Codeblocks @backend_dev2

AI Engineering Podcast Episode #1: Beyond the AI hype youtu.be/-kQRBkBuwHg Speakers: Gaurav Sen and Tanishq Singh Let us know your thoughts in the comments!

@devjlopez @arcnotes What were the system resources given ?

Awesome log parsing cheat sheet. Log parsing commands are useful for: 🔹Searching patterns in text files 🔹Analyzing network packets 🔹Parsing fields from delimited logs 🔹Replacing strings in a file 🔹Sorting a file 🔹Displaying differences in files by comparing line by line Source: Thomas Roccia Over to you: have you used any command in this list? — Get a Free System Design PDF (158 pages) by subscribing to our weekly newsletter today: bit.ly/42Ex9oZ #systemdesign #coding #interviewtips .

A nice cheat sheet of different cloud services. -- Subscribe to our weekly newsletter to get a Free System Design PDF (158 pages): bit.ly/42Ex9oZ

🎁 Giving Away 100 System Design + ML System Design Books + Newsletter Deep Dive Content 🎁 To celebrate our upcoming 1-year YouTube channel anniversary, we will be giving away: 🔹 10 signed physical books (vol. 1 + vol. 2 + ML system design; winners get all 3) 🔹 90 1-year subscriptions to the ByteByteGo online course. The course includes content for two system design books (vol. 1 and 2), vol. 3 (coming out in 2023), and an ML system design book. 🔹 10 1-year subscriptions to the ByteByteGo paid newsletter content. 🔹 Shipping is on us. If you live outside the US, you will receive a 1-year subscription to our online course. 𝐇𝐨𝐰 𝐭𝐨 𝐩𝐚𝐫𝐭𝐢𝐜𝐢𝐩𝐚𝐭𝐞: ✅ Follow me on Twitter ✅ Like & Retweet ✅ Subscribe to our free weekly newsletter: bit.ly/42Ex9oZ If you have already signed up, please enter your email again to be eligible. ⏰ The giveaway ends in 72 hours. #systemdesign #coding #giveaway .

How to learn better and faster as a software engineer? ⚡ I follow these 5 things to ensure I am learning continuously and evolving to be a better software engineer every single day. youtu.be/Je5WBk91Wlc

White papers for software engineers (Version II): 1. Google File System 2. Map Reduce 3. BigTable 4. Megastore 5. Monarch 6. Chubby 7. Spanner 8. Dapper 9. Borg 10. Zanzibar 11. Pregel 12. Amazon Aurora 13. Dynamo DB 14. Scalability at what COST 15. Foundation DB 16. Monolith: Tiktok Recommendation System 17. MilliSampler 18. Scaling Memcache at Facebook 19. Gorilla DB 20. FlexiRaft 21. Cassandra 22. TAO 23. MineSweeper - Root Cause Analysis 24. Prophet - Forecasting at Scale 25. ShardManager 26. Hadoop FileSystem 27. Kafka 28. Flink Bookmark this link for updates: interviewready.io/blog/white-pap…

Spend the first 3 years of your career ensuring these to accelerate your growth ⚡️ - become proficient in at least one stack - understand infrastructure and architecture - understand how your work fits into the big scheme - show extreme ownership and lead - help others succeed

If you want to master something, teach it.

/4 I hope you've found this thread helpful. Follow me @alexxubyte for more. Like/Retweet the first tweet below if you can:

Alex Xu @alexxubyte

3 years ago

/1 10 Key Data Structures We Use Every Day 🔹 list: keep your Twitter feeds 🔹 stack: support undo/redo of the word editor 🔹 queue: keep printer jobs, or send user actions in-game 🔹 hash table: cashing systems 🔹 Array: math operations 🔹 heap: task scheduling

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Simple Systems Scale. Simple systems are efficient, performant, and easy to understand, maintain, and scale. Hence, while designing any system, ensure that the architecture and implementation are kept really simple. Complex systems falter under stress. youtube.com/c/ArpitBhayani

@largedatabank @phil_eaton @borjasotomayor @justinjaffray These are great! Some more top of my head: - Database Internals by @ifesdjeen - Let's Build a Simple Database - cstack.github.io/db_tutorial/ This is classic. Though incomplete, still a great resource - Architecture of a Database System by Stonebraker - dsf.berkeley.edu/papers/fntdb07… (1/2)

Another interesting question on TLS certification with a layer 4 proxies.

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/1 18 Key Design Patterns Every Developer Should Know

Recently @RazorpayEngg conducted an internal ChatGPT hackathon to encourage creative ideas around ChatGPT and AI. I'm super glad to share that my project – mocktopus was one of the winning projects in the hackathon 🎉🚀 #hackathon #opensource

11 key concepts of machine learning:

10 topics I would focus on if I were to start my Machine Learning career again: 1. Python 2. Data Structures & Algorithms 3. Probabilities & Statistics 4. Learning Algebra 5. Calculus 6. ML algorithms 7. SQL 8. Testing 9. Version control 10. LLM / Langchain Here is a roadmap:

"How Cloud Computing is transforming from raw infra to app-centric services" Longer blog post 👉diagrid.io/blog/evolution… TLDR of timelines, app, infra, API changes 👇🧵(0..4)

To get feedback, you don’t have to wait for your company’s official perf cycle. You can run your own perf cycle. This technique works for any situation, but it is especially relevant when you are new to a team: - After you’ve spent a couple of months on a new team, run your own lightweight perf cycle. - Ask a few key peers if they’d be willing to provide some written feedback – it can even be anonymous – and send them this simple form to fill out. This form is especially designed to be lightweight, while still capturing the key things that would be captured in the official performance review process, whenever that is going to happen. There are many reasons for doing this of course, but the main reason is that it helps you avoid surprises in the real performance review. You see, you would rather find out if a colleague has some tough feedback (or even if they would like you to see you make minor tweaks) early-ish in the relationship than to find that out in your official performance review. Btw, this technique also works quite well with a colleague with whom you’ve especially had a hard time working. You see, by getting that colleague’s feedback in this manner, adjusting your approach based on it, and then having a conversation with that colleague afterwards about how things are going, you are significantly reducing the chances that this colleague will write you a negative review in your official perf cycle. In most cases I’ve seen that, by giving them the catharsis of sharing their feedback here, they tend to be much gentler and usually very positive during the official perf cycle because they have seen you respond well to their feedback.

@cloud_opinion Haha