Miguel 🏁

Father of 4 | Engineer | Artist

[Miguel 🏁 @guel_codes]

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[Jami @expertwith_AI]

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𝗣𝗮𝗶𝗱 𝗖𝗼𝘂𝗿𝘀𝗲 𝗙𝗥𝗘𝗘 (PART - 1)
1. Artificial Intelligence
2. Machine Learning
3. Prompt Engineering
4. Claude,Chatgpt,Grok
5. Data Analytics
6. AWS Certified
7. Data Science
8. BIG DATA
9. Python
10. Ethical Hacking

(72 Hours only )

Like + RT + comment ' Drive '

Must Follow me so I can DM you.

[Shruti @heyshrutimishra]

China deployed a 1,300-ton data center on the ocean floor off the coast of Hainan.

No cooling towers or air conditioning. Just cold seawater doing the job for free.

The result? Cooling costs drop from ~50% of total energy to under 10%.

[Science girl @sciencegirl]

Massive Attack turns a concert into a live facial recognition protest

[Karson Lacey @Karson_lacey1]

Great weekend, here are a few of highlights💯@ScoutFball @TDARecruiting @troy_report @UnLockYourGame_ @coachtufbpd @Alabama_Varsity @PrepRedzoneAL @CooperMorreale @GCoastAthletics @DaphneFBTrojans

[Science girl @sciencegirl]

MIT’s TRANSFORM project turns ordinary surfaces into shape shifting displays that respond to human touch in real time.

[PoliticsGirl @IAmPoliticsGirl]

“They were careless people… they smashed up things and creatures and then retreated back into their money or their vast carelessness or whatever it was that kept them together, and let other people clean up the mess they had made.”
- F. Scott Fitzgerald, The Great Gatsby

[Founders Inc @fdotinc]

it should be the hardest thing you ever do.

[My Mixtapez @mymixtapez]

Marian Croak is the Inventor of the tech powering Zoom, FaceTime & WhatsApp.

She Holds 200+ patents and was Inducted into the National Inventors Hall of Fame. 🌟

[Miguel 🏁 @guel_codes]

I'm working on a project that I want to #buildinpublic it's going to be REAL ugly for a while but here we go 😅

[Miguel 🏁 @guel_codes]

I honestly forgot how dark of a show Mr Robot was.

[Founders Inc @fdotinc]

"how i started dumpster diving to save America"

introducing the most advanced detection tech in trash.

lmao, it's a billion dollar business 👇

[Paolo Melchiorre @ PyCon Italia @pauloxnet]

Today was the first meeting of the navigators and captains of the Session 3 of the Djangonaut Space 🚀
I'm honored to be a navigator of the Team Saturn and to be in the company of so many great people 🫂
https://t.co/9X5rRASAKw
Look at the photo 👇
#Django #Djangonaut #Community

[𝕭𝖏ø𝖗𝖓 𝕾𝖙𝖆𝖆𝖑 @_nonfigurativ_]

Entangled #fxhash

[Aurimas Griciūnas @Aurimas_Gr]

What are the most common 𝗨𝘀𝗲 𝗖𝗮𝘀𝗲𝘀 𝗳𝗼𝗿 𝗞𝗮𝗳𝗸𝗮?

We have covered lots of concepts around Kafka already. But what are the most common use cases for The System that you are very likely to run into as a Data Engineer?

𝗟𝗲𝘁’𝘀 𝘁𝗮𝗸𝗲 𝗮 𝗰𝗹𝗼𝘀𝗲𝗿 𝗹𝗼𝗼𝗸:

𝗪𝗲𝗯𝘀𝗶𝘁𝗲 𝗔𝗰𝘁𝗶𝘃𝗶𝘁𝘆 𝗧𝗿𝗮𝗰𝗸𝗶𝗻𝗴.

➡️ The Original use case for Kafka by LinkedIn.
➡️ Events happening in the website like page views, conversions etc. are sent via a Gateway and piped to Kafka Topics.
➡️ These events are forwarded to the downstream Analytical systems or processed in Real Time.
➡️ Kafka is used as an initial buffer as the Data amounts are usually big and Kafka guarantees no message loss due to its replication mechanisms.

𝗗𝗮𝘁𝗮𝗯𝗮𝘀𝗲 𝗥𝗲𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻.

➡️ Database Commit log is piped to a Kafka topic.
➡️ The committed messages are executed against a new Database in the same order.
➡️ Database replica is created.

𝗟𝗼𝗴/𝗠𝗲𝘁𝗿𝗶𝗰𝘀 𝗔𝗴𝗴𝗿𝗲𝗴𝗮𝘁𝗶𝗼𝗻.

➡️ Kafka is used for centralized Log and Metrics collection.
➡️ Daemons like FluentD are deployed in servers or containers together with the Applications to be monitored.
➡️ Applications send their Logs/Metrics to the Daemons.
➡️ The Daemons pipe Logs/Metrics to a Kafka Topic.
➡️ Logs/Metrics are delivered downstream to storages like ElasticSearch or InfluxDB for Log/Metrics discovery respectively.
➡️ This is also how you would track your IoT Fleets.

𝗦𝘁𝗿𝗲𝗮𝗺 𝗣𝗿𝗼𝗰𝗲𝘀𝘀𝗶𝗻𝗴.

➡️ This is usually coupled with ingestion mechanisms already covered.
➡️ Instead of piping Data to a certain storage downstream we mount a Stream Processing Framework on top of Kafka Topics.
➡️ The Data is filtered, enriched and then piped to the downstream systems to be further used according to the use case.
➡️ This is also where one would be running Machine Learning Models embedded into a Stream Processing Application.

𝗠𝗲𝘀𝘀𝗮𝗴𝗶𝗻𝗴.

➡️ Kafka can be used as a replacement for more traditional messaging brokers like RabbitMQ.
➡️ Kafka has better durability guarantees and is easier to configure for several separate Consumer Groups to consume from the same Topic.

❗️Having said this - always consider the complexity you are bringing with introduction of a Distributed System. Sometimes it is better to just use traditional frameworks.

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𝗗𝗼𝗻’𝘁 𝗳𝗼𝗿𝗴𝗲𝘁 𝘁𝗼 𝗹𝗶𝗸𝗲 💙, 𝘀𝗵𝗮𝗿𝗲 𝗮𝗻𝗱 𝗰𝗼𝗺𝗺𝗲𝗻𝘁!

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[Miguel 🏁 @guel_codes]

@AdemoyeJohn I’ve been having a lot of fun with Arc it’s built on Chromium but it helps my productivity and eliminates a lot of tabs for me

[Miguel 🏁 @guel_codes]

https://t.co/Ah5kLouLYr

[Miguel 🏁 @guel_codes]

@JakeSucky Time Splitters 2

[Miguel 🏁 @guel_codes]

This SZA album has me in a chokehold.