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Comment by marginalia_nu | Hacker News Reader

> Whatever service you are using for logging, it costs money, and a fast way to burn money is to log the entire json object that was relatively small on your dev env, but blew up on production.

You could also, you know, run your own infrastructure and log to your heart's content.

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There are still going to be time and effort costs involved in scaling that infrastructure as your log volume increases

You have to output a lot of logs before you fill up even a single large consumer-grade hard drive, especially given logs are typically compressed when rotated.

It's usually only when you involve ELK or something like that your logs start to get big. Which in turn is typically necessitated by over-complicated distributed software design.

If you're at the scale where this actually matters and you're serving millions or requests per second from a worldwide user-base, then affording storage for the logs really shouldn't be a problem anymore (idk, with the possible exception of Twitter)

> You have to output a lot of logs before you fill up even a single large consumer-grade hard drive, especially given logs are typically compressed when rotated.

This is a good point - a RAID array of a few HDDs/SSDs scales surprisingly far and is cheaper than many of the cloud services out there, though whether you can or can't use either approach probably relies on compliance requirements and such.

I will definitely add that logs can compress really well - to the point where it's been close to a year since I added Logrotate to a project that didn't have it before, for a pretty basic setup, and I haven't had the need to even look at how many archives are currently retained, given that the disk usage has changed very slightly. And that's for multiple systems that filled up the available storage in months previously.

Of course, my personal gripe is that most of the logging solutions out there are rather complex - something like Graylog feels like one of the simpler self-hostable options while still being fully featured, but in my experience anything that runs ES is really resource hungry. Sometimes it feels like MariaDB/PostgreSQL would be good enough for most of the simpler low logging volume setups out there - if you don't want to manage logs as files, want to ship them somewhere, but don't want the receiving system to be too complex either.

Except you know when you.actually want to do something valuable with all those logs. You _should_ be creating logs (signals) to be valuable in some way (diagnostics, alerting, canaries statistics), etc. If you're just dumping logs into opaque blobs that are never looked at them sure write them to blobs to your heart's content and have fun hunting and pecking for reasons you're users are already screaming at you. That strategy is fine, but the limitations are clear. It's reactive.

Depends entirely on what and why you are logging.

Is it audit logs for security or due to some regulatory requirement? Then huge blobs are fine. Desirable, even.

Transaction logs for machine-loading so you're able to replay an application's state at any given moment in time? Yeah probably gonna end up with huge blobs again.

And what are you going to do when you need a human to read sixteen trillion bytes of compressed logs streamed off a single SATA disk?

Once you face the fact that the performance of a single SATA disk means you can't search the logs in any quick time, and nobody can possibly read that much log data, so nobody will use it, you start to see it as a hoarding disorder not a useful tool.

It's not unheard of to need to retain years even decades worth of logs due to regulatory compliance. Nobody is reading them, they just need to exist. In that scenario you'll probably keep the current year or so fresh on a mechanical drive and past years on tape.

You know that costs money, right?

Not as much as you'd think, and critically, the cost is largely disconnected from how you use the infra.

If your infra is not on-prem, yes it will cost you more money as you are generating more and more and bigger logs.

You actually have to log a damn lot to actually fill up even a single 16 Tb drive with gzip-compressed logs which typically have something like 50x compression for log data.

On top of that, mechanical hard drives are pretty cheap these days. Like it's a dozen dollars per terabyte, if not less.

I don't know, you're either producing just absurd amounts of logs, on the order of a hundred gigabytes a day plain text, at which sure, I guess you could probably log a bit less. Either that or you're operating at a scale with many millions of users where you should have income and be able to afford it.

... well, either that, or you're being fleeced.

> You actually have to log a damn lot to actually fill up even a single 16 Tb drive with gzip-compressed logs which typically have something like 50x compression for log data.

Now count that for queryable data source so running a database of some sort (Elasticsearch probably for logs) 24/7 at fast enough speeds that it is ops-useful

Metrics are significantly cheaper tho, at least if you use some dedicated TSDB with good storage engine like Victoriametrics or influxdb.

VictoriaMetrics author here. I'm working on VictoriaLogs right now, e.g. the logging system on top of VictoriaMetrics architecture ideas. Preliminary results are promising:

- It will need much lower amounts of disk space, disk IO, CPU and RAM comparing to ElasticSearch during data ingestion.

- It will provide fast logs' querying and tailing via easy-to-use query language (LogsQL), with the ability to calculate advanced stats over the selected logs.

- It will accept data in ElasticSearch format, so existing Filebeat and Logstash setups can be switched from ElasticSearch to VictoriaLogs in a few seconds.

Any thoughts about OpenTelemetry ? That covers both logs, tracing and metrics

> You actually have to log a damn lot to actually fill up even a single 16 Tb drive with gzip-compressed logs which typically have something like 50x compression for log data.

If you cannot search quickly in the logs, at least the "hot" ones (i.e. most recent) they don't make too much sense. Well, they still make sense but for other reasons, but you lose many interesting feature of logs. At $DAYJOB we *surely* needs to trim and shave a lot the logs apps are sending to the centralized ELK - which is one of the points of TFA - but we cannot just gzip the text files and be done, we need to be able to search for patterns anbd data in the logs to understand what the app is doing in certain cases (besides having metrics).

P.S. We also store them as gzipped files in an S3 bucket using warm/cold tiers, and it is certainly cheaper than using even magnetic disks.

When people complain about the cost of excessive logging, they are almost certainly not thinking in terms of how much a drive costs.

Services like CloudWatch are an excellent way to burn through money, though it's usually the time series storage and ingestion costs that balloon out of control.

Well, also the kind of people who worry about this are not thinking in terms of "a terabyte", like GP. It's always easy to give advice when your experience has been at a toy level.

That's unnecessarily dismissive. Handling many (or dozens, hundreds) TB worth of logs is anything but "toy level", that's more than the vast majority of businesses will generate in a decade, maybe even their lifetime.

And marginalia_nu, the GP I was referring to, was unnecessarily strident, concluding that others must be naïve or incompetent if they had to handle logs with "ELK or something like that" and that therefore one must have an "over-complicated distributed software design."

Don't move the goalposts to hundreds of TB--this user is giving advice to everyone based on a perspective that you're doing something wrong if all of your logs don't fit on a single hard drive; that you should "log less" if you have the "absurd" quantity of "hundreds of gigabytes" a day of logs, and who seems to think individual hard drive costs is an important driver of the cost of managing logs. Their words, not mine.

There's nothing interesting to be gained from hot takes based on naïve conceptions and lack of experience. Pointing out that giving overly-general advice based on your inexperienced best guesses and the NewEgg price list is not very useful is not "unnecessarily dismissive."

And if you're in a position where you have to manage petabytes+ of logs using on-prem hardware, SSDs are probably a small part of your overall budget!

Also true, though it's not zero. The different cost drivers/cost model between using SaaS and on-prem infrastructure for logs are interesting and drive different decisions. I have done both in large and small environments and I kind of like the SaaS model because it is easier to put cost incentives on product owners and development teams, which is who should own the P&L. On other words, if you pay $1/GB or whatever, you can get back money by logging fewer GBs. It naturally discourages "log whatever into a giant undifferentiated bucket 'in case you need it'".

You can pay less for equivalent on-prem infrastructure but it drives costs quite differently. For example, it tends to be hard to refresh that infrastructure because it doesn't make you money, so it gets worse over time. The unit cost of storage is very low, often because you make availability/durability tradeoffs that aren't even available to you from the SaaS provider or cloud service. But you will find that the Opex associated with it can be either quite high or poor, and this is hard to reflect in terms of investment by P&L owners.

You can do either approach well or poorly. The way SaaS sucks when doing it poorly is mostly that you are paying a huge amount of money. The way on-prem sucks when doing it poorly is much more complicated and is reflected by toil and tech debt across an organization (which is money but harder to tie to what would fix it), poor visibility, lack of insights, and possibly spending too much in Opex or licenses, depending on the technology. The cost of having a bunch of people do on-prem logging "right" is hard to justify, even for these "large organizations" where I guess, people think, money is free. And even if you've correctly identified and wish to fund the cost of delivering the infrastructure (which as you point out has hardware as only part of its cost), it's not like you can necessarily find the five quality engineers to run the thing. And if you could--do you really want these FTEs working on logging infrastructure or do you want them delivering revenue features?

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