Now that you have a micro service, you need to rethink how to handle errors, how do you? Would you do a retry? What if the retry fails, what if the service is too slow and so many clients are now doing retries, the load would increase, how do you handle it then?

We live in a micro services environment and even if not you have for sure some servers some databases and you want to be able to troubleshoot quickly issues, do you really want to scan these long logs and try to find the best way for you to find root cause at night? or do you want to be ready as a professional knowing quickly you already have all the tools for you to troubleshoot.

In this episode I give you one of my biggest tips for implementing and designing distributed systems, should you or not go about retries? what are their disadvantages? what about caches how do they hurt you? what should you avoid when calling databases and other services?

Bayesian statistics is a theory in the field of statistics based on the Bayesian interpretation of probability where probability expresses a degree of belief in an event. The degree of belief may be based on prior knowledge about the event, such as the results of previous experiments, or on personal beliefs about the event. This differs from a number of other interpretations of probability, such as the frequentist interpretation that views probability as the limit of the relative frequency of an event after many trials.

Queues in System Design Architecture.  Queues are about everywhere they are not only a data structure that you study out of the blue in computer science, but they also help distribute your system.  But once you distribute your system with queues you face new issues, namely the queue being out of capacity, what do you do in these cases?

Data Science At the Command Line grep sed awk

Couchbase part 2

Couchbase part 1