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README.md | ||
VM_logo.zip |
Single-node VictoriaMetrics
VictoriaMetrics is fast, cost-effective and scalable time series database. It can be used as a long-term remote storage for Prometheus. It is available in binary releases, docker images and in source code.
Cluster version is available here.
Prominent features
- Supports Prometheus querying API, so it can be used as Prometheus drop-in replacement in Grafana. Additionally, VictoriaMetrics extends PromQL with opt-in useful features.
- High performance and good scalability for both inserts and selects. Outperforms InfluxDB and TimescaleDB by up to 20x.
- Uses 10x less RAM than InfluxDB when working with millions of unique time series (aka high cardinality).
- High data compression, so up to 70x more data points may be crammed into a limited storage comparing to TimescaleDB.
- Optimized for storage with high-latency IO and low iops (HDD and network storage in AWS, Google Cloud, Microsoft Azure, etc). See graphs from these benchmarks.
- A single-node VictoriaMetrics may substitute moderately sized clusters built with competing solutions such as Thanos, Uber M3, Cortex, InfluxDB or TimescaleDB. See vertical scalability benchmarks.
- Easy operation:
- VictoriaMetrics consists of a single executable without external dependencies.
- All the configuration is done via explicit command-line flags with reasonable defaults.
- All the data is stored in a single directory pointed by
-storageDataPath
flag. - Easy backups from instant snapshots.
- Storage is protected from corruption on unclean shutdown (i.e. hardware reset or
kill -9
) thanks to the storage architecture. - Supports metrics' ingestion and backfilling via the following protocols:
- Prometheus remote write API
- InfluxDB line protocol
- Graphite plaintext protocol with tags
if
-graphiteListenAddr
is set. - OpenTSDB put message if
-opentsdbListenAddr
is set.
- Ideally works with big amounts of time series data from Kubernetes, IoT sensors, connected cars and industrial telemetry.
- Has open source cluster version.
Operation
Table of contents
- Single-node VictoriaMetrics
- Prominent features
- Operation
- Table of contents
- How to build from sources
- How to start VictoriaMetrics
- Setting up service
- Third-party contributions
- Prometheus setup
- Grafana setup
- How to send data from InfluxDB-compatible agents such as Telegraf?
- How to send data from Graphite-compatible agents such as StatsD?
- How to send data from OpenTSDB-compatible agents?
- How to apply new config / upgrade VictoriaMetrics?
- How to work with snapshots?
- How to delete time series?
- How to export time series?
- Federation
- Capacity planning
- High availability
- Multiple retentions
- Scalability and cluster version
- Security
- Tuning
- Monitoring
- Troubleshooting
- Contacts
- Community and contributions
- Reporting bugs
- Victoria Metrics Logo
How to build from sources
We recommend using either binary releases or docker images instead of building VictoriaMetrics from sources. Building from sources is reasonable when developing an additional features specific to your needs.
Development build
- Install Go. The minimum supported version is Go 1.12.
- Run
make victoria-metrics
from the root folder of the repository. It will buildvictoria-metrics
binary and put it into thebin
folder.
Production build
- Install docker.
- Run
make victoria-metrics-prod
from the root folder of the repository. It will buildvictoria-metrics-prod
binary and put it into thebin
folder.
Building docker images
Run make package-victoria-metrics
. It will build valyala/victoria-metrics:<PKG_TAG>
docker image locally.
<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-victoria-metrics
.
How to start VictoriaMetrics
Just start VictoriaMetrics executable or docker image with the desired command-line flags.
The following command line flags are used the most:
-storageDataPath
- path to data directory. VictoriaMetrics stores all the data in this directory.-retentionPeriod
- retention period in months for the data. Older data is automatically deleted.-httpListenAddr
- TCP address to listen to for http requests. By default it listens port8428
on all the network interfaces.-graphiteListenAddr
- TCP and UDP address to listen to for Graphite data. By default it is disabled.-opentsdbListenAddr
- TCP and UDP address to listen to for OpenTSDB data. By default it is disabled.
Pass -help
to see all the available flags with description and default values.
Setting up service
Read these instructions on how to set up VictoriaMetrics as a service in your OS.
Third-party contributions
Prometheus setup
Add the following lines to Prometheus config file (it is usually located at /etc/prometheus/prometheus.yml
):
remote_write:
- url: http://<victoriametrics-addr>:8428/api/v1/write
queue_config:
max_samples_per_send: 10000
Substitute <victoriametrics-addr>
with the hostname or IP address of VictoriaMetrics.
Then apply the new config via the following command:
kill -HUP `pidof prometheus`
Prometheus writes incoming data to local storage and to remote storage in parallel.
This means the data remains available in local storage for --storage.tsdb.retention.time
duration
if remote storage stops working.
If you plan sending data to VictoriaMetrics from multiple Prometheus instances, then add the following lines into global
section
of Prometheus config:
global:
external_labels:
datacenter: dc-123
This instructs Prometheus to add datacenter=dc-123
label to each time series sent to remote storage.
The label name may be arbitrary - datacenter
is just an example. The label value must be unique
across Prometheus instances, so time series may be filtered and grouped by this label.
Grafana setup
Create Prometheus datasource in Grafana with the following Url:
http://<victoriametrics-addr>:8428
Substitute <victoriametrics-addr>
with the hostname or IP address of VictoriaMetrics.
Then build graphs with the created datasource using Prometheus query language. VictoriaMetrics supports native PromQL and extends it with useful features.
How to send data from InfluxDB-compatible agents such as Telegraf?
Just use http://<victoriametric-addr>:8428
url instead of InfluxDB url in agents' configs.
For instance, put the following lines into Telegraf
config, so it sends data to VictoriaMetrics instead of InfluxDB:
[[outputs.influxdb]]
urls = ["http://<victoriametrics-addr>:8428"]
Do not forget substituting <victoriametrics-addr>
with the real address where VictoriaMetrics runs.
VictoriaMetrics maps Influx data using the following rules:
db
query arg is mapped intodb
label value- Field names are mapped to time series names prefixed by
{measurement}.
value - Field values are mapped to time series values
- Tags are mapped to Prometheus labels as-is
How to send data from Graphite-compatible agents such as StatsD?
- Enable Graphite receiver in VictoriaMetrics by setting
-graphiteListenAddr
command line flag. For instance, the following command will enable Graphite receiver in VictoriaMetrics on TCP and UDP port2003
:
/path/to/victoria-metrics-prod ... -graphiteListenAddr=:2003
- Use the configured address in Graphite-compatible agents. For instance, set
graphiteHost
to the VictoriaMetrics host inStatsD
configs.
How to send data from OpenTSDB-compatible agents?
- Enable OpenTSDB receiver in VictoriaMetrics by setting
-opentsdbListenAddr
command line flag. For instance, the following command will enable OpenTSDB receiver in VictoriaMetrics on TCP and UDP port4242
:
/path/to/victoria-metrics-prod ... -opentsdbListenAddr=:4242
- Send data to the given address from OpenTSDB-compatible agents.
How to apply new config / upgrade VictoriaMetrics?
VictoriaMetrics must be restarted in order to upgrade or apply new config:
- Send
SIGINT
signal to VictoriaMetrics process in order to gracefully stop it. - Wait until the process stops. This can take a few seconds.
- Start the upgraded VictoriaMetrics with new config.
How to work with snapshots?
VictoriaMetrics is able to create instant snapshots
for all the data stored under -storageDataPath
directory.
Navigate to http://<victoriametrics-addr>:8428/snapshot/create
in order to create an instant snapshot.
The page will return the following JSON response:
{"status":"ok","snapshot":"<snapshot-name>"}
Snapshots are created under <-storageDataPath>/snapshots
directory, where <-storageDataPath>
is the command-line flag value. Snapshots can be archived to backup storage via cp -L
, rsync -L
, scp -r
or any similar tool that follows symlinks during copying.
The http://<victoriametrics-addr>:8428/snapshot/list
page contains the list of available snapshots.
Navigate to http://<victoriametrics-addr>:8428/snapshot/delete?snapshot=<snapshot-name>
in order
to delete <snapshot-name>
snapshot.
Navigate to http://<victoriametrics-addr>:8428/snapshot/delete_all
in order to delete all the snapshots.
Steps for restoring from a snapshot:
- Stop VictoriaMetrics with
kill -INT
. - Remove the entire contents of the directory pointed by
-storageDataPath
command-line flag. - Copy snapshot contents to the directory pointed by
-storageDataPath
. - Start VictoriaMetrics.
How to delete time series?
Send a request to http://<victoriametrics-addr>:8428/api/v1/admin/tsdb/delete_series?match[]=<timeseries_selector_for_delete>
,
where <timeseries_selector_for_delete>
may contain any time series selector
for metrics to delete. After that all the time series matching the given selector are deleted. Storage space for
the deleted time series isn't freed instantly - it is freed during subsequent merges of data files.
How to export time series?
Send a request to http://<victoriametrics-addr>:8428/api/v1/export?match[]=<timeseries_selector_for_export>
,
where <timeseries_selector_for_export>
may contain any time series selector
for metrics to export. The response would contain all the data for the selected time series in JSON streaming format.
Each JSON line would contain data for a single time series. An example output:
{"metric":{"__name__":"up","job":"node_exporter","instance":"localhost:9100"},"values":[0,0,0],"timestamps":[1549891472010,1549891487724,1549891503438]}
{"metric":{"__name__":"up","job":"prometheus","instance":"localhost:9090"},"values":[1,1,1],"timestamps":[1549891461511,1549891476511,1549891491511]}
Optional start
and end
args may be added to the request in order to limit the time frame for the exported data. These args may contain either
unix timestamp in seconds or RFC3339 values.
Federation
VictoriaMetrics exports Prometheus-compatible federation data
at http://<victoriametrics-addr>:8428/federate?match[]=<timeseries_selector_for_federation>
.
Optional start
and end
args may be added to the request in order to scrape the last point for each selected time series on the [start ... end]
interval.
start
and end
may contain either unix timestamp in seconds or RFC3339 values. By default the last point
on the interval [now - max_lookback ... now]
is scraped for each time series. Default value for max_lookback
is 5m
(5 minutes), but can be overridden.
For instance, /federate?match[]=up&max_lookback=1h
would return last points on the [now - 1h ... now]
interval. This may be useful for time series federation
with scrape intervals exceeding 5m
.
Capacity planning
Rough estimation of the required resources:
- RAM size: less than 1KB per active time series. So, ~1GB of RAM is required for 1M active time series.
Time series is considered active if new data points have been added to it recently or if it has been recently queried.
VictoriaMetrics stores various caches in RAM. Memory size for these caches may be limited with
-memory.allowedPercent
flag. - CPU cores: a CPU core per 300K inserted data points per second. So, ~4 CPU cores are required for processing the insert stream of 1M data points per second. If you see lower numbers per CPU core, then it is likely active time series info doesn't fit caches, so you need more RAM for lowering CPU usage.
- Storage size: less than a byte per data point on average. So, ~260GB is required for storing a month-long insert stream of 100K data points per second. The actual storage size heavily depends on data randomness (entropy). Higher randomness means higher storage size requirements.
High availability
- Install multiple VictoriaMetrics instances in distinct datacenters.
- Add addresses of these instances to
remote_write
section in Prometheus config:
remote_write:
- url: http://<victoriametrics-addr-1>:8428/api/v1/write
queue_config:
max_samples_per_send: 10000
# ...
- url: http://<victoriametrics-addr-N>:8428/api/v1/write
queue_config:
max_samples_per_send: 10000
- Apply the updated config:
kill -HUP `pidof prometheus`
- Now Prometheus should write data into all the configured
remote_write
urls in parallel. - Set up Promxy in front of all the VictoriaMetrics replicas.
- Set up Prometheus datasource in Grafana that points to Promxy.
Multiple retentions
Just start multiple VictoriaMetrics instances with distinct values for the following flags:
-retentionPeriod
-storageDataPath
, so the data for each retention period is saved in a separate directory-httpListenAddr
, so clients may reach VictoriaMetrics instance with proper retention
Scalability and cluster version
Though single-node VictoriaMetrics cannot scale to multiple nodes, it is optimized for resource usage - storage size / bandwidth / IOPS, RAM, CPU. This means that a single-node VictoriaMetrics may scale vertically and substitute moderately sized cluster built with competing solutions such as Thanos, Uber M3, InfluxDB or TimescaleDB.
So try single-node VictoriaMetrics at first and then switch to cluster version if you still need horizontally scalable long-term remote storage for really large Prometheus deployments. Contact us for paid support.
Security
Do not forget protecting sensitive endpoints in VictoriaMetrics when exposing it to untrusted networks such as internet. Consider setting the following command-line flags:
-tls
,-tlsCertFile
and-tlsKeyFile
for switching from HTTP to HTTPS.-httpAuth.username
and-httpAuth.password
for protecting all the HTTP endpoints with HTTP Basic Authentication.-deleteAuthKey
for protecting/api/v1/admin/tsdb/delete_series
endpoint. See how to delete time series.-snapshotAuthKey
for protecting/snapshot*
endpoints. See how to work with snapshots.
Explicitly set internal network interface for TCP and UDP ports for data ingestion with Graphite and OpenTSDB formats.
For example, substitute -graphiteListenAddr=:2003
with -graphiteListenAddr=<internal_iface_ip>:2003
.
Tuning
- There is no need in VictoriaMetrics tuning, since it uses reasonable defaults for command-line flags, which are automatically adjusted for the available CPU and RAM resources.
- There is no need in Operating System tuning, since VictoriaMetrics is optimized for default OS settings. The only option is increasing the limit on the number open files in the OS, so Prometheus instances could establish more connections to VictoriaMetrics.
Monitoring
VictoriaMetrics exports internal metrics in Prometheus format on the /metrics
page.
Add this page to Prometheus' scrape config in order to collect VictoriaMetrics metrics.
There is an official Grafana dashboard for single-node VictoriaMetrics.
Troubleshooting
- If VictoriaMetrics works slowly and eats more than a CPU core per 100K ingested data points per second,
then it is likely you have too many active time series for the current amount of RAM.
It is recommended increasing the amount of RAM on the node with VictoriaMetrics in order to improve
ingestion performance.
Another option is to increase
-memory.allowedPercent
command-line flag value. Be careful with this option, since too big value for-memory.allowedPercent
may result in high I/O usage.
Contacts
Contact us with any questions regarding VictoriaMetrics at info@victoriametrics.com.
Community and contributions
Feel free asking any questions regarding VictoriaMetrics:
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.
Reporting bugs
Report bugs and propose new features here.
Victoria Metrics Logo
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