Wandering Thoughts archives


The problem of paying too much attention to our dashboards

On Mastodon, I said:

Our Grafana dashboards are quite shiny, at least to me (since I built them), but I really should start resisting the compulsive urge to take a look at them all the time just to see what's going on and look at the pretty zigzagging lines.

I have a bad habit of looking at shiny things that I've put together, and dashboards are extremely shiny (even if some of them are almost all text). There are two problems with this, the obvious and the somewhat subtle.

The obvious problem is that, well, I'm spending my time staring somewhat mindlessly at pretty pictures. It's interesting to look at lines wiggle around or collections of numbers, but it's generally not informative. It's especially not informative for our systems because our systems spend almost all of their time working fine, which means that there is no actual relevant information to be had from all of these dashboards. In terms of what I spend (some) time on, I would be better off if we had one dashboard with one box that said 'all is fine'.

This is a general issue with dashboards for healthy environments; if things are fine, your dashboards are probably telling you nothing or at least nothing that is of general interest and importance.

(Your dashboards may be telling you details and at some point you may want access to those details, like how many email messages you typically have in your mailer queues, but they are not generally important.)

The more subtle problem is the general problem of metrics, which is a variant of Goodhart's law. Once you have a metric and you pay attention to the metric, you start to focus on the metric. If you have a dashboard of metrics, it's natural to pay attention to the metrics and to exceptions in the metrics, whether or they actually matter. It may or may not matter that a machine has an unusually high load average, but if it's visible, you're probably going to focus on it and maybe dig into it. Perhaps there is a problem, but often there isn't, especially if you're surfacing a lot of things on your dashboards because they could be useful.

(One of the things behind this is that all measures have some amount of noise and natural variation, but as human beings we have a very strong drive to uncover patterns and meaning in what we see. If you think you see some exceptional pattern, it may or may not be real but you can easily spend a bunch of time trying to find out and testing theories.)

My overall conclusion from my own experiences with our new dashboards and metrics system is that if you have good alerts, you (or at least I) would be better off only looking at dashboards if there is some indications that there are actual problems, or if you have specific questions you'd like to answer. In practice, trawling for 'is there anything interesting' in our dashboards is a great way to spend some time and divert myself down any number of alleyways, most of them not useful ones.

(In a way the worst times are the times when looking at our dashboards actually is useful, because that just encourages me to do it more.)

PS: This is not the first time I've seen the effects of something like this; I wrote about an earlier occasion way back in Metrics considered dangerous.

DashboardAttentionProblem written at 23:15:38; Add Comment


Understanding how to pull in labels from other metrics in Prometheus

Brian Brazil recently wrote Analyse a metric by kernel version, where he shows how to analyze a particular metric in a new way by, essentially, adding a label from another metric to the metric, in this case the kernel version. His example is a neat trick, but it's also reasonably tricky to understand how it works, so today I'm going to break it down (partly so that I can remember this in six months or a year from now, when my PromQL knowledge has inevitably rusted).

The query example is:

avg without (instance)(
  * on(instance) group_left(release)

The simple version of what's happening here is that because node_uname_info's value is always 1, we're using '*' as a do-nothing arithmetic operator so we can essentially do a join between node_sockstat_TCP_tw and node_uname_info to grab a label from the latter. We have to go to these lengths because PromQL does not have an explicit 'just do a join' operator that can be used with group_left.

There are several things in here. Let's start with the basic one, which is the '* on(instance)' portion. This is one to one vector matching with a restriction on what label is being used to match up pairs of entries; we're implicitly restricting the multiplication to pairs of entries with matching 'instance' labels. Normally 'instance' will be the same for all metrics scraped from a single host's node_exporter, so it makes a good label for finding the node_uname_info metric that corresponds to a particular host's node_sockstat_TCP_tw metric.

(We have to use 'on (...)' because not all labels match. After all, we're pulling in the 'release' label from the node_uname_info metric; if it was already available as a label on node_sockstat_TCP_tw, we wouldn't need to do this work at all.)

Next is the group_left, which is being used here for its side effect of incorporating the 'release' label from node_uname_info in the label set of the results. I wrote about the basics of group_left's operation in Using group_* vector matching for database lookups, where I used group_left basically as a database join between a disk space usage metric and an alert level metric that also carried an additional label we wanted to include for who should get alerted. Brian Brazil's overall query here is similar to my case, except that here we don't care about the value that the node_uname_info metric has; we are only interested in its 'release' label.

In an ideal world, we could express this directly in PromQL to say 'match between these two metrics based on instance and then copy over the release label from the secondary one'. In this world, unfortunately group_left and group_right have the limitation that they can only be used with arithmetic and comparison operators. In my earlier entry this wasn't a problem because we already wanted to compare the values of the two metrics, Here, we don't care about the value of node_uname_info at all. Since we need an arithmetic or comparison operator in order to use group_left and we want to ignore the value of node_uname_info, we need an operator that will leave node_sockstat_TCP_tw's value unchanged. Because the value of node_uname_info is always 1, we can simply use '*', as multiplying by one will do nothing here.

(In theory we could instead use a comparison operator, which would naturally leave node_sockstat_TCP_tw's value unchanged (more or less cf). However, in practice it's often tricky to find a comparison operator that will always be true. You might not have any sockets in TIME_WAIT so a '>=' could be false here, for example. Using an arithmetic operator that will have no effect is simpler.)

The case of a secondary metric that's always 1 is the easy case, as we've seen. What about a secondary metric with a label you want that isn't necessarily always 1, and in fact may have an arbitrary value? Fortunately, Brian Brazil has provided the answer to that too. The simple but clever trick is to multiply the metric by zero and then add it:

+ on(instance) group_left(release)
  (node_uname_info * 0)

This works with arbitrary values; multiplying by zero turns the value for the right side to 0, and then adding 0 has no effect on node_sockstat_TCP_tw's value.

As a side note, this illustrates a good reason to have '1' be the value of any metric that exists to publish its labels, as is the case for node_uname_info or metrics that publish, say, the version of your program. The value these metrics have is arbitrary in one sense, but '1' is both conventional and convenient.

PrometheusPullingInLabels written at 22:16:32; Add Comment


My new favorite tool for looking at TLS things is certigo

For a long time I've used the OpenSSL command line tools to do things like looking at certificates and chasing certificate chains (although OpenSSL is no longer what you want to use to make self-signed certificates). This works, and is in many ways the canonical and most complete way to do this sort of stuff, but if you've ever used the openssl command and its many sub-options you know that it's kind of a pain in the rear. As a result of this, for some years now I've been using Square's certigo command instead.

Certigo has two main uses. My most common case is to connect to some TLS-using service to see what its active certificate and certificate chain is (and try to verify it), as well as some TLS connection details:

$ certigo connect www.cs.toronto.edu:https
** TLS Connection **
Version: TLS 1.2
Cipher Suite: ECDHE_RSA key exchange, AES_128_GCM_SHA256 cipher

Valid: 2018-04-17 00:00 UTC to 2020-04-16 23:59 UTC

Certigo will attempt to verify the certificate's OCSP status, but some OCSP verifiers seem to dislike its queries. In particular, I've never seen it succeed with Let's Encrypt certificates; it appears to always report 'ocsp: error from server: unauthorized'.

(Some digging suggest that Certigo is getting this 'unauthorized' response when it queries the OCSP status of the intermediate Let's Encrypt certificate.)

Certigo can connect to things that need STARTTLS using a variety of protocols, including SMTP but unfortunately not (yet) IMAP. For example:

$ certigo connect -t smtp smtp.cs.toronto.edu:smtp

(Fortunately IMAP servers usually also listen on imaps, port 993, which is TLS from the start.)

My other and less frequent use of Certigo is to dump the details of a particular certificate that I have sitting around on disk, with 'certigo dump ...'. If you're dumping a certificate that's in anything except PEM format, you may have to tell Certigo what format it's in.

Certigo also has a 'certigo verify' operation that will attempt to verify a certificate chain that you provide it (against a particular host name). I don't find myself using this very much, because it's not necessarily representative of what either browsers or other sorts of clients are going to do (partly because it uses your local OS's root certificate store, which is not necessarily anything like what other programs will use). Generally if I want to see a client-based view of how a HTTPS server's certificate chain looks, I turn to the SSL server test from Qualys SSL Labs.

All Certigo sub-commands take a '-v' argument to make them report more detailed things. Their normal output is relatively minimal, although not completely so.

Certigo is written in Go and uses Go's standard libraries for TLS, which means that it's limited to the TLS ciphers that Go supports. As a result I tend to not pay too much attention to the initial connection report unless it claims something pretty unusual.

(It also turns out that you can get internal errors in Certigo if you compile it with the very latest development version of Go, which may have added TLS ciphers that Certigo doesn't yet have names for. The moral here is likely that if you compile anything with bleeding edge, not yet released Go versions, you get to keep both pieces if something breaks.)

InspectingTLSWithCertigo written at 22:53:21; Add Comment


What we'll want in a new Let's Encrypt client

Over on Twitter, I said:

It looks like we're going to need a new Let's Encrypt client to replace acmetool (which we love); acmetool uses the v1 API and seems to no longer be actively developed, and the v1 API runs into problems in November: <link: End of Life Plan for ACMEv1>

(There is an unfinished ACMEv2 branch of acmetool, but, and also. It would be ideal if the community stepped forward to continue acmetool development, but sadly I don't see signs of that happening so far and I can't help with such work myself.)

November is when Let's Encrypt will turn off new account registrations through ACMEv1, which is a problem for us because we don't normally re-use Let's Encrypt accounts (for good reasons, and because it's easier). So in November, we would stop being able to install acmetool on new machines without changing our procedures to deliberately reuse accounts. Since doing so would only prolong things, we should get a new client instead. As it happens, we would like something that is as close to acmetool as possible, because acmetool is basically how we want to handle things.

Rather than try to write a lot of words about why we like acmetool so much (with our custom configuration file), I think it's simpler to demonstrate it by showing you the typical install steps for a machine:

apt-get install acmetool
mkdir /var/lib/acme/conf
cp <master>/responses /var/lib/acme/conf/
acmetool quickstart

acmetool want NAME1 ALIAS2 ...

(Alternately, we copy /var/lib/acme from the live version of the server. We may do both, using 'acmetool want' during testing and then overwriting it with the official version when we go to production.)

After this sequence, we have a new Let's Encrypt account, a cron job that automatically renews certificates at some random time of the day when they are 30 days (or less) from expiry, and a whole set of certificates, intermediate chains, and keys accessible through /var/lib/acme/live/<NAME1>/ and so on, with appropriate useful permissions (keys are root only normally, but everything else is generally readable). When a certificate is renewed, acmetool will reload or restart any potentially certificate-using service that is active on the machine. If we want to add additional certificates for different names, that's another 'acmetool want NAME2' (and then the existing cron job automatically renews them). All of this works on machines that aren't running a web server as well as machines that are running a properly configured one (and these days the Ubuntu 18.04 acmetool package sets that up for Apache).

(We consider it a strong feature that acmetool doesn't otherwise attempt to modify the configurations of other programs to improve their ability to automatically do things with Let's Encrypt certificates.)

Acmetool accomplishes this with a certain amount of magic. Not only does it keep track of state (including what names you want certificates for, even if you haven't been able to get them yet), but it also has some post-issuance hook scripts that do that magic reloading. The reloading is blind (if you're running Apache, it gets restarted whether or not it's using TLS or acmetool's certificates), but this hasn't been a problem for us and it sure is convenient.

We can probably duplicate a lot of this by using scripts on top of some other client, such as lego. But I would like us to not need a collection of home-grown scripts (and likely data files) to mimic the simplicity of operation that acmetool provides. Possibly we should explore Certbot, the more or less officially supported client, despite my long-ago previous experiences with it as a heavyweight, complex, and opinionated piece of software that wanted to worm its way into your systems. Certbot seems like it supports all of what we need and can probably be made to cooperate, and it has a very high chance of continuing to be supported in the future.

(A lot of people like minimal Let's Encrypt clients that leave you to do much of the surrounding work yourself. We don't, partly because such additional work adds many more steps to install instructions and opens the door to accidents like getting a certificate but forgetting to add a cron job that renews it.)

(My only experimentation with Certbot were so long ago that it wasn't called 'certbot' yet. I'm sure that a lot has changed since then, and that may well include the project's focus. At the time I remember feeling that the project was very focused on people who were entirely new to TLS certificates and needed a great deal of hand-holding and magic automation, even if that meant Certbot modifying their system in all sorts of nominally helpful ways.)

LetsEncryptClientWants written at 22:30:52; Add Comment


Some implications of using offset instead of delta() in Prometheus

I previously wrote about how delta() can be inferior to subtraction with offset, because delta() has to load the entire range of metric points and offset doesn't. In light of the issue I ran into recently with stale metrics and range queries, there turn out to be some implications and complexities of using offset in place of delta(), even if it lets you make queries that you couldn't otherwise do.

Let's start with the basics, which is that 'delta(mymetric[30d])' can theoretically be replaced with 'mymetric - mymetric offset 30d' to get the same result with far fewer metric points having to be loaded by Prometheus. This is an important issue for us, because we have some high-cardinality metrics that it turns out we want to query over long time scales like 30 or 90 days.

The first issue with the offset replacement is what happens when a particular set of labels for the metric didn't exist 30 days ago. Just like PromQL boolean operators (cf), PromQL math operators on vectors are filters, so you'll ignore all current metric points for mymetric that didn't exist 30 days ago. The fix for this is the inverse of ignoring stale metrics:

(mymetric - mymetric offset 30d) or mymetric

Here, if mymetric didn't exist 30 days ago we implicitly take its starting value as 0 and just consider the delta to be the current value of mymetric. Under some circumstances you may want a different delta value for 'new' metrics, which will require a different computation.

The inverse of the situation is metric labels that existed 30 days ago but don't exist now. As we saw in an earlier entry, the range query in the delta() version will include those metrics, so they will flow through to the delta() calculation and be included in your final result set. Although the delta() documentation sort of claims otherwise, the actual code implementing delta() reasonably doesn't currently extrapolate samples that start and end significantly far away from the full time range, so the delta() result will probably be just the change over the time series points available. In some cases this will go to zero, but in others it will be uninteresting and you would rather pretend that the time series is now 0. Unfortunately, as far as I know there's no good way to do that.

If you only care about time series (ie label sets) that existed at the start of the time period, I think you can extend the previous case to:

((mymetric - mymetric offset 30d) or mymetric)
    or -(mymetric offset 30d)

(As before, this assumes that a time series that disappears is implicitly going to zero.)

If you care about time series that existed in the middle of the time range but not at either the beginning or the end, I think you're out of luck. The only way to sweep those up is a range query and using delta(), which runs the risk of a 'too many metric points loaded' error.

Unfortunately all of this is increasingly verbose, especially if you're using label matches restricting mymetric to only some values (because then you need to propagate these label restrictions into at least the or clauses). It's a pity that PromQL doesn't have any function to do this for us.

I also have to modify something I said in my first entry on offset and delta(). Given all of these issues with appearing and disappearing time series, it's clear that optimizing delta() to not require the entire range is not as simple as it looks. It would probably require some deep hooks into the storage engine to say 'we don't need all the points, just the start and the end points and their timestamps', and that stuff would only be useful for gauges (since counters already have to load the entire range set and sweep over it looking for counter resets).

In our current usage we care more about how the current metrics got there than what the situation was in the past; we are essentially looking backward to ask what disk space usage grew or shrank. If some past usage went to zero and disappeared, it's okay to exclude it entirely. There are some potentially tricky cases that might cause me to rethink that someday, but for now I'm going to use the shorter version that only has one or, partly because Grafana makes it a relatively large pain to write complicated PromQL queries.

PrometheusDeltaVsOffsetII written at 00:45:45; Add Comment

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