8000 CEL Filter base [CONTP-809] #36591
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CEL Filter base [CONTP-809] #36591
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Go Package Import DifferencesBaseline: 277ce88
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Regression DetectorRegression Detector ResultsMetrics dashboard Baseline: 277ce88 Optimization Goals: ✅ No significant changes detected
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| perf | experiment | goal | Δ mean % | Δ mean % CI | trials | links |
|---|---|---|---|---|---|---|
| ➖ | quality_gate_logs | % cpu utilization | +3.77 | [+0.91, +6.62] | 1 | Logs bounds checks dashboard |
| ➖ | uds_dogstatsd_to_api_cpu | % cpu utilization | +1.97 | [+1.06, +2.88] | 1 | Logs |
| ➖ | quality_gate_idle_all_features | memory utilization | +1.84 | [+1.72, +1.96] | 1 | Logs bounds checks dashboard |
| ➖ | docker_containers_cpu | % cpu utilization | +1.32 | [-1.82, +4.47] | 1 | Logs |
| ➖ | tcp_syslog_to_blackhole | ingress throughput | +1.28 | [+1.22, +1.33] | 1 | Logs |
| ➖ | otlp_ingest_logs | memory utilization | +0.88 | [+0.76, +1.01] | 1 | Logs |
| ➖ | ddot_logs | memory utilization | +0.81 | [+0.72, +0.91] | 1 | Logs |
| ➖ | quality_gate_idle | memory utilization | +0.74 | [+0.68, +0.80] | 1 | Logs bounds checks dashboard |
| ➖ | uds_dogstatsd_20mb_12k_contexts_20_senders | memory utilization | +0.71 | [+0.66, +0.76] | 1 | Logs |
| ➖ | docker_containers_memory | memory utilization | +0.51 | [+0.43, +0.59] | 1 | Logs |
| ➖ | otlp_ingest_metrics | memory utilization | +0.36 | [+0.19, +0.52] | 1 | Logs |
| ➖ | ddot_metrics | memory utilization | +0.35 | [+0.23, +0.47] | 1 | Logs |
| ➖ | file_to_blackhole_0ms_latency | egress throughput | +0.12 | [-0.44, +0.67] | 1 | Logs |
| ➖ | file_to_blackhole_500ms_latency | egress throughput | +0.09 | [-0.49, +0.67] | 1 | Logs |
| ➖ | file_to_blackhole_1000ms_latency | egress throughput | +0.07 | [-0.54, +0.68] | 1 | Logs |
| ➖ | file_to_blackhole_100ms_latency | egress throughput | +0.06 | [-0.55, +0.67] | 1 | Logs |
| ➖ | file_to_blackhole_0ms_latency_http2 | egress throughput | +0.02 | [-0.53, +0.57] | 1 | Logs |
| ➖ | file_to_blackhole_0ms_latency_http1 | egress throughput | -0.00 | [-0.61, +0.61] | 1 | Logs |
| ➖ | uds_dogstatsd_to_api | ingress throughput | -0.00 | [-0.29, +0.29] | 1 | Logs |
| ➖ | tcp_dd_logs_filter_exclude | ingress throughput | -0.00 | [-0.01, +0.01] | 1 | Logs |
| ➖ | file_to_blackhole_300ms_latency | egress throughput | -0.03 | [-0.63, +0.57] | 1 | Logs |
| ➖ | file_to_blackhole_1000ms_latency_linear_load | egress throughput | -0.05 | [-0.28, +0.18] | 1 | Logs |
| ➖ | file_tree | memory utilization | -1.33 | [-1.53, -1.14] | 1 | Logs |
Bounds Checks: ✅ Passed
| perf | experiment | bounds_check_name | replicates_passed | links |
|---|---|---|---|---|
| ✅ | docker_containers_cpu | simple_check_run | 10/10 | |
| ✅ | docker_containers_memory | memory_usage | 10/10 | |
| ✅ | docker_containers_memory | simple_check_run | 10/10 | |
| ✅ | file_to_blackhole_0ms_latency | lost_bytes | 10/10 | |
| ✅ | file_to_blackhole_0ms_latency | memory_usage | 10/10 | |
| ✅ | file_to_blackhole_0ms_latency_http1 | lost_bytes | 10/10 | |
| ✅ | file_to_blackhole_0ms_latency_http1 | memory_usage | 10/10 | |
| ✅ | file_to_blackhole_0ms_latency_http2 | lost_bytes | 10/10 | |
| ✅ | file_to_blackhole_0ms_latency_http2 | memory_usage | 10/10 | |
| ✅ | file_to_blackhole_1000ms_latency | memory_usage | 10/10 | |
| ✅ | file_to_blackhole_1000ms_latency_linear_load | memory_usage | 10/10 | |
| ✅ | file_to_blackhole_100ms_latency | lost_bytes | 10/10 | |
| ✅ | file_to_blackhole_100ms_latency | memory_usage | 10/10 | |
| ✅ | file_to_blackhole_300ms_latency | lost_bytes | 10/10 | |
| ✅ | file_to_blackhole_300ms_latency | memory_usage | 10/10 | |
| ✅ | file_to_blackhole_500ms_latency | lost_bytes | 10/10 | |
| ✅ | file_to_blackhole_500ms_latency | memory_usage | 10/10 | |
| ✅ | quality_gate_idle | intake_connections | 10/10 | bounds checks dashboard |
| ✅ | quality_gate_idle | memory_usage | 10/10 | bounds checks dashboard |
| ✅ | quality_gate_idle_all_features | intake_connections | 10/10 | bounds checks dashboard |
| ✅ | quality_gate_idle_all_features | memory_usage | 10/10 | bounds checks dashboard |
| ✅ | quality_gate_logs | intake_connections | 10/10 | bounds checks dashboard |
| ✅ | quality_gate_logs | lost_bytes | 10/10 | bounds checks dashboard |
| ✅ | quality_gate_logs | memory_usage | 10/10 | bounds checks dashboard |
Explanation
Confidence level: 90.00%
Effect size tolerance: |Δ mean %| ≥ 5.00%
Performance changes are noted in the perf column of each table:
- ✅ = significantly better comparison variant performance
- ❌ = significantly worse comparison variant performance
- ➖ = no significant change in performance
A regression test is an A/B test of target performance in a repeatable rig, where "performance" is measured as "comparison variant minus baseline variant" for an optimization goal (e.g., ingress throughput). Due to intrinsic variability in measuring that goal, we can only estimate its mean value for each experiment; we report uncertainty in that value as a 90.00% confidence interval denoted "Δ mean % CI".
For each experiment, we decide whether a change in performance is a "regression" -- a change worth investigating further -- if all of the following criteria are true:
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Its estimated |Δ mean %| ≥ 5.00%, indicating the change is big enough to merit a closer look.
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Its 90.00% confidence interval "Δ mean % CI" does not contain zero, indicating that if our statistical model is accurate, there is at least a 90.00% chance there is a difference in performance between baseline and comparison variants.
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Its configuration does not mark it "erratic".
CI Pass/Fail Decision
✅ Passed. All Quality Gates passed.
- quality_gate_idle, 8000 bounds check memory_usage: 10/10 replicas passed. Gate passed.
- quality_gate_idle, bounds check intake_connections: 10/10 replicas passed. Gate passed.
- quality_gate_idle_all_features, bounds check memory_usage: 10/10 replicas passed. Gate passed.
- quality_gate_idle_all_features, bounds check intake_connections: 10/10 replicas passed. Gate passed.
- quality_gate_logs, bounds check memory_usage: 10/10 replicas passed. Gate passed.
- quality_gate_logs, bounds check lost_bytes: 10/10 replicas passed. Gate passed.
- quality_gate_logs, bounds check intake_connections: 10/10 replicas passed. Gate passed.
Static quality checks❌ Please find below the results from static quality gates Error
Gate failure full details
Static quality gates prevent the PR to merge! You can check the static quality gates confluence page for guidance. We also have a toolbox page available to list tools useful to debug the size increase. Successful checksInfo
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gabedos
commented
Jun 6, 2025
| // | ||
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| // Container represents a filterable container object. | ||
| type Container struct { |
There was a problem hiding this comment.
You can look through the previous commits to see the iterations that this Container struct has looked like.
What I eventually landed on in the end was using an embedded proto struct. I thought of using a proto struct because it allows third party libraries like CEL-go to be able to understand the object and its attributes. Thus, the CEL parser at compile time is able to throw precise errors if users ever misconfigure any filter. We still have access to all the attributes if we ever decide to use them in some other way.
Currently I am thinking of providing functions to help other users of this component to create the Filterable structs from the wmeta structs. However, this is something that we could theoretically do within the component itself as well. For the case of IsContainerExcluded we need to have the container's owner. This could be either a pod, task, or maybe something else. We could store a reference to wmeta internally and query for the container's owner. My only thought is that this could be repetitive work if the client already has the owner pod for other reasons but on the flip side would make the interface simpler.
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Is this component supposed to be imported in the heroku and iot agents ? |
Hey @pgimalac, In regards to Windows, I think this component would still be used in that environment because all of the core agent functionalities like Autodiscovery and Container corechecks still run on windows and we would want to give the same experience for users regardless of OS. For heroku and iot agents... I'm honestly not as familiar what the Agent does in these environments. It seems like autodiscovery is pulled into all of these flavors still? and one of the primary use cases of these filters would be to restrict what is being autodiscovered. I know in the next quarter we also want to start autodiscovering log collection on host processes (but once again unfamiliar with heroku/iot if we even collect logs there). Would appreciate if you have any significant missing context related to these 2 flavors! |
rahulkaukuntla
approved these changes
Jun 23, 2025
pgimalac
approved these changes
Jun 24, 2025
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| parts := strings.SplitN(filter, ":", 2) | ||
| if len(parts) != 2 { | ||
| return "", fmt.Errorf("invalid filter format: %s", filter) | ||
| } | ||
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| key, value := parts[0], parts[1] |
There was a problem hiding this comment.
🥜 nitpick: You can use strings.Cut
Suggested change
| parts := strings.SplitN(filter, ":", 2) | |
| if len(parts) != 2 { | |
| return "", fmt.Errorf("invalid filter format: %s", filter) | |
| } | |
| key, value := parts[0], parts[1] | |
| key, value, ok := strings.Cut(filter, ":") | |
| if !ok { | |
| return "", fmt.Errorf("invalid filter format: %s", filter) | |
| } |
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| // CreatePod creates a Filterable Pod object from a workloadmeta.KubernetesPod. | ||
| func CreatePod(pod workloadmeta.KubernetesPod) *Pod { | ||
| return &Pod{ | ||
| FilterPod: &typedef.FilterPod{ | ||
| Id: pod.ID, | ||
| Name: pod.Name, | ||
| Namespace: pod.Namespace, | ||
| Annotations: pod.Annotations, | ||
| }, | ||
| } | ||
| } |
There was a problem hiding this comment.
💬 suggestion: I believe this is only used in tests right now, if it's going to stay that way it should be moved to a test file, otherwise maybe a workloadmetautils subpackage would be best ?
That way we avoid a direct dependency from the filter component to workloadmeta types by default
Same for CreateContainer
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| // GetSharedMetricsFilters identifies the filtering component's individual Container Filters for container metrics. | ||
| func GetSharedMetricsFilters() [][]ContainerFilter { |
There w 9B73 as a problem hiding this comment.
Same for everything in this file actually ?
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What does this PR do?
Creates a new component for storing filtering programs to be eventually used across various agent components.
Motivation
Centralize filtering logic. Improve filtering expressiveness through a rule engine (cel-go)
Describe how you validated your changes
Unit-tests
Possible Drawbacks / Trade-offs
Slight increase in static binary size to pull in additional cel-go packages. Although cel-go is already an indirect dependency in the Datadog Agent repo, it's completely removed from dead code elimination. The direct use of cel-go in this PR causes the binary size to increase.
Other rule engine options include Expr but that increases the static binary size by 35MB+ and causes SMP memory usage to increase by 7MB+ due to disabling dead code elimination completely as a result of the reflection methods used in expr.
Additional Notes