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The terms “blockchain” and “distributed ledger technology” (DLT) may be widely used but are not always well understood. This article explains the differences between them. Rather than covering the technical aspects in depth, we will focus on how and why these technologies have the potential to disrupt existing business models and perhaps even create entirely new ones. By Bankless Publishing.

Blockchain first started to gain serious recognition after “Satoshi Nakamoto” authored the Bitcoin White Paper in 2008. The article then explains the following:

• Blockchain
• What is Distributed Ledger Technology (DLT)?
• All blockchains are DLTs but not all DLTs are blockchains.
• DLT networks remove the need for the middleman
• Open blockchains take the potential one step further

Unfortunately, blockchain networks are still in their infancy and are not yet capable of delivering a comparable service to the millions (or billions) of people currently using the various platforms owned by big tech. Today’s blockchains face difficulties with scaling, especially while trying to maintain a high degree of decentralisation. Nice one!

Back in June 2014, the top five most popular databases were exactly the same as June 2022: Oracle, MySQL, Microsoft SQL Server, PostgreSQL and MongoDB. The difference is their relative popularity: PostgreSQL and MongoDB have been gaining in popularity relative to the relational incumbents. By Matt Asay.

In his opening keynote, MongoDB CEO Dev Ittycheria shared statistics that showed MongoDB has become mainstream data infrastructure for over 35,000 customers, from Fortune 500 companies to garage-dwelling startups alike.

Two main trends are clear from the article:

• The rise and rise of general purpose databases
• Databases become data platforms

In 2014, MongoDB helped to spark an industry trend toward specialization; in 2022, it’s part of a movement away from specialization. The irony is that MongoDB has never touted specialization, and has instead marketed itself as a general-purpose database from the start. Why? Because, as O’Grady explained, “general purpose” makes developers’ lives easier, and MongoDB has always focused on developer convenience.

MongoDB has always handled data relations just fine; it has handled them differently than a relational database. So, back then, the company accepted the NoSQL label, despite its problems (who wants to be defined by what they’re not?), because it helped developers think beyond tabular data structures. Since that time, there has been an explosion in non-relational, or multi-model, databases. Today, DB-Engines includes nearly 400 databases, but less than half of them are relational databases. From document to time series to graph to columnar to key-value to [insert new database type here], the industry has kept using relational databases even as it has found a home for a wide variety of new databases. Good read!

There are some universal truths about open source software (OSS). It has revolutionized our world and become the foundation of our digital society, the backbone of our digital economy, and the basis of our digital existence. By @linuxfoundation.

Open source software has played a significant part in everything from the internet and mobile apps we use every day to operating systems and programming languages used to construct the future. Even the systems we traditionally think of as being closed, such as Microsoft Windows and Apple’s Mac and iPhone, are developed using open source software.

But only a few decades ago, few people had even heard of open source software, and it was limited to a small group of enthusiastic devotees. Yet the concept of free and open source software (FOSS) has been around a long time, going back to the early days of the user communities for IBM mainframes and academic institutions. FOSS is software that anyone can use, study, modify, and distribute without restriction. The term “open source” was coined to describe this type of software, and the concept was formalized with the launch of the Open Source Initiative (OSI) in 1998.

Many new industries and thousands of businesses have joined the open source revolution. Those organizations that chose a deliberate OSS strategy, incorporating best practices, methods, and engineering processes, emerged as leaders in their industries or verticals for open source initiatives.

This research is a collection of learnings and best practices that Dr. Haddad has developed, collaborating with the LF AI & Data community members who have pursued their own open source journeys for years. The link to the 31 page long research pdf is also in the article. Nice one!

Computer vision is a rapidly growing field in research and applications. Advances in computer vision research are now more directly and immediately applicable to the commercial world. By Richmond Alake.

AI developers are implementing computer vision solutions that identify and classify objects and even react to them in real time. Image classification, face detection, pose estimation, and optical flow are some of the typical tasks. Computer vision engineers are a subset of deep learning (DL) or machine learning (ML) engineers that program computer vision algorithms to accomplish these tasks.

The article further describes solutions related to:

• Cloud computing
• AutoML
• Machine learning libraries and frameworks
• Mobile devices

Computer vision technology continues to increase as AI becomes more integrated in our daily lives. Computer vision is also becoming more and more common in the latest news headlines. As this technology scales, the demand for specialists with knowledge in computer vision systems will also rise due to trends in cloud computing service, Auto ML pipelines, transformers, mobile-focused DL libraries, and computer vision mobile applications. Good read!

AIOps is a term introduced by Gartner in 2016, referring to AI for IT Operations. It combines big data and machine learning to automate IT operations processes, including event correlation, anomaly detection, and causality determination. By ODSC Community.

As more companies adopt digital transformation initiatives, we are seeing an explosion in digital systems and their associated data exhaust. By rationalizing digital signals in an intelligent way, AIOps plays a crucial role in helping companies reduce operation costs, improve engineering efficiency, and enhance customer experience. As a result, AIOps adoption has grown exponentially along with the uptick of digital transformation. Ponemon Institute© Research Report estimated that the cost-saving from AIOps systems is $17K/Outage min.

Further in the article we have:

• How to get started with Azure Metrics Advisor
• Data preparation: map your AIOps problem to the dataset
• Data onboarding
• Tuning the detection
• Root cause analysis

In addition to the detected anomalies, Azure Metrics Advisor also offers insights into what might have been the cause of the issue to help you further troubleshoot. Stakeholders can get detection results via communication channels set up by the user, along with the anomaly detected and root cause analysis. You will also find reference architecture attached. Good read!

You manage access in AWS by creating policies and attaching them to AWS Identity and Access Management (IAM) principals (roles, users, or groups of users) or AWS resources. AWS evaluates these policies when an IAM principal makes a request, such as uploading an object to an Amazon Simple Storage Service (Amazon S3) bucket. Permissions in the policies determine whether the request is allowed or denied. By Matt Luttrell and Josh Joy.

In this blog post, we will walk you through a scenario and explain when you should use which policy type, and who should own and manage the policy. You will learn when to use the more common policy types: identity-based policies, resource-based policies, permissions boundaries, and AWS Organizations service control policies (SCPs).

The article explains the following:

• Different policy types and when to use them
  • Service control policies overview
  • Permissions boundaries overview
  • Identity-based policies overview
• Resource-based policies overview
  • How to implement different policy types
  • Service control policies
  • Permissions boundary policies
  • Identity-based policies
  • Resource-based policies
• Putting it all together

In this blog post, you learned about four different policy types: identity-based policies, resource-based policies, service control policies (SCPs), and permissions boundary policies. You saw examples of situations where each policy type is commonly applied. Then, you walked through a real-life example that describes an implementation that uses these policy types. Excellent read!

With lots of frameworks to choose from, and all those strong opinions, it’s easy to feel a little lost. Comparing frameworks based on the features they list can be a headache, and features are only part of the picture. It would be awesome if you had a clear checklist you could evaluate Node.js frameworks against. By Simon Plenderleith.

The article is split into the following sections:

• What’s your use case?
• Framework styles
• Support for promises and async / await
• Documentation
• Practical examples
• Community and ecosystem
• Project health

Context is everything. Try and get clear on your requirements before you start looking at frameworks and their features. This will help you you figure out if a framework is designed to support your intended use case. Good read!

It is being said that Web3 is the future of the internet which promises a decentralised, immutable version of the global web – free of intermediaries and equipped with the same cryptographic verifiability as cryptocurrencies and non-fungible tokens (NFTs). But what does that really mean? By Stefania Volpe.

The article then explains:

• Web3, Blockchain and NFT: what do they mean?
  • What is blockchain?
  • What is an NFT?
• Impact of Web3 on the future of work
• Benefits of web3 for freelancers
• How freelancers can use web3 to monetise their services
• Becoming a Web3 developer
  • Job profiles for developers in the Web3

Web3 is currently a somewhat vague concept whose exact definition has not yet been determined. It is more of an ideal image of a future web than a usable technology stack that developers can build directly on top of. Web3, to put it simply, is the next version of the Internet. The core of Web3 is to make the Internet decentralised, meaning that: there is no one who owns the Internet, all the data on it converges, it’s independent. Nice one!

What’s the best blockchain for building Web3 applications? It depends on what you want to prioritize across the blockchain trilemma. The trilemma argues that blockchains can only provide two of the three properties of decentralization, security, and scalability, and that no matter where you build, you’ll be making a tradeoff. By Joe Bender.

Developers today have a lot of options for where to build, and it’s hard to decide what blockchain is best. In this post, we break down some of the key features in Stacks, Polygon, and Solana to make it easier for you to figure out where you want to build.

The article then dives into:

• Stacks vs. Solana vs. Polygon: An overview
• Stacks vs. Solana vs. Polygon: Programming languages
• Stacks vs. Solana vs. Polygon: Developer support
• Stacks vs. Solana vs. Polygon: Which blockchain should you choose?

Different blockchains have different strengths and weaknesses. The blockchain that you choose will be dependent on what you want to build and how you want to build it. For example, if you want a secure foundation for your Web3 applications, or if you want to tap into the latent potential in Bitcoin, Stacks is your place. Good read!

Network Address Translation (NAT) is one of the most common and versatile network functions, used by everything from your home router to the largest ISPs. Today, we’re delighted to introduce a new approach to NAT that solves the problems of traditional hardware and virtual solutions. By Annika Garbers.

The article then paint the picture of:

• What does NAT do?
• Allowing traffic from private subnets to connect to the Internet
• Enabling communication between private subnets with overlapping IP space
• Conserving IP address space
• Challenges with existing NAT solutions
• Magic NAT: everywhere, unbounded, cross-platform, and predictably priced
• Anycast: Magic NAT is everywhere, automatically

Cloudflare’s global capacity is at 141 Tbps and counting, and automated traffic management systems like Unimog allow us to take full advantage of that capacity to serve high volumes of traffic smoothly. Magic NAT, like our other network services, is priced based on the 95th percentile of clean bandwidth for your network: no installation, maintenance, or upgrades, and no surprise charges for data transfer spikes. Magic NAT is currently in beta, translating network addresses globally for a variety of workloads, large and small. Good read!