Abhay Reddy's Blog
Interest in the relationship between Docker and Kubernetes has been extremely high. The average monthly search volume in the US alone for ‘Docker vs Kubernetes’ was 12000 searches [source: Google]. This was around 10% of searches for the ‘Kubernetes’ keyword. A very high ratio that indicates a level of confusion on this topic.
Kubernetes is an open-source system for automating software deployment, scaling, and management of containerized applications. It has an expansive open-source ecosystem and is the market leader in this segment. All major players such as Google, Docker, Red Hat, Microsoft, AWS, Wind River and VMware have adopted/supported Kubernetes.
As the application container and virtual machine market continue to grow, there has been a tremendous interest in how they differ, and which of them is the better approach for specific projects. The keyword ‘virtual machines vs containers’ was searched 2400 times (on average) per month in the US alone [source: Google]
Virtual Machine provides an abstraction of the physical hardware. A Hypervisor allows multiple Virtual Machines (VM) to run on a single server. Each VM has a full copy of OS, app binaries, and libraries Pros: • Better utilization of resources than traditional methods • Applications are isolated Cons: • OS images are heavy (GB) and have a slow bootup process • Applications are not portable • Not Scalable • Can get expensive
Containers are units of software that contains the code and all dependencies so that an application can run across platforms such as desktops, data centers, and cloud. It provides an abstraction at the application layer. Each container runs as an isolated process while sharing the same OS kernel.
Container adoption has grown rapidly, and much faster than expected.
SDLC models have evolved over the years to meet customer and industry needs. Below table illustrates some of the differences between the three key models. Waterfall Model (1970) provided a linear sequential approach to managing software projects. Each phase depends on deliverables from the previous one. The sequence includes Requirement, Design, Development, Test, Deploy, and Maintenance. This model dominated for more than 2 decades
There will be more than 55.7 billion connected devices by 2025, and 75% will feature IoT connectivity which is estimated to produce 73 zettabytes of data. IT spending in 2022 touched $4.4 Trillion [Source] and is only expected to grow further. DevOps (2009) is an Agile methodology encompassing Development (Dev) and Operations (Ops). It enables end-to-end lifecycle delivery of features, fixes, and updates at frequent intervals. Agile adoption inherently left the Operations department behind with deployments piling up faster than they could be released. This trend ultimately pushed the rise of DevOps
Software Development Life Cycle (SDLC) is the process of planning, developing, testing, deploying, and maintenance of software systems. The goal is to create and deploy high-quality software that meets customers’ needs and is completed within cost and time estimates.
Top 10 Military Technologies. Unmanned aerial vehicles (Drones) are piloted either remotely or autonomously. They are already used in many applications such as military drones, photography, law enforcement, and firefighting. The price point of such drones varies from very cheap ($10-$50) to $100’s of millions depending on their sophistication and intelligence. There are currently significant investments being made in drone taxis and in military applications. Drones have completely upended military conflicts (Nagorno-Karabakh war, Ukraine-Russia war). Just wait for the cheap swarm drones that are getting much more pervasive and could easily overwhelm air defenses.
Below is a list of technologies that are receiving the most interest, funding and are transforming our world. Most of them transcend applications and industries. AI/ML (Artificial Learning & Machine Learning): The ability of machines to learn and act intelligently making it possible to automate complex tasks that were long thought of as impractical for machines to perform.
In Simple Terms 