1. You can easily resize, extend, or reduce the logical volumes without affecting the data or the file system.
2. You can create snapshots of the logical volumes, which are point-in-time copies that can be used for backup or testing purposes.
3. You can use striping or mirroring to improve the performance or reliability of the logical volumes.
4. You can add or remove physical devices to the logical volumes without disrupting the system or the users.
5. You can use encryption or compression to enhance the security or efficiency of the logical volumes.

LVM is widely used in server disk management, as it provides more flexibility and control over the storage resources. LVM can help you to optimize the disk space utilization, improve the system performance, and simplify the backup and recovery processes. LVM can also enable you to use advanced features, such as RAID, clustering, or virtualization, on your server. To demonstrate LVM, we shall use lvm2 package installed on Ubuntu 22.

The server am using for this exercise has 5 physical disks (sda, sdb, sdc, sde and sdd), “sda” was used during the OS installation to host the boot partition and you will notice it already has the default ubuntu logical volume: “ubuntu-lv”

From the output above, we can clearly see that “/dev/sda2” which is a logical partition on disk “/dev/sda” is mounted on “/boot” and in-use by the file system. In this exercise, we shall create a logical volume using two free disks “/dev/sdb” and “/dev/sdc”, and later expand the logical volume using another free disk “/dev/sdd”. So, let’s get into the action:

1.) Creating a Logical Volume (LV) from two free disks “/dev/sdb” and “/dev/sdc”

Before using any physical disk in a Logical Volume (LV), we need to first of all define it as a Physical Volume (PV). A physical volume (PV) can be created from a whole disk or just a partition on a disk. To create a physical volumes, use the “pvcreate” command, followed by the name of the disk or partition you want to use.

Notice the newly created physical volumes “/dev/sdb” and “/dev/sdc”, each with disk size of 835.75g, also notice that the newly created PV is not associated to any VG! We shall get to VGs shortly!

Before we can proceed to creating the Logical Volume (LV), we need to first put the Physical Volumes (PVs) that we created into a pool also known as a Volume Group (VG). A Volume Group (VG) is a collection of physical volumes (PVs) that creates a pool of disk space out of which logical volumes (LVs) can be allocated. The significance of a volume group is that it enables you to create logical volumes that can span multiple physical volumes, or use only a part of a physical volume. To create a Volume Group (VG), use the “vgcreate” command, followed by the name of the volume group and the physical volumes you want to include.

At this point, we are ready to create our Logical Volume (LV). To create a logical volume, use the “lvcreate” command, followed by the name of the Volume Group (VG) and the size to allocate.

To be able to use the logical volume that we have created, we need to format it, create a mount point, and mount the logical volume.

The "ext4" is a Linux file system developed as the successor to “ext3“. It has significant advantages over its predecessor such as improved design, better performance, reliability, and new features. It can support files and file systems up to 16 terabytes in size. It also supports transparent encryption, snapshots, and data deduplication.

At this point we have successfully created our logical volume and made it available for use in the file system. And we can test this by changing the director to “/techjunction_backups” and creating a few text files which we can read/write on. However, there is one small step remaining and this is because the mount points created using the “mount” command are not persistent through system reboots and this is not good for a server that you are preparing for a production environment because that means that you will lose your data when the server reboots.

Data loss can occur when you mount the disk again using the “mount” command in Linux if the disk was not properly unmounted or synced before. This can happen if you remove the disk abruptly, power off the system, or encounter a system crash. When you mount a disk, the system may cache some data in memory to improve the performance and efficiency of the disk operations. However, this also means that some data may not be written to the disk immediately, and may remain in the cache until the system flushes them to the disk. If you unmount the disk without syncing the data, or if the system loses power or crashes, the data in the cache may be lost or corrupted. This can cause inconsistency or damage to the file system on the disk, and lead to data loss or errors when you mount the disk again. To prevent data loss, you should always unmount the disk properly using the “umount” command, or use the “sync” command to force the system to write all the cached data to the disk. You should also avoid removing the disk or shutting down the system while the disk is in use. To recover data from a damaged disk, you may need to use the “fsck” command to check and repair the file system.

Note: The “tee” command is used for reading from the standard input and writing to both the standard output and a file simultaneously. The “tee -a” option means append the output to the “/etc/fstab” file instead of overwriting it.

The “mount -a” command is useful when you want to mount all the file systems that are configured in the /etc/fstab file at once, without having to specify each device or directory individually. This can save time and avoid errors when you need to access multiple file systems on your system. However, the “mount -a” command also has some limitations and risks. For example, it may fail to mount some file systems if they are not available or ready, such as network file systems or removable devices. It may also cause data loss or corruption if the file systems are not properly configured or compatible with the system.  Therefore, it is recommended to use the “mount -a” command with caution, and only when you are sure that the file systems are safe and stable to mount.

At this point, we have completed the exercise of creating a logical volume and making it ready for use by the file system. We have also ensured that this mount point configuration data is persistent throughout server reboots by editing the “fstab” file.

2.) Expanding the logical volume (lv) using another free disk “/dev/ sdd”

Now that we have successfully created our logical volume (lv) “techjunction_lv” of size 1.6T, let’s test the advantage of LVM by expanding the size of this LV. But first let’s put some test directory and test files on our logical volume to make sure that our data will be preserved during this expansion exercise. In fact, if you want to experience the true beauty of LVM, you can test this on a live application. For example, an application using a database that is running from your newly created LV. And during the resizing of the LV, your application should not experience any downtime or hiccups. That’s the true potential of LVM compared to the conventional partitioning!

To show the hard disks that are not in use, we use the “lsblk" command, which can list all the block devices in the system, such as disks, partitions, and logical volumes. This command can also show the mount points of the devices that are in use.

From the above output, you can see that drives “sdd” and “sde” don’t have any partitions, logical volumes or mountpoints defined under them. And we can proceed to use “sdd” for our expansion exercise.

Next, we use the “lvextend” command to extend the size of the logical volume “techjunction_lv”. When you extend a logical volume, you can indicate how much you want to extend the volume, or how large you want it to be after you extend it.

We are not done resizing the logical volume, in fact if you check the file system at this point, you will realize that the size change is not yet in effect!

As you can see from the output above, our logical volume (lv) “techjunction_lv” has been resized from 1.7T to 2.5T without having to restart the server and without losing the data that was on the existing logical volume.

Hope this article has helped you to appreciate the power of using LVM as opposed to the legacy partitioning system. However, it’s important to note that LVM is not a substitute for RAID because it does not provide any protection against disk failures. LVM and RAID are two different technologies that serve different purposes. LVM is a logical layer that allows you to create, resize, and manage partitions on your disks without being constrained by the physical layout of the disks. RAID is a physical layer that allows you to combine multiple disks into one or more arrays that provide redundancy, performance, or both. Without RAID implementation on your system, if one of the physical volumes that belongs to a logical volume fails, the logical volume will become inaccessible and the data on it will be lost. LVM does not have any mechanism to replicate or recover the data from the failed disk. RAID, on the other hand, can protect the data from disk failures by using techniques such as mirroring, striping, or parity. Depending on the RAID level, RAID can tolerate one or more disk failures without losing any data. RAID can also rebuild the data from the surviving disks to a new disk in case of a failure.

Therefore, LVM and RAID should be used together to enhance system reliability. By using RAID, you can create a reliable and performant storage layer that can withstand disk failures. By using LVM on top of RAID, you can create flexible and manageable partitions that can span multiple RAID arrays or use only a part of a RAID array. For example, you can create a RAID 1 array with two disks to provide mirroring, and then create a logical volume on top of the RAID 1 array to store your critical data. You can then resize, move, or rename the logical volumes as you wish, without affecting the RAID arrays.

About the Author

Joshua Makuru Nomwesigwa is a seasoned Telecommunications Engineer with vast experience in IP Technologies; he eats, drinks, and dreams IP packets. He is a passionate evangelist of the forth industrial revolution (4IR) a.k.a Industry 4.0 and all the technologies that it brings; 5G, Cloud Computing, BigData, Artificial Intelligence (AI), Machine Learning (ML), Internet of Things (IoT), Quantum Computing, etc. Basically, anything techie because a normal life is boring.

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Cisco introduces new certifications and training for network engineers

Cisco, one of the leading providers of networking products and services, has announced new certifications and training programs for network engineers who want to advance their skills and careers in the evolving network industry. The new certifications include the Cisco Certified DevNet Associate, Specialist, and Professional, which focus on the development and automation of network applications and solutions. The new training programs include the Cisco DevNet Training and Certification Program, which offers courses and exams on topics such as network programmability, DevOps, cloud, and IoT. Cisco claims that these new certifications and training programs will help network engineers to become more agile, innovative, and valuable in the network industry.

Juniper Networks launches new AI-driven network operations platform

Juniper Networks, a company that specializes in network solutions and services, has launched a new platform that uses artificial intelligence (AI) to simplify and automate network operations. The platform, called Juniper Paragon Automation, is a cloud-native software suite that leverages machine learning, telemetry, and closed-loop automation to provide network operators with real-time visibility, assurance, and optimization of their network performance and service quality. Juniper Paragon Automation can help network operators to reduce operational costs, improve customer experience, and accelerate service delivery.

Nokia and Google Cloud partner to develop cloud-native 5G network solutions

Nokia, a global leader in telecommunications and network equipment, and Google Cloud, a division of Google that offers cloud computing services, have announced a strategic partnership to develop and deliver cloud-native 5G network solutions. The partnership aims to combine Nokia’s expertise and portfolio in 5G network infrastructure and applications with Google Cloud’s capabilities and scale in cloud computing and artificial intelligence. The partnership will focus on three areas: cloud-native 5G core network, edge computing, and network slicing. The partnership will enable network operators and enterprises to leverage the benefits of cloud-native 5G network solutions, such as agility, scalability, efficiency, and innovation.

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HCF is a fiber that has a hollow region in the center, surrounded by a ring of glass tubes that look like a honeycomb. The glass tubes act as a mirror that reflects the light back into the hollow core, preventing it from escaping. The light travels faster and farther in the air than in the glass, resulting in lower latency, lower attenuation, and higher bandwidth. HCF can also support different wavelengths of light, such as visible, infrared, and ultraviolet, which can enable new applications and functionalities.

HCF has many potential use cases in various fields, such as telecommunications, sensing, metrology, medicine, and defense. For example, HCF can be used to improve the performance and efficiency of 5G networks, by reducing the delay and increasing the capacity of the wireless fronthaul and backhaul links. HCF can also be used to enhance the security and reliability of optical networks, by making them immune to electromagnetic interference, hacking, and physical damage. HCF can also be used to enable new optical technologies, such as quantum communication, optical computing, and laser-based manufacturing.

HCF is still a developing technology that faces some challenges, such as fabrication complexity, cost, and compatibility with existing optical systems. However, several companies and research institutes are working on advancing the HCF technology and bringing it to the market. HCF is expected to revolutionize the world of optical communication and open new possibilities in technology and innovation.

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InfiniBand has been widely adopted by the HPC community, as it powers some of the world’s fastest supercomputers and AI (artificial intelligence) systems. According to the latest TOP500 list of supercomputers, InfiniBand connects 141 systems, including two of the top five systems: Fugaku in Japan and Summit in the US. InfiniBand also supports some of the most demanding AI workloads, such as large language models, deep learning, and computer vision. For example, Microsoft uses InfiniBand to speed up the training and inference of its Turing Natural Language Generation model, which has 17 billion parameters.

InfiniBand is not only a high-performance interconnect, but also a platform for innovation and advancement. NVIDIA, which acquired Mellanox Technologies in 2020, is the leading provider of InfiniBand solutions, including adapters, switches, routers, gateways, cables, transceivers, and data processing units (DPUs).

NVIDIA has been developing new technologies and capabilities that enhance InfiniBand’s performance and functionality. For instance, NVIDIA Quantum-2 is the next generation of InfiniBand networking platform, which offers 400 Gb/s bandwidth per port, 64 Tb/s switch capacity, and advanced In-Network Computing features such as SHARP (Scalable Hierarchical Aggregation and Reduction Protocol). SHARP offloads collective communication operations to the switch network, reducing the amount of data traversing the network and increasing data center efficiency. NVIDIA also offers BlueField DPUs, which combine powerful computing, high-speed networking, and extensive programmability to deliver software-defined, hardware-accelerated solutions for the most demanding workloads.

InfiniBand is transforming the AI landscape by enabling faster, smarter, and more scalable computing. As AI applications become more complex and data-intensive, InfiniBand provides the extreme performance, broad accessibility, and strong security needed by cloud computing providers and supercomputing centers. InfiniBand also opens new possibilities for technology development, such as quantum computing, converged workflows for HPC and AI, and new interfaces and connectors. InfiniBand is not only a high-speed interconnect, but also a future-proof platform for innovation and discovery.

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So, what are the hottest tech careers for 2024? Based on the latest trends, research, and forecasts, here are 10 tech careers that are expected to be in high demand and offer attractive salaries and rewarding careers in the next few years:

1.) Software Engineer

Software engineers are responsible for designing, developing, testing, and maintaining software applications and systems that run on various devices and platforms, such as computers, smartphones, tablets, web browsers, etc. Software engineers use various programming languages and frameworks, such as Java, C#, Python, JavaScript, React, Angular, etc., to create software solutions for various domains and problems, such as web development, mobile development, cloud computing, artificial intelligence, etc. According to Glassdoor, the average salary of a software engineer in the U.S. was $107,888 by 2020.

2.) Data Scientist

Data scientists are responsible for extracting insights and knowledge from large and complex data sets using various methods and techniques, such as statistics, mathematics, programming, machine learning, etc. Data scientists use various tools and languages, such as Python, SQL, etc., to collect, clean, explore, analyze, and visualize data for various purposes and problems, such as business analytics, predictive analytics, big data, etc. According to Glassdoor, the average salary of a data scientist in the U.S. was $113,309 by 2020.

3.) Cybersecurity Analyst

Cybersecurity analysts are responsible for monitoring, analyzing, and responding to cyber threats and incidents, using various tools and techniques such as firewalls, antivirus software, IDS, IPS, PenTesting, etc. Cybersecurity analysts work on various aspects and levels of cybersecurity, such as network security, application security, cloud security, endpoint security, etc. According to the U.S. Bureau of Labor Statistics (the median annual wage of information security analysts in the U.S. was $99,730 by 2019.

4.) Cloud Engineer

Cloud engineers are responsible for designing, developing, deploying, and managing cloud applications and systems using various cloud platforms and services such as Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform (GCP) etc. Cloud engineers work on various aspects and types of cloud computing such as; infrastructure as a service (IaaS), platform as a service (PaaS), software as a service (SaaS) etc. According to ZipRecruiter the average salary of a cloud engineer in the U.S. was $118,626 by 2020.

5.) Artificial Intelligence Engineer

Artificial intelligence engineers are responsible for designing, developing, testing, and deploying artificial intelligence applications and systems using various tools and frameworks such as TensorFlow, PyTorch, Keras etc. Artificial intelligence engineers work on various domains and problems such as natural language processing (NLP), computer vision, speech recognition, machine learning, deep learning etc. According to Glassdoor the average salary of an artificial intelligence engineer in the U.S. was $114,121 by 2020.

6.) Blockchain Developer

Blockchain developers are responsible for creating, maintaining, and optimizing blockchain applications and systems using various tools and protocols such as Ethereum, Hyperledger, Bitcoin etc. Blockchain developers work on various types and aspects of blockchain technology such as smart contracts, cryptocurrencies, decentralized applications (DApps) etc. According to ZipRecruiter the average salary of a blockchain developer in the U.S. was $154,550 by 2020.

7.) Internet of Things (IoT) Engineer

Internet of Things engineers are responsible for designing, developing and integrating IoT devices and systems using various hardware and software components such as sensors, microcontrollers, Arduino, Raspberry Pi etc. Internet of Things engineers work on various domains and applications of IoT such as smart homes, smart cities, smart agriculture, smart healthcare etc. According to Indeed the average salary of an IoT engineer in the U.S. was $101,930 by 2020.

8.) DevOps Engineer

DevOps engineers are responsible for facilitating the collaboration and integration between software development and IT operations teams using various tools and practices such as automation, continuous integration continuous delivery (CI/CD), monitoring etc. DevOps engineers work on improving the efficiency and quality of software delivery and deployment by reducing errors, delays and costs. According to Glassdoor the average salary of a DevOps engineer in the U.S. was $99,604 by 2020.

9.) Augmented Reality/Virtual Reality (AR/VR) Developer

AR/VR developers are responsible for creating immersive and interactive digital experiences using various technologies and platforms such as Unity, Unreal Engine, Oculus, Vive etc. AR/VR developers work on various domains and applications of AR/VR such as gaming, education, entertainment, healthcare etc. According to ZipRecruiter the average salary of an AR/VR developer in the U.S. was $121,478 by 2020.

10.) Robotics Engineer

Robotics engineers are responsible for designing, developing, testing, and operating robots and robotic systems that can perform various tasks and functions, using various technologies and disciplines such as mechanical engineering, electrical engineering, computer science, etc. Robotics engineers work on various domains and applications of robotics such as manufacturing, agriculture, healthcare, military, etc. According to ZipRecruiter, the average salary of a robotics engineer in the U.S. was $99,040 by 2020.

These are some of the hottest tech careers for 2024 that you can consider if you are looking for a challenging and rewarding career in the tech industry. However, these are not the only tech careers that will be in demand in the future. There are many other tech careers that will emerge or evolve as technology advances and creates new possibilities and challenges. Therefore, it is important to keep learning and updating your skills and knowledge to stay relevant and competitive in the tech market.

About the Author

Joshua Makuru Nomwesigwa is a seasoned Telecommunications Engineer with vast experience in IP Technologies; he eats, drinks, and dreams IP packets. He is a passionate evangelist of the forth industrial revolution (4IR) a.k.a Industry 4.0 and all the technologies that it brings; 5G, Cloud Computing, BigData, Artificial Intelligence (AI), Machine Learning (ML), Internet of Things (IoT), Quantum Computing, etc. Basically, anything techie because a normal life is boring.

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