As a value-added reseller, your business model relies on providing your customers and clients with a product that works anytime they need it. If you are using a virtual desktop infrastructure (VDI) to deliver this product to your customers, you already know that this kind of platform has been all-too problematic in the past.
Much of the technology world descended on Paris recently as the OpenStack Summit held its semi-annual get-together for a meeting of the minds. It was my good fortune to attend with colleagues from Violin Systems. We even managed to see a few local sights while we were there!
Modern hosting and service providers often face the challenge of managing the cost efficiencies of their platform. A common solution is to deploy a multi-tenant or multi-instance architecture in which many customers share the same hardware. The reuse of hardware over many clients drives down costs and also reduces the required ongoing administration.
Multi-tenant deployments host many clients in the same instance of software while segregating the client data through configuration. Multi-instance designs are similar but run one instance of software per client. To the storage tier, both approaches require many sub-ecosystems to run simultaneously in a shared space and will cause similar access challenges:
- Unpredictability of usage
- Height of individual usage spikes
- Scale versus storage performance (more clients translates into a more random and parallel workload)
SSD’s are like cordless phones and DVD’s. They made an improvement on an existing technology but didn’t revolutionize its use. In technology there is a difference between the concept of modernizing and revolutionizing. Modernizing is finding a way to do the same thing, just a little bit faster or little bit easier. Revolutionizing is either eliminating or vastly changing how something is done.
Flash is about latency and IOPs so why would it be good for Data Warehousing or Business Intelligence?
Excellent question. Yes, the typical marketing and wow-factor stats around flash are based on latencies and IOPs (Input Output Per Second). Data warehousing (DW) and Business Intelligence (BI) is normally a throughput game, so what gives?
Transactional workloads are commonly defined as being small atomic pieces of work. This is in contrast to decision support, Data Warehouse, Business Intelligence or otherwise labeled reporting systems that require fewer, larger, more sequential workloads. Updates, inserts, deletes and even small result-set selects are all included in OLTP, transactional efforts.