Top 7 useful Linux commands for Sysadmins

June 29, 2021

As a system administrator, it’s your job to ensure your systems are running smoothly. This requires you to identify and solve problems, fix security vulnerabilities, and ensure your IT infrastructure is always working efficiently.

If you’re new to this role, you probably already know that being a sysadmin is a pretty demanding job. You have a lot of responsibilities to manage.

But we’re here to help make your job a little bit easier. Below are seven Linux commands every sysadmin should know.

Let’s get started.

1. Nmap

The nmap command is short for “Network Mapper.” It’s an open-source monitoring tool commonly used by sysadmins to scan and discover networks.

Thanks to its versatility, nmap has become one of the most popular tools among administrators. You can use it to:

  • Find live hosts on a network
  • Scan ports and perform ping sweeps
  • Detect operating systems running on your network
  • Perform security audits

You can even use nmap to scan for malware. Nmap comes with an expansive library of scripts, making it one of the most comprehensive tools in your arsenal.

You have to download and install nmap before you can use it. If you’re using CentOS or Fedora, use the following command:
sudo dnf install nmap

If you’re using Ubuntu or Debian, use:
sudo apt-get install nmap

2. Autoremove

Having a bunch of unwanted and unused packages on your system can be a security vulnerability. One of those packages could become an entry point for a cyberattack––and as the system administrator, it’s your job to reduce the threat vectors within your system.

That’s why we suggest removing any packages that you don’t use. This will reduce the chances of you falling victim to a cyberattack because of a software vulnerability or misconfiguration.

Use the autoremove command to delete all unwanted packages from your system. You can do this by running apt-get autoremove. This will remove any uninstalled packages that remain on your server.

Once you’re done with that, use the apt-cache pkgnames command to see a list of all your packages. When you find one or more packages you don’t need, delete them with sudo apt-get purge –auto-remove [packagename].

3. Sysv-rc-conf

This command lets you see which services are running in the background, as well as the boot time of every service you have running. You can use this tool to see whether you’ve got potentially harmful services running.

First, you need to install the program. You can do that by entering the following command: apt-get install sysv-rc-conf.

Once you’ve installed sysv-rc-conf, enter this command in your terminal: sysv-rc-conf –list | grep ‘3:on’. This will show you which services started when you booted your computer and which started later.

If you see a service that looks suspicious, disable it with: systemctl disable [servicename].

4. Iptables

Iptables is a versatile firewall tool you can use to protect your Linux system from outside threats. You can use it to block malicious parties from attacking your systems by using the following commands:

  • iptables -A INPUT -p tcp ! –syn -m state –state NEW -j DROP to force SYN packets check
  • iptables -A INPUT -p tcp –tcp-flags ALL NONE -j DROP to drop null packets
  • iptables -A INPUT -p tcp –tcp-flags ALL ALL -j DROP to drop XMAS packets
  • iptables -A INPUT -f -j DROP to drop incoming packets with fragments

5. Netstat

Open ports aren’t inherently dangerous. In fact, you need them to send and receive data over the internet.

However, having open ports that are hidden can be a problem. Hackers can use these ports to gain access to your system­­––and you won’t even know how they breached your cybersecurity measures.

You can use netstat -antp to scan your system for hidden open ports. This will give you a visual of all the open ports on your system. And when you come across a port you don’t recognize, close it using the following command: sudo kill $(sudo lsof -t -i:[portnumber]). This will effectively reduce the threat vectors that place your system at risk.

6. Chkrootkit

A rootkit is a collection of malicious tools that grant attackers remote access to your server. Think of it as a key that unwelcomed visitors can use to gain entry to your system.

Rootkits are designed to be difficult to find. Because once you discover and remove the rootkit, you end up removing the backdoor that’s been granting hackers access.

Chkrotkit is a tool that scans your server for suspicious programs that could be rootkits. You can install this program with the following command: apt-get install chkrootkit.

Once installed, use the chkrootkit command while you’re logged in as the root user. The program will scan your server for malware and notify you of any potential threats.

7. Update and Upgrade

Keeping your systems up to date is an important part of good cybersecurity. Your operating system and applications should be routinely patched to fix any security vulnerabilities that could compromise your server.

You can keep your systems updated and secure with the sudo apt-get update && apt-get upgrade command. The update command is used to update the list of packages, while upgrade downloads and installs them for you.

If you’re too busy to do manual upgrades, you can automate the process with sudo apt-get install unattended-upgrades. This enables automatic security updates, which ensures your system always stays patched.

Give Your Server a Multi-Layered Protection

There you have it. Seven Linux commands that will improve your system’s security and performance.

Combine these with BitNinja’s multi-layered protection to dramatically reduce your chances of being hacked. Cybersecurity is not optional anymore. It is a must! If you haven’t tried BitNinja yet, don’t forget to register for the 7-day free trial of Bitninja on E2E Cloud

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This is a decorative image for Project Management for AI-ML-DL Projects
June 29, 2022

Project Management for AI-ML-DL Projects

Managing a project properly is one of the factors behind its completion and subsequent success. The same can be said for any artificial intelligence (AI)/machine learning (ML)/deep learning (DL) project. Moreover, efficient management in this segment holds even more prominence as it requires continuous testing before delivering the final product.

An efficient project manager will ensure that there is ample time from the concept to the final product so that a client’s requirements are met without any delays and issues.

How is Project Management Done For AI, ML or DL Projects?

As already established, efficient project management is of great importance in AI/ML/DL projects. So, if you are planning to move into this field as a professional, here are some tips –

  • Identifying the problem-

The first step toward managing an AI project is the identification of the problem. What are we trying to solve or what outcome do we desire? AI is a means to receive the outcome that we desire. Multiple solutions are chosen on which AI solutions are built.

  • Testing whether the solution matches the problem-

After the problem has been identified, then testing the solution is done. We try to find out whether we have chosen the right solution for the problem. At this stage, we can ideally understand how to begin with an artificial intelligence or machine learning or deep learning project. We also need to understand whether customers will pay for this solution to the problem.

AI and ML engineers test this problem-solution fit through various techniques such as the traditional lean approach or the product design sprint. These techniques help us by analysing the solution within the deadline easily.

  • Preparing the data and managing it-

If you have a stable customer base for your AI, ML or DL solutions, then begin the project by collecting data and managing it. We begin by segregating the available data into unstructured and structured forms. It is easy to do the division of data in small and medium companies. It is because the amount of data is less. However, other players who own big businesses have large amounts of data to work on. Data engineers use all the tools and techniques to organise and clean up the data.

  • Choosing the algorithm for the problem-

To keep the blog simple, we will try not to mention the technical side of AI algorithms in the content here. There are different types of algorithms which depend on the type of machine learning technique we employ. If it is the supervised learning model, then the classification helps us in labelling the project and the regression helps us predict the quantity. A data engineer can choose from any of the popular algorithms like the Naïve Bayes classification or the random forest algorithm. If the unsupervised learning model is used, then clustering algorithms are used.

  • Training the algorithm-

For training algorithms, one needs to use various AI techniques, which are done through software developed by programmers. While most of the job is done in Python, nowadays, JavaScript, Java, C++ and Julia are also used. So, a developmental team is set up at this stage. These developers make a minimum threshold that is able to generate the necessary statistics to train the algorithm.  

  • Deployment of the project-

After the project is completed, then we come to its deployment. It can either be deployed on a local server or the Cloud. So, data engineers see if the local GPU or the Cloud GPU are in order. And, then they deploy the code along with the required dashboard to view the analytics.

Final Words-

To sum it up, this is a generic overview of how a project management system should work for AI/ML/DL projects. However, a point to keep in mind here is that this is not a universal process. The particulars will alter according to a specific project. 

Reference Links:

https://www.datacamp.com/blog/how-to-manage-ai-projects-effectively

https://appinventiv.com/blog/ai-project-management/#:~:text=There%20are%20six%20steps%20that,product%20on%20the%20right%20platform.

https://www.datascience-pm.com/manage-ai-projects/

https://community.pmi.org/blog-post/70065/how-can-i-manage-complex-ai-projects-#_=_

This is a decorative image for Top 7 AI & ML start-ups in Telecom Industry in India
June 29, 2022

Top 7 AI & ML start-ups in Telecom Industry in India

With the multiple technological advancements witnessed by India as a country in the last few years, deep learning, machine learning and artificial intelligence have come across as futuristic technologies that will lead to the improved management of data hungry workloads.

 

The availability of artificial intelligence and machine learning in almost all industries today, including the telecom industry in India, has helped change the way of operational management for many existing businesses and startups that are the exclusive service providers in India.

 

In addition to that, the awareness and popularity of cloud GPU servers or other GPU cloud computing mediums have encouraged AI and ML startups in the telecom industry in India to take up their efficiency a notch higher by combining these technologies with cloud computing GPU. Let us look into the 7 AI and ML startups in the telecom industry in India 2022 below.

 

Top AI and ML Startups in Telecom Industry 

With 5G being the top priority for the majority of companies in the telecom industry in India, the importance of providing network affordability for everyone around the country has become the sole mission. Technologies like artificial intelligence and machine learning are the key digital transformation techniques that can change the way networks rotates in the country. The top startups include the following:

Wiom

Founded in 2021, Wiom is a telecom startup using various technologies like deep learning and artificial intelligence to create a blockchain-based working model for internet delivery. It is an affordable scalable model that might incorporate GPU cloud servers in the future when data flow increases. 

TechVantage

As one of the companies that are strongly driven by data and unique state-of-the-art solutions for revenue generation and cost optimization, TechVantage is a startup in the telecom industry that betters the user experiences for leading telecom heroes with improved media generation and reach, using GPU cloud online

Manthan

As one of the strongest performers is the customer analytics solutions, Manthan is a supporting startup in India in the telecom industry. It is an almost business assistant that can help with leveraging deep analytics for improved efficiency. For denser database management, NVIDIA A100 80 GB is one of their top choices. 

NetraDyne

Just as NVIDIA is known as a top GPU cloud provider, NetraDyne can be named as a telecom startup, even if not directly. It aims to use artificial intelligence and machine learning to increase road safety which is also a key concern for the telecom providers, for their field team. It assists with fleet management. 

KeyPoint Tech

This AI- and ML-driven startup is all set to combine various technologies to provide improved technology solutions for all devices and platforms. At present, they do not use any available cloud GPU servers but expect to experiment with GPU cloud computing in the future when data inflow increases.

 

Helpshift

Actively known to resolve customer communication, it is also considered to be a startup in the telecom industry as it facilitates better communication among customers for increased engagement and satisfaction. 

Facilio

An AI startup in Chennai, Facilio is a facility operation and maintenance solution that aims to improve the machine efficiency needed for network tower management, buildings, machines, etc.

 

In conclusion, the telecom industry in India is actively looking to improve the services provided to customers to ensure maximum customer satisfaction. From top-class networking solutions to better management of increasing databases using GPU cloud or other GPU online services to manage data hungry workloads efficiently, AI and MI-enabled solutions have taken the telecom industry by storm. Moreover, with the introduction of artificial intelligence and machine learning in this industry, the scope of innovation and improvement is higher than ever before.

 

 

References

https://www.inventiva.co.in/trends/telecom-startup-funding-inr-30-crore/

https://www.mygreatlearning.com/blog/top-ai-startups-in-india/

This is a decorative image for Top 7 AI Startups in Education Industry
June 29, 2022

Top 7 AI Startups in Education Industry

The evolution of the global education system is an interesting thing to watch. The way this whole sector has transformed in the past decade can make a great case study on how modern technology like artificial intelligence (AI) makes a tangible difference in human life. 

In this evolution, edtech startups have played a pivotal role. And, in this write-up, you will get a chance to learn about some of them. So, read on to explore more.

Top AI Startups in the Education Industry-

Following is a list of education startups that are making a difference in the way this sector is transforming –

  1. Miko

Miko started its operations in 2015 in Mumbai, Maharashtra. Miko has made a companion for children. This companion is a bot which is powered by AI technology. The bot is able to perform an array of functions like talking, responding, educating, providing entertainment, and also understanding a child’s requirements. Additionally, the bot can answer what the child asks. It can also carry out a guided discussion for clarifying any topic to the child. Miko bots are integrated with a companion app which allows parents to control them through their Android and iOS devices. 

  1. iNurture

iNurture was founded in 2005 in Bengaluru, Karnataka. It provides universities assistance with job-oriented UG and PG courses. It offers courses in IT, innovation, marketing leadership, business analytics, financial services, design and new media, and design. One of its popular products is KRACKiN. It is an AI-powered platform which engages students and provides employment with career guidance. 

  1. Verzeo

Verzeo started its operations in 2018 in Bengaluru, Karnataka. It is a platform based on AI and ML. It provides academic programmes involving multi-disciplinary learning that can later culminate in getting an internship. These programmes are in subjects like artificial intelligence, machine learning, digital marketing and robotics.

  1. EnglishEdge 

EnglishEdge was founded in Noida in 2012. EnglishEdge provides courses driven by AI for getting skilled in English. There are several programmes to polish your English skills through courses provided online like professional edge, conversation edge, grammar edge and professional edge. There is also a portable lab for schools using smart classes for teaching the language. 

  1. CollPoll

CollPoll was founded in 2013 in Bengaluru, Karnataka. The platform is mobile- and web-based. CollPoll helps in managing educational institutions. It helps in the management of admission, curriculum, timetable, placement, fees and other features. College or university administrators, faculty and students can share opinions, ideas and information on a central server from their Android and iOS phones.

  1. Thinkster

Thinkster was founded in 2010 in Bengaluru, Karnataka. Thinkster is a program for learning mathematics and it is based on AI. The program is specifically focused on teaching mathematics to K-12 students. Students get a personalised experience as classes are conducted in a one-on-one session with the tutors of mathematics. Teachers can give scores for daily worksheets along with personalised comments for the improvement of students. The platform uses AI to analyse students’ performance. You can access the app through Android and iOS devices.

  1. ByteLearn 

ByteLearn was founded in Noida in 2020. ByteLean is an assistant driven by artificial intelligence which helps mathematics teachers and other coaches to tutor students on its platform. It provides students attention in one-on-one sessions. ByteLearn also helps students with personalised practice sessions.

Key Highlights

  • High demand for AI-powered personalised education, adaptive learning and task automation is steering the market.
  • Several AI segments such as speech and image recognition, machine learning algorithms and natural language processing can radically enhance the learning system with automatic performance assessment, 24x7 tutoring and support and personalised lessons.
  • As per the market reports of P&S Intelligence, the worldwide AI in the education industry has a valuation of $1.1 billion as of 2019.
  • In 2030, it is projected to attain $25.7 billion, indicating a 32.9% CAGR from 2020 to 2030.

Bottom Line

Rising reliability on smart devices, huge spending on AI technologies and edtech and highly developed learning infrastructure are the primary contributors to the growth education sector has witnessed recently. Notably, artificial intelligence in the education sector will expand drastically. However, certain unmapped areas require innovations.

With experienced well-coordinated teams and engaging ideas, AI education startups can achieve great success.

Reference Links:

https://belitsoft.com/custom-elearning-development/ai-in-education/ai-in-edtech

https://www.emergenresearch.com/blog/top-10-leading-companies-in-the-artificial-intelligence-in-education-sector-market

https://xenoss.io/blog/ai-edtech-startups

https://riiid.com/en/about

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