Thursday, November 26, 2020

PDQ 7.0 is Not a Turkey

Giving Thanks for the release of PDQ 7.0, after a 5-year drought, and just in time for the PDQW workshop next week.

New Featues

  1. The introduction of the STREAMING solution method for OPEN queueing networks. (cf. CANON, which can still be used).
  2. The CreateMultiNode() function is now defined for CLOSED queueing networks and distinguished via the MSC device type (cf. MSO for OPEN networks).
  3. The format of Report() has been modified to make the various types of queueing network parameters clearer.
  4. See the R Help pages in RStudio for details.
  5. Run the demo(package="pdq") command in the R console to review a variety of PDQ 7 models.

Maintenance Changes

The migration of Python from 2 to 3 has introduced maintenance complications for PDQ. Python 3 may eventually be accommodated in future PDQ releases. Perl maintenance has ended with PDQ release 6.2, which to remain compatible with the Perl::PDQ book (2011).

Sunday, November 8, 2020

PDQ Online Workshop, Nov 30-Dec 5, 2020

PDQ (Pretty Damn Quick) is a queueing graph performance analyzer that comes as:
  1. free open source software package
  2. with an online user manual

As shown in the above diagram, any modern computer system can be thought of as a directed graph of individual buffers where requests wait to be serviced at some kind of shared computational resource, e.g., a CPU or disk. Since a buffer is just a queue, any computer infrastructure, from a laptop to Facebook, can be represented as a directed graph of queues. The directed arcs or arrows correspond to workflows between the different queues. In the parlance of queueing theory, a directed graph of queues is called a queueing network model. PDQ is a tool for calculating the performance metrics, e.g., waiting time, throughput, optimal load, of such network models.

Some example PQD applications include models of:

  • Cloud applications
  • Packet networks
  • HTTP + VM + DB apps
  • PAXOS-type distributed apps

Two major benefits of using PDQ are:
  1. confirmation that monitored performance metrics have their expected values
  2. predict performance for circumstances that lie beyond current load-testing
This particular PDQ workshop has been requested for the Central European Time zone.
  • All sessions are INTERACTIVE using Skype (not canned videos)
  • Online sessions are usually 4 hours in duration
  • A typical timespan is 2pm to 6pm CET each business day
  • A nominal 5-10 minute bio break at 4pm CET
  • Attendees are encouraged to bring there own PDQ projects or data to start one
  1. Find out more about the workshop.
  2. Here is the REGISTRATION page.
Hope to see you at PDQW!