✌️ 25 Javascript Path Files Used To Store Sensitive Information In Web Application:-

1️⃣ /js/config.js
2️⃣ /js/credentials.js
3️⃣ /js/secrets.js
4️⃣ /js/keys.js
5️⃣ /js/password.js
6️⃣ /js/api_keys.js
7️⃣/js/auth_tokens.js
8️⃣/js/access_tokens.js
9️⃣/js/sessions.js

♾

1️⃣ /js/authorization.js
2️⃣ /js/encryption.js
3️⃣ /js/certificates.js
4️⃣ /js/ssl_keys.js
5️⃣ /js/passphrases.js
6️⃣ /js/policies.js
7️⃣ /js/permissions.js
8️⃣ /js/privileges.js
9️⃣ /js/hashes.js

♾

1️⃣ /js/salts.js
2️⃣ /js/nonces.js
3️⃣ js/signatures.js
4️⃣ js/digests.js
5️⃣ js/tokens.js
6️⃣ js/cookies.js
7️⃣ /js/topsecr3tdonotlook.js

Interviewer: How to make sure that, one service should not make the whole system down?

Developer:
By building Fault tolerance in Microservices. This can be achieved via Resilience4j. It provides many mechanism like RateLimiter,
TimeLimiter, Bulkhead, CircuitBreaker, Retry etc.

75 Most Asked DSA interview questions 👨‍💻

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Planning for Data Science or Data Engineering Interview.

Focus on SQL & Python first. Here are some important questions which you should know.

𝐈𝐦𝐩𝐨𝐫𝐭𝐚𝐧𝐭 𝐒𝐐𝐋 𝐪𝐮𝐞𝐬𝐭𝐢𝐨𝐧𝐬

1- Find out nth Order/Salary from the tables.
2- Find the no of output records in each join from given Table 1 & Table 2
3- YOY,MOM Growth related questions.
4- Find out Employee ,Manager Hierarchy (Self join related question) or
Employees who are earning more than managers.
5- RANK,DENSERANK related questions
6- Some row level scanning medium to complex questions using CTE or recursive CTE, like (Missing no /Missing Item from the list etc.)
7- No of matches played by every team or Source to Destination flight combination using CROSS JOIN.
8-Use window functions to perform advanced analytical tasks, such as calculating moving averages or detecting outliers.
9- Implement logic to handle hierarchical data, such as finding all descendants of a given node in a tree structure.
10-Identify and remove duplicate records from a table.

𝐈𝐦𝐩𝐨𝐫𝐭𝐚𝐧𝐭 𝐏𝐲𝐭𝐡𝐨𝐧 𝐪𝐮𝐞𝐬𝐭𝐢𝐨𝐧𝐬

1- Reversing a String using an Extended Slicing techniques.
2- Count Vowels from Given words .
3- Find the highest occurrences of each word from string and sort them in order.
4- Remove Duplicates from List.
5-Sort a List without using Sort keyword.
6-Find the pair of numbers in this list whose sum is n no.
7-Find the max and min no in the list without using inbuilt functions.
8-Calculate the Intersection of Two Lists without using Built-in Functions
9-Write Python code to make API requests to a public API (e.g., weather API) and process the JSON response.
10-Implement a function to fetch data from a database table, perform data manipulation, and update the database.

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ENJOY LEARNING 👍👍

DSA revision Guide 🚀

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🚀 Agentic AI is exploding, but which framework should you bet on?

If you’ve tried building AI agents, you know the options are multiplying: LangGraph, LangChain, Autogen, CrewAI, Make.com, n8n… but they’re not interchangeable. Here’s how to make sense of the chaos:

🦜🔄 𝗟𝗮𝗻𝗴𝗚𝗿𝗮𝗽𝗵
Think enterprise-grade orchestration. Graph-based, stateful, long-running workflows with loops, branching, and persistent memory. Perfect when your agent system needs durability + complexity.

🦜🔗 LangChain
The OG. Great for chaining prompts, tools, and RAG. If you just need a chatbot, simple agent, or MVP, start here.

🟥🟦🟩🟨 AutogenAI (Microsoft)
Built for multi-agent collaboration. If you want agents to negotiate, coordinate, and tackle big tasks together, this is your go-to.

🤖 CrewAI
Lightweight and flexible. Assemble “crews” of role-specific agents quickly, while keeping granular control. Fast deployments, minimal dependencies.

🥢 Make
Visual, no-code automation for business users. Connect AI to CRMs, reports, SaaS tools—without writing a single line of code.

🟣🔄🟤 n8n
Open-source, node-based automation. Great for RAG-powered workflows and deep data integrations with a visual touch.

💡 Bottom line:
▪️Want enterprise complexity? → LangGraph
▪️Need fast AI app prototyping? → LangChain
▪️Building collaboratively? → Autogen or CrewAI
▪️Prefer drag-and-drop ? → Make.com or n8n

The right choice depends on your workflow complexity, control needs, and dev resources. Agentic AI is not one-size-fits-all!

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