|Figure 1: Management silos|
|Figure 2: OpenStack Quantum Intro|
The OpenStack compute scheduler documentation describes the factors that can be included in deciding which compute node to use when starting a virtual machine. Notable by their absence is any mention of storage or network location. In contrast, the Hadoop scheduler is both storage and network topology aware, allowing it to place compute tasks close to storage and replicate data within racks for increased performance and across racks for availability. A previous article, System boundary, discussed the importance of including all the tightly coupled network, storage, and compute resources within an integrated control system and NUMA discussed the importance of location awareness for optimal performance.
Note: OpenStack was selected as a representative example to demonstrate architectural features that are common to many cloud stacks. This article shouldn't be seen as a specific criticism of OpenStack, but as a general discussion of cloud architectures.
|Figure 3: OpenStack Quantum Intro|
|Figure 4: VMware NSX Network Virtualization|
Each orchestration layer kicks the problem of network resource management down to lower layers, until you are left selecting from a range of vendor specific fabrics which also hide the network topology and present the abstraction of a single switch.
|Figure 5: Juniper QFabric Architecture|
- The network is reliable
- Latency is zero
- Bandwidth is infinite
- The network is secure
- Topology doesn't change
- There is one administrator
- Transport cost is zero
- The network is homogeneous
It is easy to be complacent based on the the buzz around cloud computing, software defined networking and the software defined data center. However, if these architectures don't deliver on their promise, there is competition waiting in the wings - see Return of the Borg: How Twitter Rebuilt Google’s Secret Weapon. The difference is that these alternative architectures are being developed by flexible organizations that are prepared to consider all aspects of their stack in order to make disruptive improvements.
The unified visibility across all network, server, storage and application resources provided by the multi-vendor sFlow standard offers a solution. Piercing through the layers of abstraction and architectural silos delivers the comprehensive real-time analytics and location awareness for efficient scheduling.