So what can you do with virtual router technology? The number one application, according to enterprises, is virtual networking, especially SD-WAN. All virtual-network technologies build an overlay network that has its own on- and off-ramp elements, which are really access routers. While many vendors offer this technology as appliances, most will also provide virtual routers for hosting on servers. That may make sense in the data center, where there are already racks of servers installed. Using virtual routers means that if one fails because its server went down, another can be easily spun up to take its place. Virtual routers are also essential in many cloud applications. Public cloud providers are understandably unenthusiastic about your sending your techs to install routers in their data centers, but you may need a virtual router there if you want to use virtual networking and SD-WAN optimally. For this type of cloud virtual routing, make sure your virtual router is compatible with the virtual network or SD-WAN technology you’re using.
There are a variety of roadblocks associated with moving to passwordless authentication. Foremost is that people hate change. End users push back when you ask them to abandon the familiar password-based login page and go through the rigamarole of registering a factor or device required for typical passwordless flows. Further, the app owners will often resist changing them to support passwordless flows. Overcoming these obstacles can be hard and expensive. It can also be exacerbated by the need to support more than one vendor’s passwordless solution. For example, most passwordless solutions pose app-level integration challenges that require implementing SDKs to support even simple flows. What happens if you want to support more than one solution? Or use your passwordless solution as both a primary identity and authentication provider and a step-up authentication provider? Or you want to layer in behavioral analytics? There is a way to address these human and technical challenges standing in the way of passwordless adoption using orchestration. Although common in virtualized computing stacks, orchestration is a new concept in identity architectures.
Obsolescence will always be a by-product of continuous technological advances. The best way to improve cyber security and reduce downtime risks is to prepare effectively and take proactive steps to manage obsolescence. With a proactive obsolescence management plan in place, such as a cloud-first approach, businesses can track the lifespan of products. This ensures that IT and operational technology are always protected, improving productivity and reducing costs. To plan for the future, mid-size businesses should carry out an assessment of current infrastructure to understand the components of the IT and operational technology landscape and how these systems interact. Vendors will often publish end-of-life dates for hardware and software at least twelve months in advance. IT managers should look at how much they already spend on maintenance and whether downtime has occurred before. Understanding the risks can also help businesses make more informed decisions about their equipment. Businesses should consider how the failure of a hardware or software component will impact operations, costs and reputation, and whether the equipment is compatible with the rest of the system.
One of the challenges is how differences in patient profile can drastically change the costs associated with the same procedure. For example, a healthy patient with no comorbidities can likely receive a colonoscopy at an outpatient center. However, a patient with a medical condition such as hemophilia would need that same colonoscopy performed in the more costly hospital setting because of the complications that could potentially arise. This variability makes providing accurate estimates complicated. One way to potentially address this issue is to provide best-case and worst-case estimates. Getting to the point where these estimates can be made in real time, so that a procedure can safely continue when a complication arises without the concern of being fined or not properly reimbursed, is key. Also, while the regulations are well-intended, the reality is it is probably unnecessary to have the specified level of price transparency for every encounter. We need to focus on the most problematic events – those medical episodes that bankrupt people because they had no idea what their out-of-pocket costs would be.
One of the main application areas where Icelandic datacentres make a lot of sense is in artificial intelligence (AI). With the advancement of AI methodologies such as unsupervised machine learning, for many applications, AI training and inference now needs to occur in the same location – they need to be colocated to facilitate iteration between the two processes. Foundational AI models run for weeks or months to do a re-education, so running a full training data set is very energy intensive. Businesses that depend on AI models do training continuously to get different versions of the models. For example, they might train for a specific customer who has a data set they want trained against. ... A second type of application where Icelandic datacentres make sense is in financial services. Although trading applications require very low latency and are usually placed close to exchanges in edge or metro locations, they depend on the output of larger, more compute intensive applications. These applications use thousands of computers 24 hours a day to run Monte Carlo simulations and Markov Chain analysis to make predictions about market trends.
Cyber exposures are a relatively new frontier for auto insurance. Traditional risk considerations have revolved around liability or theft, but those have evolved amid the increasingly connected landscape for vehicles. “We must evaluate the types of losses happening and what’s causing those losses. Are they related to malfunctions in a vehicle? Are they related to hacking? It’s a challenge for insurers even to determine the ultimate cause of a loss,” said Perfetto. “If there was an accident, and it wasn’t the driver’s fault per se but more of a vehicle malfunction, that may not be easily attributed. If there was a hacking incident, that might not be easy to discover.” ... “We have seen data that supports reduction in accident frequency related to certain technology added to a vehicle. But we have also seen the cost of replacing some more advanced technologies increase. Something as simple as a rear end or a minor dent in your bumper that used to be an easy and relatively inexpensive item to fix has become much more costly,” Perfetto noted.
You have to plan ahead for venture debt. Put it in place relatively soon after an equity financing. That way there is no adverse selection for the lenders; everyone (founders, VCs and lenders) around the table is happy at that time. If you try to put something in place with less than six months of cash, you will not be able to get debt. If you put it in place after an equity round, you can draw it down way into the future — that’s called a forward commitment/drawdown. That gives the startup a lot of optionality. It’s super important to understand all the terms. Often, founders don’t realize there are things like funding MACs, investor abandonment clauses, etc. These terms can be used by the lender to block the startup from either drawing down the money or creating a default after the money has been drawn. Either way, the company is in trouble and can’t count on the capital. So you really need to know your lender, have your VCs know your lender and pay attention to your terms. This is why we created the Sample Venture Debt Term Sheet, to explain all the terms.
From a security perspective, I’m hoping an increase in connected systems will lead to less human-error-related cyberattacks. This will largely revolve around increasing API accessibility and integration. Not only do better integrations allow for employees to do better, more efficient work, it also enables a more secure infrastructure throughout your entire organisation. For example, when APIs are accessible throughout the application ecosystem, this allows for systems to be configured through code, helping us introduce streamlined changes to configuration rather than having to go into specific applications. From a security perspective, this enables us to do advanced things like segregation of duty and activity monitoring at scale. These benefits are a large part of why we prioritise connectivity and API accessibility at Templafy, both in our own tech stack and our platform. We know it not only benefits our own team, but also our customers.
The rise of technology has incentivized industries to adapt in recent years. Still, that push is becoming a pull as realities like The Great Resignation and remote work push organizations to change how they interact with and relate to their customers and employees. The return on investment of developing adaptability in organizations comes from talent attraction and retention, increased innovation, improved employee engagement – and potentially, organizational survival. In the past, leaders have been able to draw from models such as William Bridges’ Transitions to understand adaptability. But while these approaches may help us to understand how a person adapts and what behaviors leaders should expect as people move through change, few have explored the why. And without that knowledge, it can be challenging for leaders to create supportive, psychologically healthy workplaces that support people as they adapt. Because adapt they must. The key to unlocking the potential of emotional intelligence is first to understand the construct and then identify the areas for development. The same goes for AQ.
Retaining developers requires more than first impressions. Just as good UX needs to be evaluated, refined, and tested over time, good DX is an investment in the long term. You won’t know how well you’ve succeeded without using analytics to evaluate your DX and test changes. Monitoring your API helps you identify users who have not been able to successfully make API calls, find patterns of success and failure for developers, and see how different users are engaging with your product over time. While tracking UX metrics is relatively straightforward for products focused on end-users, DX metrics differ in important ways. You need to develop a good strategy for API analytics so that you track relevant business value metrics while avoiding vanity metrics. ... You need to understand DX when you build products for developers so that you can attract developer users, inspire their confidence and creativity, and support their increasingly complex integrations over time. Building good UX and DX can be challenging, but with the right analytics stack, you can monitor your API and use metrics to craft the perfect API developer experience.
Quote for the day:
"Taking charge of your own learning is a part of taking charge of your life, which is the sine qua non in becoming an integrated person." -- Warren G. Bennis