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Home/computer/Page 4

Mains Answer Writing Latest Questions

Shubham Dhongadi
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Shubham DhongadiBegginer
Asked: July 18, 2024In:
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Cloud computing is the delivery of computing services—including servers, storage, databases, networking, software, and analytics—over the internet (“the cloud”). This model enables users to access and use these resources on-demand without having to own and maintain physical infrastructure or software ...

cloud computingcomputerhardwareiotitsoftware
  1. Bhavana Madas
    Bhavana Madas Begginer

    Cloud computing is like renting a library of books instead of buying them. You access these "books" (services like storage, processing power, and software) over the internet. Benefits: Cost Savings: Imagine you don’t buy the entire library but pay only for the books you read. Scalability: Need moreRead more

    Cloud computing is like renting a library of books instead of buying them. You access these “books” (services like storage, processing power, and software) over the internet.

    Benefits:

    1. Cost Savings: Imagine you don’t buy the entire library but pay only for the books you read.
    2. Scalability: Need more books? Just rent more without needing a bigger bookshelf.
    3. Accessibility: Read your rented books from anywhere, as long as you have an internet connection.
    4. Maintenance: The library staff (cloud provider) takes care of organizing and updating the books.
    5. Collaboration: Friends can read the same book simultaneously, no matter where they are.
    6. Disaster Recovery: If you lose your books, the library has backups, so you don’t lose your place.

    This way, cloud computing makes things simpler, more flexible, and cost-effective, just like an online library compared to owning physical books.

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Aryan Pratap singh
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Aryan Pratap singhBegginer
Asked: July 18, 2024In:
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computerdevelopmentdevopsittechnology
  1. Nikitananda
    Nikitananda Begginer

    Collaboration and Communication: Enhanced cooperation between development and operations teams to break down silos and improve workflow. Automation: Automated processes for code testing, integration, and deployment to increase efficiency and reduce errors. Continuous Integration and Continuous DeploRead more

    1. Collaboration and Communication:
      • Enhanced cooperation between development and operations teams to break down silos and improve workflow.
    2. Automation:
      • Automated processes for code testing, integration, and deployment to increase efficiency and reduce errors.
    3. Continuous Integration and Continuous Deployment (CI/CD):
      • Regularly integrating and deploying code to detect and fix issues early and improve product quality.
    4. Monitoring and Logging:
      • Comprehensive monitoring and logging of applications and infrastructure to detect and resolve issues quickly.
    5. Infrastructure as Code (IaC):
      • Managing and provisioning infrastructure through code, ensuring consistency and enabling rapid scalability.
    6. Agility:
      • Agile methodologies to enable rapid development cycles and quick responses to changes.

    Benefits to the Organization:

    1. Faster Time to Market:
      • Accelerated development cycles and quicker release of features and updates.
    2. Improved Collaboration:
      • Enhanced teamwork and communication between development and operations, leading to more effective problem-solving.
    3. Increased Efficiency:
      • Automation of repetitive tasks reduces manual errors and frees up time for more strategic work.
    4. Higher Quality and Reliability:
      • Continuous testing and integration lead to early detection of issues and more stable releases.
    5. Scalability:
      • IaC and automated deployment make it easier to scale applications and infrastructure.
    6. Enhanced Security:
      • Continuous monitoring and integration of security practices into the development process reduce vulnerabilities.
    7. Customer Satisfaction:
      • Faster delivery of updates and more reliable services improve customer experience and satisfaction.

    By integrating these DevOps practices, organizations can achieve greater agility, efficiency, and product quality, leading to a competitive advantage in the market.

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AT
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ATBegginer
Asked: July 19, 2024In: ,
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computerhacking
  1. Isha Vishnoi
    Isha Vishnoi Begginer

    Becoming an ethical hacker involves a structured approach to developing skills, gaining knowledge, and adhering to ethical guidelines. Here’s a concise roadmap highlighting the important points: Education and Knowledge: Formal Education: Obtain a degree in computer science, cybersecurity, or a relatRead more

    Becoming an ethical hacker involves a structured approach to developing skills, gaining knowledge, and adhering to ethical guidelines. Here’s a concise roadmap highlighting the important points:

    Education and Knowledge:

    • Formal Education: Obtain a degree in computer science, cybersecurity, or a related field to build a strong foundation.
    • Certifications: Earn certifications like Certified Ethical Hacker (CEH), Offensive Security Certified Professional (OSCP), or CompTIA Security+ to validate your skills.
    • Continuous Learning: Stay updated with the latest security trends, tools, and techniques by attending workshops, webinars, and conferences.

    Skills Development:

    • Networking and System Administration: Gain expertise in network protocols, operating systems, and system configurations.
    • Programming Languages: Learn languages like Python, Java, C++, and scripting languages like Bash to write and understand exploits.
    • Penetration Testing: Practice with tools such as Metasploit, Nmap, Wireshark, and Burp Suite in safe, controlled environments like labs or virtual machines.

    Ethical Guidelines:

    • Legal Boundaries: Always operate within the legal frameworks and obtain proper authorization before performing any hacking activities.
    • Code of Conduct: Follow a strict ethical code to ensure responsible disclosure of vulnerabilities and protect the privacy and data of individuals and organizations.
    • Documentation and Reporting: Accurately document findings and provide comprehensive reports to stakeholders, suggesting mitigation strategies.

    Practical Experience:

    • Hands-on Practice: Use platforms like Hack The Box, TryHackMe, and Capture the Flag (CTF) competitions to hone your skills.
    • Internships and Jobs: Gain practical experience through internships or entry-level positions in cybersecurity.

    In summary, becoming an ethical hacker requires a blend of formal education, skill development, adherence to ethical guidelines, and practical experience.

     

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Khushali Shah
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Khushali ShahBegginer
Asked: July 19, 2024In: , , , , , , , , , ,
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What is a major ethical concern related to AI?

aiawarenesscodecomputerethicsitpublicsecurity
  1. Prayati Paliwal
    Prayati Paliwal Begginer

    One major ethical concern related to AI is bias and fairness. AI systems can inadvertently reinforce and amplify biases present in the data they are trained on, leading to unfair and discriminatory outcomes. For example, an AI recruitment tool used by a major tech company was found to be biased agaiRead more

    One major ethical concern related to AI is bias and fairness. AI systems can inadvertently reinforce and amplify biases present in the data they are trained on, leading to unfair and discriminatory outcomes.

    For example, an AI recruitment tool used by a major tech company was found to be biased against female candidates. The tool was trained on historical resume data that predominantly featured male candidates, resulting in the system favoring men over women for technical positions. This instance highlights the challenges of ensuring fairness in AI-driven hiring processes.

    Another significant issue is seen in facial recognition technology, which has been criticized for its inaccuracies and biases. Research has shown that such systems often perform less accurately on darker-skinned and female faces compared to lighter-skinned and male faces. This discrepancy underscores the importance of using diverse and representative training data to prevent reinforcing societal inequalities.

    To address these concerns, it is crucial to implement robust testing, utilize diverse datasets, and ensure transparent and accountable methodologies in AI development. Fairness in AI is essential for building trust and ensuring that these technologies serve all individuals equitably.

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