A class is a story: Fitting content to sessions

Any given class is a story. It has a beginning, middle, and end. It arcs toward a conclusion. The story can be deliberate and designed or it can be inadvertent and confused. Ultimately, the story will be different for everyone in the room. The best that I can do as instructor is the best any performer can do: Create an environment in which the audience can participate, hoping that their outcomes approximate those I had in mind. But what do I do with a prior “story” when the class I designed for an hour and a half session last year is scheduled this year for a sesssion of one hour?

Roles vs. Silos, Contribution vs. Technology

With the developing maturity of chaos engineering techniques, I see people taking the job title, “Chaos Engineer”. Although I think chaos engineering is a truly useful field based upon important principles, I am wary of defining one’s job in those terms. It confuses technology with contribution, creates a silo where we want a role. I prefer a title like Site/Service Reliability/Resilience Engineer, which emphasizes the bearer’s contribution to the organization. An SRE may very well have training in chaos engineering and spend much of their time using those methods but their role is to improve system reliability.

What genres of readings should be assigned to Prof. MSc. students?

What sort of materials should students read in a professional MSc. course in computing science? Journal articles? Research conference papers? Systems-oriented conference papers? Articles from practitioner-oriented magazines? Blog posts? Wikipedia entries? Ultimately, what is the purpose of the readings?

The service design space (2020 Edition)

Post in an ongoing series on the issues constraining service design for datacentres. A previous post presented 2019’s version, a design space for data engineering.

Starting January 2020, I will teach a course on service design for datacentres. The roster indicates that nearly all students will be in a professional master’s program. Most will be in their second semester of a program in Big Data, some will be in their fifth semester (including a two-semester paid internship), with a few in other programs. What are the key principles that should structure such a course?

"Awareness" outcomes as preparation for internships

Note: Outside activities interrupted my posting here. Where did those five months go? I did generate a lot of potential posts on distributed systems, which I’ll discuss in coming posts. This post focusses instead on course design, addressing an issue of immediate interest to me.

I recently discussed course design with some colleagues developing a required course for a professional masters program. They wanted the course to address a common concern for such programs: How to increase the core CS technical skills of students in a program focused on a specialization outside that core. Of particular concern were students who do not have undergraduate CS degrees. Although such students bring valuable experience from other domains, it is at the cost of lacking the skills developed by long-term, broad study of CS. Even students who do have such background can benefit from revisiting these topics. How can we cover so much material in the limited time of a single course?