Collector Configuration

Overview

The OpenTelemetry Collector configuration defines how telemetry data is received, processed, and exported. KloudMate Agent includes platform-optimized configurations for host monitoring, Docker containers, and Kubernetes clusters.

All collector configurations follow the standard OpenTelemetry Collector configuration format.

Configuration Templates

KloudMate Agent ships with three pre-configured templates:

Host Mode

System monitoring for bare metal and VMs

Docker Mode

Container metrics and log collection

Kubernetes Mode

Pod, container, and cluster monitoring

Configuration Structure

Every collector configuration has four main sections:

Basic Structure

receivers:
  # Components that receive telemetry data
  
processors:
  # Components that transform telemetry data
  
exporters:
  # Components that send telemetry data
  
service:
  # Defines pipelines connecting receivers, processors, and exporters

Host Mode Configuration

Optimized for monitoring physical servers and virtual machines:

~/workspace/source/configs/host-col-config.yaml

receivers:
  hostmetrics:
    collection_interval: 60s
    scrapers:
      cpu:
        metrics:
          system.cpu.utilization:
            enabled: true
      load:
        cpu_average: true
      memory:
        metrics:
          system.memory.utilization:
            enabled: true
      filesystem:
        metrics:
          system.filesystem.usage:
            enabled: true
          system.filesystem.utilization:
            enabled: true
      disk: {}
      network: {}            
  otlp:
    protocols:
      grpc:
        endpoint: 0.0.0.0:4317
      http:
        endpoint: 0.0.0.0:4318

Host Receivers

hostmetrics - System Metrics Collection

Collects system-level metrics from the host.

collection_interval

duration

default:"60s"

How often to collect metrics from the system.

scrapers

object

required

Individual metric scrapers to enable:cpu: CPU utilization and frequency

system.cpu.utilization: Per-core and total CPU usage
system.cpu.frequency: Current CPU frequency
system.cpu.logical.count: Number of logical CPUs

load: System load averages

system.cpu.load_average.1m: 1-minute load average
system.cpu.load_average.5m: 5-minute load average
system.cpu.load_average.15m: 15-minute load average

memory: RAM utilization

system.memory.usage: Memory used by state (used, cached, free, etc.)
system.memory.utilization: Memory utilization percentage

filesystem: Disk usage

system.filesystem.usage: Bytes used per mount point
system.filesystem.utilization: Disk utilization percentage

disk: Disk I/O

system.disk.io: Read/write bytes
system.disk.operations: Read/write operations

network: Network I/O

system.network.io: Bytes transmitted/received
system.network.packets: Packets transmitted/received
system.network.errors: Network errors

otlp - Application Telemetry Receiver

Receives telemetry from instrumented applications via OTLP protocol.

protocols.grpc.endpoint

string

default:"0.0.0.0:4317"

gRPC endpoint for OTLP protocol.

protocols.http.endpoint

string

default:"0.0.0.0:4318"

HTTP endpoint for OTLP protocol.

Use cases:

Receiving traces from OpenTelemetry SDKs
Receiving metrics from application exporters
Receiving logs from log forwarders

Host Processors

~/workspace/source/configs/host-col-config.yaml:44-102

processors:
  batch:
    send_batch_size: 10000
    timeout: 10s
  resourcedetection:
    detectors: [system]
    system:
      resource_attributes:
        host.name:
          enabled: true
        host.id:
          enabled: true
        os.type:
          enabled: false
  resource:
    attributes:
      - key: service.name
        action: insert
        from_attribute: host.name
  cumulativetodelta:
    include:
      match_type: strict
      metrics:
        - system.network.io
        - system.disk.io
        - system.disk.operations.rate
        - system.network.packets.rate
        - system.network.errors.rate
        - system.network.dropped.rate
  deltatorate:
    metrics:
      - system.network.io
      - system.disk.io
      - system.disk.operations.rate
      - system.network.packets.rate
      - system.network.errors.rate
      - system.network.dropped.rate

batch - Batching Processor

Buffers telemetry data before sending to reduce network overhead.

send_batch_size

integer

default:"8192"

Number of spans/metrics/logs to batch before sending.

timeout

duration

default:"200ms"

Maximum time to wait before sending a batch (even if incomplete).

Optimization: Higher batch sizes reduce network overhead but increase memory usage and latency.

resourcedetection - Resource Detection

Automatically detects and adds resource attributes from the environment.

detectors

array

required

List of detection methods: system, env, docker, gcp, aws, azure

Detected attributes:

host.name: Hostname from OS
host.id: Unique host identifier
host.arch: CPU architecture
os.type: Operating system type

resource - Resource Manipulation

Adds, updates, or deletes resource attributes.

resource:
  attributes:
    - key: service.name
      action: insert
      from_attribute: host.name
    - key: environment
      action: insert
      value: production

Actions:

insert: Add attribute if not exists
update: Update attribute if exists
upsert: Insert or update
delete: Remove attribute

cumulativetodelta - Cumulative to Delta Conversion

Converts cumulative metrics (counters) to delta values for rate calculation.

include.metrics

array

required

List of metric names to convert.

Required for: Network I/O, disk I/O, and other counter metrics that need rate calculation.

deltatorate - Delta to Rate Conversion

Converts delta values to per-second rates.Example: Converts “bytes transferred in last minute” to “bytes per second”.

transform - Metric Transformation

Advanced metric manipulation using transformation language.

transform/ratecalculation/copymetric:
  error_mode: ignore
  metric_statements:
    - context: metric
      statements:
        - copy_metric(name="system.network.io.rate") where metric.name == "system.network.io"

See full implementation in ~/workspace/source/configs/host-col-config.yaml:81-102

Host Exporters

~/workspace/source/configs/host-col-config.yaml:32-42

exporters:
  debug:
    verbosity: basic
  otlphttp:
    sending_queue:
      enabled: true
      num_consumers: 10
      queue_size: 10000
    endpoint: ${env:KM_COLLECTOR_ENDPOINT}
    headers:
        Authorization: ${env:KM_API_KEY}

debug - Debug Exporter

Logs telemetry data to console for debugging.

verbosity

string

default:"basic"

Logging verbosity: basic, normal, detailed

Disable in production to avoid performance impact.

otlphttp - OTLP HTTP Exporter

Sends telemetry to KloudMate backend via OTLP/HTTP protocol.

endpoint

string

required

Backend endpoint URL. Uses ${env:KM_COLLECTOR_ENDPOINT} environment variable.

headers

object

HTTP headers sent with every request. Typically includes Authorization for API key.

sending_queue.enabled

boolean

default:"true"

Enable persistent queue for retry on failure.

sending_queue.num_consumers

integer

default:"10"

Number of parallel workers sending data.

sending_queue.queue_size

integer

default:"5000"

Maximum number of batches to queue before dropping.

Host Pipelines

~/workspace/source/configs/host-col-config.yaml:107-124

service:
  telemetry:
    metrics:
      level: none
  pipelines:
    metrics:
      receivers: [otlp, hostmetrics]
      processors: [resourcedetection, resource, cumulativetodelta, deltatorate, transform/ratecalculation/sumtogauge, transform/ratecalculation/copymetric, batch]
      exporters: [debug, otlphttp]
    logs:
      receivers: [otlp]
      processors: [resourcedetection, resource, batch]
      exporters: [debug, otlphttp]
    traces:
      receivers: [otlp]
      processors: [resourcedetection, resource, batch]
      exporters: [debug, otlphttp]

Docker Mode Configuration

Optimized for monitoring Docker containers and host system:

~/workspace/source/configs/docker-col-config.yaml:22-25

receivers:
  docker_stats:
    endpoint: "unix:///var/run/docker.sock"
    collection_interval: 60s
    timeout: 10s

Docker-Specific Receivers

docker_stats - Container Metrics

Collects metrics from running Docker containers via Docker API.

endpoint

string

required

Docker daemon socket endpoint.Default: unix:///var/run/docker.sock

collection_interval

duration

default:"60s"

How often to collect container metrics.

timeout

duration

default:"10s"

Timeout for Docker API requests.

Collected metrics:

container.cpu.usage.total: Container CPU usage
container.memory.usage.total: Container memory usage
container.memory.usage.limit: Container memory limit
container.network.io.usage.rx_bytes: Network bytes received
container.network.io.usage.tx_bytes: Network bytes transmitted
container.blockio.io_service_bytes_recursive: Disk I/O

Requires Docker socket to be mounted: -v /var/run/docker.sock:/var/run/docker.sock:ro

filelog - Container Log Collection

Collects logs from container log files and system logs.

~/workspace/source/configs/docker-col-config.yaml:3-20

filelog:
  include:
    - /var/log/**/*.log
    - /var/lib/docker/containers/**/*.log*
    - ${env:FILELOG_PATHS}
  exclude:
    - /var/log/kmagent*/**/*.log
    - '**/*.gz'
    - '**/*.zip'
    - '**/*.tar'
    - '**/*.xz'
    - '**/.*'
    - '**/*.tmp'
    - '**/*~'
  include_file_name_resolved: true
  include_file_path: true
  include_file_path_resolved: true
  max_log_size: "1MiB"

include

array

required

Glob patterns for log files to monitor.

exclude

array

Glob patterns for log files to ignore.

max_log_size

string

default:"1MiB"

Maximum size of a single log entry.

hostmetrics - Host System Metrics

Collects host-level metrics from the Docker host.

~/workspace/source/configs/docker-col-config.yaml:27-85

hostmetrics:
  collection_interval: 60s
  root_path: /hostfs
  scrapers:
    cpu:
    memory:
    disk:
    network:
    filesystem:
      exclude_fs_types:
        fs_types:
          - autofs
          - binfmt_misc
          - overlay
          - proc
          - sysfs
      exclude_mount_points:
        mount_points:
          - /dev/*
          - /sys/*
          - /var/lib/docker/*

root_path

string

default:"/"

Root filesystem path. In Docker, the host filesystem is typically mounted at /hostfs.

Requires host filesystem mount: -v /:/hostfs:ro

Docker Pipelines

~/workspace/source/configs/docker-col-config.yaml:162-170

service:
  pipelines:
    metrics:
      receivers: [hostmetrics, docker_stats]
      processors: [resourcedetection, resource, cumulativetodelta, deltatorate, transform/ratecalculation/sumtogauge, transform/ratecalculation/copymetric, batch]
      exporters: [otlphttp, debug]
    logs:
      receivers: [filelog]
      processors: [resourcedetection, resource, batch]
      exporters: [otlphttp, debug]

Kubernetes Mode Configuration

Optimized for Kubernetes cluster monitoring via DaemonSet:

Kubernetes Receivers

kubeletstats - Pod & Container Metrics

Collects metrics from Kubelet Stats API.

~/workspace/source/configs/daemonset-col-config.yaml:511-543

kubeletstats:
  auth_type: serviceAccount
  collection_interval: 30s
  endpoint: ${env:KM_NODE_NAME}:10250
  extra_metadata_labels:
    - container.id
  insecure_skip_verify: true
  k8s_api_config:
    auth_type: serviceAccount
  metric_groups:
    - volume
    - node
    - pod
    - container
  metrics:
    k8s.container.cpu_limit_utilization:
      enabled: true
    k8s.container.cpu_request_utilization:
      enabled: true
    k8s.container.memory_limit_utilization:
      enabled: true
    k8s.container.memory_request_utilization:
      enabled: true

auth_type

string

default:"serviceAccount"

Authentication method for Kubelet API: serviceAccount, tls, none

endpoint

string

required

Kubelet endpoint. Uses ${env:KM_NODE_NAME}:10250 to connect to local node’s Kubelet.

metric_groups

array

required

Groups of metrics to collect: node, pod, container, volume

Collected metrics:

k8s.node.cpu.utilization: Node CPU usage
k8s.node.memory.usage: Node memory usage
k8s.pod.cpu.utilization: Pod CPU usage
k8s.pod.memory.usage: Pod memory usage
k8s.container.cpu.utilization: Container CPU usage
k8s.container.memory.usage: Container memory usage
k8s.volume.available: Volume available bytes
k8s.volume.capacity: Volume total capacity

filelog/containers - Pod Log Collection

Collects logs from Kubernetes pod containers.

~/workspace/source/configs/daemonset-col-config.yaml:248-257

filelog/containers:
  exclude:
    - /**/*.gz
    - /var/log/pods/km-agent_*/**/*.log
    - ${env:KM_XLOG_PATHS:-/___no_exclude___}
  include:
    - /var/log/pods/*/*/*.log
  include_file_name_resolved: true
  include_file_path: true
  include_file_path_resolved: true
  max_log_size: 1MiB

include

array

required

Glob patterns for pod log files. Default: /var/log/pods/*/*/*.log

exclude

array

Patterns to exclude (agent’s own logs, compressed files, etc.)

Log operators: The receiver includes 20+ operators for parsing JSON logs, extracting timestamps, log levels, trace context, and more.See full implementation in ~/workspace/source/configs/daemonset-col-config.yaml:259-424

hostmetrics - Node System Metrics

Collects host-level metrics from Kubernetes nodes.

~/workspace/source/configs/daemonset-col-config.yaml:425-506

hostmetrics:
  collection_interval: 60s
  scrapers:
    cpu:
    disk:
    filesystem:
      exclude_fs_types:
        fs_types:
          - overlay
          - proc
          - sysfs
      exclude_mount_points:
        mount_points:
          - /var/lib/kubelet/*
    load:
    memory:
    network:
    paging:
    process:
    processes:
    system:

Kubernetes Processors

k8sattributes - Kubernetes Metadata Enrichment

Adds Kubernetes-specific attributes to telemetry data.

~/workspace/source/configs/daemonset-col-config.yaml:80-108

k8sattributes:
  auth_type: serviceAccount
  passthrough: false
  filter:
    node_from_env_var: KM_NODE_NAME
  extract:
    metadata:
      - k8s.pod.name
      - k8s.pod.uid
      - k8s.deployment.name
      - k8s.namespace.name
      - k8s.node.name
      - k8s.pod.start_time
      - k8s.statefulset.uid
      - k8s.replicaset.uid
      - k8s.daemonset.uid
      - k8s.deployment.uid
      - k8s.job.uid
      - k8s.pod.ip
  pod_association:
    - sources:
        - from: resource_attribute
          name: k8s.pod.uid

auth_type

string

default:"serviceAccount"

Kubernetes API authentication method.

filter.node_from_env_var

string

Filter to only process pods from the node specified in this environment variable (for DaemonSet deployments).

extract.metadata

array

required

List of Kubernetes metadata attributes to extract and add to telemetry.

Extracted attributes:

Pod: name, UID, namespace, IP, start time
Owner: Deployment, DaemonSet, StatefulSet, ReplicaSet, Job
Node: name
Container: name

attributes - Attribute Manipulation

Adds or modifies specific attributes.

~/workspace/source/configs/daemonset-col-config.yaml:10-46

attributes/metrics:
  actions:
    - key: k8s.cluster.name
      value: ${env:KM_CLUSTER_NAME}
      action: insert

attributes/logs:
  actions:
    - key: k8s.cluster.name
      from_attribute: k8s.cluster.name
      action: upsert
    - key: service.namespace
      from_attribute: k8s.namespace.name
      action: upsert

Common use cases:

Add cluster name to all metrics
Copy Kubernetes namespace to service.namespace
Set service instance ID from pod UID

metricstransform/system - Metric Transformations

Advanced metric manipulation for Kubernetes-specific calculations.

~/workspace/source/configs/daemonset-col-config.yaml:109-154

metricstransform/system:
  transforms:
    - action: insert
      experimental_match_labels:
        os.type: linux
      include: system.memory.utilization
      match_type: strict
      new_name: system.memory.utilization.consumed
      operations:
        - action: aggregate_label_values
          aggregated_values:
            - used
            - cached
          aggregation_type: sum
          label: state
          new_value: consumed

Example: Combines “used” and “cached” memory states into a single “consumed” metric for Linux systems.

transform - OTTL Transformations

Uses OpenTelemetry Transformation Language for complex log and metric processing.

~/workspace/source/configs/daemonset-col-config.yaml:193-206

transform/addservicename:
  error_mode: ignore
  log_statements:
    - context: log
      statements:
        - set(attributes["service.name"], resource.attributes["k8s.container.name"]) where resource.attributes["k8s.container.name"] != nil

Common transformations:

Extract service name from container name
Copy attributes between resource and log/metric contexts
Delete temporary attributes

groupbyattrs - Attribute-based Grouping

Groups logs by specific attributes for better correlation.

~/workspace/source/configs/daemonset-col-config.yaml:77-79

groupbyattrs/filelog:
  keys:
    - k8s.pod.uid

Use case: Groups logs from the same pod together for better trace correlation.

Kubernetes Pipelines

~/workspace/source/configs/daemonset-col-config.yaml:544-602

service:
  pipelines:
    logs/containers:
      receivers:
        - filelog/containers
      processors:
        - resource
        - resource/add_node_name
        - resource/cluster
        - attributes/logs
        - groupbyattrs/filelog
        - k8sattributes
        - transform/addservicename
        - transform/copyservicefromlogattributes
        - batch
      exporters:
        - otlphttp
    
    metrics/hostmetrics:
      receivers:
        - hostmetrics
      processors:
        - resourcedetection
        - resource
        - resource/hostmetrics
        - resource/cluster
        - k8sattributes
        - transform/ostype
        - attributes/logs
        - metricstransform/system
        - transform/deleteostype
        - attributes/metrics
        - transform/ratecalculation/copymetric
        - cumulativetodelta
        - deltatorate
        - transform/ratecalculation/sumtogauge
        - batch
      exporters:
        - otlphttp
    
    metrics/kubeletstats:
      receivers:
        - kubeletstats
      processors:
        - resourcedetection
        - resource/add_node_name
        - resource
        - k8sattributes
        - resource/cluster
        - attributes/logs
        - transform/ratecalculation/copymetric
        - transform/ratecalculation/sumtogauge
        - attributes/metrics
        - batch
      exporters:
        - otlphttp

Advanced Configuration

Custom Processors

You can add custom processors to existing pipelines:

processors:
  probabilistic_sampler:
    sampling_percentage: 10  # Sample 10% of traces

service:
  pipelines:
    traces:
      processors: [probabilistic_sampler, batch, resourcedetection]

Resource Detection

Enable additional resource detectors:

Extended Resource Detection

processors:
  resourcedetection:
    detectors:
      - env        # Environment variables
      - system     # Host information
      - docker     # Docker container info
      - gcp        # Google Cloud Platform
      - ec2        # AWS EC2
      - ecs        # AWS ECS
      - azure      # Azure
    timeout: 5s
    override: false

Multi-Backend Exporters

Send telemetry to multiple backends:

Multiple Exporters

exporters:
  otlphttp/kloudmate:
    endpoint: ${env:KM_COLLECTOR_ENDPOINT}
    headers:
      Authorization: ${env:KM_API_KEY}
  
  otlphttp/backup:
    endpoint: https://backup-collector.company.com:4318
    headers:
      Authorization: ${env:BACKUP_API_KEY}
  
  prometheus:
    endpoint: "0.0.0.0:8889"
    namespace: km_agent

service:
  pipelines:
    metrics:
      receivers: [hostmetrics]
      processors: [batch]
      exporters: [otlphttp/kloudmate, otlphttp/backup, prometheus]

Memory Limiter

Prevent OOM by limiting memory usage:

Memory Protection

processors:
  memory_limiter:
    check_interval: 1s
    limit_mib: 512
    spike_limit_mib: 128

service:
  pipelines:
    metrics:
      processors: [memory_limiter, batch, resourcedetection]

Configuration Validation

Validate your configuration before deploying:

Syntax Validation

Check YAML syntax:

yamllint config.yaml

Schema Validation

Test configuration loading:

kmagent start --config=/path/to/config.yaml --dry-run

Component Validation

Verify all referenced components are available:

otelcol validate --config=/path/to/config.yaml

Always validate configurations in a test environment before deploying to production.

Environment Variable Reference

All collector configurations use these environment variables:

Required
Kubernetes
Optional

# Exporter endpoint
export KM_COLLECTOR_ENDPOINT="https://otel.kloudmate.com:4318"

# API key for authentication
export KM_API_KEY="your-api-key"

# Cluster identification
export KM_CLUSTER_NAME="production-cluster"

# Node name (set by Kubernetes)
export KM_NODE_NAME="node-01"

# Namespace (set by Kubernetes)
export KM_NAMESPACE="km-agent"

# Custom log paths (Docker mode)
export FILELOG_PATHS="/app/logs/**/*.log"

# Exclude log paths (Kubernetes mode)
export KM_XLOG_PATHS="/var/log/sensitive/**/*.log"

Troubleshooting

Collector Won't Start

Symptom: Collector fails to start with configuration errorCommon causes:

Invalid YAML syntax
Referenced component not available in distribution
Required environment variables not set
Exporter endpoint unreachable

Solution:

# Check logs
journalctl -u kmagent -n 50 --no-pager

# Validate YAML
yamllint /etc/kmagent/config.yaml

# Test connectivity
curl -v ${KM_COLLECTOR_ENDPOINT}

No Metrics Being Received

Symptom: Collector runs but no data appears in KloudMateCommon causes:

Receivers not configured correctly
Pipeline not connecting receivers to exporters
Batch processor timeout too long
Network/firewall blocking exporter

Solution:

# Enable debug exporter temporarily
# Add to exporters section:
exporters:
  debug:
    verbosity: detailed

# Add to pipeline:
service:
  pipelines:
    metrics:
      exporters: [debug, otlphttp]

# Check output
journalctl -u kmagent -f | grep -A 5 "ResourceMetrics"

High Memory Usage

Symptom: Collector consuming excessive memoryCommon causes:

Batch size too large
Queue size too large
No memory limiter configured
Too many metrics/logs being collected

Solution:

# Add memory limiter
processors:
  memory_limiter:
    check_interval: 1s
    limit_mib: 512

# Reduce batch size
processors:
  batch:
    send_batch_size: 1000
    timeout: 5s

# Reduce queue size
exporters:
  otlphttp:
    sending_queue:
      queue_size: 1000

Kubernetes Attributes Not Appearing

Symptom: Metrics/logs missing Kubernetes metadataCommon causes:

k8sattributes processor not in pipeline
ServiceAccount lacks required permissions
Pod association not configured
Wrong node filter in DaemonSet

Solution:

# Check ServiceAccount permissions
kubectl describe serviceaccount km-agent -n km-agent

# Check ClusterRole
kubectl describe clusterrole km-agent

# Verify k8sattributes processor
kubectl logs -n km-agent ds/km-agent | grep k8sattributes

Best Practices

Start Simple

Begin with minimal configuration and add components incrementally.

Use Memory Limiter

Always configure memory_limiter processor to prevent OOM.

Batch Aggressively

Use larger batch sizes (5000-10000) to reduce network overhead.

Monitor Collector

Enable collector’s own telemetry to monitor performance.

Test Changes

Always validate configuration changes in non-production first.

Version Control

Store configurations in Git for change tracking.

Next Steps

Agent Configuration

Configure agent behavior and authentication

Configuration Structure

Understand configuration architecture

CLI Commands

Configuration API

Overview

Configuration Templates

Host Mode

Docker Mode

Kubernetes Mode

Configuration Structure

Host Mode Configuration

Host Receivers

Host Processors

Host Exporters

Host Pipelines

Docker Mode Configuration

Docker-Specific Receivers

Docker Pipelines

Kubernetes Mode Configuration

Kubernetes Receivers

Kubernetes Processors

Kubernetes Pipelines

Advanced Configuration

Custom Processors

Resource Detection

Multi-Backend Exporters

Memory Limiter

Configuration Validation

Environment Variable Reference

Troubleshooting

Best Practices

Start Simple

Use Memory Limiter

Batch Aggressively

Monitor Collector

Test Changes

Version Control

Next Steps

Agent Configuration

Configuration Structure

Build docs developers (and LLMs) love

CLI Commands

Configuration API

​Overview

​Configuration Templates

Host Mode

Docker Mode

Kubernetes Mode

​Configuration Structure

​Host Mode Configuration

​Host Receivers

​Host Processors

​Host Exporters

​Host Pipelines

​Docker Mode Configuration

​Docker-Specific Receivers

​Docker Pipelines

​Kubernetes Mode Configuration

​Kubernetes Receivers

​Kubernetes Processors

​Kubernetes Pipelines

​Advanced Configuration

​Custom Processors

​Resource Detection

​Multi-Backend Exporters

​Memory Limiter

​Configuration Validation

​Environment Variable Reference

​Troubleshooting

​Best Practices

Start Simple

Use Memory Limiter

Batch Aggressively

Monitor Collector

Test Changes

Version Control

​Next Steps

Agent Configuration

Configuration Structure

Build docs developers (and LLMs) love

Overview

Configuration Templates

Configuration Structure

Host Mode Configuration

Host Receivers

Host Processors

Host Exporters

Host Pipelines

Docker Mode Configuration

Docker-Specific Receivers

Docker Pipelines

Kubernetes Mode Configuration

Kubernetes Receivers

Kubernetes Processors

Kubernetes Pipelines

Advanced Configuration

Custom Processors

Resource Detection

Multi-Backend Exporters

Memory Limiter

Configuration Validation

Environment Variable Reference

Troubleshooting

Best Practices

Next Steps