Wednesday, Nov 29, 2023 – On-call doesn’t need to suck; ways to help make your on-call better

KWSQA is offering this KWality Talk as in person only!

Register: Online at our KWality Talk Page,

Speaker: Ken De Souza


Being on-call can be really hard at times. Incidents happen and when they do, it can cause alert fatigue, long hours, lots of stress and not getting your day job done. In this talk, Ken will discuss his experience working for a company that grew rapidly over several years and where on-call needed to evolve to make it more humane.

As part of this talk, Ken will discuss strategies such as:
– Being an advocate for better quality software, so that it prevents outages and unnecessary alarms
– Dealing with the emotional component of the firefighting related stress when incidents happen
– How to help change your organization so that it makes on-call part of the culture.

Attendees will take away:
– Way of making your on-call rotation more humane
– Identifying ways of evolving how your on-call rotation can work effectively in order to prevent incidents from happening
– Ideas around making your alerting and monitoring better to prevent burnout and to increase your visibility.


Ken De Souza has been in software development for over 20 years. He is a software developer, currently specializing in building tools and culture related to helping developers securely deploy and monitor the code they create, with a passion for delivering high quality software at a rapid pace.

He has spoken at software development conferences over the last 10 years. He currently resides in Waterloo, Ontario, Canada.

KWality Talk Details


Event starts at approximately 11:55 am. Announcements and discussion start at approximately 12:00 pm. Meeting ends at approximately 1:00 pm.


151 Charles St W Suite 100, Kitchener, ON N2G 1H6

We are happy to announce that we will be holding our first in-person Kwality Talk since 2020 at Communitech! Communitech is located in the Tannery Building at 151 Charles St W. Once you arrive please enter the main lobby of the building and look out for KWSQA board members who will be waiting to direct you in green KWSQA branded shirts.

Parking: Communitech has asked that attendees park in the City of Kitchener parking lots. The closest one to Communitech is on Water Street. (Parking not included in ticket price.)

Code of Conduct

People attending our meetings are expected to adhere to the KWSQA code of conduct.

Continue ReadingWednesday, Nov 29, 2023 – On-call doesn’t need to suck; ways to help make your on-call better

Wednesday, Oct 25, 2023 – Building Fair, Accountable and Trustworthy Machine Learning Systems

For the time being, the KWSQA is continuing to offer KWality Talks online for free via Zoom.

Register: Online at our KWality Talk Page, Zoom link will be included in registration confirmation email.

Location: Online

Time: The meeting starts between 11:55 am and 12:00 pm, a waiting room might be enabled if you arrive prior to this time. Meeting ends at approximately 1:00 pm.

Speaker: Rashmi Nagpal


Have you ever wondered why 87% of machine learning models never make it to production? Who must be held responsible if a machine learning algorithm discriminates or shows bias? Are the decisions taken by these models trustworthy? In this talk, let’s unravel the answers to such complex questions!

Machine learning has had a significant impact in many areas, including medicine, entertainment, security, and education, but its use can also result in increased cognitive dependence on technology and ethical concerns such as bias. Therefore, it is crucial to address these issues by reducing the impact of human biases and creating trustworthy, reliable, and understandable machine learning systems.

The key takeaways of my talk would likely include the importance of understanding and interpreting the decision-making processes of machine learning models, as well as the need to ensure that these models are fair, accountable, and trustworthy in their predictions and actions. Additionally, the talk may highlight the challenges of building interpretable models and the importance of evaluating and testing models for bias, as well as the need for transparency and accountability in the development and deployment of machine learning systems.


Rashmi is a Software Engineer with a passion for building products in AI/ML. In her almost 4 years career in tech, she’s brought products to life at pre-seed startups, scaled teams and software at hypergrowth unicorns, and shipped redesigns and features used by millions at established giants. When she’s not coding, capturing cosmos using her telescope, or playing board games with friends, you can find Rashmi playing with her maltese breed pet dog, Fluffy!

Continue ReadingWednesday, Oct 25, 2023 – Building Fair, Accountable and Trustworthy Machine Learning Systems