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Add support for pulling metrics from prometheus #3317

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merged 5 commits into from May 3, 2017

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@aerostitch
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aerostitch commented Apr 25, 2017

What does this PR do?

Adds the necessary helpers to be able to easily build the prometheus integration.
You provide a dictionary which has the prometheus metric as key and the name of the corresponding dd metric as value.
Only the metrics listed in this dictionary will be pushed to datadog.

Note that the prometheus' histogram metrics have a specific behavior with the notion of buckets, so for each bucket I add them with a tag which is the upper_bound. Of course, this part is optional and can be disabled.

Motivation

I need to pull data that has been pushed to prometheus by 3rd party applications and don't want to reinvent the wheel.
Plus, it seems I'm not the only one who wish to see it happening (#3119, #3254)

Additional Notes

I need to add more tests (planning to add those tomorrow) but I wanted a 1st feedback on the proposed modifications.

Once that would be integrated, the integration check.py could be as easy as:

# (C) Datadog, Inc. 2010-2017
# All rights reserved
# Licensed under Simplified BSD License (see LICENSE)
from checks import CheckException
from checks.prometheus_check import PrometheusCheck

EVENT_TYPE = SOURCE_TYPE_NAME = 'kubedns'

class KubeDNSCheck(PrometheusCheck):
    """
    Collect kube dns metrics from Prometheus
    """
    def __init__(self, name, init_config, agentConfig, instances=None):
        super(PrometheusDNSCheck, self).__init__(name, init_config, agentConfig, instances)
        self.client = PrometheusCheck(self)
        self.client.NAMESPACE='kubedns'

        self.client.metrics_mapper = {
            'skydns_skydns_dns_response_size_bytes': 'dns.response_size.bytes',
            'skydns_skydns_dns_request_duration_seconds': 'dns.request_duration.seconds',
            'skydns_skydns_dns_request_count_total': 'dns.request_count.total',
            'skydns_skydns_dns_error_count_total': 'dns.error_count.total',
            'skydns_skydns_dns_cachemiss_count_total': 'dns.cachemiss_count.total',
        }


    def check(self, instance):
        endpoint = 'http://localhost:10055/metrics'
        if endpoint is None:
            raise CheckException("Unable to find prometheus_endpoint in config file.")

        send_buckets = instance.get('send_histograms_buckets')
        if send_buckets is None:
            raise CheckException("Unable to find send_histograms_buckets in config file.")

        self.client.process(endpoint, send_histograms_buckets=send_buckets, instance=instance)

Of course, after that we could rewrite the kubernetes-state-metrics integration to use this.

@hkaj I see that you've been working on several PR around prometheus. What do you think about this idea?

Thanks
Joseph

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hkaj commented Apr 25, 2017

Hi @aerostitch
Thanks for the contrib! I actually have a branch with some work regarding this feature but didn't have time to complete it yet 9be9af8

Looks like your PR implements a similar approach, I'll review it shortly.
Thanks again!

@hkaj hkaj self-requested a review Apr 25, 2017

@hkaj hkaj added this to the Triage milestone Apr 25, 2017

# send_histograms_buckets is used to specify if yes or no you want to send the buckets as tagged values when dealing with histograms.
self.send_histograms_buckets = True
# endpoint is the metrics endpoint to use to poll metrics from Prometheus
self.endpoint = 'http://localhost:10055/metrics'

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hkaj Apr 25, 2017

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This needs to come from the check config, not sure a default value makes sense. It could actually pick up the wrong endpoint if several prometheus endpoints are local. Could you make it a parameter of process?

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aerostitch Apr 25, 2017

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Sure, I was thinking about overwriting it like that in the check method:

        endpoint = instance.get('prometheus_endpoint')
        if endpoint is None:
            raise CheckException("Unable to find prometheus_endpoint in config file.")
        self.processor.endpoint = endpoint

But having it as a parameter should do it. :)

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aerostitch Apr 25, 2017

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Note for self: done

self.endpoint = 'http://localhost:10055/metrics'
# Conf from the agent
self.log = conf.log
self.gauge = conf.gauge

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hkaj Apr 25, 2017

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these 2 lines are the reason why I went with a subclass of AgentCheck instead here: 9be9af8#diff-b97e21cc8c9598269fd1833ccdd51ae3R27

This way you get all check methods for free. Mind switching to that?

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Note for self: done

"""
Polls the data from prometheus and pushes them as gauges
"""
data = self.processor.poll()

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hkaj Apr 25, 2017

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self.processor.poll() --> self.poll()

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aerostitch Apr 25, 2017

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Good catch! :) Thanks

"""
Polls the metrics from the prometheus endpoint
"""
headers = {

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hkaj Apr 25, 2017

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We should support protobuf and text format as it's done here: 9be9af8#diff-b97e21cc8c9598269fd1833ccdd51ae3R67 and 9be9af8#diff-b97e21cc8c9598269fd1833ccdd51ae3R76

Or by making these headers a parameter.

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Note for self: support of custom headers and the 2 formats done in the query call. Need to validate that parse_metric_family is compatible with the output provided in the text format (probably not, so moving that function inside the class and modifying it to accept the different will probably be in the TODO).

req.raise_for_status()
return req.content
def _submit_gauge(self, metric_name, val, metric, custom_tags=[]):

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hkaj Apr 25, 2017

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this should also support using only some labels. Maybe a dict looking like `{"label_name": "tag_name"} that we would use to filter through labels?
It could look like

def _submit_gauge(self, metric_name, val, metric, label_tags=None, custom_tags=[]):
    tags = custom_tags
    prometheus_tags = []
    if label_tags is not None:
        for label in metric.label:
            if label in label_tags:
                prometheus_tags.append('{}:{}'.format(label_tags[label], label.value))
    else:
        prometheus_tags = ['{}:{}'.format(label.name, label.value) for label in metric.label]
    tags += prometheus_tags
    self.gauge(metric_name, val, tags)

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aerostitch Apr 25, 2017

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Not sure what you want to do there. If we want a filter to not use certains labels or if you want to overwrite certain labels.
If we want to use a filter based on the label, we could just do:

    def _submit_gauge(self, metric_name, val, metrics, label_filters=None, custom_tags=[]):
        """
        Submit a metric as a gauge, additional tags provided will be added to
        the ones from the label provided via the metrics object.
        If the `label_filters` list is provided, the metrics labels available in
        the label_filters will not be assigned to the metric.
        """
        tags = custom_tags
        for label in metrics.label:
            if label_filters is None or label.name not in label_filters:
                tags.append('{}:{}'.format(label.name, label.value))
        self.gauge('{}.{}'.format(self.NAMESPACE, metric_name), val, tags)

Right?

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aerostitch Apr 25, 2017

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Oh wait, ok, the comment explanation just arrived to my brain, took a long time, sorry!
Will do.

"""
For each metric in the message, report it as a gauge with all labels as tags
except if a labels dict is passed, in which case keys are label names we'll extract
and corresponding values are tag names we'll use (eg: {'node': 'node'}).

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oops, I added this comment in kube_state_processor but didn't actually implement the label dict thing in this PR. You can find it here: 9be9af8#diff-b97e21cc8c9598269fd1833ccdd51ae3R89
Or simply remove this part of the comment and I'll add the feature later.

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aerostitch Apr 25, 2017

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Note for self: done.

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hkaj commented Apr 25, 2017

Had a first pass at it. It's a cool feature and will definitely help writing similar checks quicker.
Here's more feedback, not tied to a particular code line:

  • I think a mother class would be better fitted for this, what do you think?
  • defining the metric names in the conf file is not ideal for several reasons, the main one being that if we write official checks with this prometheus helper, its metrics will be officially supported (i.e. not counted as custom metrics) but if users don't like the name and change them in the yaml, they will become custom metrics without the user realizing it. So I'd rather have metrics_mapper be a hardcoded class variable (empty in the mother class/helper and overloaded on a per-check basis) as in 9be9af8#diff-b97e21cc8c9598269fd1833ccdd51ae3R39 so metric names are fixed for every check.
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aerostitch commented Apr 25, 2017

Thanks a lot for the review! :)
Sorry for the mother class I thought that I should have used it only in the integration/core project.
I'll fix that and change the other elements you commented. Hopefully I'll get the updated version this morning (San Francisco time! :) )

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aerostitch commented Apr 25, 2017

I'm also wondering if I shouldn't move the check to the checks/ directory (if it's a check per say, it should probably not be in the utils directory where you find all the helpers). What do you think?

@aerostitch aerostitch force-pushed the aerostitch:prometheus_core branch from 3b84a77 to 3e86a20 Apr 25, 2017

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aerostitch commented Apr 25, 2017

Updated the PR according to the review. Let me know if it's fine with you now.
Will add the tests this afternoon (I need to check the case of parsing the metrics pulled using text format too).

@aerostitch aerostitch force-pushed the aerostitch:prometheus_core branch 2 times, most recently from 233b3b3 to 88db4fb Apr 25, 2017

@aerostitch aerostitch changed the title from Add support for pulling metrics from prometheus to [WIP] Add support for pulling metrics from prometheus Apr 26, 2017

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aerostitch commented Apr 26, 2017

Sorry I've been sidetracked a lot yesterday and today. Will push the tests asap.

FYI I tested the parse_metric_family function with the text format and of course it failed! ;)
Not sure if treating the text format should be part of this PR or should be another feature. Not sure what it brings as prometheus always comes with the protobuf format support AFAIK and with the abstraction provided by the helpers, I don't think the format we use to query the prometheus endpoint really matters to the end user.
I'll do a 1st pass without integrating this and try to integrate them right after I got something acceptable and well tested with the protobuf format.

@aerostitch aerostitch force-pushed the aerostitch:prometheus_core branch 3 times, most recently from f7aa1cb to 4e05242 Apr 26, 2017

@aerostitch aerostitch force-pushed the aerostitch:prometheus_core branch from 4e05242 to 25e0b26 Apr 27, 2017

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aerostitch commented Apr 27, 2017

@hkaj I rewrote the class to be a motherclass based on AgentCheck.
Did the changes you asked me (except the decoding of the text format that will come probably tomorrow), added tests.
I also imported parse_metric_family into the class because I'm going to change it to support both text and protobuf format input. We can deprecate the other one I guess (it would make more sense to me anyway).
Can you review the new version of the implementation when you have some time please?
Once this is ok and the text format is supported I'll submit the PR for the integration core and the doc that goes with it.
Thanks
Joseph

# AND/OR
# - create method named after the prometheus metric they will handle (see self.prometheus_metric_name)
#
# Check class example:

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That's a great idea, but I was planning on writing a few checks with it and point to them instead. Do you mind opening a new PR with this kube DNS check later instead?

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Sure, no problem, that was in the pipe. Removing the example from the comment.

_tags = custom_tags
if _tags is None:
_tags = []
for label in metric.label:

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Minor comment here: we want to be able to filter out some labels if they're not useful or if need be (typically: if they have a high cardinality/high churn rate), and using labels_mapper would be perfect for this. The approach could be something like:

if labels_mapper is None:
    report all labels as tags and keep label names as tag names
else:
    report only labels set in the labels_mapper and use the value as tag name

Makes sense?

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It could be interesting in my opinion to have both a mapper to rewrite the labels to different tag names and have also an array to filter out the tags you don't want like 2 separate features. Would be more flexible no? And generally, you are more likely to have a list of the tags you want to get rid of and less the list of all the other tags no? :)

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Basically it would end up like:

         _tags = custom_tags
        if _tags is None:
            _tags = []
        for label in metric.label:
            if exclude_labels is None or label.name not in exclude_labels:
                tag_name = label.name
                if labels_mapper is not None and label.name in labels_mapper:
                    tag_name = labels_mapper[label.name]
                _tags.append('{}:{}'.format(tag_name, label.value))
        self.gauge('{}.{}'.format(self.NAMESPACE, metric_name), val, _tags)

Makes sense?

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hkaj Apr 28, 2017

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Yes that's what we'll need eventually. I would have kept it for later but since you already did it... ;)

Could you define labels_mapper and exclude_labels the same way as metric_mapper (hardcoded in the class)? We'll loose some flexibility by doing so, but it's a tradeoff that will tag names predictable which is required for official integrations (this way we can provide better default dashboards).

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hkaj commented Apr 27, 2017

Thanks for the update @aerostitch !
We can keep text format for later. Just left a few more notes.

@aerostitch aerostitch force-pushed the aerostitch:prometheus_core branch from c446b81 to bf3fa86 Apr 28, 2017

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aerostitch commented Apr 28, 2017

Hi @hkaj I did the requested changes and almost finished to add the support for the parsing of the text format (currently the summary quantiles and histogram buckets values are represented as labels, but I should be able to fix that tomorrow and add the test).
In the mean time, if you have the time to have a look and see stuffs you don't like, please let me know.
Thanks

@hkaj

2-3 nits, we're almost there 🎉
That's some great work!

messages = {} # map with the name of the element (before the labels) and the list of occurrences with labels and values
obj_map = {} # map of the types of each metrics
obj_help = {} # help for the metrics
metrics_pattern = re.compile(r'^(\w+)(.*)\s+([0-9.+eE,]+)$')

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If we compile it, let's do it only once in __init__ and store it in the check instance.

obj_map = {} # map of the types of each metrics
obj_help = {} # help for the metrics
metrics_pattern = re.compile(r'^(\w+)(.*)\s+([0-9.+eE,]+)$')
for line in buf.splitlines():

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this loop could be moved to its own method to make this one less hairy 😄

Extracts the labels from a string that looks like:
{label_name_1="value 1", label_name_2="value 2"}
"""
lbl_pattern = re.compile(r'(\w+)="(.*?)"')

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this should be compiled in __init__ and stored in self

_tags = custom_tags
if _tags is None:
_tags = []
for label in metric.label:

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Yes that's what we'll need eventually. I would have kept it for later but since you already did it... ;)

Could you define labels_mapper and exclude_labels the same way as metric_mapper (hardcoded in the class)? We'll loose some flexibility by doing so, but it's a tradeoff that will tag names predictable which is required for official integrations (this way we can provide better default dashboards).

@aerostitch aerostitch force-pushed the aerostitch:prometheus_core branch from bf3fa86 to a79d45b Apr 29, 2017

@hkaj hkaj merged commit bc6f2a6 into DataDog:master May 3, 2017

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@aerostitch aerostitch deleted the aerostitch:prometheus_core branch May 12, 2017

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discordianfish commented Oct 25, 2017

Can someone clarify whether this can be used on it's own? Is it possible to scrape arbitrary prometheus metrics endpoints as a datadog customer? Or is it necessary to add a custom check to the agent?

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aerostitch commented Oct 25, 2017

@discordianfish You need to create a custom check to push arbitrary metrics in any case but it's really easy (just a few lines).
You can have a look at https://github.com/DataDog/integrations-core/blob/master/kube_dns/check.py as an example.

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discordianfish commented Oct 25, 2017

@aerostitch Thanks, so basically like documented here? https://docs.datadoghq.com/guides/agent_checks/ - Haven't used custom agent checks so far.

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aerostitch commented Oct 25, 2017

@discordianfish Yes. You can copy the script I mentioned earlier to the location used for custom checks, change the class name (line 6 and 11), the metrics in self.metrics_mapper and namespace (line 4 and 12), give a value to the parameters (line 31) and you should be all set.

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aerostitch commented Oct 25, 2017

@hkaj I've had several people I know hitting me directly asking the same question. Do you want me to document it somewhere? The question that generally arrives next is how do I handle histogram buckets. 😄
(Not a big fan of doing blogposts, I prefer to have good examples in the official doc 😉 )

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hkaj commented Oct 27, 2017

Thanks for the ping @aerostitch
I'll queue some work on documenting this. Will tag you for review if that's okay with you :)

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MOZGIII commented Nov 23, 2017

Any update on the docs? I was looking for the docs everywhere and cound't find anythng except for this MR. Could you maybe giva at least a little hint on how add prometheus metrics to the system?

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aerostitch commented Nov 24, 2017

@MOZGIII did you check my 3 previous responses? That should give you an example and a good start on how to use them. I don't believe that @hkaj had the time yet to put together the documentation mentionned earlier but with my 3 previous responses you should be able to easily have a working integration that pulls metrics out of prometheus.

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hkaj commented Nov 24, 2017

Hey @MOZGIII Sorry this is still in the backlog. If this comment thread doesn't help you feel free to contact our support and we'll help you set this up.

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aerostitch commented Nov 24, 2017

In the mean time I wrote a quick how-to on creating a custom check that polls the metrics out of prometheus (that's just an explanation of the check and a copy/paste of some explanations that exist in the PrometheusCheck class mainly): https://github.com/aerostitch/aerostitch.github.io/blob/master/misc/datadog_pulling_metrics_from_prometheus.md
@MOZGIII @discordianfish let me know if that doc answers all your questions.
@hkaj let me know when you're all good with your doc, I'll put mine down.

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discordianfish commented Nov 24, 2017

Yeah it was quite straight forward. Thanks!
What I'm wondering in general: Why not support pulling metrics from prometheus without having to create these 'boilerplate-only' checks?

I've created https://github.com/latency-at/datadog-agent-prometheus as a generic exporter but it would be easy to support this directly in dd-agent instead.

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aerostitch commented Nov 24, 2017

Yes, that's what I wanted to do in the 1st place but it cannot be done like that. Datadog needs the full list of metrics that you're going to send if you want the metrics not to be considered as custom metrics (the pricing differs, which is the main blocker if I recall).
That's the reason why such a generic check could only be a custom check and not an official supported one.

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MOZGIII commented Nov 24, 2017

@aerostitch, hohestly I didn't really read through all the messages, but I've checked out the kube dns check and got some info from there. Seems like you refer to that as well.
@discordianfish I'll check out your solution, cause I guess I'd write something like that for my needs. Looks like it already does what I wanted initially.
I still have to figure out what's the best way to put all this into a docker container without config volumes to just build and run.

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MOZGIII commented Nov 24, 2017

@aerostitch that's interesting, so, that means datadogs pricing will be higher if I just put prometheus metrics into it?

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aerostitch commented Nov 24, 2017

@MOZGIII You pay the plan that includes a certain number of custom metrics allowed. The checks that come from integration-core like kube-dns that are fully supported by datadog and are not considered as custom metrics hence are not part of this bucket so you can use them without requiring a plan upgrade (that's the "pricing" difference I was referencing). See: https://help.datadoghq.com/hc/en-us/articles/204271775-What-is-a-custom-metric-and-what-is-the-limit-on-the-number-of-custom-metrics-I-can-have-

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discordianfish commented Nov 24, 2017

Yeah as I understood it, it's a custom metric either way. Correct?
Or can I add a check similar to kube-dns etc and get them not to count into my custom metrics?

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MOZGIII commented Nov 24, 2017

I see, so if I want to just capture everything with prometheus I'll have to somehow convert the metrics captured to the datadogs compatible format? Like, something generic, i.e. host memory usage.
UPD: Oh, wow, plans only allow for 300 custom metrics per host. That's not much, and difficult to manage given we're going to deploy with kubernetes...

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discordianfish commented Nov 24, 2017

@MOZGIII That's what this here + my bridge does. But I would expect this to count towards the custom metrics, so you'd really need to reduce the number of metrics you keep..

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aerostitch commented Nov 24, 2017

@discordianfish If you don't want your metrics to be custom metrics, you need to write something similar to kube-dns and have it integrated inside integration-core (I wrote the prometheus integration to be able to integrate kube-dns metrics as non-custom metrics). As long as it's not there, that's correct, it'll be a custom metric.

@MOZGIII I'm not entirely sure that not having metrics through the normal agent polls and getting all through a custom script, even if they have the same name in the end, I'm pretty sure they'd still be custom metrics. But I'm not part of Datadog, just a contributor so not 100% sure.

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discordianfish commented Nov 24, 2017

Got it! So I probably should try to get as much stuff upstreamed as possible. :)

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MOZGIII commented Nov 24, 2017

Found relevant code, but to busy to read it it through: https://github.com/DataDog/dd-agent/blob/master/checks/collector.py#L261 Just mentioning it here for later.
Maybe you'll find this interesting too.

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hkaj commented Nov 24, 2017

@MOZGIII @discordianfish @aerostitch We're also working on a check that can be configured through yaml to collect metrics automatically without writing boilerplate checks. Something similar to jmxfetch (but less hairy).

Using it with your own apps will result it custom metrics, but upstreaming to integrations-core a check that has it configured for a specific program will make these metrics "standard" and included in your subscription.

For example if you write a config for this check that monitors a micro service of yours it's custom, but if you write one to collect metrics about influxdb and upstream it, we'll add it to the supported integrations and it will be included in everyone's subscription.

Actually I think this check will be similar to your implementation @discordianfish :)
The limitation here is that not all prometheus endpoints are straight-forward to parse and convert to our format, so some checks will still need to be written manually. We also need to support use cases like label/metrics renaming/blacklisting that are often requested by users. kube-dns is a good example of a check we'll be able to port to this new logic. OTOH I doubt kube-state-metrics will be supported as its collection is not as streamlined.

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hkaj commented Nov 24, 2017

@aerostitch thanks a lot for the documentation! I pointed our doc team to it, i'm sure that will help them.

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MOZGIII commented Nov 24, 2017

@hkaj I'm really looking forward to the usecase with fully-automated autodiscovery of prometheus metrics, is it something you're planing to work on?

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hkaj commented Nov 24, 2017

Not myself, but you can expect to see PRs about it in a few weeks from @mfpierre 😉

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