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author | Daniel Baumann <daniel.baumann@progress-linux.org> | 2024-04-27 11:08:07 +0000 |
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committer | Daniel Baumann <daniel.baumann@progress-linux.org> | 2024-04-27 11:08:07 +0000 |
commit | c69cb8cc094cc916adbc516b09e944cd3d137c01 (patch) | |
tree | f2878ec41fb6d0e3613906c6722fc02b934eeb80 /database/README.md | |
parent | Initial commit. (diff) | |
download | netdata-c69cb8cc094cc916adbc516b09e944cd3d137c01.tar.xz netdata-c69cb8cc094cc916adbc516b09e944cd3d137c01.zip |
Adding upstream version 1.29.3.upstream/1.29.3upstream
Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>
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-rw-r--r-- | database/README.md | 215 |
1 files changed, 215 insertions, 0 deletions
diff --git a/database/README.md b/database/README.md new file mode 100644 index 0000000..9fef705 --- /dev/null +++ b/database/README.md @@ -0,0 +1,215 @@ +<!-- +title: "Database" +description: "The Netdata Agent leverages multiple, user-configurable time-series databases that use RAM and/or disk to store metrics on any type of node." +custom_edit_url: https://github.com/netdata/netdata/edit/master/database/README.md +--> + +# Database + +Netdata is fully capable of long-term metrics storage, at per-second granularity, via its default database engine +(`dbengine`). But to remain as flexible as possible, Netdata supports a number of types of metrics storage: + +1. `dbengine`, (the default) data are in database files. The [Database Engine](/database/engine/README.md) works like a + traditional database. There is some amount of RAM dedicated to data caching and indexing and the rest of the data + reside compressed on disk. The number of history entries is not fixed in this case, but depends on the configured + disk space and the effective compression ratio of the data stored. This is the **only mode** that supports changing + the data collection update frequency (`update_every`) **without losing** the previously stored metrics. For more + details see [here](/database/engine/README.md). + +2. `ram`, data are purely in memory. Data are never saved on disk. This mode uses `mmap()` and supports [KSM](#ksm). + +3. `save`, data are only in RAM while Netdata runs and are saved to / loaded from disk on Netdata + restart. It also uses `mmap()` and supports [KSM](#ksm). + +4. `map`, data are in memory mapped files. This works like the swap. Keep in mind though, this will have a constant + write on your disk. When Netdata writes data on its memory, the Linux kernel marks the related memory pages as dirty + and automatically starts updating them on disk. Unfortunately we cannot control how frequently this works. The Linux + kernel uses exactly the same algorithm it uses for its swap memory. Check below for additional information on + running a dedicated central Netdata server. This mode uses `mmap()` but does not support [KSM](#ksm). + +5. `none`, without a database (collected metrics can only be streamed to another Netdata). + +6. `alloc`, like `ram` but it uses `calloc()` and does not support [KSM](#ksm). This mode is the fallback for all + others except `none`. + +You can select the memory mode by editing `netdata.conf` and setting: + +```conf +[global] + # dbengine (default), ram, save (the default if dbengine not available), map (swap like), none, alloc + memory mode = dbengine + + # the directory where data are saved + cache directory = /var/cache/netdata +``` + +## Running Netdata in embedded devices + +Embedded devices usually have very limited RAM resources available. + +There are 2 settings for you to tweak: + +1. `update every`, which controls the data collection frequency +2. `history`, which controls the size of the database in RAM (except for `memory mode = dbengine`) + +By default `update every = 1` and `history = 3600`. This gives you an hour of data with per second updates. + +If you set `update every = 2` and `history = 1800`, you will still have an hour of data, but collected once every 2 +seconds. This will **cut in half** both CPU and RAM resources consumed by Netdata. Of course experiment a bit. On very +weak devices you might have to use `update every = 5` and `history = 720` (still 1 hour of data, but 1/5 of the CPU and +RAM resources). + +You can also disable [data collection plugins](/collectors/README.md) you don't need. Disabling such plugins will also free both +CPU and RAM resources. + +## Running a dedicated central Netdata server + +Netdata allows streaming data between Netdata nodes. This allows us to have a central Netdata server that will maintain +the entire database for all nodes, and will also run health checks/alarms for all nodes. + +For this central Netdata, memory size can be a problem. Fortunately, Netdata supports several memory modes. **One +interesting option** for this setup is `memory mode = map`. + +### map + +In this mode, the database of Netdata is stored in memory mapped files. Netdata continues to read and write the database +in memory, but the kernel automatically loads and saves memory pages from/to disk. + +**We suggest _not_ to use this mode on nodes that run other applications.** There will always be dirty memory to be +synced and this syncing process may influence the way other applications work. This mode however is useful when we need +a central Netdata server that would normally need huge amounts of memory. Using memory mode `map` we can overcome all +memory restrictions. + +There are a few kernel options that provide finer control on the way this syncing works. But before explaining them, a +brief introduction of how Netdata database works is needed. + +For each chart, Netdata maps the following files: + +1. `chart/main.db`, this is the file that maintains chart information. Every time data are collected for a chart, this + is updated. +2. `chart/dimension_name.db`, this is the file for each dimension. At its beginning there is a header, followed by the + round robin database where metrics are stored. + +So, every time Netdata collects data, the following pages will become dirty: + +1. the chart file +2. the header part of all dimension files +3. if the collected metrics are stored far enough in the dimension file, another page will become dirty, for each + dimension + +Each page in Linux is 4KB. So, with 200 charts and 1000 dimensions, there will be 1200 to 2200 4KB pages dirty pages +every second. Of course 1200 of them will always be dirty (the chart header and the dimensions headers) and 1000 will be +dirty for about 1000 seconds (4 bytes per metric, 4KB per page, so 1000 seconds, or 16 minutes per page). + +Hopefully, the Linux kernel does not sync all these data every second. The frequency they are synced is controlled by +`/proc/sys/vm/dirty_expire_centisecs` or the `sysctl` `vm.dirty_expire_centisecs`. The default on most systems is 3000 +(30 seconds). + +On a busy server centralizing metrics from 20+ servers you will experience this: + +![image](https://cloud.githubusercontent.com/assets/2662304/23834750/429ab0dc-0764-11e7-821a-d7908bc881ac.png) + +As you can see, there is quite some stress (this is `iowait`) every 30 seconds. + +A simple solution is to increase this time to 10 minutes (60000). This is the same system with this setting in 10 +minutes: + +![image](https://cloud.githubusercontent.com/assets/2662304/23834784/d2304f72-0764-11e7-8389-fb830ffd973a.png) + +Of course, setting this to 10 minutes means that data on disk might be up to 10 minutes old if you get an abnormal +shutdown. + +There are 2 more options to tweak: + +1. `dirty_background_ratio`, by default `10`. +2. `dirty_ratio`, by default `20`. + +These control the amount of memory that should be dirty for disk syncing to be triggered. On dedicated Netdata servers, +you can use: `80` and `90` respectively, so that all RAM is given to Netdata. + +With these settings, you can expect a little `iowait` spike once every 10 minutes and in case of system crash, data on +disk will be up to 10 minutes old. + +![image](https://cloud.githubusercontent.com/assets/2662304/23835030/ba4bf506-0768-11e7-9bc6-3b23e080c69f.png) + +To have these settings automatically applied on boot, create the file `/etc/sysctl.d/netdata-memory.conf` with these +contents: + +```conf +vm.dirty_expire_centisecs = 60000 +vm.dirty_background_ratio = 80 +vm.dirty_ratio = 90 +vm.dirty_writeback_centisecs = 0 +``` + +There is another memory mode to help overcome the memory size problem. What is **most interesting for this setup** is +`memory mode = dbengine`. + +### dbengine + +In this mode, the database of Netdata is stored in database files. The [Database Engine](/database/engine/README.md) +works like a traditional database. There is some amount of RAM dedicated to data caching and indexing and the rest of +the data reside compressed on disk. The number of history entries is not fixed in this case, but depends on the +configured disk space and the effective compression ratio of the data stored. + +We suggest to use **this** mode on nodes that also run other applications. The Database Engine uses direct I/O to avoid +polluting the OS filesystem caches and does not generate excessive I/O traffic so as to create the minimum possible +interference with other applications. Using memory mode `dbengine` we can overcome most memory restrictions. For more +details see [here](/database/engine/README.md). + +## KSM + +Netdata offers all its round robin database to kernel for deduplication (except for `memory mode = dbengine`). + +In the past KSM has been criticized for consuming a lot of CPU resources. Although this is true when KSM is used for +deduplicating certain applications, it is not true with netdata, since the Netdata memory is written very infrequently +(if you have 24 hours of metrics in netdata, each byte at the in-memory database will be updated just once per day). + +KSM is a solution that will provide 60+% memory savings to Netdata. + +### Enable KSM in kernel + +You need to run a kernel compiled with: + +```sh +CONFIG_KSM=y +``` + +When KSM is enabled at the kernel is just available for the user to enable it. + +So, if you build a kernel with `CONFIG_KSM=y` you will just get a few files in `/sys/kernel/mm/ksm`. Nothing else +happens. There is no performance penalty (apart I guess from the memory this code occupies into the kernel). + +The files that `CONFIG_KSM=y` offers include: + +- `/sys/kernel/mm/ksm/run` by default `0`. You have to set this to `1` for the + kernel to spawn `ksmd`. +- `/sys/kernel/mm/ksm/sleep_millisecs`, by default `20`. The frequency ksmd + should evaluate memory for deduplication. +- `/sys/kernel/mm/ksm/pages_to_scan`, by default `100`. The amount of pages + ksmd will evaluate on each run. + +So, by default `ksmd` is just disabled. It will not harm performance and the user/admin can control the CPU resources +he/she is willing `ksmd` to use. + +### Run `ksmd` kernel daemon + +To activate / run `ksmd` you need to run: + +```sh +echo 1 >/sys/kernel/mm/ksm/run +echo 1000 >/sys/kernel/mm/ksm/sleep_millisecs +``` + +With these settings ksmd does not even appear in the running process list (it will run once per second and evaluate 100 +pages for de-duplication). + +Put the above lines in your boot sequence (`/etc/rc.local` or equivalent) to have `ksmd` run at boot. + +## Monitoring Kernel Memory de-duplication performance + +Netdata will create charts for kernel memory de-duplication performance, like this: + +![image](https://cloud.githubusercontent.com/assets/2662304/11998786/eb23ae54-aab6-11e5-94d4-e848e8a5c56a.png) + +[![analytics](https://www.google-analytics.com/collect?v=1&aip=1&t=pageview&_s=1&ds=github&dr=https%3A%2F%2Fgithub.com%2Fnetdata%2Fnetdata&dl=https%3A%2F%2Fmy-netdata.io%2Fgithub%2Fdatabase%2FREADME&_u=MAC~&cid=5792dfd7-8dc4-476b-af31-da2fdb9f93d2&tid=UA-64295674-3)](<>) |