Daily Tech Digest - April 29, 2022

Scrumfall: When Agile becomes Waterfall by another name

Agile is supposed to be centered on people, not processes — on people collaborating closely to solve problems together in a culture of autonomy and mutual respect, a sustainable culture that values the health, growth, and satisfaction of every individual. There is a faith embedded in the manifesto that this approach to software engineering is both necessary and superior to older models, such as Waterfall. Necessary because of the inherent complexity and indeterminacy of software engineering. Superior because it leverages the full collaborative might of everyone’s intelligence. But this is secondary to Agile’s most fundamental idea: We value people. It’s a rare employer today who doesn’t pay lip service to that idea. “We value our people.” But many businesses instead prioritize controlling their commodity human resources. This now being unacceptable to say out loud — in software engineering circles as in much of modern America — many companies have dressed it up in Scrum’s clothing, claiming Agile ideology while reasserting Waterfall’s hierarchical micromanagement.

Nerd Cells, ‘Super-Calculating’ Network in the Human Brain Discovered

After five years of research into the theory of the continuous attractor network, or CAN, Charlotte Boccara and her group of scientists at the Institute of Basic Medical Sciences at the University of Oslo, now at the Center for Molecular Medicine Norway (NCMM), have made a breakthrough. “We are the first to clearly establish that the human brain actually contains such ‘nerd cells’ or ‘super-calculators’ put forward by the CAN theory. We found nerve cells that code for speed, position and direction all at once,” says Boccara. ... The CAN theory hypothesizes that a hidden layer of nerve cells perform complex math and compile vast amounts of information about speed, position and direction, just as NASA’s scientists do when they are adjusting a rocket trajectory. “Previously, the existence of the hidden layer was only a theory for which no clear proof existed. Now we have succeeded in finding robust evidence for the actual existence of such a brain’s ‘nerd center,'” says the researcher,—and as such we fill in a piece of the puzzle that was missing.

Data Center Sustainability Using Digital Twins And Seagate Data Center Sustainability

Rozmanith said that Dessault’s digital twins data center construction simulation reduced time to market by 15%. He also said that the modular approach reduces design time by 20%. Their overall goal is to shorten data center stand-up time by 50% and reduce the waste commonly generated in data center construction. Even after construction, digital twins for the operation of a data center will be useful for evaluating and planning future upgrades and data center changes. Some data center companies, such as Apple have designed their data centers to be 100% sustainable for several years. Seagate recently announced that it would power its global footprint with 100% renewable energy by 2030 and achieve carbon neutrality by 2040. These goals were announced in conjunction with the release of the company’s 16th Global Citizenship Annual Report. That report included a look at the company’s annual progress towards meeting emission reduction targets, product stewardship, talent enablement, diversity goals, labor standards, fair trade, supply chain, and more.

Industry 4.0 – why smart manufacturing is moving closer to the edge

With Industry 4.0, new technologies are being built into the factory to drive increased automation. This all leads to potentially smart factories that can, for instance, benefit from predictive maintenance, as well as improved quality assurance and worker safety. At the same time, existing data challenges can be overcome. Companies operating across multiple locations often struggle to remove data silos and bring IT and OT (operational technology) together. An edge based on an open hybrid infrastructure can help them do this, as well as solving other problems. These problems include reducing latency as a result of supporting a horizontal data framework across the organization's entire IT infrastructure, instead of relying on data being funneled through a centralized network that can cause bottlenecks. Edge computing opens hybrid-aligned to cloud services can also reduce the amount of mismatched and inefficient hardware that has gradually built up, and which is located in often tight remote spaces too.

Digital twins: The art of the possible in product development and beyond

Digital twins are increasingly being used to improve future product generations. An electric-vehicle (EV) manufacturer, for example, uses live data from more than 80 sensors to track energy consumption under different driving regimes and in varying weather conditions. Analysis of that data allows it to upgrade its vehicle control software, with some updates introduced into new vehicles and others delivered over the air to existing customers. Developers of autonomous-driving systems, meanwhile, are increasingly developing their technology in virtual environments. The training and validation of algorithms in a simulated environment is safer and cheaper than real-world tests. Moreover, the ability to run numerous simulations in parallel has accelerated the testing process by more than 10,000 times. ... The adoption of digital twins is currently gaining momentum across industries, as companies aim to reap the benefits of various types of digital twins. Given the many different shapes and forms of digital twins, and the different starting points of each organization, a clear strategy is needed to help prioritize where to focus digital-twin development and what steps to take to capture the most value.

What Is Cloud-Native?

Cloud-native, according to most definitions, is an approach to software design, implementation, and deployment that aims to take full advantage of cloud-based services and delivery models. Cloud-native applications also typically operate using a distributed architecture. That means that application functionality is broken into multiple services, which are then spread across a hosting environment instead of being consolidated on a single server. Somewhat confusingly, cloud-native applications don't necessarily run in the cloud. It's possible to build an application according to cloud-native principles and deploy it on-premises using a platform such as Kubernetes, which mimics the distributed, service-based delivery model of cloud environments. Nonetheless, most cloud-native applications run in the cloud. And any application designed according to cloud-native principles is certainly capable of running in the cloud. ... Cloud-native is a high-level concept rather than a specific type of application architecture, design, or delivery process. Thus, there are multiple ways to create cloud-native software and a variety of tools that can help do it.

Predictive Analytics Could Very Well Be The Future Of Cybersecurity

Predictive analytics is gaining momentum in every industry, enabling organizations to streamline the way they do business. This branch of advanced analytics is concerned with the use of data, statistical algorithms, and machine learning to determine future performance. When it comes to data breaches, predictive analytics is making waves. Enterprises with a limited security staff can stay safe from intricate attacks. Predictive analytics tells them where threat actors tried to attack in the past, so it helps to see where they’ll strike next. Good security starts with knowing what attacks are to be feared. The conventional approach to fighting cybercrime is collecting data about malware, data breaches, phishing campaigns, and so on. Relevant information is extracted from those signatures. By signatures, it’s meant a one-of-a-kind arrangement of information that can be used to identify a cybercriminal’s attempt to exploit an operating system or an app’s vulnerability. The signatures can be compared against files, network traffic, and emails that flow in and out of the network to detect abnormalities. Everyone has distinct usage habits that technology can learn.

A Shift in Computer Vision is Coming

Neuromorphic technologies are those inspired by biological systems, including the ultimate computer, the brain and its compute elements, the neurons. The problem is that no–one fully understands exactly how neurons work. While we know that neurons act on incoming electrical signals called spikes, until relatively recently, researchers characterized neurons as rather sloppy, thinking only the number of spikes mattered. This hypothesis persisted for decades. More recent work has proven that the timing of these spikes is absolutely critical, and that the architecture of the brain is creating delays in these spikes to encode information. Today’s spiking neural networks, which emulate the spike signals seen in the brain, are simplified versions of the real thing — often binary representations of spikes. “I receive a 1, I wake up, I compute, I sleep,” Benosman explained. The reality is much more complex. When a spike arrives, the neuron starts integrating the value of the spike over time; there is also leakage from the neuron meaning the result is dynamic. There are also around 50 different types of neurons with 50 different integration profiles.

Implementing a Secure Service Mesh

One of our main goals with using a service mesh was to get Mutual Transport Layer Security (mTLS) between internal pod services for security. However, using a service mesh provides many other benefits because it allows workloads to talk between multiple Kubernetes clusters or run 100% bare-metal apps connected to Kubernetes. It offers tracing, logging around connections between pods, and it can output connection endpoint health metrics to Prometheus. This diagram shows what a workload might look like before implementing a service mesh. In the example on the left, teams are spending time building pipes instead of building products or services, common functionality is duplicated across services, there are inconsistent security and observability practices, and there are black-box implementations with no visibility. On the right, after implementing a service mesh, the same team can focus on building products and services. They’re able to build efficient distributed architectures that are ready to scale, observability is consistent across multiple platforms, and it’s easier to enforce security and compliance best practices.

5 Must-Have Features of Backup as a Service For Hybrid Environments

New backup as a service offerings have redefined backup and recovery with the simplicity and flexibility of the cloud experience. Cloud-native services can eliminate complexity of protecting your data and free you from the day-to-day hassles of managing the backup infrastructure. The innovative approach to backup lets you meet SLAs in hybrid cloud environments, and simplifies your infrastructure, driving significant value for your organization. Resilient data protection is key to always-on availability for data and applications in today’s changing hybrid cloud environments. While every organization has its own set of requirements, I would advise you to focus on cost efficiency, simplicity, performance, scalability, and future-readiness when architecting your strategy and evaluating new technologies. The simplest choice: A backup as a service solution that integrates all of these features in a pay-as-you-go consumption model. Modern solutions are architected to support today’s challenging IT environments.

Quote for the day:

"Leadership is like beauty; it's hard to define, but you know it when you see it." -- Warren Bennis

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