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author | Daniel Baumann <daniel.baumann@progress-linux.org> | 2024-05-06 01:22:31 +0000 |
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committer | Daniel Baumann <daniel.baumann@progress-linux.org> | 2024-05-06 01:22:31 +0000 |
commit | 8d4f58e49b9dc7d3545651023a36729de773ad86 (patch) | |
tree | 7bc7be4a8e9e298daa1349348400aa2a653866f2 /database/README.md | |
parent | Initial commit. (diff) | |
download | netdata-upstream.tar.xz netdata-upstream.zip |
Adding upstream version 1.12.0.upstream/1.12.0upstream
Signed-off-by: Daniel Baumann <daniel.baumann@progress-linux.org>
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-rw-r--r-- | database/README.md | 208 |
1 files changed, 208 insertions, 0 deletions
diff --git a/database/README.md b/database/README.md new file mode 100644 index 0000000..aedf4d5 --- /dev/null +++ b/database/README.md @@ -0,0 +1,208 @@ +# Database + +Although `netdata` does all its calculations using `long double`, it stores all values using +a [custom-made 32-bit number](../libnetdata/storage_number/). + +So, for each dimension of a chart, netdata will need: `4 bytes for the value * the entries +of its history`. It will not store any other data for each value in the time series database. +Since all its values are stored in a time series with fixed step, the time each value +corresponds can be calculated at run time, using the position of a value in the round robin database. + +The default history is 3.600 entries, thus it will need 14.4KB for each chart dimension. +If you need 1.000 dimensions, they will occupy just 14.4MB. + +Of course, 3.600 entries is a very short history, especially if data collection frequency is set +to 1 second. You will have just one hour of data. + +For a day of data and 1.000 dimensions, you will need: 86.400 seconds * 4 bytes * 1.000 +dimensions = 345MB of RAM. + +Currently the only option you have to lower this number is to use +**[Memory Deduplication - Kernel Same Page Merging - KSM](#ksm)**. + +## Memory modes + +Currently netdata supports 5 memory modes: + +1. `ram`, data are purely in memory. Data are never saved on disk. This mode uses `mmap()` and + supports [KSM](#ksm). + +2. `save`, (the default) 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). + +3. `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). + +4. `none`, without a database (collected metrics can only be streamed to another netdata). + +5. `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: + +``` +[global] + # ram, save (the default, save on exit, load on start), map (swap like) + memory mode = save + + # 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 + +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) 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. What is interesting for this setup is `memory mode = 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 ideal 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: + +``` +vm.dirty_expire_centisecs = 60000 +vm.dirty_background_ratio = 80 +vm.dirty_ratio = 90 +vm.dirty_writeback_centisecs = 0 +``` + +## KSM + +Netdata offers all its round robin database to kernel for deduplication. + +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)]() |