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These functions return timestamp in seconds for the minimum and maximum value for `m` over time range `d` |
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README.md | ||
VM_logo.zip |
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.
Join our Slack or contact us with consulting and support questions.
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 datavminsert
- proxies the ingested data tovmstorage
shards using consistent hashingvmselect
- performs incoming queries using the data fromvmstorage
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/tagsvmselect
- https://hub.docker.com/r/victoriametrics/vmselect/tagsvmstorage
- https://hub.docker.com/r/victoriametrics/vmstorage/tags
Building from sources
Source code for cluster version is available at cluster branch.
Development Builds
- Install go. The minimum supported version is Go 1.12.
- Run
make
from the repository root. It should buildvmstorage
,vmselect
andvminsert
binaries and put them into thebin
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 port8480
onvminsert
nodes. - requests starting with
/select
must be routed to port8481
onvmselect
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
- 8480vmselect
- 8481vmstorage
- 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 APIinflux/write
orinflux/api/v2/write
- for inserting data with Influx line protocolopentsdb/api/put
- for accepting OpenTSDB HTTP /api/put requests.prometheus/api/v1/import
- for importing data obtained viaapi/v1/export
onvmselect
(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 queryapi/v1/query_range
- performs PromQL range queryapi/v1/series
- performs series queryapi/v1/labels
- returns a list of label namesapi/v1/label/<label_name>/values
- returns values for the given<label_name>
according to APIfederate
- returns federated metricsapi/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 thedelete_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 on8482
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 acrossvmstorage
nodes.
Cluster resizing and scalability.
Cluster performance and capacity scales with adding new nodes.
vminsert
andvmselect
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 morevminsert
nodes scales data ingestion rate. See this comment about ingestion rate scalability. Adding morevmselect
nodes scales select queries rate.vmstorage
nodes own the ingested data, so they cannot be removed without data loss. Adding morevmstorage
nodes scales cluster capacity.
Steps to add vmstorage
node:
- Start new
vmstorage
node with the same-retentionPeriod
as existing nodes in the cluster. - Gradually restart all the
vmselect
nodes with new-storageNode
arg containing<new_vmstorage_host>:8401
. - 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
andvmselect
nodes. -
The cluster remains available if at least a single
vmstorage
node exists:vminsert
re-routes incoming data from unavailablevmstorage
nodes to healthyvmstorage
nodesvmselect
continues serving partial responses if at least a singlevmstorage
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 ofvmstorage
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 onvminsert
instances could increase ingestion capacity at the cost of higher network bandwidth usage betweenvminsert
andvmstorage
.
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:
- Create an instant snapshot by navigating to
/snapshot/create
HTTP handler. It will create snapshot and return its name. - Archive the created snapshot from
<-storageDataPath>/snapshots/<snapshot_name>
folder using vmbackup. The archival process doesn't interfere withvmstorage
work, so it may be performed at any suitable time. - 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:
- Stop
vmstorage
node withkill -INT
. - Restore data from backup using vmrestore into
-storageDataPath
directory. - 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.
Victoria Metrics Logo
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