WebAssembly is intended to execute code at native or near-native speeds.

WebAssembly is a representation of your code that can easily be executed in a high-performance manner by optimizing itself for each platform at runtime. We are still in the early days of WebAssembly, but it is already rivaling the performance of the V8 JavaScript engine, which has been optimized over countless years.


The Three Pillars of WebAssembly - The New Stack



Let’s start with security. It’s at the forefront of many minds these days, with supply chain issues, cryptojacking and data breaches being common news stories. WebAssembly brings some big guns to the security fight in a number of ways, starting with its security sandbox.

When WASM is executed, the code is not given access to anything, including the network, file system or anything else out of the box. This is known as a deny-by-default security model. For the code running inside the WASM sandbox to interact with the outside world, it must be explicitly granted access to host functions.


Language portability is the ability for modules written in one language, like Rust, to run inside a system written in another, like Go. Because WASM runtimes can be embedded within other software, they can be used to introduce specialized components that wouldn’t otherwise be possible in your team’s primary language.

This concept can also be applied to applications that are built by composing together multiple WASM modules written in different languages to form a single piece of software, such as with the Atmo framework, which our company, Suborbital maintains.


WebAssembly is not tied to any hardware architecture, so it can be executed on several different platforms without needing to re-compile. When a WASM module is executed, it is compiled to machine-native code either ahead-of-time (AOT) or just-in-time (JIT).

WASM runtimes such as Chrome’s V8, Wasmtime or Wasmer perform this compilation automatically. I can see this becoming useful in scenarios where your code gets moved automatically from a central cloud instance to an edge compute network when a spike in traffic causes a certain module to be pummeled by incoming requests.



To combat the rise of supply-chain attacks, there are also efforts to make cryptographic signing of WebAssembly modules a standard part of the specification. The ability to sign a module with a trusted key and have that signature verified any time a system attempts to run that module will be a big win, and helps cement the “defense in depth” mindset when working with WebAssembly to build applications.


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Cloud computing is on-demand access, via the internet, to computing resources—applications, servers (physical servers and virtual servers), data storage, development tools, networking capabilities, and more—hosted at a remote data center managed by a cloud services provider (or CSP). The CSP makes these resources available for a monthly subscription fee or bills them according to usage.

Cloud computing has the following benefits:

  1. Lower IT costs
  2. Improved agility and Time-To-Value
  3. Better scaling.



What is Cloud Computing?

Big data Hadoop
  • Ability to store and process huge amounts of any kind of data, quickly. With data volumes and varieties constantly increasing, especially from social media and the Internet of Things (IoT) , that's a key consideration.
  • Computing power. Hadoop's distributed computing model processes big data fast. The more computing nodes you use, the more processing power you have.
  • Fault tolerance. Data and application processing are protected against hardware failure. If a node goes down, jobs are automatically redirected to other nodes to make sure the distributed computing does not fail. Multiple copies of all data are stored automatically.
  • Flexibility. Unlike traditional relational databases, you don’t have to preprocess data before storing it. You can store as much data as you want and decide how to use it later. That includes unstructured data like text, images and videos.
  • Low cost. The open-source framework is free and uses commodity hardware to store large quantities of data.
  • Scalability. You can easily grow your system to handle more data simply by adding nodes. Little administration is required.

MapReduce programming is not a good match for all problems. It’s good for simple information requests and problems that can be divided into independent units, but it's not efficient for iterative and interactive analytic tasks. MapReduce is file-intensive. Because the nodes don’t intercommunicate except through sorts and shuffles, iterative algorithms require multiple map-shuffle/sort-reduce phases to complete. This creates multiple files between MapReduce phases and is inefficient for advanced analytic computing.

There’s a widely acknowledged talent gap. It can be difficult to find entry-level programmers who have sufficient Java skills to be productive with MapReduce. That's one reason distribution providers are racing to put relational (SQL) technology on top of Hadoop. It is much easier to find programmers with SQL skills than MapReduce skills. And, Hadoop administration seems part art and part science, requiring low-level knowledge of operating systems, hardware and Hadoop kernel settings.



What Is Hadoop & How Does It Work?

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