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Testing kubernetes and_open_shift_at_scale_20170209
- 1. Testing Kubernetes and OpenShift @ Scale Mike Fiedler - OpenShift System Test
- 2. Agenda ● Kubernetes/OpenShift runtimes & scalability goals ● OpenShift system testing: what does it cover? ● Installing large clusters ● Scalability test tools (the Kubernetes performance test repo and the the OpenShift SVT repo) ● Sample results
- 4. K8s and OpenShift runtimes ● Primarily targeted at cloud platforms ○ Amazon EC2, Google Cloud Platform, Microsoft Azure ○ Enterprise-hosted cloud offerings/infra ○ On-prem cloud infra such as OpenStack ○ Bare metal and other virtualization environments, too ● Cluster sizes from all-in-one dev/sandbox to multi-master, 1000+ nodes or federated clusters
- 5. Persistent Volume StorageNodes node 1 node 2 EBS (Persistent Volumes) S3 (Registry) node 1000 Control Plane master1 + etcd1 SSD master2 + etcd2 SSD master3 + etcd3 SSD Infrastructure Group infra2: HAProxy router2 docker-registry2 infra1: HAProxy router1 docker-registry1 Application ELB (Routes) External ELB (Console) Internet Int ELB (Nodes) What does a cluster look like? AWS sample:
- 6. Kubernetes SIG-scale ● Scalability special interest group ○ https://github.com/kubernetes/community/tree/master/sig-scalability ● Container workload is what matters - listen to your applications ○ The numbers here are more “control plane” - think small pods/containers ● Stated future goals: ○ Assumption: core/node = 64 (higher in the future) ○ Pods/core = 10 (depends on workload) ○ Pods/node = 500 - 640 (depends on workload, these would be small pods) ○ nodes/cluster = 5000 ○ pods/cluster = 500,000 (note: less than node x pods/node) ○ pod startup time < 5 seconds ○ Schedule 100 pods/second
- 7. Current OpenShift numbers ● Nodes/cluster = 1000 ● Pods/core = 10 (default, tunable) ● Pods/node = 250
- 9. System Test team in Red Hat ● Kubernetes and OpenShift Scalability ○ Cluster horizontal scale ■ # of nodes ■ # of running pods across all nodes ■ application traffic ○ Node vertical scale ■ # of pods running on a single node ■ workload that a single node can support (applications, builds, storage) ○ Application scalability ■ Scale # of application replicas up/down
- 10. System Test team in Red Hat ● Performance ○ Resource usage and response times for scenarios and workloads ■ Application workload and access performance ■ Builds (OpenShift) ■ Metrics and Log collection ○ OpenShift infrastructure performance ■ Resource usage of processes under load ■ Network (SDN) throughput ■ Routing ■ Storage (EBS, Ceph, Gluster, Cinder, etc)
- 11. System Test team in Red Hat ● Reliability ○ Simulated user workloads ■ monthly, weekly, daily, hourly, minute activities ■ accelerated to run faster than real-time ○ Run for extended periods and measure CPU, memory, I/O, network over time
- 12. SVT Challenges/Fun ● Installation ○ 1000+ node installs are time consuming (multiple hours) ○ On public cloud providers, time = $$$. Maximize time testing ○ 500 node test cluster on AWS is around USD $1500 - 2000/day ● Verifying that a cluster is viable ○ Don’t waste time on buggy clusters ● Loading up a cluster with application containers ● Putting a workload on the cluster ● Collecting performance data in large clusters
- 14. Install ● Upstream Kubernetes has a variety of install methods ○ Scripted, kubeadm, GKE, Ansible ● OpenShift install is Ansible-based ○ RPM install + pull of docker images. Containerized install available, too. ○ Network intensive - try to minimize downloads ● OpenShift SVT Gold image provisioner ○ Watches for new builds of OpenShift - multiple per week ○ Creates AMI and qcow2 images for every OpenShift puddle ○ RHEL OS setup, filesystem setup, tools ○ Pre-install OpenShift RPMs and pre-pull all docker images ○ Clone git repos and install performance tools
- 15. Install ● Ansible install and then verify cluster “core” ○ masters, etcd, load balancer, infrastructure + 3-5 app nodes ○ run e2e conformance tests (more on this later) ● Scale up with additional application nodes ● Playbooks: ○ github.com/openshift/openshift-ansible/playbooks/byo/config.yml ○ github.com/openshift/openshift-ansible/playbooks/byo/openshift-node/scaleup.yml
- 16. Persistent Volume StorageNodes node 1 node 2 EBS (Persistent Volumes) S3 (Registry) node 1000 Control Plane master1 + etcd1 SSD master2 + etcd2 SSD master3 + etcd3 SSD Infra Group infra2: HAProxy router2 docker-registry2 infra1: HAProxy router1 docker-registry1 Application ELB (Routes) External ELB (Console) Internet Int ELB (Nodes)
- 18. Kubernetes e2e and perf test ● e2e (end-to-end) tests ○ https://github.com/kubernetes/community/blob/master/contributors/devel/e2e-te sts.md ○ Subset of e2e tests are tagged as Conformance. ○ Conformance = minimum supported functionality for operational cluster ○ OpenShift also adds some additional Conformance tests if you yum install atomic-openshift-tests on top of OpenShift ● Performance tests ○ https://github.com/kubernetes/perf-tests ○ Work in progress
- 19. OpenShift SVT repo ● https://github.com/openshift/svt ● Tools for OpenShift performance, scale, reliability ○ cluster load-up ○ traffic generation ○ concurrent builds, deployments, pod start/stop ○ reliability testing ○ network performance ○ logging and metrics tests ● Automated and executed from Jenkins
- 20. Cluster load-up ● cluster-loader - python tool to quickly load clusters according to a YAML test specification. Takes advantage of OpenShift’s template capabilities ● Can be used with Kubernetes or OpenShift ● SVT repository has sample YAML configurations for node vertical, cluster horizontal, “Quick Start” applications with and without persistent storage. “I want an environment with thousands of deployments, pods (with persistent storage), build configurations, routes, services, secrets and more…” projects: - num: 1000 basename: nginx-explorer tuning: default templates: - num: 10 file: cluster-loader/nginx.yaml - num: 20 file: cluster-loader/explorer-pod.yaml
- 21. Cluster traffic generation ● cluster-loader can also run in traffic generation mode ● Runs a JMeter pod to generate traffic against applications (installed by cluster-loader or otherwise) ● Hit rate, throughput, response codes, response times, etc ● Discovers applications, exposed routes, etc ● Currently OpenShift only, but working on an upstream version.
- 23. Performance Tools ● PBench: Performance and Benchmark Analysis Framework ○ pbench-agent: collection agent and harness for running tests. ■ Collects data from sar, vmstat, iostat, pidstat, perf, etc ■ Extensible: additional data collectors can be added ■ Packages raw data from a test and ships it to pbench-server ○ pbench-server: processes raw data from all systems under test ○ web-server: provides visualization of data https://github.com/distributed-system-analysis/pbench
- 24. Sample Results
- 25. Loading 250 pods/node 20 pods at a time with 3 minute pauses
- 26. Master 1 - is the controller leader for most of the run Master 2 - has to pick up controller leader when Master 1 fails Loading on OSP 8 cluster: ● 500 nodes ● 20K projects ● 52K pods Masters are 40vCPU and peak out at 22 cores used.
- 27. Create/delete hundreds of pods : Amazon EBS IOPs credit exhaustion - AWS “I/O cliff” gp2 EBS volumes on EC2 can run “fast” until their IOPS credits are exhausted After that, they are throttled to 3 iops/gb until credits build back up
- 28. Resources Kubernetes sig-testing: https://kubernetes.slack.com/messages/sig-testing/ Kubernetes sig-scale: https://kubernetes.slack.com/messages/sig-scale/ OpenShift IRC: #openshift-dev OpenShift SVT repo: https://github.com/openshift/svt