The reason is to cover vulnerability GO-2022-0969 Found in: net/http@go1.18.5 Fixed in: net/http@go1.19.1 More info: https://pkg.go.dev/vuln/GO-2022-0969 Signed-off-by: hagen1778 <roman@victoriametrics.com> Signed-off-by: hagen1778 <roman@victoriametrics.com>
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vmctl
VictoriaMetrics command-line tool
vmctl provides various useful actions with VictoriaMetrics components.
Features:
- migrate data from Prometheus to VictoriaMetrics using snapshot API
- migrate data from Thanos to VictoriaMetrics
- migrate data from InfluxDB to VictoriaMetrics
- migrate data from OpenTSDB to VictoriaMetrics
- migrate data between VictoriaMetrics single or cluster version.
- verify exported blocks from VictoriaMetrics single or cluster version.
To see the full list of supported modes run the following command:
$ ./vmctl --help
NAME:
vmctl - VictoriaMetrics command-line tool
USAGE:
vmctl [global options] command [command options] [arguments...]
COMMANDS:
opentsdb Migrate timeseries from OpenTSDB
influx Migrate timeseries from InfluxDB
prometheus Migrate timeseries from Prometheus
vm-native Migrate time series between VictoriaMetrics installations via native binary format
verify-block Verifies correctness of data blocks exported via VictoriaMetrics Native format. See https://docs.victoriametrics.com/#how-to-export-data-in-native-format
Each mode has its own unique set of flags specific (e.g. prefixed with influx
for influx mode)
to the data source and common list of flags for destination (prefixed with vm
for VictoriaMetrics):
$ ./vmctl influx --help
OPTIONS:
--influx-addr value InfluxDB server addr (default: "http://localhost:8086")
--influx-user value InfluxDB user [$INFLUX_USERNAME]
...
--vm-addr vmctl VictoriaMetrics address to perform import requests.
Should be the same as --httpListenAddr value for single-node version or vminsert component.
When importing into the clustered version do not forget to set additionally --vm-account-id flag.
Please note, that vmctl performs initial readiness check for the given address by checking `/health` endpoint. (default: "http://localhost:8428")
--vm-user value VictoriaMetrics username for basic auth [$VM_USERNAME]
--vm-password value VictoriaMetrics password for basic auth [$VM_PASSWORD]
When doing a migration user needs to specify flags for source (where and how to fetch data) and for destination (where to migrate data). Every mode has additional details and nuances, please see them below in corresponding sections.
For the destination flags see the full description by running the following command:
$ ./vmctl influx --help | grep vm-
Some flags like --vm-extra-label or --vm-significant-figures has additional sections with description below. Details about tweaking and adjusting settings are explained in Tuning section.
Please note, that if you're going to import data into VictoriaMetrics cluster do not
forget to specify the --vm-account-id
flag. See more details for cluster version
here.
Articles
- How to migrate data from Prometheus
- How to migrate data from Prometheus. Filtering and modifying time series
Migrating data from OpenTSDB
vmctl
supports the opentsdb
mode to migrate data from OpenTSDB to VictoriaMetrics time-series database.
See ./vmctl opentsdb --help
for details and full list of flags.
Important: OpenTSDB migration is not possible without a functioning meta table to search for metrics/series. Check in OpenTSDB config that appropriate options are activated and HBase meta tables are present. W/o them migration won't work.
OpenTSDB migration works like so:
- Find metrics based on selected filters (or the default filter set
['a','b','c','d','e','f','g','h','i','j','k','l','m','n','o','p','q','r','s','t','u','v','w','x','y','z']
)
- e.g.
curl -Ss "http://opentsdb:4242/api/suggest?type=metrics&q=sys"
- Find series associated with each returned metric
- e.g.
curl -Ss "http://opentsdb:4242/api/search/lookup?m=system.load5&limit=1000000"
Here results
return field should not be empty. Otherwise it means that meta tables are absent and needs to be turned on previously.
- Download data for each series in chunks defined in the CLI switches
- e.g.
-retention=sum-1m-avg:1h:90d
meanscurl -Ss "http://opentsdb:4242/api/query?start=1h-ago&end=now&m=sum:1m-avg-none:system.load5\{host=host1\}"
curl -Ss "http://opentsdb:4242/api/query?start=2h-ago&end=1h-ago&m=sum:1m-avg-none:system.load5\{host=host1\}"
curl -Ss "http://opentsdb:4242/api/query?start=3h-ago&end=2h-ago&m=sum:1m-avg-none:system.load5\{host=host1\}"
- ...
curl -Ss "http://opentsdb:4242/api/query?start=2160h-ago&end=2159h-ago&m=sum:1m-avg-none:system.load5\{host=host1\}"
This means that we must stream data from OpenTSDB to VictoriaMetrics in chunks. This is where concurrency for OpenTSDB comes in. We can query multiple chunks at once, but we shouldn't perform too many chunks at a time to avoid overloading the OpenTSDB cluster.
$ ./vmctl opentsdb --otsdb-addr http://opentsdb:4242/ --otsdb-retentions sum-1m-avg:1h:1d --otsdb-filters system --otsdb-normalize --vm-addr http://victoria:8428/
OpenTSDB import mode
2021/04/09 11:52:50 Will collect data starting at TS 1617990770
2021/04/09 11:52:50 Loading all metrics from OpenTSDB for filters: [system]
Found 9 metrics to import. Continue? [Y/n]
2021/04/09 11:52:51 Starting work on system.load1
23 / 402200 [>____________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________________] 0.01% 2 p/s
Where :8428
is Prometheus port of VictoriaMetrics.
For clustered VictoriaMetrics setup --vm-account-id
flag needs to be added, for example:
$ ./vmctl opentsdb --otsdb-addr http://opentsdb:4242/ --otsdb-retentions sum-1m-avg:1h:1d --otsdb-filters system --otsdb-normalize --vm-addr http://victoria:8480/ --vm-account-id 0
This time :8480
port is vminsert/Prometheus input port.
Retention strings
Starting with a relatively simple retention string (sum-1m-avg:1h:30d
), let's describe how this is converted into actual queries.
There are two essential parts of a retention string:
Aggregation
Retention strings essentially define the two levels of aggregation for our collected series.
sum-1m-avg
would become:
- First order:
sum
- Second order:
1m-avg-none
First Order Aggregations
First-order aggregation addresses how to aggregate any un-mentioned tags.
This is, conceptually, directly opposite to how PromQL deals with tags. In OpenTSDB, if a tag isn't explicitly mentioned, all values assocaited with that tag will be aggregated.
It is recommended to use sum
for the first aggregation because it is relatively quick and should not cause any changes to the incoming data (because we collect each individual series).
Second Order Aggregations
Second-order aggregation (1m-avg
in our example) defines any windowing that should occur before returning the data
It is recommended to match the stat collection interval so we again avoid transforming incoming data.
We do not allow for defining the "null value" portion of the rollup window (e.g. in the aggreagtion, 1m-avg-none
, the user cannot change none
), as the goal of this tool is to avoid modifying incoming data.
Windows
There are two important windows we define in a retention string:
- the "chunk" range of each query
- The time range we will be querying on with that "chunk"
From our example, our windows are 1h:30d
.
Window "chunks"
The window 1h
means that each individual query to OpenTSDB should only span 1 hour of time (e.g. start=2h-ago&end=1h-ago
).
It is important to ensure this window somewhat matches the row size in HBase to help improve query times.
For example, if the query is hitting a rollup table with a 4 hour row size, we should set a chunk size of a multiple of 4 hours (e.g. 4h
, 8h
, etc.) to avoid requesting data across row boundaries. Landing on row boundaries allows for more consistent request times to HBase.
The default table created in HBase for OpenTSDB has a 1 hour row size, so if you aren't sure on a correct row size to use, 1h
is a reasonable choice.
Time range
The time range 30d
simply means we are asking for the last 30 days of data. This time range can be written using h
, d
, w
, or y
. (We can't use m
for month because it already means minute
in time parsing).
Results of retention string
The resultant queries that will be created, based on our example retention string of sum-1m-avg:1h:30d
look like this:
http://opentsdb:4242/api/query?start=1h-ago&end=now&m=sum:1m-avg-none:<series>
http://opentsdb:4242/api/query?start=2h-ago&end=1h-ago&m=sum:1m-avg-none:<series>
http://opentsdb:4242/api/query?start=3h-ago&end=2h-ago&m=sum:1m-avg-none:<series>
...
http://opentsdb:4242/api/query?start=721h-ago&end=720h-ago&m=sum:1m-avg-none:<series>
Chunking the data like this means each individual query returns faster, so we can start populating data into VictoriaMetrics quicker.
Restarting OpenTSDB migrations
One important note for OpenTSDB migration: Queries/HBase scans can "get stuck" within OpenTSDB itself. This can cause instability and performance issues within an OpenTSDB cluster, so stopping the migrator to deal with it may be necessary. Because of this, we provide the timstamp we started collecting data from at thebeginning of the run. You can stop and restart the importer using this "hard timestamp" to ensure you collect data from the same time range over multiple runs.
Migrating data from InfluxDB (1.x)
vmctl
supports the influx
mode for migrating data from InfluxDB to VictoriaMetrics
time-series database.
See ./vmctl influx --help
for details and full list of flags.
To use migration tool please specify the InfluxDB address --influx-addr
, the database --influx-database
and VictoriaMetrics address --vm-addr
.
Flag --vm-addr
for single-node VM is usually equal to --httpListenAddr
, and for cluster version
is equal to --httpListenAddr
flag of vminsert component. Please note, that vmctl performs initial readiness check for the given address
by checking /health
endpoint. For cluster version it is additionally required to specify the --vm-account-id
flag.
See more details for cluster version here.
As soon as required flags are provided and all endpoints are accessible, vmctl
will start the InfluxDB scheme exploration.
Basically, it just fetches all fields and timeseries from the provided database and builds up registry of all available timeseries.
Then vmctl
sends fetch requests for each timeseries to InfluxDB one by one and pass results to VM importer.
VM importer then accumulates received samples in batches and sends import requests to VM.
The importing process example for local installation of InfluxDB(http://localhost:8086
)
and single-node VictoriaMetrics(http://localhost:8428
):
./vmctl influx --influx-database benchmark
InfluxDB import mode
2020/01/18 20:47:11 Exploring scheme for database "benchmark"
2020/01/18 20:47:11 fetching fields: command: "show field keys"; database: "benchmark"; retention: "autogen"
2020/01/18 20:47:11 found 10 fields
2020/01/18 20:47:11 fetching series: command: "show series "; database: "benchmark"; retention: "autogen"
Found 40000 timeseries to import. Continue? [Y/n] y
40000 / 40000 [-----------------------------------------------------------------------------------------------------------------------------------------------] 100.00% 21 p/s
2020/01/18 21:19:00 Import finished!
2020/01/18 21:19:00 VictoriaMetrics importer stats:
idle duration: 13m51.461434876s;
time spent while importing: 17m56.923899847s;
total samples: 345600000;
samples/s: 320914.04;
total bytes: 5.9 GB;
bytes/s: 5.4 MB;
import requests: 40001;
2020/01/18 21:19:00 Total time: 31m48.467044016s
Data mapping
Vmctl maps InfluxDB data the same way as VictoriaMetrics does by using the following rules:
influx-database
arg is mapped intodb
label value unlessdb
tag exists in the InfluxDB line.- Field names are mapped to time series names prefixed with {measurement}{separator} value,
where {separator} equals to _ by default.
It can be changed with
--influx-measurement-field-separator
command-line flag. - Field values are mapped to time series values.
- Tags are mapped to Prometheus labels format as-is.
For example, the following InfluxDB line:
foo,tag1=value1,tag2=value2 field1=12,field2=40
is converted into the following Prometheus format data points:
foo_field1{tag1="value1", tag2="value2"} 12
foo_field2{tag1="value1", tag2="value2"} 40
Configuration
The configuration flags should contain self-explanatory descriptions.
Filtering
The filtering consists of two parts: timeseries and time.
The first step of application is to select all available timeseries
for given database and retention. User may specify additional filtering
condition via --influx-filter-series
flag. For example:
./vmctl influx --influx-database benchmark \
--influx-filter-series "on benchmark from cpu where hostname='host_1703'"
InfluxDB import mode
2020/01/26 14:23:29 Exploring scheme for database "benchmark"
2020/01/26 14:23:29 fetching fields: command: "show field keys"; database: "benchmark"; retention: "autogen"
2020/01/26 14:23:29 found 12 fields
2020/01/26 14:23:29 fetching series: command: "show series on benchmark from cpu where hostname='host_1703'"; database: "benchmark"; retention: "autogen"
Found 10 timeseries to import. Continue? [Y/n]
The timeseries select query would be following:
fetching series: command: "show series on benchmark from cpu where hostname='host_1703'"; database: "benchmark"; retention: "autogen"
The second step of filtering is a time filter and it applies when fetching the datapoints from Influx. Time filtering may be configured with two flags:
- --influx-filter-time-start
- --influx-filter-time-end
Here's an example of importing timeseries for one day only:
./vmctl influx --influx-database benchmark --influx-filter-series "where hostname='host_1703'" --influx-filter-time-start "2020-01-01T10:07:00Z" --influx-filter-time-end "2020-01-01T15:07:00Z"
Please see more about time filtering here.
Migrating data from InfluxDB (2.x)
Migrating data from InfluxDB v2.x is not supported yet (#32). You may find useful a 3rd party solution for this - https://github.com/jonppe/influx_to_victoriametrics.
Migrating data from Prometheus
vmctl
supports the prometheus
mode for migrating data from Prometheus to VictoriaMetrics time-series database.
Migration is based on reading Prometheus snapshot, which is basically a hard-link to Prometheus data files.
See ./vmctl prometheus --help
for details and full list of flags. Also see Prometheus related articles here.
To use migration tool please specify the file path to Prometheus snapshot --prom-snapshot
(see how to make a snapshot here) and VictoriaMetrics address --vm-addr
.
Please note, that vmctl
do not make a snapshot from Prometheus, it uses an already prepared snapshot. More about Prometheus snapshots may be found here and here.
Flag --vm-addr
for single-node VM is usually equal to --httpListenAddr
, and for cluster version
is equal to --httpListenAddr
flag of vminsert component. Please note, that vmctl performs initial readiness check for the given address
by checking /health
endpoint. For cluster version it is additionally required to specify the --vm-account-id
flag.
See more details for cluster version here.
As soon as required flags are provided and all endpoints are accessible, vmctl
will start the Prometheus snapshot exploration.
Basically, it just fetches all available blocks in provided snapshot and read the metadata. It also does initial filtering by time
if flags --prom-filter-time-start
or --prom-filter-time-end
were set. The exploration procedure prints some stats from read blocks.
Please note that stats are not taking into account timeseries or samples filtering. This will be done during importing process.
The importing process takes the snapshot blocks revealed from Explore procedure and processes them one by one
accumulating timeseries and samples. Please note, that vmctl
relies on responses from InfluxDB on this stage,
so ensure that Explore queries are executed without errors or limits. Please see this
issue for details.
The data processed in chunks and then sent to VM.
The importing process example for local installation of Prometheus
and single-node VictoriaMetrics(http://localhost:8428
):
./vmctl prometheus --prom-snapshot=/path/to/snapshot \
--vm-concurrency=1 \
--vm-batch-size=200000 \
--prom-concurrency=3
Prometheus import mode
Prometheus snapshot stats:
blocks found: 14;
blocks skipped: 0;
min time: 1581288163058 (2020-02-09T22:42:43Z);
max time: 1582409128139 (2020-02-22T22:05:28Z);
samples: 32549106;
series: 27289.
Found 14 blocks to import. Continue? [Y/n] y
14 / 14 [-------------------------------------------------------------------------------------------] 100.00% 0 p/s
2020/02/23 15:50:03 Import finished!
2020/02/23 15:50:03 VictoriaMetrics importer stats:
idle duration: 6.152953029s;
time spent while importing: 44.908522491s;
total samples: 32549106;
samples/s: 724786.84;
total bytes: 669.1 MB;
bytes/s: 14.9 MB;
import requests: 323;
import requests retries: 0;
2020/02/23 15:50:03 Total time: 51.077451066s
Data mapping
VictoriaMetrics has very similar data model to Prometheus and supports RemoteWrite integration. So no data changes will be applied.
Configuration
The configuration flags should contain self-explanatory descriptions.
Filtering
The filtering consists of three parts: by timeseries and time.
Filtering by time may be configured via flags --prom-filter-time-start
and --prom-filter-time-end
in in RFC3339 format. This filter applied twice: to drop blocks out of range and to filter timeseries in blocks with
overlapping time range.
Example of applying time filter:
./vmctl prometheus --prom-snapshot=/path/to/snapshot \
--prom-filter-time-start=2020-02-07T00:07:01Z \
--prom-filter-time-end=2020-02-11T00:07:01Z
Prometheus import mode
Prometheus snapshot stats:
blocks found: 2;
blocks skipped: 12;
min time: 1581288163058 (2020-02-09T22:42:43Z);
max time: 1581328800000 (2020-02-10T10:00:00Z);
samples: 1657698;
series: 3930.
Found 2 blocks to import. Continue? [Y/n] y
Please notice, that total amount of blocks in provided snapshot is 14, but only 2 of them were in provided
time range. So other 12 blocks were marked as skipped
. The amount of samples and series is not taken into account,
since this is heavy operation and will be done during import process.
Filtering by timeseries is configured with following flags:
--prom-filter-label
- the label name, e.g.__name__
orinstance
;--prom-filter-label-value
- the regular expression to filter the label value. By default matches all.*
For example:
./vmctl prometheus --prom-snapshot=/path/to/snapshot \
--prom-filter-label="__name__" \
--prom-filter-label-value="promhttp.*" \
--prom-filter-time-start=2020-02-07T00:07:01Z \
--prom-filter-time-end=2020-02-11T00:07:01Z
Prometheus import mode
Prometheus snapshot stats:
blocks found: 2;
blocks skipped: 12;
min time: 1581288163058 (2020-02-09T22:42:43Z);
max time: 1581328800000 (2020-02-10T10:00:00Z);
samples: 1657698;
series: 3930.
Found 2 blocks to import. Continue? [Y/n] y
14 / 14 [------------------------------------------------------------------------------------------------------------------------------------------------------] 100.00% ? p/s
2020/02/23 15:51:07 Import finished!
2020/02/23 15:51:07 VictoriaMetrics importer stats:
idle duration: 0s;
time spent while importing: 37.415461ms;
total samples: 10128;
samples/s: 270690.24;
total bytes: 195.2 kB;
bytes/s: 5.2 MB;
import requests: 2;
import requests retries: 0;
2020/02/23 15:51:07 Total time: 7.153158218s
Migrating data from Thanos
Thanos uses the same storage engine as Prometheus and the data layout on-disk should be the same. That means
vmctl
in mode prometheus
may be used for Thanos historical data migration as well.
These instructions may vary based on the details of your Thanos configuration.
Please read carefully and verify as you go. We assume you're using Thanos Sidecar on your Prometheus pods,
and that you have a separate Thanos Store installation.
Current data
-
For now, keep your Thanos Sidecar and Thanos-related Prometheus configuration, but add this to also stream metrics to VictoriaMetrics:
remote_write: - url: http://victoria-metrics:8428/api/v1/write
-
Make sure VM is running, of course. Now check the logs to make sure that Prometheus is sending and VM is receiving. In Prometheus, make sure there are no errors. On the VM side, you should see messages like this:
2020-04-27T18:38:46.474Z info VictoriaMetrics/lib/storage/partition.go:207 creating a partition "2020_04" with smallPartsPath="/victoria-metrics-data/data/small/2020_04", bigPartsPath="/victoria-metrics-data/data/big/2020_04" 2020-04-27T18:38:46.506Z info VictoriaMetrics/lib/storage/partition.go:222 partition "2020_04" has been created
-
Now just wait. Within two hours, Prometheus should finish its current data file and hand it off to Thanos Store for long term storage.
Historical data
Let's assume your data is stored on S3 served by minio. You first need to copy that out to a local filesystem,
then import it into VM using vmctl
in prometheus
mode.
-
Copy data from minio.
- Run the
minio/mc
Docker container. mc config host add minio http://minio:9000 accessKey secretKey
, substituting appropriate values for the last 3 items.mc cp -r minio/prometheus thanos-data
- Run the
-
Import using
vmctl
.- Follow the instructions to compile
vmctl
on your machine. - Use prometheus mode to import data:
vmctl prometheus --prom-snapshot thanos-data --vm-addr http://victoria-metrics:8428
- Follow the instructions to compile
Migrating data from VictoriaMetrics
Native protocol
The native binary protocol was introduced in 1.42.0 release and provides the most efficient way to migrate data between VM instances: single to single, cluster to cluster, single to cluster and vice versa. Please note that both instances (source and destination) should be of v1.42.0 or higher.
See ./vmctl vm-native --help
for details and full list of flags.
In this mode vmctl
acts as a proxy between two VM instances, where time series filtering is done by "source" (src
)
and processing is done by "destination" (dst
). Because of that, vmctl
doesn't actually know how much data will be
processed and can't show the progress bar. It will show the current processing speed and total number of processed bytes:
./vmctl vm-native --vm-native-src-addr=http://localhost:8528 \
--vm-native-dst-addr=http://localhost:8428 \
--vm-native-filter-match='{job="vmagent"}' \
--vm-native-filter-time-start='2020-01-01T20:07:00Z'
VictoriaMetrics Native import mode
Initing export pipe from "http://localhost:8528" with filters:
filter: match[]={job="vmagent"}
Initing import process to "http://localhost:8428":
Total: 336.75 KiB ↖ Speed: 454.46 KiB p/s
2020/10/13 17:04:59 Total time: 952.143376ms
Importing tips:
- Migrating big volumes of data may result in reaching the safety limits on
src
side. Please verify that-search.maxExportDuration
and-search.maxExportSeries
were set with proper values forsrc
. If hitting the limits, follow the recommendations here. - Migrating all the metrics from one VM to another may collide with existing application metrics
(prefixed with
vm_
) at destination and lead to confusion when using official Grafana dashboards. To avoid such situation try to filter out VM process metrics via--vm-native-filter-match
flag. - Migration is a backfilling process, so it is recommended to read Backfilling tips section.
vmctl
doesn't provide relabeling or other types of labels management in this mode. Instead, use relabeling in VictoriaMetrics.- When importing in or from cluster version remember to use correct URL format
and specify
accountID
param. - When migrating large volumes of data it might be useful to use
--vm-native-step-interval
flag to split single process into smaller steps.
Using time-based chunking of migration
It is possible split migration process into set of smaller batches based on time. This is especially useful when migrating large volumes of data as this adds indication of progress and ability to restore process from certain point in case of failure.
To use this you need to specify --vm-native-step-interval
flag. Supported values are: month
, day
, hour
.
Note that in order to use this it is required --vm-native-filter-time-start
to be set to calculate time ranges for export process.
Every range is being processed independently, which means that:
- after range processing is finished all data within range is migrated
- if process fails on one of stages it is guaranteed that data of prior stages is already written, so it is possible to restart process starting from failed range
It is recommended using the month
step when migrating the data over multiple months, since the migration with day
and hour
steps may take longer time to complete
because of additional overhead.
Usage example:
./vmctl vm-native
--vm-native-filter-time-start 2022-06-17T00:07:00Z \
--vm-native-filter-time-end 2022-10-03T00:07:00Z \
--vm-native-src-addr http://localhost:8428 \
--vm-native-dst-addr http://localhost:8528 \
--vm-native-step-interval=month
VictoriaMetrics Native import mode
2022/08/30 19:48:24 Processing range 1/5: 2022-06-17T00:07:00Z - 2022-06-30T23:59:59Z
2022/08/30 19:48:24 Initing export pipe from "http://localhost:8428" with filters:
filter: match[]={__name__!=""}
start: 2022-06-17T00:07:00Z
end: 2022-06-30T23:59:59Z
Initing import process to "http://localhost:8428":
2022/08/30 19:48:24 Import finished!
Total: 16 B ↗ Speed: 28.89 KiB p/s
2022/08/30 19:48:24 Processing range 2/5: 2022-07-01T00:00:00Z - 2022-07-31T23:59:59Z
2022/08/30 19:48:24 Initing export pipe from "http://localhost:8428" with filters:
filter: match[]={__name__!=""}
start: 2022-07-01T00:00:00Z
end: 2022-07-31T23:59:59Z
Initing import process to "http://localhost:8428":
2022/08/30 19:48:24 Import finished!
Total: 16 B ↗ Speed: 164.35 KiB p/s
2022/08/30 19:48:24 Processing range 3/5: 2022-08-01T00:00:00Z - 2022-08-31T23:59:59Z
2022/08/30 19:48:24 Initing export pipe from "http://localhost:8428" with filters:
filter: match[]={__name__!=""}
start: 2022-08-01T00:00:00Z
end: 2022-08-31T23:59:59Z
Initing import process to "http://localhost:8428":
2022/08/30 19:48:24 Import finished!
Total: 16 B ↗ Speed: 191.42 KiB p/s
2022/08/30 19:48:24 Processing range 4/5: 2022-09-01T00:00:00Z - 2022-09-30T23:59:59Z
2022/08/30 19:48:24 Initing export pipe from "http://localhost:8428" with filters:
filter: match[]={__name__!=""}
start: 2022-09-01T00:00:00Z
end: 2022-09-30T23:59:59Z
Initing import process to "http://localhost:8428":
2022/08/30 19:48:24 Import finished!
Total: 16 B ↗ Speed: 141.04 KiB p/s
2022/08/30 19:48:24 Processing range 5/5: 2022-10-01T00:00:00Z - 2022-10-03T00:07:00Z
2022/08/30 19:48:24 Initing export pipe from "http://localhost:8428" with filters:
filter: match[]={__name__!=""}
start: 2022-10-01T00:00:00Z
end: 2022-10-03T00:07:00Z
Initing import process to "http://localhost:8428":
2022/08/30 19:48:24 Import finished!
Total: 16 B ↗ Speed: 186.32 KiB p/s
2022/08/30 19:48:24 Total time: 12.680582ms
Verifying exported blocks from VictoriaMetrics
In this mode, vmctl
allows verifying correctness and integrity of data exported via native format from VictoriaMetrics.
You can verify exported data at disk before uploading it by vmctl verify-block
command:
# export blocks from VictoriaMetrics
curl localhost:8428/api/v1/export/native -g -d 'match[]={__name__!=""}' -o exported_data_block
# verify block content
./vmctl verify-block exported_data_block
2022/03/30 18:04:50 verifying block at path="exported_data_block"
2022/03/30 18:04:50 successfully verified block at path="exported_data_block", blockCount=123786
2022/03/30 18:04:50 Total time: 100.108ms
Tuning
InfluxDB mode
The flag --influx-concurrency
controls how many concurrent requests may be sent to InfluxDB while fetching
timeseries. Please set it wisely to avoid InfluxDB overwhelming.
The flag --influx-chunk-size
controls the max amount of datapoints to return in single chunk from fetch requests.
Please see more details here.
The chunk size is used to control InfluxDB memory usage, so it won't OOM on processing large timeseries with
billions of datapoints.
Prometheus mode
The flag --prom-concurrency
controls how many concurrent readers will be reading the blocks in snapshot.
Since snapshots are just files on disk it would be hard to overwhelm the system. Please go with value equal
to number of free CPU cores.
VictoriaMetrics importer
The flag --vm-concurrency
controls the number of concurrent workers that process the input from InfluxDB query results.
Please note that each import request can load up to a single vCPU core on VictoriaMetrics. So try to set it according
to allocated CPU resources of your VictoriMetrics installation.
The flag --vm-batch-size
controls max amount of samples collected before sending the import request.
For example, if --influx-chunk-size=500
and --vm-batch-size=2000
then importer will process not more
than 4 chunks before sending the request.
Importer stats
After successful import vmctl
prints some statistics for details.
The important numbers to watch are following:
idle duration
- shows time that importer spent while waiting for data from InfluxDB/Prometheus to fill up--vm-batch-size
batch size. Value shows total duration across all workers configured via--vm-concurrency
. High value may be a sign of too slow InfluxDB/Prometheus fetches or too high--vm-concurrency
value. Try to improve it by increasing--<mode>-concurrency
value or decreasing--vm-concurrency
value.import requests
- shows how many import requests were issued to VM server. The import request is issued once the batch size(--vm-batch-size
) is full and ready to be sent. Please prefer big batch sizes (50k-500k) to improve performance.import requests retries
- shows number of unsuccessful import requests. Non-zero value may be a sign of network issues or VM being overloaded. See the logs during import for error messages.
Silent mode
By default vmctl
waits confirmation from user before starting the import. If this is unwanted
behavior and no user interaction required - pass -s
flag to enable "silence" mode:
-s Whether to run in silent mode. If set to true no confirmation prompts will appear. (default: false)
Significant figures
vmctl
allows to limit the number of significant figures
before importing. For example, the average value for response size is 102.342305
bytes and it has 9 significant figures.
If you ask a human to pronounce this value then with high probability value will be rounded to first 4 or 5 figures
because the rest aren't really that important to mention. In most cases, such a high precision is too much.
Moreover, such values may be just a result of floating point arithmetic,
create a false precision and result into bad compression ratio
according to information theory.
vmctl
provides the following flags for improving data compression:
-
--vm-round-digits
flag for rounding processed values to the given number of decimal digits after the point. For example,--vm-round-digits=2
would round1.2345
to1.23
. By default the rounding is disabled. -
--vm-significant-figures
flag for limiting the number of significant figures in processed values. It takes no effect if set to 0 (by default), but set--vm-significant-figures=5
and102.342305
will be rounded to102.34
.
The most common case for using these flags is to improve data compression for time series storing aggregation
results such as average
, rate
, etc.
Adding extra labels
vmctl
allows to add extra labels to all imported series. It can be achived with flag --vm-extra-label label=value
.
If multiple labels needs to be added, set flag for each label, for example, --vm-extra-label label1=value1 --vm-extra-label label2=value2
.
If timeseries already have label, that must be added with --vm-extra-label
flag, flag has priority and will override label value from timeseries.
Rate limiting
Limiting the rate of data transfer could help to reduce pressure on disk or on destination database.
The rate limit may be set in bytes-per-second via --vm-rate-limit
flag.
Please note, you can also use vmagent
as a proxy between vmctl
and destination with -remoteWrite.rateLimit
flag enabled.
How to build
It is recommended using binary releases - vmctl
is located in vmutils-*
archives there.
Development build
- Install Go. The minimum supported version is Go 1.19.1.
- Run
make vmctl
from the root folder of the repository. It buildsvmctl
binary and puts it into thebin
folder.
Production build
- Install docker.
- Run
make vmctl-prod
from the root folder of the repository. It buildsvmctl-prod
binary and puts it into thebin
folder.
Building docker images
Run make package-vmctl
. It builds victoriametrics/vmctl:<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-vmctl
.
The base docker image is alpine but it is possible to use any other base image
by setting it via <ROOT_IMAGE>
environment variable. For example, the following command builds the image on top of scratch image:
ROOT_IMAGE=scratch make package-vmctl
ARM build
ARM build may run on Raspberry Pi or on energy-efficient ARM servers.
Development ARM build
- Install Go. The minimum supported version is Go 1.19.1.
- Run
make vmctl-linux-arm
ormake vmctl-linux-arm64
from the root folder of the repository. It buildsvmctl-linux-arm
orvmctl-linux-arm64
binary respectively and puts it into thebin
folder.
Production ARM build
- Install docker.
- Run
make vmctl-linux-arm-prod
ormake vmctl-linux-arm64-prod
from the root folder of the repository. It buildsvmctl-linux-arm-prod
orvmctl-linux-arm64-prod
binary respectively and puts it into thebin
folder.