Brij kishore Pandey

If you're an IT professional, navigating the Linux file system is a skill that can take you far.



It's meticulously organized - like a well-structured library.

Each directory has a unique, specific purpose.

Let's demystify the key directories: 🚀


🗃️ /bin: Binaries - This directory holds the essential user command binaries that all users can access.

🔧 /sbin: System Binaries - Contains the essential binaries used by the system administrator for system maintenance and troubleshooting.

⚙️ /etc: System Configuration - Houses the system configuration files, acting as the control panel on Linux.

💽 /dev: Device Files - Home to all device files, such as hard disks, USB, CD-ROM, etc.

📊 /proc: Process Information - A virtual directory detailing system and process information.

📁 /var: Variable Files - This is the variable data directory storing changing data like logs, mails, print spools, etc.

🗑️ /tmp: Temporary Files - This directory stores temporary files created by the system and users.

👥 /usr: User Binaries - Contains multi-user utilities, applications, and libraries.

🏠 /home: User Home Directories - Contains the home directories for users and other accounts.

📚 /lib: System Libraries - Houses library files that are needed by the system and the users.

🎁 /opt: Optional Software - Stores optional or additional software from vendors.

📝 /mnt: Mount Directory - Used for mounting other temporary file systems.

💿 /media: Removable Media - Acts as a temporary mount directory for removable devices.

🔨 /srv: Service Data - This directory contains server-specific services related data.

🚀 /boot: Boot Files - Contains boot loader related files.

👑 /root: Root Home - This is the home directory for the root user.

🔌 /run: Application Information - A tmpfs file system that contains application information.

🧑‍🔬 /usr/local: User Local - Contains user's programs that are installed from the source.

📦 /lib64: 64-bit Libraries - This is where the 64-bit library files are stored.


𝗪𝗵𝘆 𝗶𝘀 𝘁𝗵𝗶𝘀 𝗶𝗺𝗽𝗼𝗿𝘁𝗮𝗻𝘁, 𝘆𝗼𝘂 𝗺𝗶𝗴𝗵𝘁 𝗮𝘀𝗸?🤔

Well, understanding the Linux file system is crucial for many reasons: It helps you locate files swiftly, troubleshoot issues more effectively, and makes you a proficient developer or system administrator.💼👨‍💻

In an era where Linux skills are increasingly in demand, understanding the file system structure isn't just an add-on; it's a necessity.📈🌐

Let's continue to upskill and rise together!

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Did you know? Even though people usually use 4-5 HTTP methods, there are actually 39!


🌟 It's good to know at least 9 of these methods:

1️⃣ GET Method: Gets data from a server.

2️⃣ POST Method: Sends data to a server to create something new.

3️⃣ PUT Method: Changes something that's already on a server.

4️⃣ PATCH Method: Changes part of something on a server.

5️⃣ DELETE Method: Removes something from a server.

6️⃣ HEAD Method: Gets information about something on a server.

7️⃣ OPTIONS Method: Tells you how you can interact with something on a server.

8️⃣ TRACE Method: Shows the path of communication between you and the server.

9️⃣ CONNECT Method: Makes a special kind of connection to a server.


Thanks for your support, let's keep learning together!

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#api #apitesting #softwareengineering

Essential Cybersecurity Knowledge for IT Professionals

As technology becomes increasingly integral to business operations, a solid understanding of cybersecurity fundamentals is crucial for all IT professionals.

This knowledge is key to effectively safeguarding our organizations against evolving threats.

Key cybersecurity concepts every IT professional should understand:

1. Phishing: Recognizing and preventing email-based attacks that can lead to data breaches.

2. Ransomware: Understanding encryption-based extortion tactics to ensure business continuity.

3. Denial-of-Service (DoS): Identifying and mitigating attacks that disrupt service availability.

4. Man-in-the-Middle (MitM): Protecting the integrity and confidentiality of data in transit.

5. SQL Injection: Safeguarding databases against unauthorized access and manipulation.

6. Cross-Site Scripting (XSS): Securing web applications against client-side code injection.

7. Zero-Day Exploits: Developing strategies to defend against previously unknown vulnerabilities.

8. DNS Spoofing: Preventing the redirection of traffic to malicious destinations.

Proficiency in these areas enables IT professionals to identify risks, implement effective countermeasures, and contribute to a robust security posture. Continuous learning in cybersecurity is not just beneficial—it's imperative for the protection of our digital assets and the trust of our stakeholders.

What cybersecurity topics do you think deserve more attention in IT professional development?

These Free API courses are updated now and they are all about real skills that can help you stand out in tech.

Whether you're prepping for interviews or just want to level up, these are perfect for you.

Bonus - Attend Free Workshop on creating Robust GenAI Apps using Mysql Database.

RSVP here - https://brij.guru/ai

 1. 𝗔𝗣𝗜 𝗙𝘂𝗻𝗱𝗮𝗺𝗲𝗻𝘁𝗮𝗹𝘀: https://lnkd.in/e8eMet_k
 2. 𝗔𝗣𝗜 𝗦𝗶𝗺𝗽𝗹𝗶𝗳𝗶𝗲𝗱: https://lnkd.in/er9JiGxw
 3. 𝗔𝗣𝗜 𝗠𝗲𝘁𝗵𝗼𝗱𝘀: https://lnkd.in/ey9v7-hU
 4. 𝗔𝗣𝗜 𝗧𝗲𝗿𝗺𝗶𝗻𝗼𝗹𝗼𝗴𝗶𝗲𝘀: https://lnkd.in/eRsPMzpd
 5. 𝗔𝗣𝗜 𝗔𝘂𝘁𝗵𝗲𝗻𝘁𝗶𝗰𝗮𝘁𝗶𝗼𝗻: https://lnkd.in/eNPfpAdE
 6. 𝗔𝗣𝗜 𝗦𝘁𝗮𝘁𝘂𝘀 𝗖𝗼𝗱𝗲𝘀: https://lnkd.in/egXizUrS
 7. 𝗥𝗘𝗦𝗧 𝗔𝗣𝗜 𝘃𝘀 𝗚𝗿𝗮𝗽𝗵𝗤𝗟: https://lnkd.in/eZHREdgC
 8. 𝗔𝗣𝗜 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻: https://lnkd.in/eDASPP5m
 9. 𝗔𝗣𝗜 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻 𝗶𝗻 𝗗𝗲𝘁𝗮𝗶𝗹: https://lnkd.in/eZwFVrH7
10. 𝗔𝗣𝗜 𝗧𝗲𝘀𝘁𝗶𝗻𝗴: https://lnkd.in/emgmWJqH
11. 𝗔𝗣𝗜 𝘄𝗶𝘁𝗵 𝗣𝘆𝘁𝗵𝗼𝗻: https://lnkd.in/eM23ah2y
12. 𝗔𝗣𝗜 𝗦𝗰𝗮𝗹𝗶𝗻𝗴: https://lnkd.in/e3mZSvmn
13. 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗶𝗻𝗴 𝗥𝗼𝗯𝘂𝘀𝘁 𝗔𝗣𝗜𝘀: https://lnkd.in/eBXzbFyg
14. 𝗔𝗣𝗜𝘀 𝘄𝗶𝘁𝗵 𝗣𝗼𝘀𝘁𝗺𝗮𝗻: https://lnkd.in/ezue3d4B
15. 𝗧𝗲𝘀𝘁𝗶𝗻𝗴 𝗔𝗣𝗜𝘀 𝘄𝗶𝘁𝗵 𝗣𝗼𝘀𝘁𝗺𝗮𝗻: https://lnkd.in/eCPnGTGi
16. 𝗔𝗣𝗜 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆: https://lnkd.in/e79ZYfPa
17. 𝗔𝗣𝗜𝘀 𝗳𝗼𝗿 𝗘𝘃𝗲𝗿𝘆𝗼𝗻𝗲: https://lnkd.in/e4WGDffA

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This is just on a lighter note😂😂 -


As a society, it seems that we have become more focused on correcting others than on truly helping them. We love pointing out when someone has made a mistake or when they could have done something differently. But when it comes to actually offering support and assistance, we often fall short.

This mentality is damaging to both individuals and communities. When we focus on correcting others, we create a culture of criticism and judgment. This can be harmful to people's self-esteem and sense of worth, leading to feelings of inadequacy and inadequacy.

On the other hand, when we prioritize helping others, we create a culture of support and compassion. This can foster a sense of belonging and connectedness, and can even inspire people to be more empathetic and compassionate towards others.

So instead of focusing on what others are doing wrong, let's focus on how we can help them. Let's offer support, guidance, and encouragement. Let's create a culture of support and compassion, rather than one of criticism and judgment.

#softwareengineering #dataengineering

Explaining JSON Web Tokens (JWTs) to a 10-Year-Old :



Imagine you want to enter a secret club, but the club has a special rule:

you need a special pass with your name, age, and the club's name on it.

Your friend, who is a member of the club, can create that pass for you.

They use a secret code to lock the pass so that no one can change the information on it.

This process is called signing.

They take the information on the pass (your name, age, club name) and use the secret code to create a unique signature.

They then attach the signature to the pass.

When you go to the club, the security has the same secret code that your friend used to create the pass.

The security checks your pass by taking the information on it and using the secret code to create a new signature.

They then compare this new signature to the one attached to your pass.

✅ If the new signature matches the one on your pass, it means the pass hasn't been tampered with, and the guard lets you in.

🚫 If the signatures don't match, the guard knows that the pass is fake or has been changed, and you won't be allowed to enter.

𝗡𝗼𝘄, 𝘁𝗵𝗲 𝗮𝗰𝘁𝘂𝗮𝗹 𝗱𝗲𝗳𝗶𝗻𝗶𝘁𝗶𝗼𝗻:

JSON Web Tokens (JWTs) are a compact and secure way to transmit information between two parties.

They are often used for authentication and authorization purposes in modern APIs.

The information in a JWT is stored as a JSON object, which is then encoded and signed with a secret key to ensure its integrity.

𝗘𝘅𝗮𝗺𝗽𝗹𝗲:

1. A user logs in to a website with their username and password.
   
2. The server checks the credentials, and if they are valid, it creates a JWT with the user's information (like their user ID) and signs it using a secret key.
   
3. The server sends the JWT to the user's browser, which stores it (usually in a cookie or local storage).
   
4. When the user requests protected resources from the server (like their profile page), the browser sends the JWT along with the request.
   
5. The server verifies the JWT using the secret key.
   
6. If the JWT is valid, the server allows access to the requested resources.

JWTs are significant in modern APIs because they provide a stateless, scalable, and secure way to authenticate and authorize users.

They enable servers to offload session management tasks and reduce the overhead associated with traditional session-based authentication methods.

What are your thoughts on this analogy?

Please let me know in the comment section below.


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#api #softwareengineering

I'm re-sharing this carefully curated series of FREE courses aimed at professionals eager to build foundational to advanced skills in APIs.

This sequence is ideal for developers, software engineers, data engineers, product managers, and technical program managers.


Bonus - 

Free Workshop on creating Multi-Agent GenAI Apps:

🦜𝗥𝗦𝗩𝗣 𝗵𝗲𝗿𝗲 : https://brij.guru/ai

Let's elevate our understanding of APIs step-by-step:

✅API Fundamentals - lnkd.in/e8eMet_k
✅API Simplified - lnkd.in/er9JiGxw
✅API Methods - lnkd.in/ey9v7-hU
✅API Terminologies - lnkd.in/eRsPMzpd
✅API Authentication - lnkd.in/eNPfpAdE
✅API Status Codes - lnkd.in/egXizUrS
✅REST API vs GraphQL - lnkd.in/eZHREdgC
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✅API with Python - lnkd.in/eM23ah2y
✅API Scaling - lnkd.in/e3mZSvmn
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I encourage you to take advantage of these resources to sharpen your API skills and advance your career.

Follow me here for more resources like this - Brij kishore Pandey

Navigating the Microservice Landscape: A Comprehensive Roadmap

In today's complex world of microservices, it's easy to get lost in the plethora of technologies and frameworks. That's why I wanted to share this insightful microservice roadmap, which provides a clear overview of the key components and tools you'll encounter on your microservice journey.

At the heart of this roadmap lies the API Management layer, acting as the central hub for service registration, application gateway, and load balancing. Surrounding this core are essential elements such as caching, databases, distributed tracing, and container orchestration, each playing a vital role in building and managing robust microservice architectures.

🔹 Cloud Providers & Databases
From industry giants like AWS, GCP, and Azure to databases like MongoDB, MySQL, and Postgres, this roadmap covers the most popular cloud platforms and data storage solutions. Understanding their strengths and use cases is crucial for designing scalable and resilient microservices.

🔹 Container Orchestration & Monitoring
Kubernetes takes center stage as the leading container orchestration platform, alongside Docker and Swarm. Effective monitoring and alerting solutions like Prometheus and Grafana ensure the health and performance of your microservices.

🔹 Languages & Frameworks
The roadmap showcases a diverse range of programming languages and frameworks commonly used in microservice development, including Java, Python, Node.js, and Go. Whether you prefer established frameworks like Spring Boot and Django or newer entrants like Quarkus and Micronaut, there's a wealth of options to choose from.

🔹 Message Brokers & Distributed Tracing
Message brokers like RabbitMQ and Kafka enable reliable communication between microservices, while distributed tracing tools such as Zipkin and Jaeger help troubleshoot and optimize performance across complex service interactions.

By familiarizing yourself with the technologies and concepts presented in this roadmap, you'll be well-equipped to navigate the microservice landscape with confidence. Whether you're a seasoned developer or just starting your microservice journey, keeping this roadmap handy will help you make informed decisions and stay up-to-date with the evolving ecosystem.

What are your thoughts on this microservice roadmap?

Which technologies and tools have you found most valuable in your own microservice projects?

Top  9  types of API testing you need to know in 2024:

𝟭. 𝗩𝗮𝗹𝗶𝗱𝗮𝘁𝗶𝗼𝗻 𝗧𝗲𝘀𝘁𝗶𝗻𝗴: This is like a checkpoint. It makes sure your API does what it should. It checks things like data formats, how errors are handled, and if responses are right, no matter the input.

𝟮. 𝗙𝘂𝗻𝗰𝘁𝗶𝗼𝗻𝗮𝗹 𝗧𝗲𝘀𝘁𝗶𝗻𝗴: Here we test if the API is strong and works correctly. We send different kinds of data to see if each part of the API is working well.

𝟯. 𝗨𝗜 𝗧𝗲𝘀𝘁𝗶𝗻𝗴: This connects the user interface with the API. It checks if what users see on the screen is what the API is actually getting, spotting issues in showing and syncing data.

𝟰. 𝗟𝗼𝗮𝗱 𝗧𝗲𝘀𝘁𝗶𝗻𝗴: This is like a practice run for busy times. It tests how the API handles a lot of users at once, finding any weak spots to make sure it can handle busy times.

𝟱. 𝗥𝘂𝗻𝘁𝗶𝗺𝗲/𝗘𝗿𝗿𝗼𝗿 𝗗𝗲𝘁𝗲𝗰𝘁𝗶𝗼𝗻: This is like a guard dog. It watches your API as it works, catching any errors or strange things that might happen.

𝟲. 𝗦𝗲𝗰𝘂𝗿𝗶𝘁𝘆 𝗧𝗲𝘀𝘁𝗶𝗻𝗴: This is about making your API super safe. It looks for weak spots like chances for unauthorized access or data leaks.

𝟳. 𝗣𝗲𝗻𝗲𝘁𝗿𝗮𝘁𝗶𝗼𝗻 𝗧𝗲𝘀𝘁𝗶𝗻𝗴: Think of this as friendly hacking. It tries to break into your API on purpose to find and fix security holes before the bad guys do.

𝟴. 𝗙𝘂𝘇𝘇 𝗧𝗲𝘀𝘁𝗶𝗻𝗴: This is a bit wild. It throws all sorts of weird and wrong data at your API to find unexpected weak spots.

𝟵. 𝗜𝗻𝘁𝗲𝗿𝗼𝗽𝗲𝗿𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝗧𝗲𝘀𝘁𝗶𝗻𝗴: This makes sure your API plays well with others. It tests if different software and parts can easily connect and talk to your API.

Remember, testing your API is a continuous process. Here are some tips to stay on top:

Use automation tools: They're a big help in making testing easier and faster.

Work with others: Understand what people using your API need and want. This helps make better tests.

Keep records: Write down what you test and the results. This helps you improve over time.

Share your own tips and favorite tools in the comments!

Let's learn and grow together in API testing!

And follow me here -  Brij kishore Pandey for more tech insights!

A proxy server is a gatekeeper that sits between a client and a server.

When a client requests a resource from a server, the proxy server forwards the request on behalf of the client.

Proxy servers are important for a number of reasons. They are a common way to improve the security, performance, and scalability of web applications.

Forward proxies are like secret agents that help you browse the web anonymously. They can be used to bypass geo-restrictions, hide your IP address, and filter traffic.

Reverse proxies are like traffic cops that manage web traffic. They can be used to load balance requests across multiple servers, improve security, and rewrite URLs.

Here is a simple way to remember the difference between forward proxies and reverse proxies:

Forward proxies are like your secret friend who helps you see what's going on outside without being noticed.

Reverse proxies are like a really organized helper at a busy office who takes your messages and makes sure they get to the right department.

Here are some of the specific things that forward proxies and reverse proxies can do:

Forward proxies can:

• Hide the client's IP address: This can be useful for protecting the client's privacy or for bypassing geo-restrictions.
  
• Cache frequently accessed content: This can improve performance by reducing the number of times the client has to request the same content.
  
• Filter traffic: This can be used to block malicious requests or content.
  
Reverse proxies can:

• Load balance requests across multiple servers: This can improve scalability by ensuring that no single server is overloaded.
  
• Terminate SSL connections: This can improve security by encrypting traffic between the client and the server.
  
• Rewrite URLs: This can be useful for redirecting traffic or for implementing content negotiation.

Nailing your SQL interview is easier than you think. Get prepared with these common questions -


• What are the different types of SQL joins and when would you use each one?
• What is the difference between INNER JOIN and OUTER JOIN in SQL?
• Explain the concept of normalization in database design and why it's important.
• What is a primary key and why is it used in a database?
• Explain the difference between UNION and UNION ALL in SQL.
• How do you create a new table in SQL? Provide an example.
• What is a subquery in SQL and how can it be used in a query?
• Explain the concept of indexing in databases and how it can improve query performance.
• How do you retrieve the top N records from a table in SQL?
• What are stored procedures and functions in SQL, and how do they differ?
• Explain the difference between VARCHAR and CHAR data types in SQL.
• How do you calculate the average, sum, minimum, and maximum values of a column in SQL?
• What is a foreign key and how is it used in a database?
• Explain the concept of ACID properties in the context of database transactions.
• What is the purpose of the GROUP BY clause in SQL and how does it work?
• How do you add, modify, and delete data in a table using SQL?
• Explain the concept of NULL in SQL and how it's handled in queries.
• What is a view in SQL and why would you use it?
• How do you retrieve data from multiple tables using JOINs in SQL?
• Explain the difference between a clustered and a non-clustered index in SQL.
• What are triggers in SQL and how do they work?
• How do you handle duplicate records in a table using SQL?
• Explain the difference between a candidate key, primary key, and super key in database design.
• What is the purpose of the HAVING clause in SQL and how does it differ from the WHERE clause?
• Explain the concept of a self-join in SQL and when it might be used.
• How do you perform data aggregation across multiple groups in SQL?
• Explain the difference between a database and a schema in SQL.
• What is the purpose of the ORDER BY clause in SQL and how does it work?
• What are window functions? Explain with examples.
• How do you perform string manipulation and pattern matching in SQL?
• Explain the difference between a left outer join and a right outer join in SQL.
• What are the different types of subqueries in SQL and how are they used?
• How do you find and remove duplicate records from a table in SQL?
• Explain the concept of a materialized view in SQL and how it differs from a regular view.
• How do you perform data validation and data cleansing in SQL?
• Explain the difference between a transaction and a savepoint in SQL.
• What is a schema in SQL and why is it used?
• How do you calculate the difference between two dates in SQL?
• Explain the concept of a composite key in database design and when it might be used.
• What is a temporary table in SQL and how is it used?

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#sql #dataanalytics #dataengineering

For the last couple of years, Large Language Models (LLMs) have dominated AI, driving advancements in text generation, search, and automation.

But 2025 marks a shift—one that moves beyond token-based predictions to a deeper, more structured understanding of language. 

Meta’s Large Concept Models (LCMs), launched in December 2024, redefine AI’s ability to reason, generate, and interact by focusing on concepts rather than individual words. 

Unlike LLMs, which rely on token-by-token generation, LCMs operate at a higher abstraction level, processing entire sentences and ideas as unified concepts. This shift enables AI to grasp deeper meaning, maintain coherence over longer contexts, and produce more structured outputs. 

Attached is a fantastic graphic created by Manthan Patel

How LCMs Work: 


🔹 Conceptual Processing – Instead of breaking sentences into discrete words, LCMs encode entire ideas, allowing for higher-level reasoning and contextual depth. 

🔹 SONAR Embeddings – A breakthrough in representation learning, SONAR embeddings capture the essence of a sentence rather than just its words, making AI more context-aware and language-agnostic. 

🔹 Diffusion Techniques – Borrowing from the success of generative diffusion models, LCMs stabilize text generation, reducing hallucinations and improving reliability. 

🔹 Quantization Methods – By refining how AI processes variations in input, LCMs improve robustness and minimize errors from small perturbations in phrasing. 

🔹 Multimodal Integration – Unlike traditional LLMs that primarily process text, LCMs seamlessly integrate text, speech, and other data types, enabling more intuitive, cross-lingual AI interactions. 

Why LCMs Are a Paradigm Shift: 

✔️ Deeper Understanding: LCMs go beyond word prediction to grasp the underlying intent and meaning behind a sentence. 

✔️ More Structured Outputs: Instead of just generating fluent text, LCMs organize thoughts logically, making them more useful for technical documentation, legal analysis, and complex reports. 

✔️ Improved Reasoning & Coherence: LLMs often lose track of long-range dependencies in text. LCMs, by processing entire ideas, maintain context better across long conversations and documents. 

✔️ Cross-Domain Applications: From research and enterprise AI to multilingual customer interactions, LCMs unlock new possibilities where traditional LLMs struggle. 

LCMs vs. LLMs: The Key Differences 

🔹 LLMs predict text at the token level, often leading to word-by-word optimizations rather than holistic comprehension. 

🔹 LCMs process entire concepts, allowing for abstract reasoning and structured thought representation. 

🔹 LLMs may struggle with context loss in long texts, while LCMs excel in maintaining coherence across extended interactions. 

🔹 LCMs are more resistant to adversarial input variations, making them more reliable in critical applications like legal tech, enterprise AI, and scientific research.

Top 12 Microservice Design Patterns with Keywords

Microservices are a popular architectural style for building scalable, resilient, and independent applications.

But how do you choose the right design patterns for your microservices?

Here are the top 12 microservice design patterns, along with some keywords that can help you remember them:

 1. 𝗔𝘀𝘆𝗻𝗰 𝗠𝗲𝘀𝘀𝗮𝗴𝗲𝘀: Decouples the sender and receiver of messages, allowing them to operate independently. (decoupling, asynchronous, communication)
    
 2. 𝗖𝗵𝗮𝗶𝗻 𝗼𝗳 𝗥𝗲𝘀𝗽𝗼𝗻𝘀𝗶𝗯𝗶𝗹𝗶𝘁𝘆: Allows a request to be passed through a chain of handlers, each of which can decide whether to handle the request or pass it on to the next handler. (delegation, filtering, routing)
    
 3. 𝗕𝘂𝗹𝗸𝗵𝗲𝗮𝗱: Isolates a microservice from failures in other microservices, preventing a cascading failure. (isolation, fault tolerance, resilience)
    
 4. 𝗘𝘃𝗲𝗻𝘁 𝗦𝗼𝘂𝗿𝗰𝗶𝗻𝗴: Stores the history of events that have occurred in a microservice, allowing for easier auditing and debugging. (auditing, tracing, event-driven)
    
 5. 𝗖𝗶𝗿𝗰𝘂𝗶𝘁 𝗕𝗿𝗲𝗮𝗸𝗲𝗿: Prevents a microservice from becoming overloaded by failing requests, by automatically pausing requests to the microservice when it reaches a certain threshold. (fault tolerance, resilience, throttling)
    
 6. 𝗦𝗲𝗿𝘃𝗶𝗰𝗲 𝗥𝗲𝗴𝗶𝘀𝘁𝗿𝘆 𝗮𝗻𝗱 𝗗𝗶𝘀𝗰𝗼𝘃𝗲𝗿𝘆: Provides a central location for storing information about microservices, such as their location and endpoints. (lookup, discovery, naming)
    
 7. 𝗦𝗮𝗴𝗮: Helps to coordinate a series of transactions across multiple microservices. (orchestration, coordination, transactions)
    
 8. 𝗦𝗶𝗱𝗲𝗰𝗮𝗿: Adds additional functionality to a microservice, such as logging or monitoring. (extension, instrumentation, monitoring)
    
 9. 𝗔𝗴𝗴𝗿𝗲𝗴𝗮𝘁𝗼𝗿: Combines the output of multiple microservices into a single view. (consolidation, summarization, view)
    
10. 𝗔𝗣𝗜 𝗚𝗮𝘁𝗲𝘄𝗮𝘆: Acts as a single entry point for all requests to a microservices architecture. (abstraction, security, throttling)
    
11. 𝗦𝘁𝗿𝗮𝗻𝗴𝗹𝗲𝗿 𝗙𝗶𝗴: Gradually replaces an old microservice with a new one, without disrupting the existing system. (migration, replacement, graceful degradation)
    
12. 𝗖𝗤𝗥𝗦 (Command Query Responsibility Segregation): Separates read and write operations into different models, which can help to improve the performance, scalability, and flexibility of a microservices architecture. (separation of concerns, performance, scalability)
    
These are just a few of the many microservice design patterns that are available.

The best pattern for your microservices will depend on your specific requirements and goals.

Do you use any of these microservice design patterns in your work?

Share your thoughts in the comments below!

🙏 Follow me here : Brij kishore Pandey

The Top 8 API Architectural Styles You Should Know in 2024

As APIs continue to power the digital world, understanding the core API architectural styles is key for IT professionals.

Here are 8 styles that have stood the test of time and remain essential knowledge:

REST (Representational State Transfer): The undisputed champion of APIs, REST leverages HTTP methods to provide a simple yet powerful way to interact with resources. Like a trusty Swiss army knife, it's versatile enough to handle nearly any task.

GraphQL: The new kid on the block providing increased flexibility. GraphQL allows clients to request exactly the data they need. It's like having a genie deliver wishes on-demand.

gRPC (Google Remote Procedure Call): When speed is essential, gRPC delivers. Using HTTP/2 and protobufs, gRPC is blazing fast. Think Formula 1 racer whizzing down the track.

SOAP (Simple Object Access Protocol): The heavyweight veteran that thrives on structure and robustness. SOAP uses XML for rigorous standardized messaging. It's the 18-wheeler truck tackling any terrain.

WebSockets: Want real-time, bidirectional communication? WebSockets are the answer. Like an always-on phone call, WebSockets keep an open channel between client and server.

Webhooks: The notifier of the API world. Webhooks alert clients when key server-side events happen. It's your personal butler keeping you informed.

MQTT (Message Queuing Telemetry Transport): Built for resource-constrained environments, MQTT is a lightweight but determined messenger. Think a carrier pigeon delivering through wind and rain.

AMQP (Advanced Message Queuing Protocol): The robust backbone for reliable messaging in middleware. AMQP sets up a well-oiled assembly line to efficiently move data.

The right API architecture depends on your specific needs.

Analyze requirements around data, performance, security and scalability.

Then match the style that best fits your application.

With the fundamentals covered, you can build APIs that deliver.

Retrieval-augmented generation (RAG) has transformed AI by integrating 𝗿𝗲𝗮𝗹-𝘁𝗶𝗺𝗲 𝗸𝗻𝗼𝘄𝗹𝗲𝗱𝗴𝗲 𝗿𝗲𝘁𝗿𝗶𝗲𝘃𝗮𝗹 with 𝗹𝗮𝗿𝗴𝗲 𝗹𝗮𝗻𝗴𝘂𝗮𝗴𝗲 𝗺𝗼𝗱𝗲𝗹𝘀 (𝗟𝗟𝗠𝘀) to enhance responses.

But as AI applications scale, 𝘀𝘁𝗮𝘁𝗶𝗰 𝗿𝗲𝘁𝗿𝗶𝗲𝘃𝗮𝗹 𝗶𝘀𝗻’𝘁 𝗲𝗻𝗼𝘂𝗴𝗵—we need AI systems that can 𝗿𝗲𝗮𝘀𝗼𝗻, 𝗽𝗹𝗮𝗻, 𝗮𝗻𝗱 𝘁𝗮𝗸𝗲 𝗮𝗰𝘁𝗶𝗼𝗻 dynamically. 

That’s where 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗥𝗔𝗚 comes in. 

𝗧𝗿𝗮𝗱𝗶𝘁𝗶𝗼𝗻𝗮𝗹 𝗥𝗔𝗚 → Uses 𝘃𝗲𝗰𝘁𝗼𝗿 𝘀𝗲𝗮𝗿𝗰𝗵 to fetch relevant information before passing it to an LLM for generation. While powerful, it 𝗿𝗲𝗹𝗶𝗲𝘀 𝘀𝗼𝗹𝗲𝗹𝘆 𝗼𝗻 𝗽𝗮𝘀𝘀𝗶𝘃𝗲 𝗿𝗲𝘁𝗿𝗶𝗲𝘃𝗮𝗹 without deeper decision-making. 

𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗥𝗔𝗚 → Introduces 𝗺𝗲𝗺𝗼𝗿𝘆, 𝗿𝗲𝗮𝘀𝗼𝗻𝗶𝗻𝗴, 𝗽𝗹𝗮𝗻𝗻𝗶𝗻𝗴, 𝗮𝗻𝗱 𝘁𝗼𝗼𝗹 𝘂𝘀𝗲, allowing AI agents to: 

• Ask 𝗳𝗼𝗹𝗹𝗼𝘄-𝘂𝗽 𝗾𝘂𝗲𝗿𝗶𝗲𝘀 to refine retrieval  
• Use 𝗺𝘂𝗹𝘁𝗶𝗽𝗹𝗲 𝗱𝗮𝘁𝗮 𝘀𝗼𝘂𝗿𝗰𝗲𝘀 & 𝘀𝗲𝗮𝗿𝗰𝗵 𝗲𝗻𝗴𝗶𝗻𝗲𝘀 dynamically  
• Plan 𝗺𝘂𝗹𝘁𝗶-𝘀𝘁𝗲𝗽 𝗿𝗲𝗮𝘀𝗼𝗻𝗶𝗻𝗴 𝗽𝗮𝘁𝗵𝘀 (𝗥𝗲𝗔𝗖𝗧, 𝗖𝗼𝗧)  
• Execute 𝗲𝘅𝘁𝗲𝗿𝗻𝗮𝗹 𝘁𝗼𝗼𝗹𝘀 & 𝗔𝗣𝗜𝘀 for real-world interaction 

𝗪𝗵𝘆 𝗧𝗵𝗶𝘀 𝗦𝗵𝗶𝗳𝘁 𝗠𝗮𝘁𝘁𝗲𝗿𝘀 

⇲ 𝗙𝗿𝗼𝗺 𝗦𝘁𝗮𝘁𝗶𝗰 𝗥𝗲𝘀𝗽𝗼𝗻𝘀𝗲𝘀 𝘁𝗼 𝗔𝗱𝗮𝗽𝘁𝗶𝘃𝗲 𝗗𝗲𝗰𝗶𝘀𝗶𝗼𝗻-𝗠𝗮𝗸𝗶𝗻𝗴 – Instead of just retrieving documents, AI 𝗮𝗻𝗮𝗹𝘆𝘇𝗲𝘀, 𝗽𝗹𝗮𝗻𝘀, 𝗮𝗻𝗱 𝗮𝗱𝗷𝘂𝘀𝘁𝘀 in real time. 

⇲ 𝗕𝗲𝘆𝗼𝗻𝗱 𝗩𝗲𝗰𝘁𝗼𝗿 𝗗𝗕𝘀: 𝗘𝘅𝗽𝗮𝗻𝗱𝗶𝗻𝗴 𝗗𝗮𝘁𝗮 𝗛𝗼𝗿𝗶𝘇𝗼𝗻𝘀 – AI can pull 𝗰𝗼𝗻𝘁𝗲𝘅𝘁 𝗳𝗿𝗼𝗺 𝗺𝘂𝗹𝘁𝗶𝗽𝗹𝗲 𝘀𝗼𝘂𝗿𝗰𝗲𝘀 (vector databases, live web search, emails, APIs) to construct a more 𝗶𝗻𝗳𝗼𝗿𝗺𝗲𝗱 𝗿𝗲𝘀𝗽𝗼𝗻𝘀𝗲. 

⇲ 𝗣𝗲𝗿𝘀𝗶𝘀𝘁𝗲𝗻𝘁 𝗠𝗲𝗺𝗼𝗿𝘆 & 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 – Agentic RAG allows AI to 𝗿𝗲𝘁𝗮𝗶𝗻 𝗰𝗼𝗻𝘁𝗲𝘅𝘁 over long conversations and interactions, crucial for 𝗲𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲 𝗔𝗜, 𝗰𝗵𝗮𝘁𝗯𝗼𝘁𝘀, 𝗮𝗻𝗱 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻. 

⇲ 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗻𝗴 𝗖𝗼𝗺𝗽𝗹𝗲𝘅 𝗪𝗼𝗿𝗸𝗳𝗹𝗼𝘄𝘀 – AI agents can 𝘀𝗲𝗮𝗿𝗰𝗵, 𝗳𝗶𝗹𝘁𝗲𝗿, 𝗮𝗻𝗱 𝘀𝘆𝗻𝘁𝗵𝗲𝘀𝗶𝘇𝗲 knowledge, enabling 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻-𝘀𝘂𝗽𝗽𝗼𝗿𝘁 𝘀𝘆𝘀𝘁𝗲𝗺𝘀 in finance, healthcare, and cybersecurity. 

𝗧𝗵𝗲 𝗙𝘂𝘁𝘂𝗿𝗲 𝗼𝗳 𝗔𝗜: 𝗥𝗲𝘁𝗿𝗶𝗲𝘃𝗮𝗹 + 𝗥𝗲𝗮𝘀𝗼𝗻𝗶𝗻𝗴 + 𝗔𝗰𝘁𝗶𝗼𝗻 

With 𝗔𝗴𝗲𝗻𝘁𝗶𝗰 𝗥𝗔𝗚, we move beyond 𝗿𝗲𝘁𝗿𝗶𝗲𝘃𝗶𝗻𝗴 𝘀𝘁𝗮𝘁𝗶𝗰 𝗱𝗼𝗰𝘂𝗺𝗲𝗻𝘁𝘀—AI can now 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝘇𝗲, 𝗮𝗰𝘁, 𝗮𝗻𝗱 𝗿𝗲𝗳𝗶𝗻𝗲 𝗿𝗲𝘀𝗽𝗼𝗻𝘀𝗲𝘀 𝗶𝗻 𝗿𝗲𝗮𝗹-𝘁𝗶𝗺𝗲, making it a game-changer for 𝗮𝘂𝘁𝗼𝗻𝗼𝗺𝗼𝘂𝘀 𝗔𝗜 𝗮𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻𝘀. 


What are your thoughts on Agentic RAG and its impact on AI-driven systems?

Use this Template, to Learn How to Implement a Robust Backend for Your APIs

The following diagram provides a high-level overview of a microservices architecture for a web application:

💡 Also, bear in mind that this is just a baseline diagram and the tools/technology mentioned here are merely examples - feel free to swap them out with equivalent tools or technology that align with your team's preferences and specific requirements.

📱 𝗪𝗲𝗯/𝗠𝗼𝗯𝗶𝗹𝗲 𝗔𝗽𝗽: The front-end of the application where users engage directly. This can be a browser-based web application or a native mobile application. It communicates with the backend through the API gateway.

🚪 𝗔𝗣𝗜 𝗚𝗮𝘁𝗲𝘄𝗮𝘆: An entry point for the application's backend. This component typically manages request routing, authentication, rate limiting, and other cross-cutting concerns. Essentially, it functions as a reverse proxy, directing requests to the relevant services.

🔀 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻 𝗟𝗮𝘆𝗲𝗿: Here, you'll often find business logic, especially when various microservices and external services come into play. This layer orchestrates calls to different services, manages data transformations, and facilitates communication between components.

🛠 𝗠𝗶𝗰𝗿𝗼𝘀𝗲𝗿𝘃𝗶𝗰𝗲𝘀: These represent small, autonomous services that oversee specific chunks of business logic or domain functionality. Each microservice ideally has its standalone database for decoupling, scalability, and maintainability, allowing them to be developed, deployed, and scaled independently.

🗃 𝗗𝗮𝘁𝗮𝗯𝗮𝘀𝗲 (𝗗𝗕): This refers to persistent storage for application data. In line with the microservices paradigm, each microservice would optimally have its own database to maintain data integrity for its specific domain.

𝗢𝘁𝗵𝗲𝗿 𝗖𝗼𝗺𝗽𝗼𝗻𝗲𝗻𝘁𝘀:

In addition to the diagram's components, several other components might find use in a microservices architecture, such as:

🌐 𝗦𝗲𝗿𝘃𝗶𝗰𝗲 𝗠𝗲𝘀𝗵: A service mesh offers service discovery, load balancing, and fault tolerance features for microservices.

🖥 𝗖𝗲𝗻𝘁𝗿𝗮𝗹𝗶𝘇𝗲𝗱 𝗟𝗼𝗴𝗴𝗶𝗻𝗴 𝗮𝗻𝗱 𝗠𝗼𝗻𝗶𝘁𝗼𝗿𝗶𝗻𝗴: A centralized system for logging and monitoring to monitor application health and performance.

⚡ 𝗖𝗗𝗡 (𝗖𝗼𝗻𝘁𝗲𝗻𝘁 𝗗𝗲𝗹𝗶𝘃𝗲𝗿𝘆 𝗡𝗲𝘁𝘄𝗼𝗿𝗸): A CDN enhances application performance by caching static content at edge locations.

⚖️ 𝗟𝗼𝗮𝗱 𝗕𝗮𝗹𝗮𝗻𝗰𝗲𝗿𝘀: These help distribute incoming traffic across multiple servers, boosting performance and reliability.

💾 𝗖𝗮𝗰𝗵𝗶𝗻𝗴: Caching stores frequently accessed data in memory to elevate application performance.

Did I miss any crucial concept?

Your input is invaluable.

Please let me know!

It's 2023, and the world of work has changed dramatically.

We've seen a paradigm shift towards the agile way of working and it's only going to get bigger from here.

With that in mind, now is the perfect time to brush up on your knowledge of important agile terms!

If you're looking for an easy and quick guide that will help you understand all the basics of agile terminology, then look no further!

This 7-minute guide will walk you through everything from scrum ceremonies to technical debt.

By understanding these terms, you'll be able to speak confidently about them during interviews or when discussing projects at your current job.

Plus, if there are any terms I missed that you think should be included in this guide - let me know in the comments below and I'll make sure they're added!

So don't wait another minute - take control of your career today by getting familiar with all those essential agile words like sprints, refinement and backlogs.

You never know where knowing this stuff could lead - so why not give yourself every opportunity for success? Good luck everyone!

📌 If you like my posts, please me Brij Kishore Pandey and hit the 🔔 on my profile to get notifications for all my new posts.

#success #job #opportunity #work #career #help #agile #projects #scrum #softwareengineering #projectmanagement #scrum #kanban

Mastering Linux can truly set you apart in the tech world.


Whether you're a developer, sysadmin, or cloud engineer, Linux knowledge is invaluable.

Here are some other top Linux commands every tech pro should know:

 1. grep: Search for patterns in files
 2. sed: Stream editor for filtering and transforming text
 3. awk: Pattern scanning and text processing
 4. find: Search for files in a directory hierarchy
 5. tar: Compress and extract files
 6. ps: Report current processes
 7. top: Display system tasks
 8. ssh: Secure shell for remote access
 9. chmod: Change file permissions
10. chown: Change file ownership
11. systemctl: Control the systemd system and service manager
12. journalctl: Query the systemd journal
13. iptables: Configure firewall rules
14. rsync: Remote file copying tool
15. cron: Schedule tasks to run automatically

Pro Tip: Combine these commands with pipes (|) and redirections (> or >>) to create powerful one-liners!

Mastering these commands can significantly boost your productivity and make you comfortable with Linux wizard!

What's your favorite Linux command?

In today's competitive job market, it's more important than ever to have a strong understanding of SQL and NoSQL concepts.\n\nThese are the foundational skills that every aspirants needs to know.\n\nIf you're preparing for a job interview, be sure to brush up on these essential concepts.\n\nHere are a few things to keep in mind:\n\n1. Know the difference between SQL and NoSQL\n2. Be familiar with the basic SQL commands\n3. Learn about the different NoSQL data models\n4. Practice your SQL and NoSQL skills\n   \nThe best way to learn these skills is to practice. There are many online resources where you can practice your SQL and NoSQL skills.\n\nI have attached a guide that you can use as a quick reference. \n\nThis guide covers the basic SQL and NoSQL concepts that you need to know for any job interview.\n\nI hope this helps!\n\nDid I miss any crucial concept?\n\nYour feedback is invaluable.\n\nPlease let me know!

Let's speed things up!

Here's a beginner-friendly guide to optimizing your SQL queries, starting with some tips from my infographic:

1. Be Selective with DISTINCT: Only use DISTINCT when you absolutely need unique results. It can slow down your query if used unnecessarily.

2. Rethink Scalar Functions: Instead of using functions that return a single value for each row in SELECT statements, try using aggregate functions. They're often faster!

3. Cursor Caution: Avoid cursors when possible. They're like going through your data one by one, which can be slow. Set-based operations are usually faster.

4. WHERE vs HAVING: Use WHERE to filter rows before grouping, and HAVING to filter after grouping. This can significantly reduce the amount of data processed.

5. Index for Success: Think of indexes like the table of contents in a book. Create them on columns you frequently search or join on for faster lookups.

6. JOIN Smartly: INNER JOIN is often faster than using WHERE for the same condition. It's like telling the database exactly how to connect your tables.

7. CASE for Clarity: Use CASE WHEN statements instead of multiple OR conditions. It's clearer and can be more efficient.

8. Divide and Conquer: Break down complex queries into simpler parts. It's easier to optimize and understand smaller pieces.

But wait, there's more! Here are some extra tips to supercharge your queries:

9. EXISTS vs IN: Use EXISTS instead of IN for subqueries. It's often faster, especially with large datasets.

10. LIKE with Caution: Avoid using wildcards (%) at the beginning of your LIKE patterns. It prevents the use of indexes.

11. Analyze Your Plans: Learn to read query execution plans. They're like a roadmap showing how your database processes your query.

12. Partitioning Power: For huge tables, consider partitioning. It's like organizing your data into smaller, manageable chunks.

13. Table Variables: Sometimes, using table variables instead of temporary tables can boost performance.

14. Subquery Switcheroo: Try converting subqueries to JOINs or CTE. In many cases, this can speed up your query.

Remember, optimization is a journey, not a destination. Start with these tips and keep learning!

What's your favorite SQL optimization trick? Share in the comments!

I'm sharing a curated series of FREE courses for professionals looking to develop foundational to advanced skills in APIs. \n\nThis collection is perfect for developers, software engineers, data engineers, product managers, and technical program managers.\n\n𝗕𝗼𝗻𝘂𝘀 - Join me for a free workshop on building a Forecasting system using AI !\n\n✅. 𝗥𝗦𝗩𝗣 𝗵𝗲𝗿𝗲 -  https://brij.guru/learn\n\nStep up your API skills with these courses:\n\n🔹 API Fundamentals: lnkd.in/e8eMet_k  \n🔹 API Simplified: lnkd.in/er9JiGxw  \n🔹 API Methods: lnkd.in/ey9v7-hU  \n🔹 API Terminologies: lnkd.in/eRsPMzpd  \n🔹 API Authentication: lnkd.in/eNPfpAdE  \n🔹 API Status Codes: lnkd.in/egXizUrS  \n🔹 REST API vs GraphQL: lnkd.in/eZHREdgC  \n🔹 API Integration: lnkd.in/eDASPP5m  \n🔹 API Integration in Detail: lnkd.in/eZwFVrH7  \n🔹 API Testing: lnkd.in/emgmWJqH  \n🔹 API with Python: lnkd.in/eM23ah2y  \n🔹 API Scaling: lnkd.in/e3mZSvmn  \n🔹 Developing Robust APIs: lnkd.in/eBXzbFyg  \n🔹 APIs with Postman: lnkd.in/ezue3d4B  \n🔹 Testing APIs with Postman: lnkd.in/eCPnGTGi  \n🔹 API Security: lnkd.in/e79ZYfPa  \n🔹 APIs for Everyone: lnkd.in/e4WGDffA  \n\nI encourage you to make the most of these resources to refine your API skills and advance your career.

API Protocols: The Good, the Bad, and the Ugly

Choosing the right API protocol can be a real headache. Here's a no-nonsense rundown to help you navigate this maze:

1. REST
Simple, widely used. Great for public APIs. If in doubt, start here.

2. GraphQL
Flexible data fetching. Clients love it. Backend devs... it's complicated.

3. SOAP
Old school, but still kicking in enterprise. Verbose, but gets the job done.

4. gRPC
Fast. Really fast. Great for microservices if you can handle the learning curve.

5. Webhooks
For when you need real-time updates without constant polling.

6. WebSockets
Real-time, two-way communication. Chat apps' best friend.

7. MQTT
IoT's darling. Lightweight and works in sketchy networks.

8. AMQP
Reliable messaging for big systems. When you absolutely, positively need that message delivered.

9. EDA
Event-Driven Architecture. For systems that need to react quickly to changes.

10. EDI
B2B's old reliable. Not sexy, but gets the job done in retail and healthcare.

11. SSE
One-way updates from server to client. Simpler than WebSockets.

Remember, there's no one-size-fits-all. Mix and match based on what your system needs.

What's your go-to protocol? Drop your thoughts below.

Gif Credit - @Wallarm 

#Softwareengineering #API

Implementing CI/CD in Agile Teams

By adopting CI/CD, Agile teams can deliver high-quality software to users more quickly and reliably. This comprehensive guide outlines the step-by-step process for implementing CI/CD in your Agile team.

Step 1: Product Owner Crafts Engaging User Stories
The Product Owner plays a crucial role in creating user stories that clearly define the features and functionality to be developed. These stories serve as the foundation for the development process.

Step 2: Development Team Brings User Stories to Life
Using tools like Jira or Rally, the development team manages and tracks the progress of user stories. This ensures that the team stays aligned and focused on delivering value to the end-users.

Step 3: Foster Transparency and Collaboration
Effective communication is key to the success of any Agile team. Tools like Slack or Teams facilitate seamless collaboration, while version control systems like GitHub or Bitbucket ensure transparency and enable efficient code management.

Step 4: Implement Continuous Integration
Continuous Integration (CI) is the practice of regularly merging code changes into a central repository. Tools like SonarQube and DevOps are used to perform static code analysis, trigger builds, and provide valuable feedback to the development team.

Step 5: Ensure Code Quality with Unit Tests and Code Coverage
Unit tests and code coverage are essential for maintaining code quality. Tools like JaCoCo and JUnit help implement unit tests and measure code coverage. Build and deployment automation can be achieved using Jenkins and Maven.

Step 6: Rigorous Testing and Quality Assurance
To ensure the software meets the highest quality standards, tools like Selenium are used for regression and User Acceptance Testing (UAT). Nexus or Artifactory can be utilized as binary repositories to store and manage dependencies.

Step 7: Prioritize Security and Infrastructure Management
Security is a critical aspect of any software development process. Tools like Qualys can be employed to conduct routine security scans. Infrastructure management tools such as Terraform and Ansible help automate the provisioning and configuration of resources.

Additional Tips for Successful CI/CD Implementation:
- Start small and gradually expand your CI/CD pipeline as your needs grow.
- Ensure buy-in from your team and communicate the benefits of CI/CD clearly.
- Automate as much as possible to improve the efficiency of your CI/CD pipeline.
- Strive to reach key automation milestones, including unit test execution, build automation, code coverage checks, code quality checks, security scanning, automated deployments with gating, feedback automation to production teams, binary storage automation into a repo manager, and infrastructure setup automation.

Let's keep things simple: CICD with Agile is complex, don't make it harder than it needs to be.

CI/CD, which stands for continuous integration and continuous delivery/deployment, is a set of practices that automates the software development process. \n\nThis means that code changes can be integrated, tested, and deployed more frequently, which can help to improve the quality of your software and get it to market faster.\n\n𝗛𝗲𝗿𝗲'𝘀 𝗮 𝗯𝗿𝗲𝗮𝗸𝗱𝗼𝘄𝗻 𝗼𝗳 𝗵𝗼𝘄 𝗖𝗜/𝗖𝗗 𝘄𝗼𝗿𝗸𝘀 𝗼𝗻 𝗮 𝗵𝗶𝗴𝗵 𝗹𝗲𝘃𝗲𝗹:\n\n• 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁: Developers work on their code in a local branch.\n  \n• 𝗣𝘂𝗹𝗹 𝗥𝗲𝗾𝘂𝗲𝘀𝘁: When a developer is happy with their changes, they create a pull request. This submits their code for review by other developers.\n  \n• 𝗣𝗲𝗲𝗿 𝗥𝗲𝘃𝗶𝗲𝘄: Other developers review the code and make sure it meets quality standards.\n  \n• 𝗠𝗲𝗿𝗴𝗲: If the code is approved, it is merged into the main branch.\n  \n• 𝗖𝗼𝗻𝘁𝗶𝗻𝘂𝗼𝘂𝘀 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻: When code is merged into the main branch, a CI pipeline is triggered. This pipeline automates the process of building, testing, and deploying the code.\n  \n• 𝗕𝘂𝗶𝗹𝗱: The code is compiled into an executable application.\n  \n• 𝗧𝗲𝘀𝘁𝗶𝗻𝗴: The application is then tested to ensure that it works as expected. This may include unit tests, integration tests, and end-to-end tests.\n  \n• 𝗣𝗿𝗲-𝗣𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 𝗗𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁: If the tests pass, the application is deployed to a pre-production environment. This environment is a replica of the production environment, but it is not accessible to end users.\n  \n• 𝗣𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻 𝗗𝗲𝗽𝗹𝗼𝘆𝗺𝗲𝗻𝘁: If the application works well in pre-production, it can be deployed to the production environment. This is the environment that end users will use.\n\n𝗕𝗲𝗻𝗲𝗳𝗶𝘁𝘀 𝗼𝗳 𝗖𝗜/𝗖𝗗\n\nThere are many benefits to using CI/CD, including:\n\n• Improved software quality: CI/CD helps to identify and fix bugs early in the development process.\n  \n• Faster time to market: CI/CD can help you to get your software to market faster.\n  \n• Reduced risk: CI/CD can help to reduce the risk of deploying broken code to production.\n  \n• Increased developer productivity: CI/CD can help developers to focus on writing code instead of manual tasks.\n\n𝗚𝗲𝘁𝘁𝗶𝗻𝗴 𝗦𝘁𝗮𝗿𝘁𝗲𝗱 𝘄𝗶𝘁𝗵 𝗖𝗜/𝗖𝗗\n\nThere are a number of CI/CD tools available, such as Jenkins, GitLab, and CircleCI. \n\nThese tools can help you to automate the CI/CD pipeline.\n\nIf you're looking to improve your software development process, CI/CD is a great place to start. \n\nBy automating the process of building, testing, and deploying your code, you can deliver high-quality software faster and with less risk.\n\n#cicd #devops #softwareengineering

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