diff options
-rw-r--r-- | daemon/config/README.md | 42 | ||||
-rw-r--r-- | database/README.md | 213 | ||||
-rw-r--r-- | database/engine/README.md | 206 | ||||
-rw-r--r-- | docs/store/change-metrics-storage.md | 95 | ||||
-rw-r--r-- | docs/store/distributed-data-architecture.md | 67 |
5 files changed, 329 insertions, 294 deletions
diff --git a/daemon/config/README.md b/daemon/config/README.md index 32d64405b5..7b4d27ecff 100644 --- a/daemon/config/README.md +++ b/daemon/config/README.md @@ -82,21 +82,33 @@ Please note that your data history will be lost if you have modified `history` p ### [db] section options -| setting | default | info | -|:----------------------------------:|:----------:|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| -| mode | `dbengine` | `dbengine`: The default for long-term metrics storage with efficient RAM and disk usage. Can be extended with `dbengine page cache size MB` and `dbengine disk space MB`. <br />`save`: Netdata will save its round robin database on exit and load it on startup. <br />`map`: Cache files will be updated in real-time. Not ideal for systems with high load or slow disks (check `man mmap`). <br />`ram`: The round-robin database will be temporary and it will be lost when Netdata exits. <br />`none`: Disables the database at this host, and disables health monitoring entirely, as that requires a database of metrics. | -| retention | `3600` | Used with `mode = save/map/ram/alloc`, not the default `mode = dbengine`. This number reflects the number of entries the `netdata` daemon will by default keep in memory for each chart dimension. Check [Memory Requirements](/database/README.md) for more information. | -| update every | `1` | The frequency in seconds, for data collection. For more information see the [performance guide](/docs/guides/configure/performance.md). | -| dbengine page cache size MB | 32 | Determines the amount of RAM in MiB that is dedicated to caching Netdata metric values. | -| dbengine disk space MB | 256 | Determines the amount of disk space in MiB that is dedicated to storing Netdata metric values and all related metadata describing them. | -| dbengine multihost disk space MB | 256 | Same functionality as `dbengine disk space MB`, but includes support for storing metrics streamed to a parent node by its children. Can be used in single-node environments as well. | -| memory deduplication (ksm) | `yes` | When set to `yes`, Netdata will offer its in-memory round robin database and the dbengine page cache to kernel same page merging (KSM) for deduplication. For more information check [Memory Deduplication - Kernel Same Page Merging - KSM](/database/README.md#ksm) | -| cleanup obsolete charts after secs | `3600` | See [monitoring ephemeral containers](/collectors/cgroups.plugin/README.md#monitoring-ephemeral-containers), also sets the timeout for cleaning up obsolete dimensions | -| gap when lost iterations above | `1` | | -| cleanup orphan hosts after secs | `3600` | How long to wait until automatically removing from the DB a remote Netdata host (child) that is no longer sending data. | -| delete obsolete charts files | `yes` | See [monitoring ephemeral containers](/collectors/cgroups.plugin/README.md#monitoring-ephemeral-containers), also affects the deletion of files for obsolete dimensions | -| delete orphan hosts files | `yes` | Set to `no` to disable non-responsive host removal. | -| enable zero metrics | `no` | Set to `yes` to show charts when all their metrics are zero. | +| setting | default | info | +|:---------------------------------------------:|:----------:|:------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| +| mode | `dbengine` | `dbengine`: The default for long-term metrics storage with efficient RAM and disk usage. Can be extended with `dbengine page cache size MB` and `dbengine disk space MB`. <br />`save`: Netdata will save its round robin database on exit and load it on startup. <br />`map`: Cache files will be updated in real-time. Not ideal for systems with high load or slow disks (check `man mmap`). <br />`ram`: The round-robin database will be temporary and it will be lost when Netdata exits. <br />`none`: Disables the database at this host, and disables health monitoring entirely, as that requires a database of metrics. | +| retention | `3600` | Used with `mode = save/map/ram/alloc`, not the default `mode = dbengine`. This number reflects the number of entries the `netdata` daemon will by default keep in memory for each chart dimension. Check [Memory Requirements](/database/README.md) for more information. | +| storage tiers | `1` | The number of storage tiers you want to have in your dbengine. Check the tiering mechanism in the [dbengine's reference](/database/engine/README.md#tiering). You can have up to 5 tiers of data (including the _Tier 0_). This number ranges between 1 and 5. | +| dbengine page cache size MB | `32` | Determines the amount of RAM in MiB that is dedicated to caching for _Tier 0_ Netdata metric values. | +| dbengine tier **`N`** page cache size MB | `32` | Determines the amount of RAM in MiB that is dedicated for caching Netdata metric values of the **`N`** tier. <br /> `N belongs to [1..4]` || + | dbengine disk space MB | `256` | Determines the amount of disk space in MiB that is dedicated to storing _Tier 0_ Netdata metric values and all related metadata describing them. This option is available **only for legacy configuration** (`Agent v1.23.2 and prior`). | +| dbengine multihost disk space MB | `256` | Same functionality as `dbengine disk space MB`, but includes support for storing metrics streamed to a parent node by its children. Can be used in single-node environments as well. This setting is only for _Tier 0_ metrics. | +| dbengine tier **`N`** multihost disk space MB | `256` | Same functionality as `dbengine multihost disk space MB`, but stores metrics of the **`N`** tier (both parent node and its children). Can be used in single-node environments as well. <br /> `N belongs to [1..4]` | +| update every | `1` | The frequency in seconds, for data collection. For more information see the [performance guide](/docs/guides/configure/performance.md). These metrics stored as _Tier 0_ data. Explore the tiering mechanism in the [dbengine's reference](/database/engine/README.md#tiering). | +| dbengine tier **`N`** update every iterations | `60` | The down sampling value of each tier from the previous one. For each Tier, the greater by one Tier has N (equal to 60 by default) less data points of any metric it collects. This setting can take values from `2` up to `255`. <br /> `N belongs to [1..4]` | +| dbengine tier **`N`** back fill | `New` | Specifies the strategy of recreating missing data on each Tier from the exact lower Tier. <br /> `New`: Sees the latest point on each Tier and save new points to it only if the exact lower Tier has available points for it's observation window (`dbengine tier N update every iterations` window). <br /> `none`: No back filling is applied. <br /> `N belongs to [1..4]` | +| memory deduplication (ksm) | `yes` | When set to `yes`, Netdata will offer its in-memory round robin database and the dbengine page cache to kernel same page merging (KSM) for deduplication. For more information check [Memory Deduplication - Kernel Same Page Merging - KSM](/database/README.md#ksm) | +| cleanup obsolete charts after secs | `3600` | See [monitoring ephemeral containers](/collectors/cgroups.plugin/README.md#monitoring-ephemeral-containers), also sets the timeout for cleaning up obsolete dimensions | +| gap when lost iterations above | `1` | | +| cleanup orphan hosts after secs | `3600` | How long to wait until automatically removing from the DB a remote Netdata host (child) that is no longer sending data. | +| delete obsolete charts files | `yes` | See [monitoring ephemeral containers](/collectors/cgroups.plugin/README.md#monitoring-ephemeral-containers), also affects the deletion of files for obsolete dimensions | +| delete orphan hosts files | `yes` | Set to `no` to disable non-responsive host removal. | +| enable zero metrics | `no` | Set to `yes` to show charts when all their metrics are zero. | + +:::info + +The multiplication of all the **enabled** tiers `dbengine tier N update every iterations` values must be less than `65535`. + +::: + ### [directories] section options diff --git a/database/README.md b/database/README.md index 4873fefd80..119e21336b 100644 --- a/database/README.md +++ b/database/README.md @@ -7,199 +7,138 @@ custom_edit_url: https://github.com/netdata/netdata/edit/master/database/README. # 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: +(`dbengine`). But to remain as flexible as possible, Netdata supports several storage options: 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). + 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). +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). +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). +4. `map`, data are in memory mapped files. This works like the swap. 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. This mode uses `mmap()` but does not support [KSM](#ksm). _Keep in mind though, this option will have a + constant write on your disk._ -5. `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`. -6. `alloc`, like `ram` but it uses `calloc()` and does not support [KSM](#ksm). This mode is the fallback for all - others except `none`. +6. `none`, without a database (collected metrics can only be streamed to another Netdata). -You can select the database mode by editing `netdata.conf` and setting: - -```conf -[db] - # dbengine (default), ram, save (the default if dbengine not available), map (swap like), none, alloc - mode = dbengine -``` - -## Running Netdata in embedded devices - -Embedded devices usually have very limited RAM resources available. - -There are 2 settings for you to tweak: - -1. `[db].update every`, which controls the data collection frequency -2. `[db].retention`, which controls the size of the database in memory (except for `[db].mode = dbengine`) - -By default `[db].update every = 1` and `[db].retention = 3600`. This gives you an hour of data with per second updates. - -If you set `[db].update every = 2` and `[db].retention = 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 `[db].update every = 5` and `[db].retention = 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 parent Netdata server - -Netdata allows streaming data between Netdata nodes in real-time. This allows having one or more parent Netdata servers that will maintain -the entire database for all the nodes that connect to them (their children), and will also run health checks/alarms for all these nodes. - -### map +## Which database mode to use -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. +The default mode `[db].mode = dbengine` has been designed to scale for longer retentions and is the only mode suitable +for parent Agents in the _Parent - Child_ setups -**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 parent Netdata server that would normally need huge amounts of memory. +The other available database modes are designed to minimize resource utilization and should only be considered on +[Parent - Child](/docs/metrics-storage-management/how-streaming-works) setups at the children side and only when the +resource constraints are very strict. -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. +So, -For each chart, Netdata maps the following files: +- On a single node setup, use `[db].mode = dbengine`. +- On a [Parent - Child](/docs/metrics-storage-management/how-streaming-works) setup, use `[db].mode = dbengine` on the + parent to increase retention, a more resource efficient mode like, `dbengine` with light retention settings, and + `save`, `ram` or `none` modes for the children to minimize resource utilization. -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. +## Choose your database mode -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. +You can select the database mode by editing `netdata.conf` and setting: -There are 2 more options to tweak: +```conf +[db] + # dbengine (default), ram, save (the default if dbengine not available), map (swap like), none, alloc + mode = dbengine +``` -1. `dirty_background_ratio`, by default `10`. -2. `dirty_ratio`, by default `20`. +## Netdata Longer Metrics Retention -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. +Metrics retention is controlled only by the disk space allocated to storing metrics. But it also affects the memory and +CPU required by the agent to query longer timeframes. -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. +Since Netdata Agents usually run on the edge, on production systems, Netdata Agent **parents** should be considered. +When having a [**parent - child**](/docs/metrics-storage-management/how-streaming-works.md) setup, the child (the +Netdata Agent running on a production system) delegates all of its functions, including longer metrics retention and +querying, to the parent node that can dedicate more resources to this task. A single Netdata Agent parent can centralize +multiple children Netdata Agents (dozens, hundreds, or even thousands depending on its available resources). -![image](https://cloud.githubusercontent.com/assets/2662304/23835030/ba4bf506-0768-11e7-9bc6-3b23e080c69f.png) +## Running Netdata on embedded devices -To have these settings automatically applied on boot, create the file `/etc/sysctl.d/netdata-memory.conf` with these -contents: +Embedded devices typically have very limited RAM resources available. -```conf -vm.dirty_expire_centisecs = 60000 -vm.dirty_background_ratio = 80 -vm.dirty_ratio = 90 -vm.dirty_writeback_centisecs = 0 -``` +There are two settings for you to configure: -There is another mode to help overcome the memory size problem. What is **most interesting for this setup** is -`[db].mode = dbengine`. +1. `[db].update every`, which controls the data collection frequency +2. `[db].retention`, which controls the size of the database in memory (except for `[db].mode = dbengine`) -### dbengine +By default `[db].update every = 1` and `[db].retention = 3600`. This gives you an hour of data with per second updates. -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. +If you set `[db].update every = 2` and `[db].retention = 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 to find the right setting. +On very weak devices you might have to use `[db].update every = 5` and `[db].retention = 720` (still 1 hour of data, but +1/5 of the CPU and RAM resources). -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 mode `dbengine` we can overcome most memory restrictions. For more -details see [here](/database/engine/README.md). +You can also disable [data collection plugins](/collectors/README.md) that you don't need. Disabling such plugins will also +free both CPU and RAM resources. -## KSM +## Memory optimizations -Netdata offers all its in-memory database to kernel for deduplication. +### KSM -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 performs memory deduplication by scanning through main memory for physical pages that have identical content, and +identifies the virtual pages that are mapped to those physical pages. It leaves one page unchanged, and re-maps each +duplicate page to point to the same physical page. Netdata offers all of its in-memory database to kernel for +deduplication. -KSM is a solution that will provide 60+% memory savings to Netdata. +In the past, KSM has been criticized for consuming a lot of CPU resources. This is true when KSM is used for +deduplicating certain applications, but it is not true for Netdata. Agent's 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: +To enable KSM in kernel, you need to run a kernel compiled with the following: ```sh CONFIG_KSM=y ``` -When KSM is enabled at the kernel is just available for the user to enable it. +When KSM is enabled at the kernel, it 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). +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 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. +- `/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. +they are willing to have used by `ksmd`. ### Run `ksmd` kernel daemon -To activate / run `ksmd` you need to run: +To activate / run `ksmd,` you need to run the following: ```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 +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 +### Monitoring Kernel Memory de-duplication performance Netdata will create charts for kernel memory de-duplication performance, like this: diff --git a/database/engine/README.md b/database/engine/README.md index e48bee59b4..c67e400f4c 100644 --- a/database/engine/README.md +++ b/database/engine/README.md @@ -6,74 +6,114 @@ custom_edit_url: https://github.com/netdata/netdata/edit/master/database/engine/ # Database engine -The Database Engine works like a traditional database. It dedicates a certain amount of RAM to data caching and -indexing, while the rest of the data resides compressed on disk. Unlike other [database modes](/database/README.md), the -amount of historical metrics stored is based on the amount of disk space you allocate and the effective compression +The Database Engine works like a traditional time series database. Unlike other [database modes](/database/README.md), +the amount of historical metrics stored is based on the amount of disk space you allocate and the effective compression ratio, not a fixed number of metrics collected. -By using both RAM and disk space, the database engine allows for long-term storage of per-second metrics inside of the -Agent itself. +## Tiering -In addition, the dbengine is the only mode that supports changing the data collection update frequency -(`update every`) without losing the metrics your Agent already gathered and stored. +Tiering is a mechanism of providing multiple tiers of data with +different [granularity on metrics](/docs/store/distributed-data-architecture.md#granularity-of-metrics). -## Configuration +For Netdata Agents with version `netdata-1.35.0.138.nightly` and greater, `dbengine` supports Tiering, allowing almost +unlimited retention of data. -To use the database engine, open `netdata.conf` and set `[db].mode` to `dbengine`. -```conf +### Metric size + +Every Tier down samples the exact lower tier (lower tiers have greater resolution). You can have up to 5 +Tiers **[0. . 4]** of data (including the Tier 0, which has the highest resolution) + +Tier 0 is the default that was always available in `dbengine` mode. Tier 1 is the first level of aggregation, Tier 2 is +the second, and so on. + +Metrics on all tiers except of the _Tier 0_ also store the following five additional values for every point for accurate +representation: + +1. The `sum` of the points aggregated +2. The `min` of the points aggregated +3. The `max` of the points aggregated +4. The `count` of the points aggregated (could be constant, but it may not be due to gaps in data collection) +5. The `anomaly_count` of the points aggregated (how many of the aggregated points found anomalous) + +Among `min`, `max` and `sum`, the correct value is chosen based on the user query. `average` is calculated on the fly at +query time. + +### Tiering in a nutshell + +The `dbengine` is capable of retaining metrics for years. To further understand the `dbengine` tiering mechanism let's +explore the following configuration. + +``` [db] mode = dbengine + + # per second data collection + update every = 1 + + # enables Tier 1 and Tier 2, Tier 0 is always enabled in dbengine mode + storage tiers = 3 + + # Tier 0, per second data for a week + dbengine multihost disk space MB = 1100 + + # Tier 1, per minute data for a month + dbengine tier 1 multihost disk space MB = 330 + + # Tier 2, per hour data for a year + dbengine tier 2 multihost disk space MB = 67 ``` -To configure the database engine, look for the `dbengine page cache size MB` and `dbengine multihost disk space MB` settings in the -`[db]` section of your `netdata.conf`. The Agent ignores the `[db].retention` setting when using the dbengine. +For 2000 metrics, collected every second and retained for a week, Tier 0 needs: 1 byte x 2000 metrics x 3600 secs per +hour x 24 hours per day x 7 days per week = 1100MB. -```conf -[db] - dbengine page cache size MB = 32 - dbengine multihost disk space MB = 256 -``` +By setting `dbengine multihost disk space MB` to `1100`, this node will start maintaining about a week of data. But pay +attention to the number of metrics. If you have more than 2000 metrics on a node, or you need more that a week of high +resolution metrics, you may need to adjust this setting accordingly. + +Tier 1 is by default sampling the data every **60 points of Tier 0**. In our case, Tier 0 is per second, if we want to +transform this information in terms of time then the Tier 1 "resolution" is per minute. + +Tier 1 needs four times more storage per point compared to Tier 0. So, for 2000 metrics, with per minute resolution, +retained for a month, Tier 1 needs: 4 bytes x 2000 metrics x 60 minutes per hour x 24 hours per day x 30 days per month += 330MB. + +Tier 2 is by default sampling data every 3600 points of Tier 0 (60 of Tier 1, which is the previous exact Tier). Again +in term of "time" (Tier 0 is per second), then Tier 2 is per hour. + +The storage requirements are the same to Tier 1. -The above values are the default values for Page Cache size and DB engine disk space quota. +For 2000 metrics, with per hour resolution, retained for a year, Tier 2 needs: 4 bytes x 2000 metrics x 24 hours per day +x 365 days per year = 67MB. -The `dbengine page cache size MB` option determines the amount of RAM dedicated to caching Netdata metric v |