@@ -219,40 +219,6 @@ supporting even more than 64 bit) could be implemented, but it is not
a priority right now. A counter, even if incremented one million times per
second, will only run into precision issues after over 285 years.
### Why does Prometheus use a custom storage backend rather than [some other storage method]? Isn't the "one file per time series" approach killing performance?
NOTE: **NOTE:** This FAQ entry is about Prometheus 1.x. Prometheus 2.0 uses a different (but also custom-built) storage engine, for much of the same reasons. The performance numbers and characteristics differ.
Initially, Prometheus ran completely on LevelDB, but to achieve better
performance, we had to change the storage for bulk sample data. We evaluated
many storage backends that were available at the time, without getting
satisfactory results. So we implemented exactly the parts we needed, while
keeping LevelDB for indexes and making heavy use of file system
capabilities. Obviously, we could not evaluate every single storage backend out
there, and storage backends have evolved meanwhile. However, the performance of
the solution implemented now is satisfactory for most use-cases. Our most
important requirements are an acceptable query speed for common queries and a
sustainable ingestion rate of hundreds of thousands of samples per second. The
latter depends on many parameters, like the compressibility of the sample data,
the number of time series the samples belong to, the retention policy, and even
more subtle aspects like how full your SSD is. If you want to know all the
details, read
[this document with detailed benchmark results](https://docs.google.com/document/d/1lRKBaz9oXI5nwFZfvSbPhpwzUbUr3-9qryQGG1C6ULk/edit?usp=sharing). The highlights:
* On a typical bare-metal server with 64GiB RAM, 32 CPU cores, and SSD,
Prometheus sustained an ingestion rate of 900k samples per second, belonging
to 1M time series, scraped from 720 targets.
* On a server with HDD and 128GiB RAM, Prometheus sustained an ingestion rate
of 250k samples per second, belonging to 1M time series, scraped from 720
targets.
Running out of inodes is unlikely in a usual set-up. However, if you have a lot
of short-lived time series, or you have configured your file system with an
unusual low amount of inodes, you might run into inode depletion. Also, if you
want to delete Prometheus's storage directory, you will notice that some file
systems are very slow when deleting a large number of files.
### Why don't the Prometheus server components support TLS or authentication? Can I add those?
While TLS and authentication are frequently requested features, we have
