{"id":5808,"date":"2018-09-10T22:23:22","date_gmt":"2018-09-11T05:23:22","guid":{"rendered":"https:\/\/www.couchbase.com\/blog\/?p=5808"},"modified":"2025-06-13T23:43:03","modified_gmt":"2025-06-14T06:43:03","slug":"performance-certification-of-couchbase-server-5-5-on-kubernetes-platform","status":"publish","type":"post","link":"https:\/\/www.couchbase.com\/blog\/es\/performance-certification-of-couchbase-server-5-5-on-kubernetes-platform\/","title":{"rendered":"Certificaci\u00f3n del rendimiento de Couchbase Autonomous Operator en Kubernetes"},"content":{"rendered":"

En Couchbase nos tomamos el rendimiento muy en serio, y con el lanzamiento de nuestro nuevo producto, Couchbase Autonomous Operator 1.0, quer\u00edamos asegurarnos de que es de nivel empresarial y est\u00e1 listo para la producci\u00f3n para los clientes. <\/span><\/p>\n

En esta entrada del blog vamos a discutir los resultados detallados de rendimiento de la ejecuci\u00f3n de pruebas de rendimiento YCSB en Couchbase Server 5.5 utilizando el Operador Aut\u00f3nomo para desplegar en la plataforma Kubernetes. Una de las grandes preocupaciones de las empresas que planean ejecutar bases de datos en Kubernetes es el rendimiento. <\/span><\/p>\n

Este documento ofrece una comparaci\u00f3n r\u00e1pida de dos cargas de trabajo, a saber <\/span>YCSB A & E <\/span><\/a>con Couchbase Server 5.5 en Kubernetes <\/span>frente al metal desnudo.<\/span><\/p>\n

Carga de trabajo YCSB A<\/b>: <\/span>Esta carga de trabajo tiene una mezcla de 50\/50 lecturas y escrituras. Un ejemplo de aplicaci\u00f3n es un almac\u00e9n de sesiones que registra acciones recientes.<\/span><\/p>\n

Carga de trabajo E: Rangos cortos:\u00a0<\/b>En esta carga de trabajo, se consultan rangos cortos de registros, en lugar de registros individuales. Ejemplo de aplicaci\u00f3n: conversaciones hilvanadas, en las que cada b\u00fasqueda corresponde a los mensajes de un hilo determinado (se supone que se agrupan por identificador de hilo).<\/p>\n

En general, no observamos una degradaci\u00f3n significativa del rendimiento al ejecutar Couchbase Cluster en Kubernetes, <\/span>La carga de trabajo A tuvo un rendimiento a la par en comparaci\u00f3n con el metal desnudo y la carga de trabajo E tuvo aproximadamente menos de 10% de degradaci\u00f3n.\u00a0<\/span><\/p>\n

Configurar<\/b>:<\/span><\/p>\n

Para la configuraci\u00f3n, Couchbase se instal\u00f3 utilizando el despliegue Operator como se indica a continuaci\u00f3n. Para m\u00e1s detalles sobre la instalaci\u00f3n, consulte <\/span>aqu\u00ed<\/span><\/a><\/p>\n

\"\"<\/p>\n

Archivos:<\/b><\/p>\n

Despliegue del operador: deployment.yaml (V\u00e9ase el Ap\u00e9ndice)<\/span><\/p>\n

Despliegue de Couchbase: couchbase-cluster-simple-selector.yaml (Ver Ap\u00e9ndice)<\/span><\/p>\n

Despliegue del cliente\/generador de carga de trabajo: pillowfight-ycsb.yaml (Ver Ap\u00e9ndice) (Imagen docker oficial de pillowfight desde dockerhub e instalado java y YCSB manualmente sobre ella)<\/span><\/p>\n

Hardware:<\/b><\/p>\n

7 servidores<\/span><\/p>\n

24 CPU x 64 GB RAM por servidor<\/span><\/p>\n

Configuraci\u00f3n de Couchbase<\/b><\/p>\n

4 servidores: 2 nodos de datos, 2 nodos de \u00edndice+consulta<\/span><\/p>\n

Cuota de 40 GB de RAM para el servicio de datos<\/span><\/p>\n

Cuota de 40 GB de RAM para servicios de \u00edndice<\/span><\/p>\n

1 r\u00e9plica de datos\/cubo<\/span><\/p>\n

1 r\u00e9plica de \u00edndice primario<\/span><\/p>\n

Pruebas:<\/b><\/p>\n

YCSB Carga de trabajoA y Carga de trabajoE<\/span><\/p>\n

10 millones de documentos<\/span><\/p>\n

Flujo de trabajo tras inicializar un nuevo cl\u00faster k8s vac\u00edo en 7 servidores:<\/b><\/p>\n

# assign labels to the nodes so all services\/pods will be assigned to right servers:\r\n\r\nkubectl label nodes arke06-sa09 type=power\r\nkubectl label nodes arke07-sa10 type=client\r\nkubectl label nodes ark08-sa11 type=client\r\nkubectl label nodes arke01-sa04 type=kv\r\nkubectl label nodes arke00-sa03 type=kv\r\nkubectl label nodes arke02-sa05 type=kv\r\nkubectl label nodes arke03-sa06 type=kv\r\n<\/pre>\n
#deploy Operator:\r\n\r\nkubectl create -f deployment.yaml\r\n\r\n#deploy Couchbase\r\n\r\nkubectl create -f couchbase-cluster-simple-selector.yaml\r\n\r\n#deploy Client(s):\r\n\r\nkubectl create -f pillowfight-ycsb.yaml\r\n\r\nI ran my tests directly from the client node by logging into the docker image of the client pod:\r\n\r\ndocker exec -it --user root <pillowfight-yscb container id> bash\r\n\r\nAnd installing YCSB environment there manually:\r\n\r\napt-get upgrade\r\n\r\napt-get update\r\n\r\napt-get install -y software-properties-common\r\n\r\napt-get install python\r\n\r\nsudo apt-add-repository ppa:webupd8team\/java\r\n\r\nsudo apt-get update\r\n\r\nsudo apt-get install oracle-java8-installer\r\n\r\nexport JAVA_HOME=\/usr\/lib\/jvm\/java-8-oracle\r\n\r\ncd \/opt\r\n\r\nwget https:\/\/download.nextag.com\/apache\/maven\/maven-3\/3.5.4\/binaries\/apache-maven-3.5.4-bin.tar.gz\r\n\r\nsudo tar -xvzf apache-maven-3.5.4-bin.tar.gz\r\n\r\nexport M2_HOME=\"\/opt\/apache-maven-3.5.4\"\r\n\r\nexport PATH=$PATH:\/opt\/apache-maven-3.5.4\/bin\r\n\r\nsudo update-alternatives --install \"\/usr\/bin\/mvn\" \"mvn\" \"\/opt\/apache-maven-3.5.4\/bin\/mvn\" 0\r\n\r\nsudo update-alternatives --set mvn \/opt\/apache-maven-3.5.4\/bin\/mvn\r\n\r\ngit clone https:\/\/github.com\/couchbaselabs\/YCSB<\/pre>\n
 <\/p>\n
Ejecuci\u00f3n de las cargas de trabajo:<\/strong><\/p>\n
Examples of YCSB commands used in this exercise:\r\n\r\nWorkload A\r\n\r\nLoad:\r\n\r\n.\/bin\/ycsb load couchbase2 -P workloads\/workloade -p couchbase.password=password -p couchbase.host=10.44.0.2 -p couchbase.bucket=default -p couchbase.upsert=true -p couchbase.epoll=true -p couchbase.boost=48 -p couchbase.persistTo=0 -p couchbase.replicateTo=0 -p couchbase.sslMode=none -p writeallfields=true -p recordcount=10000000 -threads 50 -p maxexecutiontime=3600 -p operationcount=1000000000\r\n\r\nRun:\r\n\r\n.\/bin\/ycsb run couchbase2 -P workloads\/workloada -p couchbase.password=password -p couchbase.host=10.44.0.2 -p couchbase.bucket=default -p couchbase.upsert=true -p couchbase.epoll=true -p couchbase.boost=48 -p couchbase.persistTo=0 -p couchbase.replicateTo=0 -p couchbase.sslMode=none -p writeallfields=true -p recordcount=10000000 -threads 50 \u00a0-p operationcount=1000000000 -p maxexecutiontime=600 -p exportfile=ycsb_workloadA_22vCPU.log<\/pre>\n
 <\/p>\n
Resultados de las pruebas:<\/b><\/p>\n
\n\n\n\n\n\n
Env<\/b><\/td>\nConfiguraci\u00f3n directa<\/b><\/td>\nRecursos del pod Kubernetes<\/b><\/td>\nPrueba<\/b><\/td>\nMetal desnudo<\/b><\/td>\nKubernetes<\/b><\/td>\nDelta<\/b><\/td>\n<\/tr>\n
Env 1<\/span><\/td>\n22 vCPU, 48 GB RAM<\/span><\/p>\n
(los n\u00facleos de CPU y la RAM disponible se establecen en el nivel de n\u00facleo del sistema operativo)<\/span><\/td>\n
Limitar a:<\/span><\/p>\n
cpu: 22000m = ~22vCPU<\/span><\/p>\n
mem: 48 GB <\/span><\/p>\n
Todos los pods est\u00e1n en nodos dedicados<\/span><\/td>\n
Carga de trabajoA<\/span><\/p>\n
50\/50 get\/upsert<\/span><\/td>\n
Rendimiento: <\/span>194,158<\/b> req\/seg<\/span><\/p>\n
Uso medio de la CPU: 86% de los 22 n\u00facleos<\/span><\/td>\n
Rendimiento: <\/span>192,190<\/b> req\/seg<\/span><\/p>\n
Uso medio de CPU: 94% de la cuota de cpu<\/span><\/td>\n
– 1%<\/span><\/td>\n<\/tr>\n
Env 2<\/span><\/td>\n16 vCPU, 48 GB RAM<\/span><\/p>\n
(los n\u00facleos de CPU y la RAM disponible se establecen en el nivel de n\u00facleo del sistema operativo)<\/span><\/td>\n
Limitar a:<\/span><\/p>\n
cpu: 16000m = ~16vCPU<\/span><\/p>\n
mem: 48 GB <\/span><\/p>\n
Todos los pods est\u00e1n en nodos dedicados<\/span><\/td>\n
Carga de trabajoA<\/span><\/p>\n
50\/50 get\/upsert<\/span><\/td>\n
Rendimiento: <\/span>141,909<\/b> req\/seg<\/span><\/p>\n
Uso medio de la CPU: 89% de los 16 n\u00facleos<\/span><\/td>\n
Rendimiento: <\/span>145,430<\/b> req\/seg<\/span><\/p>\n
Uso medio de CPU: 100% de la cuota de cpu<\/span><\/td>\n
+ 2.5%<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n
Workload E:\r\n\r\nLoad:\r\n\r\n.\/bin\/ycsb load couchbase2 -P workloads\/workloade -p couchbase.password=password -p couchbase.host=10.44.0.2 -p couchbase.bucket=default -p couchbase.upsert=true -p couchbase.epoll=true -p couchbase.boost=48 -p couchbase.persistTo=0 -p couchbase.replicateTo=0 -p couchbase.sslMode=none -p writeallfields=true -p recordcount=10000000 -threads 50 -p maxexecutiontime=3600 -p operationcount=1000000000\r\n\r\nRun:\r\n\r\n.\/bin\/ycsb run couchbase2 -P workloads\/workloade -p couchbase.password=password -p couchbase.host=10.44.0.2 -p couchbase.bucket=default -p couchbase.upsert=true -p couchbase.epoll=true -p couchbase.boost=48 -p couchbase.persistTo=0 -p couchbase.replicateTo=0 -p couchbase.sslMode=none -p writeallfields=true -p recordcount=10000000 -threads 50 \u00a0-p operationcount=1000000000 -p maxexecutiontime=600 -p exportfile=ycsb_workloadE_22vCPU.log\r\n<\/pre>\n
\n\n\n\n\n\n
Env<\/b><\/td>\nConfiguraci\u00f3n directa<\/b><\/td>\nRecursos del pod Kubernetes<\/b><\/td>\nPrueba<\/b><\/td>\nMetal desnudo<\/b><\/td>\nKubernetes<\/b><\/td>\nDelta<\/b><\/td>\n<\/tr>\n
Env 1<\/span><\/td>\n22 vCPU, 48 GB RAM<\/span><\/p>\n
(los n\u00facleos de CPU y la RAM disponible se establecen en el nivel de n\u00facleo del sistema operativo)<\/span><\/td>\n
Limitar a:<\/span><\/p>\n
cpu: 22000m = ~22vCPU<\/span><\/p>\n
mem: 48 GB <\/span><\/p>\n
Todos los pods est\u00e1n en nodos dedicados<\/span><\/td>\n
Carga de trabajoE<\/span><\/p>\n
95\/5 escanear\/insertar<\/span><\/td>\n
Rendimiento: <\/span>15,823<\/b> req\/seg<\/span><\/p>\n
Uso medio de la CPU: 85% de los 22 n\u00facleos<\/span><\/td>\n
Rendimiento: <\/span>14,281<\/b> req\/seg<\/span><\/p>\n
Uso medio de CPU: 87% de la cuota de cpu<\/span><\/td>\n
– 9.7%<\/span><\/td>\n<\/tr>\n
Env 2<\/span><\/td>\n16 vCPU, 48 GB RAM<\/span><\/p>\n
(los n\u00facleos de CPU y la RAM disponible se establecen en el nivel de n\u00facleo del sistema operativo)<\/span><\/td>\n
Limitar a:<\/span><\/p>\n
cpu: 16000m = ~16vCPU<\/span><\/p>\n
mem: 48 GB <\/span><\/p>\n
Todos los pods est\u00e1n en nodos dedicados<\/span><\/td>\n
Carga de trabajoE<\/span><\/p>\n
95\/5 escanear\/insertar<\/span><\/td>\n
Rendimiento: <\/span>13,014<\/b> req\/seg<\/span><\/p>\n
Uso medio de la CPU: 91% de los 16 n\u00facleos<\/span><\/td>\n
Rendimiento: <\/span>12,579<\/b> req\/seg<\/span><\/p>\n
Uso medio de CPU: 100% de la cuota de cpu<\/span><\/td>\n
– 3.3%<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n
Conclusiones<\/strong>:<\/span><\/p>\n
Couchbase Server 5.5 est\u00e1 listo para ser desplegado en Kubernetes con el Operador Aut\u00f3nomo. Rendimiento de Couchbase Server 5.5 en Kubernetes comparable a la ejecuci\u00f3n en metal desnudo. \u00a0<\/span>\u00a0<\/span>Hay poca penalizaci\u00f3n de rendimiento en la ejecuci\u00f3n de Couchbase Server en la plataforma Kubernetes. Si se observan los resultados, la carga de trabajo A tuvo un rendimiento similar al de la carga b\u00e1sica y la carga de trabajo E sufri\u00f3 una degradaci\u00f3n inferior a 10%. <\/span><\/p>\n
Referencias<\/strong>:<\/span><\/p>\n
    \n
  1. Carga de trabajo de YCSB <\/span>https:\/\/github.com\/brianfrankcooper\/YCSB\/wiki\/Core-Workloads<\/span><\/a><\/li>\n
  2. P\u00e1gina de Couchbase Kubernetes <\/span>https:\/\/www.couchbase.com\/products\/cloud\/kubernetes<\/span><\/a><\/li>\n
  3. Descargar Couchbase Autonomous Operator <\/span>https:\/\/www.couchbase.com\/downloads<\/span><\/a>\u00a0\u00a0<\/span><\/li>\n
  4. Presentaci\u00f3n de Couchbase Operator https:\/\/www.couchbase.com\/blog\/couchbase-autonomous-operator-1-0-for-kubernetes-and-openshift\/<\/a><\/li>\n<\/ol>\n
    Anexo<\/strong><\/p>\n
    Mi archivo deployment.yaml<\/b><\/p>\n
    apiVersion: extensions\/v1beta1\r\n\r\nkind: Deployment\r\n\r\nmetadata:\r\n\r\n\u00a0name: couchbase-operator\r\n\r\nspec:\r\n\r\n\u00a0replicas: 1\r\n\r\n\u00a0template:\r\n\r\n\u00a0\u00a0\u00a0metadata:\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0labels:\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0name: couchbase-operator\r\n\r\n\u00a0\u00a0\u00a0spec:\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0nodeSelector:\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0type: power\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0containers:\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0- name: couchbase-operator\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0image: couchbase\/couchbase-operator-internal:1.0.0-292\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0command:\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0- couchbase-operator\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0# Remove the arguments section if you are installing the CRD manually\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0args:\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0- -create-crd\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0- -enable-upgrades=false\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0env:\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0- name: MY_POD_NAMESPACE\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0valueFrom:\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0fieldRef:\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0fieldPath: metadata.namespace\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0- name: MY_POD_NAME\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0valueFrom:\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0fieldRef:\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0fieldPath: metadata.name\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0ports:\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0- name: readiness-port\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0containerPort: 8080\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0readinessProbe:\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0httpGet:\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0path: \/readyz\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0port: readiness-port\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0initialDelaySeconds: 3\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0periodSeconds: 3\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0failureThreshold: 19<\/pre>\n
    Mi archivo couchbase-cluster-simple-selector.yaml<\/b><\/p>\n
    apiVersion: couchbase.database.couchbase.com\/v1\r\n\r\nkind: CouchbaseCluster\r\n\r\nmetadata:\r\n\r\n\u00a0name: cb-example\r\n\r\nspec:\r\n\r\n\u00a0baseImage: couchbase\/server\r\n\r\n\u00a0version: enterprise-5.5.0\r\n\r\n\u00a0authSecret: cb-example-auth\r\n\r\n\u00a0exposeAdminConsole: true\r\n\r\n\u00a0antiAffinity: true\r\n\r\n\u00a0exposedFeatures:\r\n\r\n\u00a0\u00a0\u00a0- xdcr\r\n\r\n\u00a0cluster:\r\n\r\n\u00a0\u00a0\u00a0dataServiceMemoryQuota: 40000\r\n\r\n\u00a0\u00a0\u00a0indexServiceMemoryQuota: 40000\r\n\r\n\u00a0\u00a0\u00a0searchServiceMemoryQuota: 1000\r\n\r\n\u00a0\u00a0\u00a0eventingServiceMemoryQuota: 1024\r\n\r\n\u00a0\u00a0\u00a0analyticsServiceMemoryQuota: 1024\r\n\r\n\u00a0\u00a0\u00a0indexStorageSetting: memory_optimized\r\n\r\n\u00a0\u00a0\u00a0autoFailoverTimeout: 120\r\n\r\n\u00a0\u00a0\u00a0autoFailoverMaxCount: 3\r\n\r\n\u00a0\u00a0\u00a0autoFailoverOnDataDiskIssues: true\r\n\r\n\u00a0\u00a0\u00a0autoFailoverOnDataDiskIssuesTimePeriod: 120\r\n\r\n\u00a0\u00a0\u00a0autoFailoverServerGroup: false\r\n\r\n\u00a0buckets:\r\n\r\n\u00a0\u00a0\u00a0- name: default\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0type: couchbase\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0memoryQuota: 20000\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0replicas: 1\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0ioPriority: high\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0evictionPolicy: fullEviction\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0conflictResolution: seqno\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0enableFlush: true\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0enableIndexReplica: false\r\n\r\n\u00a0servers:\r\n\r\n\u00a0\u00a0\u00a0- size: 2\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0name: data\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0services:\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0- data\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0pod:\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0nodeSelector:\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0type: kv\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0resources:\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0limits:\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0cpu: 22000m\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0memory: 48Gi\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0requests:\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0cpu: 22000m\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0memory: 48Gi\r\n\r\n\u00a0\u00a0\u00a0- size: 2\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0name: qi\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0services:\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0- index\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0- query\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0pod:\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0nodeSelector:\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0type: kv\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0resources:\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0limits:\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0cpu: 22000m\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0memory: 48Gi\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0requests:\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0cpu: 22000m\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0memory: 48Gi\r\n<\/pre>\n
     <\/p>\n
    Mi archivo pillowfight-ycsb.yaml<\/b><\/p>\n
    apiVersion: batch\/v1\r\n\r\nkind: Job\r\n\r\nmetadata:\r\n\r\n\u00a0name: pillowfight\r\n\r\nspec:\r\n\r\n\u00a0template:\r\n\r\n\u00a0\u00a0\u00a0metadata:\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0name: pillowfight\r\n\r\n\u00a0\u00a0\u00a0spec:\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0containers:\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0- name: pillowfight\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0image: sequoiatools\/pillowfight:v5.0.1\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0command: [\"sh\", \"-c\", \"tail -f \/dev\/null\"]\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0restartPolicy: Never\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0nodeSelector:\r\n\r\n\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0type: client<\/pre>\n
     <\/p>","protected":false},"excerpt":{"rendered":"
    At Couchbase we take performance very seriously, and with the launch of our new product, Couchbase Autonomous Operator 1.0, we wanted to make sure it\u2019s Enterprise-grade and production ready for customers. In this blog post we will discuss the detailed […]<\/p>","protected":false},"author":86,"featured_media":13873,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"inline_featured_image":false,"footnotes":""},"categories":[1816,1812],"tags":[1545],"ppma_author":[9073],"class_list":["post-5808","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-couchbase-server","category-n1ql-query","tag-kubernetes"],"acf":[],"yoast_head":"\nPerformance of Couchbase Autonomous Operator on Kubernetes<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.couchbase.com\/blog\/es\/performance-certification-of-couchbase-server-5-5-on-kubernetes-platform\/\" \/>\n<meta property=\"og:locale\" content=\"es_MX\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Performance Certification of Couchbase Autonomous Operator on Kubernetes\" \/>\n<meta property=\"og:description\" content=\"At Couchbase we take performance very seriously, and with the launch of our new product, Couchbase Autonomous Operator 1.0, we wanted to make sure it\u2019s Enterprise-grade and production ready for customers. In this blog post we will discuss the detailed […]\" \/>\n<meta property=\"og:url\" content=\"https:\/\/www.couchbase.com\/blog\/es\/performance-certification-of-couchbase-server-5-5-on-kubernetes-platform\/\" \/>\n<meta property=\"og:site_name\" content=\"The Couchbase Blog\" \/>\n<meta property=\"article:published_time\" content=\"2018-09-11T05:23:22+00:00\" \/>\n<meta property=\"article:modified_time\" content=\"2025-06-14T06:43:03+00:00\" \/>\n<meta property=\"og:image\" content=\"https:\/\/www.couchbase.com\/blog\/wp-content\/uploads\/sites\/1\/2018\/09\/Screen-Shot-2018-09-10-at-3.31.49-PM.png\" \/>\n\t<meta property=\"og:image:width\" content=\"1184\" \/>\n\t<meta property=\"og:image:height\" content=\"906\" \/>\n\t<meta property=\"og:image:type\" content=\"image\/png\" \/>\n<meta name=\"author\" content=\"Raju Suravarjjala, Senior Director, Quality Engineering, Couchbase\" \/>\n<meta name=\"twitter:card\" content=\"summary_large_image\" \/>\n<meta name=\"twitter:creator\" 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Couchbase\",\"image\":{\"@type\":\"ImageObject\",\"inLanguage\":\"es\",\"@id\":\"https:\/\/www.couchbase.com\/blog\/#\/schema\/person\/image\/48c2407fddef3eae40eb98ba7fbb6b7f\",\"url\":\"https:\/\/secure.gravatar.com\/avatar\/7bd8dd6207a459854ac05f4b5f485740a283dc6b177385d99d4b9678020e6d62?s=96&d=mm&r=g\",\"contentUrl\":\"https:\/\/secure.gravatar.com\/avatar\/7bd8dd6207a459854ac05f4b5f485740a283dc6b177385d99d4b9678020e6d62?s=96&d=mm&r=g\",\"caption\":\"Raju Suravarjjala, Senior Director, Quality Engineering, Couchbase\"},\"description\":\"Raju Suravarjjala is a Senior Director of Quality Engineering at Couchbase. 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