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At some point the technical boundaries for increasing the performance of backup are reached. When talking about technical boundaries, we should differentiate between application-specific boundaries (Section 7.6.1) and those that are determined by server-centric IT architecture (Section 7.6.2).
7.6.1 Application-specific performance bottlenecks
Application-specific performance bottlenecks are all those bottlenecks that can be traced back to the 'network backup' application. These performance bottlenecks play no role for other applications.
The main candidate for application-specific performance bottlenecks is the metadata database. A great deal is demanded of this. Almost every action in the network backup system is associated with one or more operations in the metadata database. If, for example, several versions of a file are backed up, an entry is made in the metadata database for each version. The backup of a file system with several hundreds of thousands of files can thus be associated with a whole range of database operations.
A further candidate for application-specific performance bottlenecks is the storage hierarchy: when copying the data from hard disk to tape the media manager has to load the data from the hard disk into the main memory via the I/O bus and the internal buses, only to forward it from there to the tape drive via the internal buses and I/O bus. This means that the buses can get clogged up during the copying of the data from hard disk to tape. The same applies to tape reclamation.
7.6.2 Performance bottlenecks due to server-centric IT architecture
In addition to these two application-specific performance bottlenecks, some problems crop up in network backup that are typical of a server-centric IT architecture. Let us mention once again as a reminder the fact that in a server-centric IT architecture storage devices only exist in relation to servers; access to storage devices always takes place via the computer to which the storage devices are connected. The performance bottlenecks described in the following apply for all applications that are operated in a server-centric IT architecture.
Let us assume that a backup client wants to back data up to the backup server (Figure 7.3). The backup client loads the data to be backed up from the hard disk into the main memory of the application server via the SCSI bus, the PCI bus and the system bus, only to forward it from there to the network card via the system bus and the PCI bus. On the backup server the data must once again be passed through the buses twice. In backup, large quantities of data are generally backed up in one go. During backup, therefore, the buses of the participating computers can become a bottleneck, particularly if the application server also has to bear the I/O load of the application or the backup server is supposed to support several simultaneous backup operations.
The network card transfers the data to the backup server via TCP/IP and Ethernet. Previously the data exchange via TCP/IP was associated with a high CPU load. However, the CPU load caused by TCP/IP data traffic can be disregarded with the increasing use of TCP/IP offload engines (TOE) (Section 3.5.2 'TCP/IP and Ethernet as an I/O technology').
Figure 7.3 In network backup, all data to be backed up must be passed through both computers. Possible performance bottlenecks are: internal buses, CPU and the LAN
Use the following table of contents to navigate to chapter excerpts or click here to view Network Backup in its entirety.
Storage Networks Explained
1: Storage network backup: General conditions for backup
2: Storage network backup services
3: Storage network backup: Server components
4: Storage network back-up clients
5: Storage network back-up performance gains
6:Storage network backup performance bottlenecks
7: Storage network backup: Limited opportunities for increasing performance
8: Storage network backup: Next generation
9: Storage network backup of file servers
10: Storage network backup of databases
11:Storage network backup: Organizational aspects
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|Authors Ulf Troppens and Rainer Erkens are both employed at IBM TotalStorage Interoperability Center in Mainz, Germany a testing, development and demonstration laboratory for storage products and storage networks. Both authors work at the interface between technology and customers. Wolfgang Müller is currently working as a software architect in the Storage Software Development Department at IBM in Mainz, Germany, where the focus is on software development projects supporting open standards such as SMI-S/CIM/WBEM and IEEE 1244.|