The object storage is a collection of RBD images containing a sequence of objects (SWHID + content). To allow for fast random reads, a rocksdb index is updated when an object is added, using the signature from SWHID as a key, the identifier of the image that contains it and the offset at which it is to be found.

Benchmark based on these assumptions:

• RBD images are ~1TB big
• The content of the image is as described in T3048

The expected result would be:

• A 1TB RBD image can be populated at a rate > 100MB/s by a single writer that:
  • Appends to the RBD image
  • Updates a global index containging 5 billions entries
• Sequential read of the 1TB RBD image is at least > 100MB/s
• Random reads of the 1TB RBD image is at least > 100MB/s
• The RBD space overhead is less than 20% (see T3014#57836), i.e. storing 100 bytes does not require more than 120 bytes

The methodology would be similar to what David did for S3 T2706, i.e.:

• Write a script to
  • Pre-populate a global index with 5 billion entries
  • Setup a Ceph cluster with 20TB of storage and 4+2 RBD pool
• Create a workload to populate
  • 10 1TB images
• Interpret results