Add dcgm scraper to collect nvidia GPU metrics #160

movence · 2024-02-14T16:41:40Z

Revisions

rev3:
- rename k8s attribute vars with Attribute prefix
- support multiple datapoints when converting pmetric into fields/tags
- move RawContainerInsightsMetric struct to stores package
- update feature toggle flag var name to match json key
rev2:
- update feature toggle flag fromgpu_metrics to accelerated_computing_metrics
- consolidate CI metrics structs into single RawContainerInsights
- use constant variables
- use the same scrape configs in dcgm scraper test
- remove unnecessary attribute decoration for GPU metrics
- add dcgm as a new source for Sources attribute
rev1:
- Add GPU metric consumer which intercepts metrics to decorate with k8s attributes
- Update k8s decorator to use CIMetric interface rather than cadvisor

Description:

Add a new prometheus scraper to scrape NVIDIA GPU metrics from dcgm-exporter under container insights receiver
Add a feature flag for GPU data collection
Move scraper mock for testing out of k8sapi package to share with other scrapers

Testing:
Tested on a test cluster with 1 GPU node (with 4 GPUs) + 1 regular node: only 3 GPUs get workload

running pods

amazon-cloudwatch  cloudwatch-agent-52jfj                                           ●  1/1   Running         0 x.x.x.x  ip-x.x.x.x.us-west │.us-west │
│ amazon-cloudwatch  cloudwatch-agent-gr4kr                                           ●  1/1   Running         0 x.x.x.x  ip-x.x.x.x.us-west │.us-west │
│ amazon-cloudwatch  dcgm-exporter-md5p4                                              ●  1/1   Running         0 x.x.x.x  ip-x.x.x.x.us-west │
│ amazon-cloudwatch  gpu-burn-1-5b78d96f7b-w8kgf                                      ●  1/1   Running         0 x.x.x.x  ip-x.x.x.x.us-west │

exporter/awsemfexporter/config.go

exporter/awsemfexporter/metric_translator.go

exporter/awsemfexporter/metric_translator_test.go

receiver/awscontainerinsightreceiver/internal/gpu/dcgmscraper.go

receiver/awscontainerinsightreceiver/receiver.go

receiver/awscontainerinsightreceiver/internal/stores/servicestore.go

receiver/awscontainerinsightreceiver/internal/gpu/dcgmscraper.go

receiver/awscontainerinsightreceiver/config.go

receiver/awscontainerinsightreceiver/internal/gpu/dcgmscraper.go

sam6134 · 2024-02-27T12:08:22Z

receiver/awscontainerinsightreceiver/internal/gpu/dcgmscraper.go

+			},
+		},
+		RelabelConfigs: []*relabel.Config{
+			{


Might be little late, but why exactly do we need this, is this used somewhere in the agent at the end?

Some rules need to be removed. Thanks!

sam6134 · 2024-02-27T13:18:40Z

internal/aws/containerinsight/const.go

@@ -151,6 +151,10 @@ const (
 	// Special type for pause container
 	// because containerd does not set container name pause container name to POD like docker does.
 	TypeInfraContainer = "InfraContainer"
+	TypeGpuContainer   = "ContainerGPU"
+	TypeGpuPod         = "PodGPU"
+	TypeGpuNode        = "NodeGPU"


TypeGpuNode, and TypeGpuCluster are nowhere used, do we need this?

You are right that they are not currently being used. The intention is to use them for GPU count metrics.

sam6134 · 2024-02-27T15:03:31Z

receiver/awscontainerinsightreceiver/internal/gpu/decorator.go

+// Copyright The OpenTelemetry Authors
+// SPDX-License-Identifier: Apache-2.0
+
+package gpu


Can we make this decorator generic , I get it now its only for GPU but if we make it configurable i.e it adds unit based on the Map provided, also adding the K8 Label seem to re-usable say in Neuron monitor.

Strongly agree with this.

jefchien · 2024-02-27T16:06:50Z

internal/aws/containerinsight/utils.go

+	}
+
+	// value is not needed for label decoration
+	fields[m.Name()] = 0


nit: Could set it to nil to be more explicit that it's not going to be used.

Is this the only field?

internal/aws/containerinsight/utils.go

receiver/awscontainerinsightreceiver/internal/gpu/decorator.go

receiver/awscontainerinsightreceiver/internal/cadvisor/extractors/extractor.go

receiver/awscontainerinsightreceiver/internal/gpu/dcgmscraper.go

receiver/awscontainerinsightreceiver/internal/gpu/dcgmscraper_test.go

receiver/awscontainerinsightreceiver/internal/gpu/decorator.go

receiver/awscontainerinsightreceiver/internal/stores/utils.go

straussb · 2024-02-27T19:57:30Z

internal/aws/containerinsight/utils.go

+		logger.Warn("Unsupported metric type", zap.String("metric", m.Name()), zap.String("type", m.Type().String()))
+	}
+
+	// should support metrics with more than 1 datapoints?
+	if dps.Len() > 1 {
+		logger.Warn("Metric with more than 1 datapoint is not supported", zap.String("metric", m.Name()), zap.Int("datapoints", dps.Len()))


How would we ever know if we're hitting these in production? Do we have a guarantee that DcgmScraper is only producing metrics in your supported format? How do you know it won't change? (Not to mention, by putting this method in a common utils package, you're implying that any OTLP metrics producer should be able to call it...)

If we have to do this ConvertToFieldsAndTags, then probably you should just handle all cases. Return an array if you have to?

Long term, it kind of seems like the decorator should become a processor and operate on OTLP metrics directly, so we don't have to do this double-conversion back and forth (OTLP -> fields/tags -> OTLP)... does that sound right?

Makes sense. There is no guarantee that it won't change. I will update to handle all cases.

It was done this way to leverage existing k8s decorator, but I do agree we can skip those conversions and just make it more like a processor to selectively decorate GPU specific stuffs without getting all unnecessary attributes from k8sdecorator. This could be a future improvement.

Missed making this update?

straussb · 2024-02-27T20:00:41Z

receiver/awscontainerinsightreceiver/internal/gpu/decorator.go

+	resourceTags := make(map[string]string)
+	rms := md.ResourceMetrics()
+	for i := 0; i < rms.Len(); i++ {


Probably better to move this entire loop into the ConvertToFieldsAndTags() method. It would be the inverse of the existing ConvertToOTLPMetrics() method. Take in pmetrics.Metrics and return an array of fields/tags pairs (or wrap in struct).

Then here in decoratorConsumer, iterate through again and call the decorator.

That was my original idea as well to make it inverse of ConvertToOTLPMetrics. However, existing CI metrics do get populated on the fly which makes sense to start from fields/tags set where the tags get applied at resource level. For GPU, OTLP metrics are already constructed, and they just need to be decorated at datapoint level by leveraging the k8sdecorator which consumes fields/tags. With this approach, we can avoid the last portion of conversion process: OTLP-fields/tags-OTLP.

Oh, interesting point, we are only using K8sDecorator for tags in this case, we don't need the fields at all. Hmm... seems like we could have done some additional refactoring then... separate K8sDecorator into a series of sub-decorators - cadvisor would use all but dcgm would only use the couple that it needs. I won't push on it now though.

Also worth noting that Cadvisor/K8sDecorator only work this way because they were ported from the original CWAgent. If we were writing from scratch, we would probably operate on OTLP metrics directly.

Ah that makes sense. I was wondering why existing decorator wouldn't just start with OTLP metrics.

Breaking k8sdecorator will be an interesting one. It currently depends on 2 stores (podstore and servicestore) that it uses to decorate. podstore is the main one with most of data (such as node and container) available at the pod level. Making these pluggable for different needs will be nice and reduce unnecessary overhead and processing.

straussb · 2024-02-27T20:06:11Z

receiver/awscontainerinsightreceiver/internal/gpu/decorator.go

+// Copyright The OpenTelemetry Authors
+// SPDX-License-Identifier: Apache-2.0
+
+package gpu


Strongly agree with this.

straussb · 2024-02-27T21:59:25Z

receiver/awscontainerinsightreceiver/internal/gpu/dcgmscraper.go

+	}
+
+	promFactory := prometheusreceiver.NewFactory()
+	promReceiver, err := promFactory.CreateMetricsReceiver(opts.Ctx, params, &promConfig, &decoConsumer)


Can you explain what will happen if there is no DCGM exporter running on the node? How often does the scraper retry? Will we get a bunch of errors in the logs?

The scraper will print out en error message every minute if dcgm exporter is not available. If this becomes concern, we could probably check the instance type withEnableGpuMetrics flag to decide whether to register gpu scraper or not.

Yes, it will be very confusing to see those errors if we enable the scraper on a non-GPU node. Can the operator only set enable_gpu_metrics if it also deploys DCGM exporter on a node? Or can the agent do something, like only start up the Prometheus scraper if it sees a local DCGM exporter?

dcgm exporter is an independent daemonset that is not controlled by the operator. It gets started by nodeAffinity rule which we pass all NVIDIA GPU instance types.
I think this is an improvement that we should do as a fast follow. Options I can think of:

Check the current node type (maybe IMDS?) similar to how dcgm exporter does with nodeAffinity

Check if dcgm exporter pod exists on the same node

Sorry you're right, I should say add-on, not operator.

Can you show what the log will look like on a non-GPU node?

I will say this is a blocker, it's going to affect every non-GPU customer. I like your idea of checking for DCGM exporter. Or can we do something quick to swallow the error message? (Although we don't want to lose it for troubleshooting purposes if there are real errors contacting DCGM exporter on a GPU node.)

Actually, it will print a debug log that looks like:

2024-03-01T14:06:52Z D! {"caller":"scrape/scrape.go:1351","msg":"Scrape failed","kind":"receiver","name":"awscontainerinsightreceiver","data_type":"metr │ │ ics","scrape_pool":"containerInsightsDCGMExporterScraper","target":"http://dcgm-exporter-service.amazon-cloudwatch.svc:9400/metrics","error":"Get \"http │ │ ://dcgm-exporter-service.amazon-cloudwatch.svc:9400/metrics\": context deadline exceeded"}

I think we can troubleshoot by running the agent in debug mode in case there is an issue. For other cases, scraper won't clutter the logs.

As the long term solution, we should not run the scraper at all on non-GPU instances. I will start work on that DCGM pod scanning option for the next phase.

OK that's great, debug line is fine. Agree on your plans for the next phase as well.

straussb · 2024-02-29T14:26:57Z

internal/aws/containerinsight/k8sconst.go

@@ -20,6 +20,7 @@ const (

 	PodStatus       = "pod_status"
 	ContainerStatus = "container_status"
+	GpuDevice       = "GpuDevice"


Very minor: move this up a few lines to the previous block of constants - it's an attribute not a metric name.

Could also rename it AttributeGpuDevice so it's clear without the comment.

like renaming to make it more intuitive

receiver/awscontainerinsightreceiver/config.go

receiver/awscontainerinsightreceiver/internal/cadvisor/extractors/extractor.go

receiver/awscontainerinsightreceiver/internal/cadvisor/extractors/extractor_helpers_test.go

receiver/awscontainerinsightreceiver/internal/cadvisor/extractors/extractor_test.go

straussb · 2024-02-29T14:41:53Z

receiver/awscontainerinsightreceiver/internal/gpu/dcgmscraper_test.go

+		// skip prometheus metadata metrics including "up"
+		if !strings.HasPrefix(metric.Name(), "DCGM") {
+			continue
+		}


Hm, is there no way to filter these out at the scraper side? Otherwise they propagate down the OTel pipeline. Or does k8sapiserver have the same issue and we filter these out some other way?

I don't think there is a way. prometheus_scraper also gets those meta metrics:

mock response: https://github.com/amazon-contributing/opentelemetry-collector-contrib/blob/aws-cwa-dev/receiver/awscontainerinsightreceiver/internal/k8sapiserver/prometheus_scraper_test.go#L27

actual response even after relabeling

// only expected metric is 'http_connected_total` ===== up ===== scrape_duration_seconds ===== scrape_samples_scraped ===== scrape_samples_post_metric_relabeling ===== scrape_series_added ===== http_connected_total

Interesting, OK, I guess it gets filtered out some other way?

I should look deeper to see exactly at what point these metadata metrics get dropped.

straussb · 2024-02-29T18:04:08Z

receiver/awscontainerinsightreceiver/internal/gpu/dcgmscraper_test.go

+	mp.Wg.Wait()
+	mp.Wg.Wait()


Sorry, didn't think to have this comment on aditya-purang#1 , but can you add an assertion that the mockConsumer actually did get called? Otherwise we could be completely skipping validation and would have no idea. Maybe add a boolean flag to mockConsumer that it sets at the end of ConsumeMetrics().

I see that we're waiting for the scrapes, but then what? It doesn't look like we're verifying anything.

The metric consumer is passed as a parameter to the scraper. ConsumeMetrics has some assertions.

receiver/awscontainerinsightreceiver/internal/gpu/dcgmscraper_test.go

jefchien · 2024-02-29T18:39:57Z

internal/aws/containerinsight/k8sconst.go

@@ -20,6 +20,7 @@ const (

 	PodStatus       = "pod_status"
 	ContainerStatus = "container_status"
+	GpuDevice       = "GpuDevice"


Could also rename it AttributeGpuDevice so it's clear without the comment.

jefchien · 2024-02-29T18:40:41Z

internal/aws/containerinsight/utils.go

+		logger.Warn("Unsupported metric type", zap.String("metric", m.Name()), zap.String("type", m.Type().String()))
+	}
+
+	// should support metrics with more than 1 datapoints?


Does this need to be answered or is this more of a TODO?

jefchien · 2024-02-29T19:52:01Z

receiver/awscontainerinsightreceiver/internal/gpu/decorator.go

+	var result []*extractors.RawContainerInsightsMetric
+	for _, m := range metrics {
+		// add tags for EKS
+		if dc.containerOrchestrator == ci.EKS {


nit: Move this check out of the for-loop or even out of the function.

jefchien · 2024-02-29T19:59:42Z

receiver/awscontainerinsightreceiver/internal/gpu/decorator.go

+	Shutdown() error
+}
+
+func (dc *decorateConsumer) decorateMetrics(metrics []*extractors.RawContainerInsightsMetric) []*extractors.RawContainerInsightsMetric {


Why are we returning a slice that we don't use?

jefchien · 2024-02-29T20:03:12Z

receiver/awscontainerinsightreceiver/internal/gpu/dcgmscraper_test.go

+	mp.Wg.Wait()
+	mp.Wg.Wait()


I see that we're waiting for the scrapes, but then what? It doesn't look like we're verifying anything.

receiver/awscontainerinsightreceiver/internal/gpu/decorator_test.go

jefchien · 2024-02-29T20:08:07Z

receiver/awscontainerinsightreceiver/internal/gpu/decorator_test.go

+type mockNextConsumer struct {
+}
+
+func (mc *mockNextConsumer) Capabilities() consumer.Capabilities {
+	return consumer.Capabilities{
+		MutatesData: true,
+	}
+}
+
+func (mc *mockNextConsumer) ConsumeMetrics(_ context.Context, md pmetric.Metrics) error {
+	return nil
+}


nit: This isn't used.

jefchien · 2024-02-29T20:08:55Z

receiver/awscontainerinsightreceiver/internal/gpu/decorator_test.go

+type mockGpuMetric struct {
+	tags   map[string]string
+	fields map[string]any
+}
+
+func (m *mockGpuMetric) HasField(key string) bool {
+	return m.fields[key] != nil
+}
+
+func (m *mockGpuMetric) AddField(key string, val any) {
+	m.fields[key] = val
+}
+
+func (m *mockGpuMetric) GetField(key string) any {
+	return m.fields[key]
+}
+
+func (m *mockGpuMetric) HasTag(key string) bool {
+	return m.tags[key] != ""
+}
+
+func (m *mockGpuMetric) AddTag(key, val string) {
+	m.tags[key] = val
+}
+
+func (m *mockGpuMetric) GetTag(key string) string {
+	return m.tags[key]
+}
+
+func (m *mockGpuMetric) RemoveTag(key string) {
+	delete(m.tags, key)
+}


nit: This isn't used.

jefchien · 2024-02-29T20:11:21Z

receiver/awscontainerinsightreceiver/internal/gpu/decorator.go

+				// copy down resource metrics only when it's missing at datapoint
+				for rtk, rtv := range resourceTags {
+					if _, ok := tags[rtk]; !ok {
+						tags[rtk] = rtv
+					}
+				}


I think you mean "copy down resource attributes". Can you explain why we're doing this in the receiver?

Yeah, this doesn't really add any value. removed.

If you are asking why we are adding attributes in the receiver? It was modeled similar to CI metric generation. There is no strong reason this should be done at the receiver.

jefchien · 2024-03-01T16:11:53Z

receiver/awscontainerinsightreceiver/internal/stores/utils.go

+			c.Logger.Debug(fmt.Sprintf("metric being merged has conflict in fields, src: %v, dest: %v \n", *src, *c))
+			c.Logger.Debug("metric being merged has conflict in fields", zap.String("src", src.ContainerName), zap.String("dest", c.ContainerName))


Are there meant to be two of these? Seems like a merge that had a conflict.

now sure how I missed this...

jefchien · 2024-03-01T16:12:45Z

receiver/awscontainerinsightreceiver/internal/stores/utils.go

+func NewRawContainerInsightsMetricWithData(mType string, fields map[string]any, tags map[string]string, logger *zap.Logger) *RawContainerInsightsMetric {
+	metric := NewRawContainerInsightsMetric(mType, logger)
+	metric.Fields = fields
+	metric.Tags = tags


Is this meant to overwrite the ci.MetricType that was inserted into the Tags in the NewRawContainerInsightsMetric function? If not, then maybe you can just call the AddTag/AddField functions for the passed in maps.

yes, type in tags parameter takes precedence. Existing CI flow won't use this function in the first place just fyi.

Then is there a point in passing the mType in? It's just going to get overwritten by the tags.

I see your point. It is just to follow the convention with existing initializer without data params.

Okay I think it's just a bit misleading and a bit of unexpected behavior. Can we at least document?

// NewRawContainerInsightsMetricsWithData sets the fields and tags on the metric. Discards the mType.

straussb · 2024-03-01T16:49:39Z

internal/aws/containerinsight/utils.go

+		})
+		converted = append(converted, FieldsAndTagsPair{
+			Fields: map[string]any{
+				m.Name(): nil, // metric value not needed for attribute decoration


If we're going to have this limitation (plus only supporting gauge and sum), then I think just move this helper method to the gpu decorator (it's only used from there right now anyway). Having it here in this common place implies that it should work for any OTLP metric.

straussb · 2024-03-01T16:50:35Z

receiver/awscontainerinsightreceiver/internal/gpu/dcgmscraper.go

+	}
+
+	promFactory := prometheusreceiver.NewFactory()
+	promReceiver, err := promFactory.CreateMetricsReceiver(opts.Ctx, params, &promConfig, &decoConsumer)


OK that's great, debug line is fine. Agree on your plans for the next phase as well.

…cks package

update dcgm relabeling rules

use constant variables use the same scrape configs in dcgm scraper test remove unnecessary attribute decoration for GPU metrics add dcgm as source for dim

support multiple datapoints when converting pmetric into fields/tags move RawContainerInsightsMetric struct to stores package update feature toggle flag var name to match json key

Paramadon

lgtm

movence requested a review from mxiamxia as a code owner February 14, 2024 16:41

jefchien reviewed Feb 15, 2024

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movence mentioned this pull request Feb 16, 2024

Support NVIDIA GPU metrics aws/amazon-cloudwatch-agent#1033

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movence mentioned this pull request Mar 1, 2024

Support NVIDIA GPU metrics aws/amazon-cloudwatch-agent#1068

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movence force-pushed the ci-nvidia-gpu branch from f98d686 to 9f58b9f Compare March 1, 2024 16:14

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movence added 6 commits March 1, 2024 13:55

add dcgm exporter scraper and move prometheus scraper test mock to mo…

0d98f61

…cks package

update emf exporter to handle GPU metrics with different metric types

66a683b

update dcgm relabeling rules

remove custom logic in emf exporter

edc2cee

update gpu flag comment

a6443f1

remove comments and test codes

782f24a

remove unused codes and rename scraper init funcs

18db72a

movence added 9 commits March 1, 2024 13:56

remove comments

5d11f3c

add changelog for gpu

9ed6770

add gpu metric consumer that uses k8s decorator for attributes

e8af343

address comments

0b7c895

handle the case with no dp

bc8d269

consolidate CI metrics structs into single RawContainerInsights

43ba471

use constant variables use the same scrape configs in dcgm scraper test remove unnecessary attribute decoration for GPU metrics add dcgm as source for dim

update feature toggle flag name

5a4f394

rename k8s attributes vars with Attribute prefix

3ee43f6

support multiple datapoints when converting pmetric into fields/tags move RawContainerInsightsMetric struct to stores package update feature toggle flag var name to match json key

merge conflicts

6a2de95

movence dismissed stale reviews from straussb and jefchien via 6a2de95 March 1, 2024 19:36

movence force-pushed the ci-nvidia-gpu branch from 22dab16 to 6a2de95 Compare March 1, 2024 19:36

remove unused variable and code for setting metric type to it

cc3bf6e

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clean ups

852fff7

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movence merged commit d3bf111 into amazon-contributing:aws-cwa-dev Mar 1, 2024
43 of 53 checks passed

		c.Logger.Debug(fmt.Sprintf("metric being merged has conflict in fields, src: %v, dest: %v \n", src, c))
		c.Logger.Debug("metric being merged has conflict in fields", zap.String("src", src.ContainerName), zap.String("dest", c.ContainerName))

Add dcgm scraper to collect nvidia GPU metrics #160

Add dcgm scraper to collect nvidia GPU metrics #160

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