A very good summary of all fundamentals. As someone who is gearing up for System Design interviews in the near future - this is a very good reference material 🙌
Also, I think in the Observability section it would be worthwhile to add the section on Alerting. What do you think?
Alert if things go wrong based on logs, performance metrics, business metrics (stuck state), failed SLOs, third-party failures, etc.
The line about unclear dashboards delaying detection speaks to my field. I have worked in data analytics for a decade. Dashboards are often made to be too complicated and do not empathize with the needs or level of data literacy of the end user. With that, their intended purpose, like making detections of next steps to take are often missed.
A very good summary of all fundamentals. As someone who is gearing up for System Design interviews in the near future - this is a very good reference material 🙌
Also, I think in the Observability section it would be worthwhile to add the section on Alerting. What do you think?
Alert if things go wrong based on logs, performance metrics, business metrics (stuck state), failed SLOs, third-party failures, etc.
Examples: OpsGenie, PagerDuty, incident.io
Thank you! Definitely, alerting is important. On-call as well. Could have expanded more that section!
Excellent write-up, crisp and clear!
Thank you, Arvind!
Brilliant article!
Thank you, Fusco!
Excellent writeup and something I’m going to bookmark and come back to over and over again!
Thank you so much, Gaurav!
This is one of the most practical and clearly structured breakdowns of system design I’ve seen written for engineering leaders. Thanks for sharing it!
Glad you enjoyed it! Thank you, William!
Thank you for the comprehensive writeup, Rafa.
So many things to think about, it feels overwhelming.
But I am definitely going to use this as a guide when starting new projects or hardening existing ones.
Indeed, and this is just an overview. Thank you, Matej.
The line about unclear dashboards delaying detection speaks to my field. I have worked in data analytics for a decade. Dashboards are often made to be too complicated and do not empathize with the needs or level of data literacy of the end user. With that, their intended purpose, like making detections of next steps to take are often missed.
Thank you for adding your thoughts, Colette!