install kafka cluster in istio ,the pod can not be created
13567436138 opened this issue · 4 comments
13567436138 commented
We use GitHub issues to discuss Kafka operator bugs and new features.
For support requests please use the channels listed in SUPPORT.md
[root@node01 kafka_mesh]# kubectl get KafkaCluster --all-namespaces
NAMESPACE NAME CLUSTER STATE CLUSTER ALERT COUNT LAST SUCCESSFUL UPGRADE UPGRADE ERROR COUNT AGE
istio kafka ClusterReconciling 0 0 2m39s
apiVersion: kafka.banzaicloud.io/v1beta1
kind: KafkaCluster
metadata:
labels:
controller-tools.k8s.io: "1.0"
name: kafka
spec:
headlessServiceEnabled: false
ingressController: "istioingress"
istioControlPlane:
name: istiod
namespace: istio-system
istioIngressConfig:
gatewayConfig:
mode: ISTIO_MUTUAL
zkAddresses:
- "zookeeper-client.zookeeper:2181"
oneBrokerPerNode: false
clusterImage: "ghcr.io/banzaicloud/kafka:2.13-3.1.0"
readOnlyConfig: |
auto.create.topics.enable=false
cruise.control.metrics.topic.auto.create=true
cruise.control.metrics.topic.num.partitions=1
cruise.control.metrics.topic.replication.factor=2
brokerConfigGroups:
default:
brokerAnnotations:
sidecar.istio.io/userVolumeMount: '[{"name":"exitfile", "mountPath":"/var/run/wait", "readonly":true}]'
storageConfigs:
- mountPath: "/kafka-logs"
pvcSpec:
accessModes:
- ReadWriteOnce
resources:
requests:
storage: 10Gi
brokers:
- id: 0
brokerConfigGroup: "default"
- id: 1
brokerConfigGroup: "default"
- id: 2
brokerConfigGroup: "default"
rollingUpgradeConfig:
failureThreshold: 1
listenersConfig:
internalListeners:
- type: "plaintext"
name: "internal"
containerPort: 29092
usedForInnerBrokerCommunication: true
- type: "plaintext"
name: "controller"
containerPort: 29093
usedForInnerBrokerCommunication: false
usedForControllerCommunication: true
externalListeners:
- type: "plaintext"
name: "external"
externalStartingPort: 19090
containerPort: 9094
cruiseControlConfig:
topicConfig:
partitions: 12
replicationFactor: 3
config: |
# Copyright 2017 LinkedIn Corp. Licensed under the BSD 2-Clause License (the "License"). See License in the project root for license information.
#
# This is an example property file for Kafka Cruise Control. See KafkaCruiseControlConfig for more details.
# Configuration for the metadata client.
# =======================================
# The maximum interval in milliseconds between two metadata refreshes.
#metadata.max.age.ms=300000
# Client id for the Cruise Control. It is used for the metadata client.
#client.id=kafka-cruise-control
# The size of TCP send buffer bytes for the metadata client.
#send.buffer.bytes=131072
# The size of TCP receive buffer size for the metadata client.
#receive.buffer.bytes=131072
# The time to wait before disconnect an idle TCP connection.
#connections.max.idle.ms=540000
# The time to wait before reconnect to a given host.
#reconnect.backoff.ms=50
# The time to wait for a response from a host after sending a request.
#request.timeout.ms=30000
# Configurations for the load monitor
# =======================================
# The number of metric fetcher thread to fetch metrics for the Kafka cluster
num.metric.fetchers=1
# The metric sampler class
metric.sampler.class=com.linkedin.kafka.cruisecontrol.monitor.sampling.CruiseControlMetricsReporterSampler
# Configurations for CruiseControlMetricsReporterSampler
metric.reporter.topic.pattern=__CruiseControlMetrics
# The sample store class name
sample.store.class=com.linkedin.kafka.cruisecontrol.monitor.sampling.KafkaSampleStore
# The config for the Kafka sample store to save the partition metric samples
partition.metric.sample.store.topic=__KafkaCruiseControlPartitionMetricSamples
# The config for the Kafka sample store to save the model training samples
broker.metric.sample.store.topic=__KafkaCruiseControlModelTrainingSamples
# The replication factor of Kafka metric sample store topic
sample.store.topic.replication.factor=2
# The config for the number of Kafka sample store consumer threads
num.sample.loading.threads=8
# The partition assignor class for the metric samplers
metric.sampler.partition.assignor.class=com.linkedin.kafka.cruisecontrol.monitor.sampling.DefaultMetricSamplerPartitionAssignor
# The metric sampling interval in milliseconds
metric.sampling.interval.ms=120000
metric.anomaly.detection.interval.ms=180000
# The partition metrics window size in milliseconds
partition.metrics.window.ms=300000
# The number of partition metric windows to keep in memory
num.partition.metrics.windows=1
# The minimum partition metric samples required for a partition in each window
min.samples.per.partition.metrics.window=1
# The broker metrics window size in milliseconds
broker.metrics.window.ms=300000
# The number of broker metric windows to keep in memory
num.broker.metrics.windows=20
# The minimum broker metric samples required for a partition in each window
min.samples.per.broker.metrics.window=1
# The configuration for the BrokerCapacityConfigFileResolver (supports JBOD and non-JBOD broker capacities)
capacity.config.file=config/capacity.json
#capacity.config.file=config/capacityJBOD.json
# Configurations for the analyzer
# =======================================
# The list of goals to optimize the Kafka cluster for with pre-computed proposals
default.goals=com.linkedin.kafka.cruisecontrol.analyzer.goals.ReplicaCapacityGoal,com.linkedin.kafka.cruisecontrol.analyzer.goals.DiskCapacityGoal,com.linkedin.kafka.cruisecontrol.analyzer.goals.NetworkInboundCapacityGoal,com.linkedin.kafka.cruisecontrol.analyzer.goals.NetworkOutboundCapacityGoal,com.linkedin.kafka.cruisecontrol.analyzer.goals.CpuCapacityGoal,com.linkedin.kafka.cruisecontrol.analyzer.goals.ReplicaDistributionGoal,com.linkedin.kafka.cruisecontrol.analyzer.goals.PotentialNwOutGoal,com.linkedin.kafka.cruisecontrol.analyzer.goals.DiskUsageDistributionGoal,com.linkedin.kafka.cruisecontrol.analyzer.goals.NetworkInboundUsageDistributionGoal,com.linkedin.kafka.cruisecontrol.analyzer.goals.NetworkOutboundUsageDistributionGoal,com.linkedin.kafka.cruisecontrol.analyzer.goals.CpuUsageDistributionGoal,com.linkedin.kafka.cruisecontrol.analyzer.goals.TopicReplicaDistributionGoal,com.linkedin.kafka.cruisecontrol.analyzer.goals.LeaderBytesInDistributionGoal
# The list of supported goals
goals=com.linkedin.kafka.cruisecontrol.analyzer.goals.ReplicaCapacityGoal,com.linkedin.kafka.cruisecontrol.analyzer.goals.DiskCapacityGoal,com.linkedin.kafka.cruisecontrol.analyzer.goals.NetworkInboundCapacityGoal,com.linkedin.kafka.cruisecontrol.analyzer.goals.NetworkOutboundCapacityGoal,com.linkedin.kafka.cruisecontrol.analyzer.goals.CpuCapacityGoal,com.linkedin.kafka.cruisecontrol.analyzer.goals.ReplicaDistributionGoal,com.linkedin.kafka.cruisecontrol.analyzer.goals.PotentialNwOutGoal,com.linkedin.kafka.cruisecontrol.analyzer.goals.DiskUsageDistributionGoal,com.linkedin.kafka.cruisecontrol.analyzer.goals.NetworkInboundUsageDistributionGoal,com.linkedin.kafka.cruisecontrol.analyzer.goals.NetworkOutboundUsageDistributionGoal,com.linkedin.kafka.cruisecontrol.analyzer.goals.CpuUsageDistributionGoal,com.linkedin.kafka.cruisecontrol.analyzer.goals.TopicReplicaDistributionGoal,com.linkedin.kafka.cruisecontrol.analyzer.goals.LeaderBytesInDistributionGoal,com.linkedin.kafka.cruisecontrol.analyzer.kafkaassigner.KafkaAssignerDiskUsageDistributionGoal,com.linkedin.kafka.cruisecontrol.analyzer.goals.PreferredLeaderElectionGoal
# The list of supported hard goals
hard.goals=com.linkedin.kafka.cruisecontrol.analyzer.goals.ReplicaCapacityGoal,com.linkedin.kafka.cruisecontrol.analyzer.goals.DiskCapacityGoal,com.linkedin.kafka.cruisecontrol.analyzer.goals.NetworkInboundCapacityGoal,com.linkedin.kafka.cruisecontrol.analyzer.goals.NetworkOutboundCapacityGoal,com.linkedin.kafka.cruisecontrol.analyzer.goals.CpuCapacityGoal
# The minimum percentage of well monitored partitions out of all the partitions
min.monitored.partition.percentage=0.95
# The balance threshold for CPU
cpu.balance.threshold=1.1
# The balance threshold for disk
disk.balance.threshold=1.1
# The balance threshold for network inbound utilization
network.inbound.balance.threshold=1.1
# The balance threshold for network outbound utilization
network.outbound.balance.threshold=1.1
# The balance threshold for the replica count
replica.count.balance.threshold=1.1
# The capacity threshold for CPU in percentage
cpu.capacity.threshold=0.8
# The capacity threshold for disk in percentage
disk.capacity.threshold=0.8
# The capacity threshold for network inbound utilization in percentage
network.inbound.capacity.threshold=0.8
# The capacity threshold for network outbound utilization in percentage
network.outbound.capacity.threshold=0.8
# The threshold to define the cluster to be in a low CPU utilization state
cpu.low.utilization.threshold=0.0
# The threshold to define the cluster to be in a low disk utilization state
disk.low.utilization.threshold=0.0
# The threshold to define the cluster to be in a low network inbound utilization state
network.inbound.low.utilization.threshold=0.0
# The threshold to define the cluster to be in a low disk utilization state
network.outbound.low.utilization.threshold=0.0
# The metric anomaly percentile upper threshold
metric.anomaly.percentile.upper.threshold=90.0
# The metric anomaly percentile lower threshold
metric.anomaly.percentile.lower.threshold=10.0
# How often should the cached proposal be expired and recalculated if necessary
proposal.expiration.ms=60000
# The maximum number of replicas that can reside on a broker at any given time.
max.replicas.per.broker=10000
# The number of threads to use for proposal candidate precomputing.
num.proposal.precompute.threads=1
# the topics that should be excluded from the partition movement.
#topics.excluded.from.partition.movement
# Configurations for the executor
# =======================================
# The max number of partitions to move in/out on a given broker at a given time.
num.concurrent.partition.movements.per.broker=10
# The interval between two execution progress checks.
execution.progress.check.interval.ms=10000
# Configurations for anomaly detector
# =======================================
# The goal violation notifier class
anomaly.notifier.class=com.linkedin.kafka.cruisecontrol.detector.notifier.SelfHealingNotifier
# The metric anomaly finder class
metric.anomaly.finder.class=com.linkedin.kafka.cruisecontrol.detector.KafkaMetricAnomalyFinder
# The anomaly detection interval
anomaly.detection.interval.ms=10000
# The goal violation to detect.
anomaly.detection.goals=com.linkedin.kafka.cruisecontrol.analyzer.goals.ReplicaCapacityGoal,com.linkedin.kafka.cruisecontrol.analyzer.goals.DiskCapacityGoal,com.linkedin.kafka.cruisecontrol.analyzer.goals.NetworkInboundCapacityGoal,com.linkedin.kafka.cruisecontrol.analyzer.goals.NetworkOutboundCapacityGoal,com.linkedin.kafka.cruisecontrol.analyzer.goals.CpuCapacityGoal
# The interested metrics for metric anomaly analyzer.
metric.anomaly.analyzer.metrics=BROKER_PRODUCE_LOCAL_TIME_MS_MAX,BROKER_PRODUCE_LOCAL_TIME_MS_MEAN,BROKER_CONSUMER_FETCH_LOCAL_TIME_MS_MAX,BROKER_CONSUMER_FETCH_LOCAL_TIME_MS_MEAN,BROKER_FOLLOWER_FETCH_LOCAL_TIME_MS_MAX,BROKER_FOLLOWER_FETCH_LOCAL_TIME_MS_MEAN,BROKER_LOG_FLUSH_TIME_MS_MAX,BROKER_LOG_FLUSH_TIME_MS_MEAN
## Adjust accordingly if your metrics reporter is an older version and does not produce these metrics.
#metric.anomaly.analyzer.metrics=BROKER_PRODUCE_LOCAL_TIME_MS_50TH,BROKER_PRODUCE_LOCAL_TIME_MS_999TH,BROKER_CONSUMER_FETCH_LOCAL_TIME_MS_50TH,BROKER_CONSUMER_FETCH_LOCAL_TIME_MS_999TH,BROKER_FOLLOWER_FETCH_LOCAL_TIME_MS_50TH,BROKER_FOLLOWER_FETCH_LOCAL_TIME_MS_999TH,BROKER_LOG_FLUSH_TIME_MS_50TH,BROKER_LOG_FLUSH_TIME_MS_999TH
# The zk path to store failed broker information.
failed.brokers.zk.path=/CruiseControlBrokerList
# Topic config provider class
topic.config.provider.class=com.linkedin.kafka.cruisecontrol.config.KafkaTopicConfigProvider
# The cluster configurations for the KafkaTopicConfigProvider
cluster.configs.file=config/clusterConfigs.json
# The maximum time in milliseconds to store the response and access details of a completed user task.
completed.user.task.retention.time.ms=21600000
# The maximum time in milliseconds to retain the demotion history of brokers.
demotion.history.retention.time.ms=86400000
# The maximum number of completed user tasks for which the response and access details will be cached.
max.cached.completed.user.tasks=100
# The maximum number of user tasks for concurrently running in async endpoints across all users.
max.active.user.tasks=25
# Enable self healing for all anomaly detectors, unless the particular anomaly detector is explicitly disabled
self.healing.enabled=true
# Enable self healing for broker failure detector
#self.healing.broker.failure.enabled=true
# Enable self healing for goal violation detector
#self.healing.goal.violation.enabled=true
# Enable self healing for metric anomaly detector
#self.healing.metric.anomaly.enabled=true
# configurations for the webserver
# ================================
# HTTP listen port
webserver.http.port=9090
# HTTP listen address
webserver.http.address=0.0.0.0
# Whether CORS support is enabled for API or not
webserver.http.cors.enabled=false
# Value for Access-Control-Allow-Origin
webserver.http.cors.origin=http://localhost:8080/
# Value for Access-Control-Request-Method
webserver.http.cors.allowmethods=OPTIONS,GET,POST
# Headers that should be exposed to the Browser (Webapp)
# This is a special header that is used by the
# User Tasks subsystem and should be explicitly
# Enabled when CORS mode is used as part of the
# Admin Interface
webserver.http.cors.exposeheaders=User-Task-ID
# REST API default prefix
# (dont forget the ending *)
webserver.api.urlprefix=/kafkacruisecontrol/*
# Location where the Cruise Control frontend is deployed
webserver.ui.diskpath=./cruise-control-ui/dist/
# URL path prefix for UI
# (dont forget the ending *)
webserver.ui.urlprefix=/*
# Time After which request is converted to Async
webserver.request.maxBlockTimeMs=10000
# Default Session Expiry Period
webserver.session.maxExpiryTimeMs=60000
# Session cookie path
webserver.session.path=/
# Server Access Logs
webserver.accesslog.enabled=true
# Location of HTTP Request Logs
webserver.accesslog.path=access.log
# HTTP Request Log retention days
webserver.accesslog.retention.days=14
clusterConfig: |
{
"min.insync.replicas": 3
}
Thanks!
stoader commented
Please attach your koperator, istio-oprator and istiod logs. Also, your IstioControlPlane custom resource.
pdaxjohnventura commented
Hi, I've been having the same trouble, I followed the document to setup https://banzaicloud.com/docs/supertubes/kafka-operator/install-kafka-operator/ , everything runs well if i use this yaml file to run the kafka brokers https://github.com/banzaicloud/koperator/blob/master/config/samples/simplekafkacluster.yaml; However if i use this one https://github.com/banzaicloud/koperator/blob/master/config/samples/kafkacluster-with-istio.yaml there aren't any kafka brokers created and only this two pods are shown running without any errors.
stoader commented
The https://github.com/banzaicloud/koperator/blob/master/config/samples/kafkacluster-with-istio.yaml requires to have an Istio mesh deployed into your Kubernetes cluster using https://github.com/banzaicloud/istio-operator/tree/v2.11.7
Can you confirm that you deployed Istio first and is up and running? If so please attach you koperator, istio-operator logs and also your IstioControlPlane custom resource.
stoader commented
Closing this ticket as did not receive the requested info which is needed to further investigate this issue and rule out that is not a user error.