Cluster version

VictoriaMetrics is fast, cost-effective and scalable time series database. It can be used as a long-term remote storage for Prometheus.

It is recommended using single-node version instead of cluster version for ingestion rates lower than a million of data points per second. Single-node version scales perfectly with the number of CPU cores, RAM and available storage space. Single-node version is easier to configure and operate comparing to cluster version, so think twice before sticking to cluster version.

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Prominent features

• Supports all the features of single-node version.
• Performance and capacity scales horizontally.
• Supports multiple independent namespaces for time series data (aka multi-tenancy).

Architecture overview

VictoriaMetrics cluster consists of the following services:

• vmstorage - stores the data
• vminsert - proxies the ingested data to vmstorage shards using consistent hashing
• vmselect - performs incoming queries using the data from vmstorage

Each service may scale independently and may run on the most suitable hardware. vmstorage nodes don't know about each other, don't communicate with each other and don't share any data. This is shared nothing architecture. It increases cluster availability, simplifies cluster maintenance and cluster scaling.

Binaries

Compiled binaries for cluster version are available in the assets section of releases page. See archives containing cluster word.

Docker images for cluster version are available here:

• vminsert - https://hub.docker.com/r/victoriametrics/vminsert/tags
• vmselect - https://hub.docker.com/r/victoriametrics/vmselect/tags
• vmstorage - https://hub.docker.com/r/victoriametrics/vmstorage/tags

Building from sources

Source code for cluster version is available at cluster branch.

Development Builds

1. Install go. The minimum supported version is Go 1.12.
2. Run make from the repository root. It should build vmstorage, vmselect and vminsert binaries and put them into the bin folder.

Production builds

There is no need in installing Go on a host system since binaries are built inside the official docker container for Go. This makes reproducible builds. So install docker and run the following command:

make vminsert-prod vmselect-prod vmstorage-prod

Production binaries are built into statically linked binaries for GOARCH=amd64, GOOS=linux. They are put into bin folder with -prod suffixes:

$ make vminsert-prod vmselect-prod vmstorage-prod
$ ls -1 bin
vminsert-prod
vmselect-prod
vmstorage-prod

Building docker images

Run make package. It will build the following docker images locally:

• victoriametrics/vminsert:<PKG_TAG>
• victoriametrics/vmselect:<PKG_TAG>
• victoriametrics/vmstorage:<PKG_TAG>

<PKG_TAG> is auto-generated image tag, which depends on source code in the repository. The <PKG_TAG> may be manually set via PKG_TAG=foobar make package.

Operation

Cluster setup

A minimal cluster must contain the following nodes:

• a single vmstorage node with -retentionPeriod and -storageDataPath flags
• a single vminsert node with -storageNode=<vmstorage_host>:8400
• a single vmselect node with -storageNode=<vmstorage_host>:8401

It is recommended to run at least two nodes for each service for high availability purposes.

An http load balancer must be put in front of vminsert and vmselect nodes:

• requests starting with /insert must be routed to port 8480 on vminsert nodes.
• requests starting with /select must be routed to port 8481 on vmselect nodes.

Ports may be altered by setting -httpListenAddr on the corresponding nodes.

It is recommended setting up monitoring for the cluster.

Monitoring

All the cluster components expose various metrics in Prometheus-compatible format at /metrics page on the TCP port set in -httpListenAddr command-line flag. By default the following TCP ports are used:

• vminsert - 8480
• vmselect - 8481
• vmstorage - 8482

It is recommended setting up Prometheus to scrape /metrics pages from all the cluster components, so they can be monitored and analyzed with the official Grafana dashboard for VictoriaMetrics cluster.

URL format

• URLs for data ingestion: http://<vminsert>:8480/insert/<accountID>/<suffix>, where:

  • <accountID> is an arbitrary number identifying namespace for data ingestion (aka tenant)
  • <suffix> may have the following values:
    • prometheus - for inserting data with Prometheus remote write API
    • influx/write or influx/api/v2/write - for inserting data with Influx line protocol
    • opentsdb/api/put - for accepting OpenTSDB HTTP /api/put requests.
    • prometheus/api/v1/import - for importing data obtained via api/v1/export on vmselect (see below).

• URLs for querying: http://<vmselect>:8481/select/<accountID>/prometheus/<suffix>, where:

  • <accountID> is an arbitrary number identifying data namespace for the query (aka tenant)
  • <suffix> may have the following values:
    • api/v1/query - performs PromQL instant query
    • api/v1/query_range - performs PromQL range query
    • api/v1/series - performs series query
    • api/v1/labels - returns a list of label names
    • api/v1/label/<label_name>/values - returns values for the given <label_name> according to API
    • federate - returns federated metrics
    • api/v1/export - exports raw data. See this article for details

• URL for time series deletion: http://<vmselect>:8481/delete/<accountID>/prometheus/api/v1/admin/tsdb/delete_series?match[]=<timeseries_selector_for_delete>. Note that the delete_series handler should be used only in exceptional cases such as deletion of accidentally ingested incorrect time series. It shouldn't be used on a regular basis, since it carries non-zero overhead.

• vmstorage nodes provide the following HTTP endpoints on 8482 port:

  • /snapshot/create - create instant snapshot, which can be used for backups in background. Snapshots are created in <storageDataPath>/snapshots folder, where <storageDataPath> is the corresponding command-line flag value.
  • /snapshot/list - list available snasphots.
  • /snapshot/delete?snapshot=<id> - delete the given snapshot.
  • /snapshot/delete_all - delete all the snapshots.

  Snapshots may be created independently on each vmstorage node. There is no need in synchronizing snapshots' creation across vmstorage nodes.

Cluster resizing and scalability.

Cluster performance and capacity scales with adding new nodes.

• vminsert and vmselect nodes are stateless and may be added / removed at any time. Do not forget updating the list of these nodes on http load balancer. Adding more vminsert nodes scales data ingestion rate. See this comment about ingestion rate scalability. Adding more vmselect nodes scales select queries rate.
• vmstorage nodes own the ingested data, so they cannot be removed without data loss. Adding more vmstorage nodes scales cluster capacity.

Steps to add vmstorage node:

1. Start new vmstorage node with the same -retentionPeriod as existing nodes in the cluster.
2. Gradually restart all the vmselect nodes with new -storageNode arg containing <new_vmstorage_host>:8401.
3. Gradually restart all the vminsert nodes with new -storageNode arg containing <new_vmstorage_host>:8400.

Cluster availability

• HTTP load balancer must stop routing requests to unavailable vminsert and vmselect nodes.

• The cluster remains available if at least a single vmstorage node exists:

  • vminsert re-routes incoming data from unavailable vmstorage nodes to healthy vmstorage nodes
  • vmselect continues serving partial responses if at least a single vmstorage node is available.

Updating / reconfiguring cluster nodes

All the node types - vminsert, vmselect and vmstorage - may be updated via graceful shutdown. Send SIGINT signal to the corresponding process, wait until it finishes and then start new version with new configs.

Cluster should remain in working state if at least a single node of each type remains available during the update process. See cluster availability section for details.

Capacity planning

Each instance type - vminsert, vmselect and vmstorage - can run on the most suitable hardware.

vminsert

• The recommended total number of vCPU cores for all the vminsert instances can be calculated from the ingestion rate: vCPUs = ingestion_rate / 150K.
• The recommended number of vCPU cores per each vminsert instance should equal to the number of vmstorage instances in the cluster.
• The amount of RAM per each vminsert instance should be 1GB or more. RAM is used as a buffer for spikes in ingestion rate.
• Sometimes -rpc.disableCompression command-line flag on vminsert instances could increase ingestion capacity at the cost of higher network bandwidth usage between vminsert and vmstorage.

vmstorage

• The recommended total number of vCPU cores for all the vmstorage instances can be calculated from the ingestion rate: vCPUs = ingestion_rate / 150K.
• The recommended total amount of RAM for all the vmstorage instances can be calculated from the number of active time series: RAM = active_time_series * 1KB. Time series is active if it received at least a single data point during the last hour or if it has been queried during the last hour.
• The recommended total amount of storage space for all the vmstorage instances can be calculated from the ingestion rate and retention: storage_space = ingestion_rate * retention_seconds.

vmselect

The recommended hardware for vmselect instances highly depends on the type of queries. Lightweight queries over small number of time series usually require small number of vCPU cores and small amount of RAM on vmselect, while heavy queries over big number of time series (>10K) usually require bigger number of vCPU cores and bigger amounts of RAM.

Helm

Helm chart simplifies managing cluster version of VictoriaMetrics in Kubernetes. It is available in the helm-charts repository.

Upgrade follows Cluster resizing procedure under the hood.

Replication and data safety

VictoriaMetrics offloads replication to the underlying storage pointed by -storageDataPath. It is recommended storing data on Google Compute Engine persistent disks, since they are protected from data loss and data corruption. They also provide consistently high performance and may be resized without downtime. HDD-based persistent disks should be enough for the majority of use cases.

It is recommended using durable replicated persistent volumes in Kubernetes.

Note that replication doesn't save from disaster.

Backups

It is recommended performing periodical backups from instant snapshots for protecting from user errors such as accidental data deletion.

The following steps must be performed for each vmstorage node for creating a backup:

1. Create an instant snapshot by navigating to /snapshot/create HTTP handler. It will create snapshot and return its name.
2. Archive the created snapshot from <-storageDataPath>/snapshots/<snapshot_name> folder using vmbackup. The archival process doesn't interfere with vmstorage work, so it may be performed at any suitable time.
3. Delete unused snapshots via /snapshot/delete?snapshot=<snapshot_name> or /snapshot/delete_all in order to free up occupied storage space.

There is no need in synchronizing backups among all the vmstorage nodes.

Restoring from backup:

1. Stop vmstorage node with kill -INT.
2. Restore data from backup using vmrestore into -storageDataPath directory.
3. Start vmstorage node.

Community and contributions

We are open to third-party pull requests provided they follow KISS design principle:

• Prefer simple code and architecture.
• Avoid complex abstractions.
• Avoid magic code and fancy algorithms.
• Avoid big external dependencies.
• Minimize the number of moving parts in the distributed system.
• Avoid automated decisions, which may hurt cluster availability, consistency or performance.

Adhering KISS principle simplifies the resulting code and architecture, so it can be reviewed, understood and verified by many people.

Due to KISS cluster version of VictoriaMetrics has no the following "features" popular in distributed computing world:

• Fragile gossip protocols. See failed attempt in Thanos.
• Hard-to-understand-and-implement-properly Paxos protocols.
• Complex replication schemes, which may go nuts in unforesseen edge cases. The replication is offloaded to the underlying durable replicated storage such as persistent disks in Google Compute Engine.
• Automatic data reshuffling between storage nodes, which may hurt cluster performance and availability.
• Automatic cluster resizing, which may cost you a lot of money if improperly configured.
• Automatic discovering and addition of new nodes in the cluster, which may mix data between dev and prod clusters :)
• Automatic leader election, which may result in split brain disaster on network errors.

Reporting bugs

Report bugs and propose new features here.

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