{"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\/performance-certification-of-couchbase-server-5-5-on-kubernetes-platform\/","title":{"rendered":"Performance Certification of Couchbase Autonomous Operator on Kubernetes"},"content":{"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. <\/span><\/p>\n

In this blog post we will discuss the detailed performance results from running YCSB Performance Benchmark tests on Couchbase Server 5.5 using the Autonomous Operator to deploy on Kubernetes platform. One of the big concerns for Enterprises planning to run database on Kubernetes is ‘performance’ . <\/span><\/p>\n

This document gives a quick comparison of two workloads, namely <\/span>YCSB A & E <\/span><\/a>with Couchbase Server 5.5 on Kubernetes <\/span>vs bare metal.<\/span><\/p>\n

YCSB Workload A<\/b>: <\/span>This workload has a mix of 50\/50 reads and writes. An application example is a session store recording recent actions.<\/span><\/p>\n

Workload E: Short ranges:\u00a0<\/b>In this workload, short ranges of records are queried, instead of individual records. Application example: threaded conversations, where each scan is for the posts in a given thread (assumed to be clustered by thread id).<\/p>\n

In general, we observed no significant performance degradation in running Couchbase Cluster on Kubernetes, <\/span>Workload A had on par performance compared to bare metal and Workload E had approximately less than 10% degradation.\u00a0<\/span><\/p>\n

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

For the setup, Couchbase was installed using the Operator deployment as stated below. For more details on the setup, please refer <\/span>here<\/span><\/a><\/p>\n

\"\"<\/p>\n

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

Operator deployment: deployment.yaml (See Appendix)<\/span><\/p>\n

Couchbase deployment: couchbase-cluster-simple-selector.yaml\u00a0(See Appendix)<\/span><\/p>\n

Client \/ workload generator deployment: pillowfight-ycsb.yaml \u00a0(See Appendix)\u00a0(Official pillowfight docker image from dockerhub and installed java and YCSB manually on top of it)<\/span><\/p>\n

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

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

24 CPU x 64GB RAM per server<\/span><\/p>\n

Couchbase setup<\/b><\/p>\n

4 servers: 2 data nodes, 2 index+query nodes<\/span><\/p>\n

40GB RAM quota for data service<\/span><\/p>\n

40GB RAM quota for index services<\/span><\/p>\n

1 data\/bucket replica<\/span><\/p>\n

1 primary index replica<\/span><\/p>\n

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

YCSB WorkloadA and WorkloadE<\/span><\/p>\n

10M docs<\/span><\/p>\n

Workflow after new empty k8s cluster is initialized on 7 servers:<\/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
Running the workloads:<\/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
Test results:<\/b><\/p>\n
\n\n\n\n\n\n
Env<\/b><\/td>\nDirect setup<\/b><\/td>\nKubernetes pod resources<\/b><\/td>\nTest<\/b><\/td>\nBare metal<\/b><\/td>\nKubernetes<\/b><\/td>\nDelta<\/b><\/td>\n<\/tr>\n
Env 1<\/span><\/td>\n22 vCPU, 48 GB RAM<\/span><\/p>\n
(cpu cores and RAM available \u00a0are set on OS core level)<\/span><\/td>\n
Limit to:<\/span><\/p>\n
cpu: 22000m = ~22vCPU<\/span><\/p>\n
mem: 48GB <\/span><\/p>\n
All pods are on dedicated nodes<\/span><\/td>\n
WorkloadA<\/span><\/p>\n
50\/50 get\/upsert<\/span><\/td>\n
Throughput: <\/span>194,158<\/b> req\/sec<\/span><\/p>\n
CPU usage avg: 86% of all 22 cores<\/span><\/td>\n
Throughput: <\/span>192,190<\/b> req\/sec<\/span><\/p>\n
CPU usage avg: 94% of the cpu quota<\/span><\/td>\n
– 1%<\/span><\/td>\n<\/tr>\n
Env 2<\/span><\/td>\n16 vCPU, 48 GB RAM<\/span><\/p>\n
(cpu cores and RAM available \u00a0are set on OS core level)<\/span><\/td>\n
Limit to:<\/span><\/p>\n
cpu: 16000m = ~16vCPU<\/span><\/p>\n
mem: 48GB <\/span><\/p>\n
All pods are on dedicated nodes<\/span><\/td>\n
WorkloadA<\/span><\/p>\n
50\/50 get\/upsert<\/span><\/td>\n
Throughput: <\/span>141,909<\/b> req\/sec<\/span><\/p>\n
CPU usage avg: 89% of all 16 cores<\/span><\/td>\n
Throughput: <\/span>145,430<\/b> req\/sec<\/span><\/p>\n
CPU usage avg: 100% of the cpu quota<\/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>\nDirect setup<\/b><\/td>\nKubernetes pod resources<\/b><\/td>\nTest<\/b><\/td>\nBare metal<\/b><\/td>\nKubernetes<\/b><\/td>\nDelta<\/b><\/td>\n<\/tr>\n
Env 1<\/span><\/td>\n22 vCPU, 48 GB RAM<\/span><\/p>\n
(cpu cores and RAM available \u00a0are set on OS core level)<\/span><\/td>\n
Limit to:<\/span><\/p>\n
cpu: 22000m = ~22vCPU<\/span><\/p>\n
mem: 48GB <\/span><\/p>\n
All pods are on dedicated nodes<\/span><\/td>\n
WorkloadE<\/span><\/p>\n
95\/5 scan\/insert<\/span><\/td>\n
Throughput: <\/span>15,823<\/b> req\/sec<\/span><\/p>\n
CPU usage avg: 85% of all 22 cores<\/span><\/td>\n
Throughput: <\/span>14,281<\/b> req\/sec<\/span><\/p>\n
CPU usage avg: 87% of the cpu quota<\/span><\/td>\n
– 9.7%<\/span><\/td>\n<\/tr>\n
Env 2<\/span><\/td>\n16 vCPU, 48 GB RAM<\/span><\/p>\n
(cpu cores and RAM available \u00a0are set on OS core level)<\/span><\/td>\n
Limit to:<\/span><\/p>\n
cpu: 16000m = ~16vCPU<\/span><\/p>\n
mem: 48GB <\/span><\/p>\n
All pods are on dedicated nodes<\/span><\/td>\n
WorkloadE<\/span><\/p>\n
95\/5 scan\/insert<\/span><\/td>\n
Throughput: <\/span>13,014<\/b> req\/sec<\/span><\/p>\n
CPU usage avg: 91% of all 16 cores<\/span><\/td>\n
Throughput: <\/span>12,579<\/b> req\/sec<\/span><\/p>\n
CPU usage avg: 100% of the cpu quota<\/span><\/td>\n
– 3.3%<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n
Conclusions<\/strong>:<\/span><\/p>\n
Couchbase Server 5.5 is production ready to be deployed on Kubernetes with the Autonomous Operator. Performance of Couchbase Server 5.5 on Kubernetes comparable to running on bare metal. \u00a0<\/span>\u00a0<\/span>There is little performance penalty in running Couchbase Server on Kubernetes platform. Looking at the results Workload A had on par performance compared to bare metal and Workload E had approximately less than 10% degradation. <\/span><\/p>\n
References<\/strong>:<\/span><\/p>\n
    \n
  1. YCSB Workloads <\/span>https:\/\/github.com\/brianfrankcooper\/YCSB\/wiki\/Core-Workloads<\/span><\/a><\/li>\n
  2. Couchbase Kubernetes page <\/span>https:\/\/www.couchbase.com\/products\/cloud\/kubernetes<\/span><\/a><\/li>\n
  3. Download Couchbase Autonomous Operator <\/span>https:\/\/www.couchbase.com\/downloads<\/span><\/a>\u00a0\u00a0<\/span><\/li>\n
  4. Introducing Couchbase Operator https:\/\/www.couchbase.com\/blog\/couchbase-autonomous-operator-1-0-for-kubernetes-and-openshift\/<\/a><\/li>\n<\/ol>\n
    Appendix<\/strong><\/p>\n
    My deployment.yaml file<\/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
    My couchbase-cluster-simple-selector.yaml file<\/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
    My pillowfight-ycsb.yaml file<\/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>\n","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>\n","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\/performance-certification-of-couchbase-server-5-5-on-kubernetes-platform\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\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\/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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