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This website/page will be End-of-life (EOL) after 31 August 2024. We recommend you to visit OpenEBS Documentation for the latest Mayastor documentation (v2.6 and above).
Mayastor is now also referred to as OpenEBS Replicated PV Mayastor.
This quickstart guide describes the actions necessary to perform a basic installation of Mayastor on an existing Kubernetes cluster, sufficient for evaluation purposes. It assumes that the target cluster will pull the Mayastor container images directly from OpenEBS public container repositories. Where preferred, it is also possible to build Mayastor locally from source and deploy the resultant images but this is outside of the scope of this guide.
Deploying and operating Mayastor in production contexts requires a foundational knowledge of Mayastor internals and best practices, found elsewhere within this documentation.
This website/page will be End-of-life (EOL) after 31 August 2024. We recommend you to visit OpenEBS Documentation for the latest Mayastor documentation (v2.6 and above).
Mayastor is now also referred to as OpenEBS Replicated PV Mayastor.
All worker nodes must satisfy the following requirements:
x86-64 CPU cores with SSE4.2 instruction support
(Tested on) Linux kernel 5.15 (Recommended) Linux kernel 5.13 or higher. The kernel should have the following modules loaded:
nvme-tcp
ext4 and optionally xfs
Helm version must be v3.7 or later.
Each worker node which will host an instance of an io-engine pod must have the following resources free and available for exclusive use by that pod:
Two CPU cores
1GiB RAM
HugePage support
A minimum of 2GiB of 2MiB-sized pages
Ensure that the following ports are not in use on the node:
10124: Mayastor gRPC server will use this port.
8420 / 4421: NVMf targets will use these ports.
The firewall settings should not restrict connection to the node.
Disks must be unpartitioned, unformatted, and used exclusively by the DiskPool.
The minimum capacity of the disks should be 10 GB.
Kubernetes core v1 API-group resources: Pod, Event, Node, Namespace, ServiceAccount, PersistentVolume, PersistentVolumeClaim, ConfigMap, Secret, Service, Endpoint, Event.
Kubernetes batch API-group resources: CronJob, Job
Kubernetes apps API-group resources: Deployment, ReplicaSet, StatefulSet, DaemonSet
Kubernetes storage.k8s.io
API-group resources: StorageClass, VolumeSnapshot, VolumeSnapshotContent, VolumeAttachment, CSI-Node
Kubernetes apiextensions.k8s.io
API-group resources: CustomResourceDefinition
Mayastor Custom Resources that is openebs.io
API-group resources: DiskPool
Custom Resources from Helm chart dependencies of Jaeger that is helpful for debugging:
ConsoleLink Resource from console.openshift.io
API group
ElasticSearch Resource from logging.openshift.io
API group
Kafka and KafkaUsers from kafka.strimzi.io
API group
ServiceMonitor from monitoring.coreos.com
API group
Ingress from networking.k8s.io
API group and from extensions API group
Route from route.openshift.io
API group
All resources from jaegertracing.io
API group
The minimum supported worker node count is three nodes. When using the synchronous replication feature (N-way mirroring), the number of worker nodes to which Mayastor is deployed should be no less than the desired replication factor.
Mayastor supports the export and mounting of volumes over NVMe-oF TCP only. Worker node(s) on which a volume may be scheduled (to be mounted) must have the requisite initiator support installed and configured. In order to reliably mount Mayastor volumes over NVMe-oF TCP, a worker node's kernel version must be 5.13 or later and the nvme-tcp kernel module must be loaded.
This website/page will be End-of-life (EOL) after 31 August 2024. We recommend you to visit OpenEBS Documentation for the latest Mayastor documentation (v2.6 and above).
Mayastor is now also referred to as OpenEBS Replicated PV Mayastor.
The objective of this section is to provide the user and evaluator of Mayastor with a topological view of the gross anatomy of a Mayastor deployment. A description will be made of the expected pod inventory of a correctly deployed cluster, the roles and functions of the constituent pods and related Kubernetes resource types, and of the high level interactions between them and the orchestration thereof.
More detailed guides to Mayastor's components, their design and internal structure, and instructions for building Mayastor from source, are maintained within the project's GitHub repository.
Control Plane
agent-core
Deployment
Principle control plane actor
Single
csi-controller
Deployment
Hosts Mayastor's CSI controller implementation and CSI provisioner side car
Single
api-rest
Pod
Hosts the public API REST server
Single
api-rest
Service
Exposes the REST API server
operator-diskpool
Deployment
Hosts DiskPool operator
Single
csi-node
DaemonSet
Hosts CSI Driver node plugin containers
All worker nodes
etcd
StatefulSet
Hosts etcd Server container
Configurable(Recommended: Three replicas)
etcd
Service
Exposes etcd DB endpoint
Single
etcd-headless
Service
Exposes etcd DB endpoint
Single
io-engine
DaemonSet
Hosts Mayastor I/O engine
User-selected nodes
DiskPool
CRD
Declares a Mayastor pool's desired state and reflects its current state
User-defined, one or many
Additional components
metrics-exporter-pool
Sidecar container (within io-engine DaemonSet)
Exports pool related metrics in Prometheus format
All worker nodes
pool-metrics-exporter
Service
Exposes exporter API endpoint to Prometheus
Single
promtail
DaemonSet
Scrapes logs of Mayastor-specific pods and exports them to Loki
All worker nodes
loki
StatefulSet
Stores the historical logs exported by promtail pods
Single
loki
Service
Exposes the Loki API endpoint via ClusterIP
Single
The io-engine pod encapsulates Mayastor containers, which implement the I/O path from the block devices at the persistence layer, up to the relevant initiators on the worker nodes mounting volume claims. The Mayastor process running inside this container performs four major functions:
Creates and manages DiskPools hosted on that node.
Creates, exports, and manages volume controller objects hosted on that node.
Creates and exposes replicas from DiskPools hosted on that node over NVMe-TCP.
Provides a gRPC interface service to orchestrate the creation, deletion and management of the above objects, hosted on that node. Before the io-engine pod starts running, an init container attempts to verify connectivity to the agent-core in the namespace where Mayastor has been deployed. If a connection is established, the io-engine pod registers itself over gRPC to the agent-core. In this way, the agent-core maintains a registry of nodes and their supported api-versions. The scheduling of these pods is determined declaratively by using a DaemonSet specification. By default, a nodeSelector field is used within the pod spec to select all worker nodes to which the user has attached the label openebs.io/engine=mayastor
as recipients of an io-engine pod. In this way, the node count and location are set appropriately to the hardware configuration of the worker nodes, and the capacity and performance demands of the cluster.
The csi-node pods within a cluster implement the node plugin component of Mayastor's CSI driver. As such, their function is to orchestrate the mounting of Mayastor-provisioned volumes on worker nodes on which application pods consuming those volumes are scheduled. By default, a csi-node pod is scheduled on every node in the target cluster, as determined by a DaemonSet resource of the same name. Each of these pods encapsulates two containers, csi-node, and csi-driver-registrar. The node plugin does not need to run on every worker node within a cluster and this behavior can be modified, if desired, through the application of appropriate node labeling and the addition of a corresponding nodeSelector entry within the pod spec of the csi-node DaemonSet. However, it should be noted that if a node does not host a plugin pod, then it will not be possible to schedule an application pod on it, which is configured to mount Mayastor volumes.
etcd is a distributed reliable key-value store for the critical data of a distributed system. Mayastor uses etcd as a reliable persistent store for its configuration and state data.
The supportability tool is used to create support bundles (archive files) by interacting with multiple services present in the cluster where Mayastor is installed. These bundles contain information about Mayastor resources like volumes, pools and nodes, and can be used for debugging. The tool can collect the following information:
Topological information of Mayastor's resource(s) by interacting with the REST service
Historical logs by interacting with Loki. If Loki is unavailable, it interacts with the kube-apiserver to fetch logs.
Mayastor-specific Kubernetes resources by interacting with the kube-apiserver
Mayastor-specific information from etcd (internal) by interacting with the etcd server.
Loki aggregates and centrally stores logs from all Mayastor containers which are deployed in the cluster.
Promtail is a log collector built specifically for Loki. It uses the configuration file for target discovery and includes analogous features for labeling, transforming, and filtering logs from containers before ingesting them to Loki.