The Backend Engineering Show with Hussein Nasser

In this video I explain the difference between Agile & Water, the pros & cons and more. Chapters 0:00 Intro 1:00 Waterfall 5:00 Agile

In this video I explain how WebSockets work in the new HTTP/2 protocol. This is explained in the  Bootstrapping WebSockets with HTTP/2 in RFC8441 https://tools.ietf.org/html/rfc8441 https://link.medium.com/v5sB9nbUp6  1:00 HTTP2 5:50 HTTP/2 limitations

Metroexpress lane is implementing a Machine Learning Occupancy Detection System which I found interesting. In this video I discuss machine learning, supervised learning, labeling and much more.

In this video I explain the multi-tenancy architecture. The basic idea is to have a single instance of your application to serve multiple tenants or customers and the properties are this. This is as opposed to isolated or dedicated infrastructure. Shared Instance One database hosting multiple customers Isolation at the application level Can be multi-processes and multi-instances as long as they are pooled Stateless Tags Multitenancy, software Multitenancy, Multitenancy explained, Multitenancy architecture https://www.zdnet.com/article/defining-the-true-meaning-of-cloud/

Algorithms & Data Structures are critical to Backend Engineering however it really depends on what kind of application and infrastructure you are building. In this video I want to go through the following   1 Backend Engineers are two types - Integrating Existing Backend  - Core Backend  Example Building a CRUD API? Online Cinema system, URL shortener, You will pick up a database and write your logic Building a social network?  * are you gonna be integrator use a ready made graph database?  * Are you gonna use a off the shelf database and write your logic in the application? * Are you gonna build your own graph database platform?  * Any of these scenarios you will run into problems slow performance and you need to understand why  Building a monitoring system? are you gonna integrate an existing database ? or build your own?     2. Be Pragmatic  (Algorithms are not always the solution)   * Most performance issues are not algorithm problems, they are just bad bugs. and misuse .. paging  We are a sorted 100 items takes 1 minute to sort and return.. merge sort or heap or quick sort won’t help you   3. Always keep learning to be open to learn new Algorithms

In this video I want to talk about my preferred method of learning backend engineering technologies, I prefer podcasts and youtube videos some people prefer books. My First Programming Book My Problem with Learning in Books My Preferred Method of learning (Podcasts) YouTube Videos Problem is Biased .. Details in WIkipedia then Recommended Podcasts https://softwareengineeringdaily.com/ https://www.dataengineeringpodcast.com/ https://changelog.com/podcast Recommended YouTube Channels https://www.youtube.com/user/TechGuyWeb https://www.youtube.com/user/99baddawg https://www.youtube.com/channel/UCRPMAqdtSgd0Ipeef7iFsKw https://www.youtube.com/channel/UCn1XnDWhsLS5URXTi5wtFTA

Message Queues system like RabbitMQ and Kafka are amazing technologies but when should you actually use a message queue? I discuss this in this video.

In this video I talk about RabbitMQ Channels compared to HTTP/2 Streams and how QUIC helps mitigate some of the major limitations in Channels and Streams. Chapters 0:00 Intro 0:10 RabbitMQ Channels 3:10 HTTP/2 Streams 6:00 How QUIC Helps

In this video I discuss why QUIC will make a great communication protocol for databases and how it solves a critical problem with stateless web applications. Web applications uses database connection pooling to establish database connections on the backend. But that creates other sorts of problems. Timecodes 0:00 Intro 0:20 Database Communication Protocols 2:00 Problem with Sharing Database Connections 6:50 How QUIC streams can help Databases

Database Application level sharding is the process of splitting a table into multiple database instances in order to distribute the load. However, Sharding a database is an expensive operation (maintainability and overhead) and I suggest you do that only when you absolutely need to. That means when your single instance database can no longer serve queries with minimum latency. So I suggest you monitor that and only shard if necessary.. I rather do replication make master / backup and make requests read from replica than Sharding just because it is easier.. good question... nice idea for a video 5:00 Partition horizontally 7:45 Replication (Master/backup) Scale reads 11:00 Scale writes by region 12:30 Sharding 16:40 Sharding in YouTube