README
¶
Kubernetes Attributes Processor
| Status | |
|---|---|
| Stability | beta: logs, metrics, traces |
| Distributions | contrib |
| Issues |   |
| Code Owners | @dmitryax, @rmfitzpatrick, @fatsheep9146, @TylerHelmuth |
Kubernetes attributes processor allow automatic setting of spans, metrics and logs resource attributes with k8s metadata.
The processor automatically discovers k8s resources (pods), extracts metadata from them and adds the extracted metadata to the relevant spans, metrics and logs as resource attributes. The processor uses the kubernetes API to discover all pods running in a cluster, keeps a record of their IP addresses, pod UIDs and interesting metadata. The rules for associating the data passing through the processor (spans, metrics and logs) with specific Pod Metadata are configured via "pod_association" key. It represents a list of associations that are executed in the specified order until the first one is able to do the match.
Configuration
The processor stores the list of running pods and the associated metadata. When it sees a datapoint (log, trace or metric), it will try to associate the datapoint to the pod from where the datapoint originated, so we can add the relevant pod metadata to the datapoint. By default, it associates the incoming connection IP to the Pod IP. But for cases where this approach doesn't work (sending through a proxy, etc.), a custom association rule can be specified.
Each association is specified as a list of sources of associations. A source is a rule that matches metadata from the datapoint to pod metadata. In order to get an association applied, all the sources specified need to match.
Each sources rule is specified as a pair of from (representing the rule type) and name (representing the attribute name if from is set to resource_attribute).
The following rule types are available:
connection: Takes the IP attribute from connection context (if available). In this case the processor must appear before any batching or tail sampling, which remove this information.resource_attribute: Allows specifying the attribute name to lookup in the list of attributes of the received Resource. Semantic convention should be used for naming.
Pod association configuration.
pod_association:
# below association takes a look at the datapoint's k8s.pod.ip resource attribute and tries to match it with
# the pod having the same attribute.
- sources:
- from: resource_attribute
name: k8s.pod.ip
# below association matches for pair `k8s.pod.name` and `k8s.namespace.name`
- sources:
- from: resource_attribute
name: k8s.pod.name
- from: resource_attribute
name: k8s.namespace.name
If Pod association rules are not configured, resources are associated with metadata only by connection's IP Address.
Which metadata to collect is determined by metadata configuration that defines list of resource attributes
to be added. Items in the list called exactly the same as the resource attributes that will be added.
The following attributes are added by default:
- k8s.namespace.name
- k8s.pod.name
- k8s.pod.uid
- k8s.pod.start_time
- k8s.deployment.name
- k8s.node.name
You can change this list with metadata configuration.
Not all the attributes are guaranteed to be added. Only attribute names from metadata should be used for
pod_association's resource_attribute, because empty or non-existing values will be ignored.
Additional container level attributes can be extracted provided that certain resource attributes are provided:
- If the
container.idresource attribute is provided, the following additional attributes will be available:- k8s.container.name
- container.image.name
- container.image.tag
- If the
k8s.container.nameresource attribute is provided, the following additional attributes will be available:- container.image.name
- container.image.tag
- If the
k8s.container.restart_countresource attribute is provided, it can be used to associate with a particular container instance. If it's not set, the latest container instance will be used:- container.id (not added by default, has to be specified in
metadata)
- container.id (not added by default, has to be specified in
The k8sattributesprocessor can also set resource attributes from k8s labels and annotations of pods, namespaces and nodes. The config for associating the data passing through the processor (spans, metrics and logs) with specific Pod/Namespace/Node annotations/labels is configured via "annotations" and "labels" keys. This config represents a list of annotations/labels that are extracted from pods/namespaces/nodes and added to spans, metrics and logs. Each item is specified as a config of tag_name (representing the tag name to tag the spans with), key (representing the key used to extract value) and from (representing the kubernetes object used to extract the value). The "from" field has only three possible values "pod", "namespace" and "node" and defaults to "pod" if none is specified.
A few examples to use this config are as follows:
extract:
annotations:
- tag_name: a1 # extracts value of annotation from pods with key `annotation-one` and inserts it as a tag with key `a1`
key: annotation-one
from: pod
- tag_name: a2 # extracts value of annotation from namespaces with key `annotation-two` with regexp and inserts it as a tag with key `a2`
key: annotation-two
regex: field=(?P<value>.+)
from: namespace
- tag_name: a3 # extracts value of annotation from nodes with key `annotation-three` with regexp and inserts it as a tag with key `a3`
key: annotation-three
regex: field=(?P<value>.+)
from: node
labels:
- tag_name: l1 # extracts value of label from namespaces with key `label1` and inserts it as a tag with key `l1`
key: label1
from: namespace
- tag_name: l2 # extracts value of label from pods with key `label2` with regexp and inserts it as a tag with key `l2`
key: label2
regex: field=(?P<value>.+)
from: pod
- tag_name: l3 # extracts value of label from nodes with key `label3` and inserts it as a tag with key `l3`
key: label3
from: node
Config example
k8sattributes:
k8sattributes/2:
auth_type: "serviceAccount"
passthrough: false
filter:
node_from_env_var: KUBE_NODE_NAME
extract:
metadata:
- k8s.pod.name
- k8s.pod.uid
- k8s.deployment.name
- k8s.namespace.name
- k8s.node.name
- k8s.pod.start_time
labels:
- tag_name: app.label.component
key: app.kubernetes.io/component
from: pod
pod_association:
- sources:
- from: resource_attribute
name: k8s.pod.ip
- sources:
- from: resource_attribute
name: k8s.pod.uid
- sources:
- from: connection
Role-based access control
Cluster-scoped RBAC
If you'd like to set up the k8sattributesprocessor to receive telemetry from across namespaces, it will need get, watch and list permissions on both pods and namespaces resources, for all namespaces and pods included in the configured filters. Additionally, when using k8s.deployment.name (which is enabled by default) or k8s.deployment.uid the processor also needs get, watch and list permissions for replicasets resources. When using k8s.node.uid or extracting metadata from node, the processor needs get, watch and list permissions for nodes resources.
Here is an example of a ClusterRole to give a ServiceAccount the necessary permissions for all pods, nodes, and namespaces in the cluster (replace <OTEL_COL_NAMESPACE> with a namespace where collector is deployed):
apiVersion: v1
kind: ServiceAccount
metadata:
name: collector
namespace: <OTEL_COL_NAMESPACE>
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRole
metadata:
name: otel-collector
rules:
- apiGroups: [""]
resources: ["pods", "namespaces", "nodes"]
verbs: ["get", "watch", "list"]
- apiGroups: ["apps"]
resources: ["replicasets"]
verbs: ["get", "list", "watch"]
- apiGroups: ["extensions"]
resources: ["replicasets"]
verbs: ["get", "list", "watch"]
---
apiVersion: rbac.authorization.k8s.io/v1
kind: ClusterRoleBinding
metadata:
name: otel-collector
subjects:
- kind: ServiceAccount
name: collector
namespace: <OTEL_COL_NAMESPACE>
roleRef:
kind: ClusterRole
name: otel-collector
apiGroup: rbac.authorization.k8s.io
Namespace-scoped RBAC
When running the k8sattributesprocessor to receive telemetry traffic from pods in a specific namespace, you can use a k8s Role and Rolebinding to provide collector access to query pods and replicasets in the namespace. This would require setting the filter::namespace config as shown below.
k8sattributes:
filter:
namespace: <WORKLOAD_NAMESPACE>
With the namespace filter set, the processor will only look up pods and replicasets in the selected namespace. Note that with just a role binding, the processor can not query metadata such as labels and annotations from k8s nodes and namespaces which are cluster-scoped objects. This also means that the processor can not set the value for k8s.cluster.uid attribute if enabled, since the k8s.cluster.uid attribute is set to the uid of the namespace kube-system which is not queryable with namespaced rbac.
Example Role and RoleBinding to create in the namespace being watched.
apiVersion: v1
kind: ServiceAccount
metadata:
name: otel-collector
namespace: <OTEL_COL_NAMESPACE>
---
apiVersion: rbac.authorization.k8s.io/v1
kind: Role
metadata:
name: otel-collector
namespace: <WORKLOAD_NAMESPACE>
rules:
- apiGroups: [""]
resources: ["pods"]
verbs: ["get", "watch", "list"]
- apiGroups: ["apps"]
resources: ["replicasets"]
verbs: ["get", "list", "watch"]
---
apiVersion: rbac.authorization.k8s.io/v1
kind: RoleBinding
metadata:
name: otel-collector
namespace: <WORKLOAD_NAMESPACE>
subjects:
- kind: ServiceAccount
name: otel-collector
namespace: <OTEL_COL_NAMESPACE>
roleRef:
kind: Role
name: otel-collector
apiGroup: rbac.authorization.k8s.io
Deployment scenarios
The processor can be used in collectors deployed both as an agent (Kubernetes DaemonSet) or as a gateway (Kubernetes Deployment).
As an agent
When running as an agent, the processor detects IP addresses of pods sending spans, metrics or logs to the agent and uses this information to extract metadata from pods. When running as an agent, it is important to apply a discovery filter so that the processor only discovers pods from the same host that it is running on. Not using such a filter can result in unnecessary resource usage especially on very large clusters. Once the filter is applied, each processor will only query the k8s API for pods running on it's own node.
Node filter can be applied by setting the filter.node config option to the name of a k8s node. While this works
as expected, it cannot be used to automatically filter pods by the same node that the processor is running on in
most cases as it is not know before hand which node a pod will be scheduled on. Luckily, kubernetes has a solution
for this called the downward API. To automatically filter pods by the node the processor is running on, you'll need
to complete the following steps:
- Use the downward API to inject the node name as an environment variable. Add the following snippet under the pod env section of the OpenTelemetry container.
spec:
containers:
- env:
- name: KUBE_NODE_NAME
valueFrom:
fieldRef:
apiVersion: v1
fieldPath: spec.nodeName
This will inject a new environment variable to the OpenTelemetry container with the value as the name of the node the pod was scheduled to run on.
- Set "filter.node_from_env_var" to the name of the environment variable holding the node name.
k8sattributes:
filter:
node_from_env_var: KUBE_NODE_NAME # this should be same as the var name used in previous step
This will restrict each OpenTelemetry agent to query pods running on the same node only dramatically reducing resource requirements for very large clusters.
As a gateway
When running as a gateway, the processor cannot correctly detect the IP address of the pods generating the telemetry data without any of the well-known IP attributes, when it receives them from an agent instead of receiving them directly from the pods. To workaround this issue, agents deployed with the k8sattributes processor can be configured to detect the IP addresses and forward them along with the telemetry data resources. Collector can then match this IP address with k8s pods and enrich the records with the metadata. In order to set this up, you'll need to complete the following steps:
- Setup agents in passthrough mode Configure the agents' k8sattributes processors to run in passthrough mode.
# k8sattributes config for agent
k8sattributes:
passthrough: true
This will ensure that the agents detect the IP address as add it as an attribute to all telemetry resources. Agents will not make any k8s API calls, do any discovery of pods or extract any metadata.
- Configure the collector as usual No special configuration changes are needed to be made on the collector. It'll automatically detect the IP address of spans, logs and metrics sent by the agents as well as directly by other services/pods.
Caveats
There are some edge-cases and scenarios where k8sattributes will not work properly.
Host networking mode
The processor cannot correct identify pods running in the host network mode and enriching telemetry data generated by such pods is not supported at the moment, unless the association rule is not based on IP attribute.
As a sidecar
The processor does not support detecting containers from the same pods when running as a sidecar. While this can be done, we think it is simpler to just use the kubernetes downward API to inject environment variables into the pods and directly use their values as tags.
Timestamp Format
By default, the k8s.pod.start_time uses Time.String() to format the
timestamp value.
The k8sattr.rfc3339 feature gate can be enabled to format the k8s.pod.start_time timestamp value with an RFC3339
compliant timestamp. See Time.MarshalText() for more information.
Documentation
¶
Index ¶
Constants ¶
This section is empty.
Variables ¶
This section is empty.
Functions ¶
func NewFactory ¶
NewFactory returns a new factory for the k8s processor.
Types ¶
type Config ¶
type Config struct {
k8sconfig.APIConfig `mapstructure:",squash"`
// Passthrough mode only annotates resources with the pod IP and
// does not try to extract any other metadata. It does not need
// access to the K8S cluster API. Agent/Collector must receive spans
// directly from services to be able to correctly detect the pod IPs.
Passthrough bool `mapstructure:"passthrough"`
// Extract section allows specifying extraction rules to extract
// data from k8s pod specs
Extract ExtractConfig `mapstructure:"extract"`
// Filter section allows specifying filters to filter
// pods by labels, fields, namespaces, nodes, etc.
Filter FilterConfig `mapstructure:"filter"`
// Association section allows to define rules for tagging spans, metrics,
// and logs with Pod metadata.
Association []PodAssociationConfig `mapstructure:"pod_association"`
// Exclude section allows to define names of pod that should be
// ignored while tagging.
Exclude ExcludeConfig `mapstructure:"exclude"`
}
Config defines configuration for k8s attributes processor.
type ExcludeConfig ¶
type ExcludeConfig struct {
Pods []ExcludePodConfig `mapstructure:"pods"`
}
ExcludeConfig represent a list of Pods to exclude
type ExcludePodConfig ¶
type ExcludePodConfig struct {
Name string `mapstructure:"name"`
}
ExcludePodConfig represent a Pod name to ignore
type ExtractConfig ¶
type ExtractConfig struct {
// Metadata allows to extract pod/namespace/node metadata from a list of metadata fields.
// The field accepts a list of strings.
//
// Metadata fields supported right now are,
// k8s.pod.name, k8s.pod.uid, k8s.deployment.name,
// k8s.node.name, k8s.namespace.name, k8s.pod.start_time,
// k8s.replicaset.name, k8s.replicaset.uid,
// k8s.daemonset.name, k8s.daemonset.uid,
// k8s.job.name, k8s.job.uid, k8s.cronjob.name,
// k8s.statefulset.name, k8s.statefulset.uid,
// k8s.container.name, container.image.name,
// container.image.tag, container.id
// k8s.cluster.uid
//
// Specifying anything other than these values will result in an error.
// By default, the following fields are extracted and added to spans, metrics and logs as resource attributes:
// - k8s.pod.name
// - k8s.pod.uid
// - k8s.pod.start_time
// - k8s.namespace.name
// - k8s.node.name
// - k8s.deployment.name (if the pod is controlled by a deployment)
// - k8s.container.name (requires an additional attribute to be set: container.id)
// - container.image.name (requires one of the following additional attributes to be set: container.id or k8s.container.name)
// - container.image.tag (requires one of the following additional attributes to be set: container.id or k8s.container.name)
Metadata []string `mapstructure:"metadata"`
// Annotations allows extracting data from pod annotations and record it
// as resource attributes.
// It is a list of FieldExtractConfig type. See FieldExtractConfig
// documentation for more details.
Annotations []FieldExtractConfig `mapstructure:"annotations"`
// Labels allows extracting data from pod labels and record it
// as resource attributes.
// It is a list of FieldExtractConfig type. See FieldExtractConfig
// documentation for more details.
Labels []FieldExtractConfig `mapstructure:"labels"`
}
ExtractConfig section allows specifying extraction rules to extract data from k8s pod specs.
type FieldExtractConfig ¶
type FieldExtractConfig struct {
// TagName represents the name of the resource attribute that will be added to logs, metrics or spans.
// When not specified, a default tag name will be used of the format:
// - k8s.pod.annotations.<annotation key>
// - k8s.pod.labels.<label key>
// For example, if tag_name is not specified and the key is git_sha,
// then the attribute name will be `k8s.pod.annotations.git_sha`.
// When key_regex is present, tag_name supports back reference to both named capturing and positioned capturing.
// For example, if your pod spec contains the following labels,
//
// app.kubernetes.io/component: mysql
// app.kubernetes.io/version: 5.7.21
//
// and you'd like to add tags for all labels with prefix app.kubernetes.io/ and also trim the prefix,
// then you can specify the following extraction rules:
//
// extract:
// labels:
// - tag_name: $$1
// key_regex: kubernetes.io/(.*)
//
// this will add the `component` and `version` tags to the spans or metrics.
TagName string `mapstructure:"tag_name"`
// Key represents the annotation (or label) name. This must exactly match an annotation (or label) name.
Key string `mapstructure:"key"`
// KeyRegex is a regular expression used to extract a Key that matches the regex.
// Out of Key or KeyRegex, only one option is expected to be configured at a time.
KeyRegex string `mapstructure:"key_regex"`
// Regex is an optional field used to extract a sub-string from a complex field value.
// The supplied regular expression must contain one named parameter with the string "value"
// as the name. For example, if your pod spec contains the following annotation,
//
// kubernetes.io/change-cause: 2019-08-28T18:34:33Z APP_NAME=my-app GIT_SHA=58a1e39 CI_BUILD=4120
//
// and you'd like to extract the GIT_SHA and the CI_BUILD values as tags, then you must
// specify the following two extraction rules:
//
// extract:
// annotations:
// - tag_name: git.sha
// key: kubernetes.io/change-cause
// regex: GIT_SHA=(?P<value>\w+)
// - tag_name: ci.build
// key: kubernetes.io/change-cause
// regex: JENKINS=(?P<value>[\w]+)
//
// this will add the `git.sha` and `ci.build` resource attributes.
Regex string `mapstructure:"regex"`
// From represents the source of the labels/annotations.
// Allowed values are "pod" and "namespace". The default is pod.
From string `mapstructure:"from"`
}
FieldExtractConfig allows specifying an extraction rule to extract a resource attribute from pod (or namespace) annotations (or labels).
type FieldFilterConfig ¶
type FieldFilterConfig struct {
// Key represents the key or name of the field or labels that a filter
// can apply on.
Key string `mapstructure:"key"`
// Value represents the value associated with the key that a filter
// operation specified by the `Op` field applies on.
Value string `mapstructure:"value"`
// Op represents the filter operation to apply on the given
// Key: Value pair. The following operations are supported
// equals, not-equals, exists, does-not-exist.
Op string `mapstructure:"op"`
}
FieldFilterConfig allows specifying exactly one filter by a field. It can be used to represent a label or generic field filter.
type FilterConfig ¶
type FilterConfig struct {
// Node represents a k8s node or host. If specified, any pods not running
// on the specified node will be ignored by the tagger.
Node string `mapstructure:"node"`
// NodeFromEnv can be used to extract the node name from an environment
// variable. The value must be the name of the environment variable.
// This is useful when the node a Otel agent will run on cannot be
// predicted. In such cases, the Kubernetes downward API can be used to
// add the node name to each pod as an environment variable. K8s tagger
// can then read this value and filter pods by it.
//
// For example, node name can be passed to each agent with the downward API as follows
//
// env:
// - name: K8S_NODE_NAME
// valueFrom:
// fieldRef:
// fieldPath: spec.nodeName
//
// Then the NodeFromEnv field can be set to `K8S_NODE_NAME` to filter all pods by the node that
// the agent is running on.
//
// More on downward API here: https://kubernetes.io/docs/tasks/inject-data-application/environment-variable-expose-pod-information/
NodeFromEnvVar string `mapstructure:"node_from_env_var"`
// Namespace filters all pods by the provided namespace. All other pods are ignored.
Namespace string `mapstructure:"namespace"`
// Fields allows to filter pods by generic k8s fields.
// Only the following operations are supported:
// - equals
// - not-equals
//
// Check FieldFilterConfig for more details.
Fields []FieldFilterConfig `mapstructure:"fields"`
// Labels allows to filter pods by generic k8s pod labels.
// Only the following operations are supported:
// - equals
// - not-equals
// - exists
// - not-exists
//
// Check FieldFilterConfig for more details.
Labels []FieldFilterConfig `mapstructure:"labels"`
}
FilterConfig section allows specifying filters to filter pods by labels, fields, namespaces, nodes, etc.
type PodAssociationConfig ¶
type PodAssociationConfig struct {
// List of pod association sources which should be taken
// to identify pod
Sources []PodAssociationSourceConfig `mapstructure:"sources"`
}
PodAssociationConfig contain single rule how to associate Pod metadata with logs, spans and metrics
Source Files
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