I reread this article from time to time just to make sure that I stay within
some boundaries – 21 Experts Define Cloud Computing. Among the 21, there
are a couple that I really like; I’m going to cite a few of them over the
next few days, and tell you what I like and don’t like about them (Also –
remember, the title reads “21 Experts…” – it didn’t say “21
Experts in Cloud Computing…” – details matter). This article was
brought to my attention in a blog post, “Rumblings in the Cloud,” by
Louis Lovas at Progress Apama.
Dynamic Cloud Resources – While You Wait (or “I’ll have an EC2 grid,
monster that, please”)
“What is cloud computing all about? Amazon has coined the word
“elasticity” which gives a good idea about the key features: you can
scale your infrastructure on demand within minutes or even seconds, instead
of days or weeks, thereby avoiding under-utilizatio... (more)
Cloud Event Processing has moved off the white board and into the real world
of, ‘hey, we’ve got customers!’
When building a system like DarkStar, one can always run into difficulties
– how does one demo a cloud based, distributed event processing system
incorporating streaming map/reduce, complex event processing, and event
driven pattern matching agents to prospective customers? Our background
includes very high velocity feeds, like equities and option market data
feeds, but using those for demo purposes can be difficult. So we decided on
using Twitter. We decided ... (more)
Every year, I like to decompress a bit and take a break. Usually, I like to
go scuba diving – the dive sites I like are usually far removed from email,
Twitter, Facebook, etc. and it gives me a chance to actually unplug, defrag,
and think a bit.
This year, the family went to Grand Cayman to experience some of the
world’s best diving. Within Grand Cayman is Hell, a small township
dedicated to tourism and aptly named given the attached photo.
We visited Hell in between dives, and rather than make my ex-wife room
reservations or send out postcards, I thought I’d amplify a few predic... (more)
On this continuing series, I am examining thoughts and specific
implementation details around building a back-testing platform for algo
trading. Eventually, we’ll see where complex event processing plays and
how to implement it.
Appendix to Part One – The Data Format
Rather than looking at various database solutions first and then trying to
define the problem in terms of those solutions, let’s first examine what
market data looks like. In its most simple form, market data looks like
this (there’s usually a little more, but this is fine for our purposes):
Date: The date of the ... (more)
VMWare has been on a buying spree lately.
In the last month, they’ve announced both Redis and RabbitMQ.
Here’s VMware’s take on Redis, and spring source’s on RabbitMQ.
RabbitMQ is built with Erlang.
Much Rejoicing in the Village
We use both of these technologies at Cloud Event Processing. And we love
Erlang too. VMware’s acquisition of these technologies not only validates
our decisions, which we are very selfishly pleased about, but also sends an
The Message Please
Everyone’s busy abstracting resources in the cloud – making resources
like compute, stora... (more)