitoring system can specifically ask to “upgrade” metrics to traces. Or to log entries.
The same thing with metric cardinality: by default, only report metrics in a fully aggregated manner. But do tell the monitoring system how they can potentially be broken up if needed (i.e., which labels to add).
1. Every major vendor is still in some weird alpha/beta support for OTel even after all this time.
2. The performance hit is substantial and makes you question what the point of performance instrumentation is if you need twice as much compute/RAM to run the same workload now.
3. Serverless runtimes pay a heavy penalty for cold starts with OTel.
4. You're basically forced to run both gateway collectors and edge collectors for any realistic usage.
5. You still need to configure destination exporters in unique ways. This leaves you questioning what the value of OTel was.
6. Vendors that go beyond the scope of what OTel covers still need their own bespoke instrumentation. What was the point of any of this then?
You most certainly don't. You can run your app (especially if it's "serverless") without the collector agent.
App-to-agent and agent-to-sink use the same protocol, so all you need to do is set up the tracing/logging/metrics exporters to directly speak with the sink. These days, it typically means specifying the URL and the DSN header.
It's missing a few things that I'd like, but I was able to implement them myself. I guess the major design issue is that the sampling decision is made at the _start_ of the segment. So I hacked up a few improvements:
1. Ability to mark segments as "boring", so they are dropped before the export. For things like healthchecks, empty "get the pending jobs" queries, etc.
2. Ability to downgrade errors for segments that are expected to return an error (e.g. HEAD on a non-existing object in S3 to check if there's a cached blob).
I understand the author's perspective in the linked article, but none of that data shows a project in trouble? Some languages have more resources than others, but those all look like healthy open source projects
At least with Open Telemetry, anyone can write an OTLP "source" using free, open specifications, and it'll "just work" with dozens of third-party "sinks". That's huge!
Sure, there's a lot of experimental tags on semantic conventions, but at the end of the day, that's not that critical. It's just data: most sinks don't "interpret" these tags, they just display them as-is, so changes aren't breaking changes.
Neither Prometheus metrics nor Jaeger traces are magic bullets. Neither of them are complicated, either, and in fact the fact that they're not complicated is their greatest strength. You can and should understand every facet of what they entail. You should build the (very small) shims that they need for your company's framework every time. It's not hard. It's not hard because it's not complicated. The fact that it's not complicated seems to break people's brains. They are accurate because they're simple and they're easy to work with because they're simple, and OTel is neither.
Node exporter runs on my Prometheus server next to Blackbox Exporter. Blackbox Exporter handles TLS expiry metrics.
Jaeger uses the OTLP protocol nowadays. So it _is_ OTEL.
1. The worst thing you can do is try to stuff too many things into one specification. So you want an API? That's great. What's that? You want a rigid set of types so that any tiny changes over time aren't compatible? You want to try to define every conceivable use case as a new call? You want to combine multiple elements from different domains into one flat set of functions? You don't have any hierarchy or inheritance? You don't support extensions?
2. The second-worst thing you can do is to force a whole lot of different people to go through a single standards body. So you want to support a thousand different 3rd party components. What's that? You want to require everyone get their adapter approved by one group? And there's only one supported adapter per 3rd party component?
If you're trying to feed an entire city, it's logistically incredibly difficult to try to do it all yourself. If instead you just define where food can be dropped off or picked up, and ask volunteers to bring their own food there whenever they can/want, now you don't have a logistical nightmare on your hands anymore. The tech alternative? Add support for "plugins", make the plugin interface incredibly loose/backwards-compatible/layered, and invite people to publish their own plugins. If you under-engineer it, it actually works better.
How does the monitoring system have any of the context to add labels? That would only exist in application memory.
Grafana went the other way - your app exports all labels, and then you selectively aggregate on ingest: https://grafana.com/docs/grafana-cloud/observe-and-act/adapt...
> That may be prohibitively expensive in terms of CPU/network load.
In practice I've not experienced this even on quite high request rates. While it isn't free, exporting everything has been cheap enough that the real cost in dollars spent is basically marginal (it's _storing_ the data that's expensive)
Indeed. If you have a protocol that doesn’t allow exposing that kind of information, then that only lives in application memory. But my suggestion is that it’s exposed.