Del Mar is projecting more than $26.6 million in total purses over the course of the eight-week meeting, the seaside track&#x27;s 85th summer session. The seaside track will offer $7.875 million in stakes purses, including six grade 1 stakes.

Del Mar Announces $7.8M Stakes Program for 2024 - BloodHorse

Star router Next and the speedy No Nay Mets are among the top contenders in two of Churchill Downs&#x27; featured stakes races May 1 leading up to Kentucky Derby (G1) weekend.

No Nay Mets, Next Star in Churchill Feature Stakes - BloodHorse

Here&#x27;s your day-to-day look at post times, ticket prices, stakes races and more ahead of Kentucky Derby Week at Churchill Downs; races start Saturday.

Kentucky Derby Week 2024: Post times, ticket prices, stakes races, more at Churchill Downs

Stakes is a social wagering platform for NFTs that transforms sports betting into a more social activity

Stakes

High-Speed Internet and High-Stakes Piracy

While artificial intelligence (AI) shows potential to increase profitability across most industries, its adoption is also resulting in a widening global skills gap, making upskilling workforces in AI and machine learning (ML) imperative for progress. A report by KPMG shows that among leading businesses prioritizing technology investment for profitability, a resounding 68% identify AI and machine learning as indispensable to their short-term plans. This means the need for AI skilling is such that it requires employees, employers, business organizations, and educational institutions all to pitch in. In short, building the AI-skilled workforce has to be a truly global effort. Enhancing skills in AI and Machine Learning is no longer optional but a necessity
Ruban Phukan, co-founder and CEO of GoodGist “Enhancing skills in AI and Machine Learning is no longer optional but a necessity,” Ruban Phukan, co-founder and CEO of GoodGist, an autonomous learning startup, told The Tech Panda. And the reason for this necessity, he says, is that AI saves time. “In an era where time is the scarcest resource and the boundaries between work and personal life increasingly blur, leveraging AI to optimize time is one of the most significant steps individuals can take to boost both their professional and personal productivity. This reality underscores the importance of upskilling,” Phukan explains. According to a Slack survey, workplace adoption of AI tools has sped up 24% over the previous quarter, with one out of four desk workers saying they have used AI tools at their work as of January 2024, as compared to one in five as of September 2023. “Upskilling, however, transcends mere familiarity with AI usage. It’s a critical response to the profound shifts in the business landscape and job market triggered by the rapid evolution of technology,” he adds. According to the World Economic Forum, nearly 1 billion people worldwide will need to upskill by 2030, with Korn Ferry warning that failing to do so could result in an $8.5 trillion loss in potential revenue. This is a stark backdrop to McKinsey’s projection that 87% of companies will experience a skills gap in the coming years, making upskilling not just imperative but urgent as time is of the essence here. Job postings for AI are high, but where is the talent? As AI gets integrated into all kinds of sectors, companies are starting to compete for AI talent. AI job postings surged 42% since ChatGPT’s debut, as Big Tech companies like Amazon, Google, Apple, and others like global logistics firm UPS, are beginning to shift resources to channel money into hiring machine learning engineers and data scientists. Companies are actively in search of skilled professionals to fill roles from technical leadership to applied research. These include eBay, Krutrim, Accenture, Dentsu, Gramener and others. According to an AIM report on generative AI salaries in India, large companies are offering INR 1 crore or more annually for senior roles, while startups and mid-size companies are ready to give out approx. INR 30-40 lakh. However, are these companies finding the talent they seek? As per new research, about three in four employers are struggling to hire for the AI skills they seek even though they are willing to boost salaries 43% in marketing and 35-42% across HR, finance, and legal roles. In fact, with the acceleration in AI adoption, companies are beginning to rely on education partnerships and gig work to reach the talent required. This is why skilling programs in AI are afoot. In March, IIM Lucknow and Emeritus launched the “Digital Transformation and AI for Business Leaders” Program to shape the next generation of AI leaders, an 11-month program designed to help leaders gain comprehensive insights into the intricacies of digital transformation and AI. Similarly, Physics Wallah (PW), an Indian EdTech platform, launched PW Institute of Innovation (PW IOI), a four-year residential program in Computer Science and AI to address the critical challenges faced by the Indian software industry, strategically located in Bengaluru, the Silicon Valley of India. The significant increase in the demand-supply gap for skilled AI and data science professionals further highlights the need for a comprehensive transformation in the learning approach
Vishwa Mohan, CIO at PW & President of PW IOI Vishwa Mohan, CIO at PW & President of PW IOI, said, “It is indeed concerning that despite the exponential growth witnessed in the Indian software industry, the employability rate of Indian engineering graduates has remained relatively low, with only marginal improvement over the years. Additionally, the significant increase in the demand-supply gap for skilled AI and data science professionals further highlights the need for a comprehensive transformation in the learning approach.” Employees want AI skilling from employers At the same time, employee expectations are starting to include skilling and training in AI. According to a study by EPAM India, 93% of modern engineers seek upskilling opportunities in AI, Cloud, and other new-age technologies, while 92% look for opportunities to enhance their problem-solving skills to identify and implement the best solutions. Also, 91% of respondents stated that future developmental and on-job training opportunities are their top expectations from their workplaces. Regarding their perspective for the future, 68% and 46% of modern engineers, respectively, believe that Data Analytics and AI will be the demand in the future, enabling enhancing consumer experience and collaboration. Some companies have started working on these expectations in a bid to retain talent. For example, Findability Sciences, an enterprise AI solution has trained over 100 of its data analysts and scientists across its Boston, India, and Japan operations with intensive training in problem formulation and prompt design and engineering skills. Empowering our team with these new skills is a strategic move that will pay dividends for our clients and the company. The future of AI is generative, and we are now more than ready to take it head-on
Mandar Kulkarni, AVP of Pre-sales Mandar Kulkarni, AVP of Pre-sales, said, “Empowering our team with these new skills is a strategic move that will pay dividends for our clients and the company. The future of AI is generative, and we are now more than ready to take it head-on.”?? The aim is to arm its team with the latest skills to cater to the evolving requirements of its existing and incoming customers in the generative AI arena. “This training is more than an investment in our team; it’s an investment in our clients,” says Anurag Srivastava, the Global Delivery Head. In a tech-driven business landscape, AI and machine learning expertise empower professionals to navigate disruption and contribute significantly to short-term viability and long-term success, hence its necessity as a skill is becoming inevitable. Every ecosystem has to pool in resources to meet the AI demand that will only go up in the future. Navanwita Sachdev, Editor, The Tech Panda While artificial intelligence (AI) shows potential to increase profitability across most industries, its adoption is also resulting in a widening global skills gap, making upskilling workforces in AI and machine learning (ML) imperative for progress. artificial intelligence A report by KPMG shows that among leading businesses prioritizing technology investment for profitability, a resounding 68% identify AI and machine learning as indispensable to their short-term plans. report by KPMG This means the need for AI skilling is such that it requires employees, employers, business organizations, and educational institutions all to pitch in. In short, building the AI-skilled workforce has to be a truly global effort. Enhancing skills in AI and Machine Learning is no longer optional but a necessity Ruban Phukan, co-founder and CEO of GoodGist Enhancing skills in AI and Machine Learning is no longer optional but a necessity Enhancing skills in AI and Machine Learning is no longer optional but a necessity Enhancing skills in AI and Machine Learning is no longer optional but a necessity Ruban Phukan, co-founder and CEO of GoodGist “Enhancing skills in AI and Machine Learning is no longer optional but a necessity,” Ruban Phukan , co-founder and CEO of GoodGist , an autonomous learning startup, told The Tech Panda . And the reason for this necessity, he says, is that AI saves time. Ruban Phukan GoodGist The Tech Panda “In an era where time is the scarcest resource and the boundaries between work and personal life increasingly blur, leveraging AI to optimize time is one of the most significant steps individuals can take to boost both their professional and personal productivity. This reality underscores the importance of upskilling,” Phukan explains. According to a Slack survey , workplace adoption of AI tools has sped up 24% over the previous quarter, with one out of four desk workers saying they have used AI tools at their work as of January 2024, as compared to one in five as of September 2023. a Slack survey “Upskilling, however, transcends mere familiarity with AI usage. It’s a critical response to the profound shifts in the business landscape and job market triggered by the rapid evolution of technology,” he adds. According to the World Economic Forum , nearly 1 billion people worldwide will need to upskill by 2030, with Korn Ferry warning that failing to do so could result in an $8.5 trillion loss in potential revenue. This is a stark backdrop to McKinsey’s projection that 87% of companies will experience a skills gap in the coming years, making upskilling not just imperative but urgent as time is of the essence here. According to the World Economic Forum Korn Ferry warning McKinsey’s projection Job postings for AI are high, but where is the talent? Job postings for AI are high, but where is the talent? As AI gets integrated into all kinds of sectors, companies are starting to compete for AI talent. AI job postings surged 42% since ChatGPT’s debut, as Big Tech companies like Amazon, Google, Apple, and others like global logistics firm UPS, are beginning to shift resources to channel money into hiring machine learning engineers and data scientists. AI job postings Companies are actively in search of skilled professionals to fill roles from technical leadership to applied research. These include eBay, Krutrim, Accenture, Dentsu, Gramener and others. According to an AIM report on generative AI salaries in India, large companies are offering INR 1 crore or more annually for senior roles, while startups and mid-size companies are ready to give out approx. INR 30-40 lakh. These include an AIM report However, are these companies finding the talent they seek? As per new research , about three in four employers are struggling to hire for the AI skills they seek even though they are willing to boost salaries 43% in marketing and 35-42% across HR, finance, and legal roles. In fact, with the acceleration in AI adoption, companies are beginning to rely on education partnerships and gig work to reach the talent required. research This is why skilling programs in AI are afoot. In March, IIM Lucknow and Emeritus launched the “Digital Transformation and AI for Business Leaders” Program to shape the next generation of AI leaders, an 11-month program designed to help leaders gain comprehensive insights into the intricacies of digital transformation and AI. IIM Lucknow Emeritus Similarly, Physics Wallah (PW), an Indian EdTech platform, launched PW Institute of Innovation (PW IOI), a four-year residential program in Computer Science and AI to address the critical challenges faced by the Indian software industry, strategically located in Bengaluru, the Silicon Valley of India. Physics Wallah The significant increase in the demand-supply gap for skilled AI and data science professionals further highlights the need for a comprehensive transformation in the learning approach Vishwa Mohan, CIO at PW & President of PW IOI The significant increase in the demand-supply gap for skilled AI and data science professionals further highlights the need for a comprehensive transformation in the learning approach The significant increase in the demand-supply gap for skilled AI and data science professionals further highlights the need for a comprehensive transformation in the learning approach The significant increase in the demand-supply gap for skilled AI and data science professionals further highlights the need for a comprehensive transformation in the learning approach Vishwa Mohan, CIO at PW & President of PW IOI Vishwa Mohan, CIO at PW & President of PW IOI, said, “It is indeed concerning that despite the exponential growth witnessed in the Indian software industry, the employability rate of Indian engineering graduates has remained relatively low, with only marginal improvement over the years. Additionally, the significant increase in the demand-supply gap for skilled AI and data science professionals further highlights the need for a comprehensive transformation in the learning approach.” Employees want AI skilling from employers Employees want AI skilling from employers At the same time, employee expectations are starting to include skilling and training in AI. According to a study by EPAM India, 93% of modern engineers seek upskilling opportunities in AI, Cloud, and other new-age technologies, while 92% look for opportunities to enhance their problem-solving skills to identify and implement the best solutions. Also, 91% of respondents stated that future developmental and on-job training opportunities are their top expectations from their workplaces. study Regarding their perspective for the future, 68% and 46% of modern engineers, respectively, believe that Data Analytics and AI will be the demand in the future, enabling enhancing consumer experience and collaboration. Some companies have started working on these expectations in a bid to retain talent. For example, Findability Sciences , an enterprise AI solution has trained over 100 of its data analysts and scientists across its Boston, India, and Japan operations with intensive training in problem formulation and prompt design and engineering skills. Findability Sciences Empowering our team with these new skills is a strategic move that will pay dividends for our clients and the company. The future of AI is generative, and we are now more than ready to take it head-on Mandar Kulkarni, AVP of Pre-sales Empowering our team with these new skills is a strategic move that will pay dividends for our clients and the company. The future of AI is generative, and we are now more than ready to take it head-on Empowering our team with these new skills is a strategic move that will pay dividends for our clients and the company. The future of AI is generative, and we are now more than ready to take it head-on Empowering our team with these new skills is a strategic move that will pay dividends for our clients and the company. The future of AI is generative, and we are now more than ready to take it head-on Mandar Kulkarni, AVP of Pre-sales Mandar Kulkarni, AVP of Pre-sales, said, “Empowering our team with these new skills is a strategic move that will pay dividends for our clients and the company. The future of AI is generative, and we are now more than ready to take it head-on.”?? The aim is to arm its team with the latest skills to cater to the evolving requirements of its existing and incoming customers in the generative AI arena. “This training is more than an investment in our team; it’s an investment in our clients,” says Anurag Srivastava, the Global Delivery Head. In a tech-driven business landscape, AI and machine learning expertise empower professionals to navigate disruption and contribute significantly to short-term viability and long-term success, hence its necessity as a skill is becoming inevitable. Every ecosystem has to pool in resources to meet the AI demand that will only go up in the future. Navanwita Sachdev, Editor, The Tech Panda Navanwita Sachdev, Editor, The Tech Panda Navanwita Sachdev, Navanwita Sachdev, Navanwita Sachdev, Editor, The Tech Panda

The Talent Quest: Companies' High Stakes in the AI Workforce Race

In my previous article, Managing Architectural Tech Debt, I talked about understanding and managing architectural technical debt. Architectural technical debt is the often ignored, but ironically, one of the most damaging, categories of technical debt. In this article, I want to dive deeper into one way to manage architectural technical debt (and technical debt as a whole)—architectural observability (AO). AO is a new category of observability that I believe is just as important, if not more so, as application performance management (APM). I believe we need to shift left observability—to the architectural stage—where we can not just see symptoms, but fix core problems. Let’s take a look. APM Is (Half) the Answer You already know that APM is important. Gartner defines it as “software that enables the observation and analysis of application health, performance and user experience.” And IDC reports that companies using APM solutions see a 2.5x improvement in mean time to resolution (MTTR) and a 50% reduction in the number of incidents. APM and observability: Helps to ensure better user experiences by monitoring, in real-time, performance and responsiveness.
Can help identify defects.
Can provide data to teams, such as usage patterns, bottlenecks, and overall health to keep systems healthy. Overall, APM has become a necessary tool for troubleshooting and fixing issues in enterprise environments. APM has become table stakes. And APM works! In my current role, we use APM to observe the usage of our APIs to understand the breakdown of URI (uniform resource identifier) requests across all of our consumers. When our APIs are not functioning as expected, we lean to APM in order to gain visibility into performance bottlenecks. In cases where an alert is triggered, the same interface can be utilized for initial troubleshooting efforts in order to help pin down the root cause. But even though APM works, there’s a problem. APM identifies the symptoms of the defects, but not the actual defects themselves. It’s up to the team to track down why the problems are occurring. And with the pressure we often feel in prod to “just fix the problem as fast as you can,” I often see that while symptoms may be addressed, teams don’t have the time (or organizational support) to find and fix the actual core problems. Imagine taking aspirin because you get a headache every night, but never taking the time to figure out why you keep having headaches. To find—and address—the why of our defects, we need architectural observability. Architectural Observability: Getting to the Real Answers We need to shift our processes left, stop focusing on symptoms, and instead focus on the root cause of these problems and actually reduce the number of incidents caught with APM. That’s where architectural observability comes in. Architectural observability is the ability to analyze an application’s architecture (both statically and dynamically), understand how it works, observe changes, and identify and fix architectural technical debt. Architectural observability is the next step in observability tools. Architectural observability gives you visibility into your application architecture, helping you solve problems (not just identify symptoms) earlier in the SDLC by identifying architectural issues. You probably already have the data you need to implement AO—it uses the same data sources as APM (for example, OpenTelemetry (OTel). But AO takes that data and applies a layer of intelligence that focuses on analyzing the architecture and the sources of architectural technical debt. For example, an AO tool might analyze: Architectural complexity - The interdependence and relationships of services within the architecture, the number of flows in a service, identifying multi-hop flows and circular flows. Dependency mappings - Relationships among services including circular dependencies. Architectural drift - What has changed since your last release, what new domains/services were added, what new dependencies and flows were introduced. Technical debt - Such as resource exclusivity, service dependencies, duplicate services that should be merged, and complexity. Technical debt is a huge problem in the industry. 70% of organizations say that technical debt is a major obstacle to innovation. Database-related issues - Examine if multiple services are accessing tables. Architectural observability is proactive and strategic. Where APM tools alert on the leaks in the roof when it is already raining, AO identifies architectural issues that can lead to those leaks, way before they actually occur. Using Tools to Gain Architectural Observability Used well, AO doesn’t just help you find issues earlier, but helps you: Truly discover and understand your architecture and its relationships and dependencies.
Prevent issues caused by architectural changes.
Make systems more resilient and scalable by continually monitoring, modernizing, and strengthening your architecture.
Minimize technical debt. I love that last one. As I pointed out in my last article, architectural debt is a foe of mine that I have been battling for over a decade. Architectural observability is a new field and is starting to gain traction as something teams must have. There aren’t many tools yet built around the concept, but let’s look at how your team might use one of the first AO tools—vFunction—to gain AO. Once you’ve connected to your applications (through the OTel connector or similar), the tool analyzes your system (in this case with vFunction, it’s using AI to understand and analyze your architecture). Then you get a report on the current state of your architecture. You’ll see details such as: A visualization of the architecture across your entire app portfolio
A map of services and entry points, cross services APIs, and external APIs
Exclusivity of database tables (Kafka, Redis, MongoDB) and other resources
Complexity scores
And more… And you can use architectural observability to monitor your architecture not just in the present state, but dynamically as it changes. Changes to your architecture (a.k.a., architectural drift)? You’ll know right away.
Add a dependency impacting resiliency? You’ll catch it before migrating.
Did you create a circular flow? Did you significantly increase the complexity of your system? Find out early. Incurring even more technical debt? You can’t hide from it now. With architectural observability, you now have hard proof of how architectural debt is affecting your systems and how, by using AO, you can identify and prioritize the actual problems in your systems early and often, rather than only addressing the symptoms in production. AO makes applications more resilient, more scalable, and helps your team move faster. And AO can help proactively. Is your team moving from a monolith to a microservice? AO can give you a plan to move your architecture forward. With AO, you could analyze your monolith, understand how its domains and functionality are structured and connected, and then get actionable steps on how to modularize and move the functionality to microservices. And once you have a distributed architecture (microservices or distributed monoliths), you’ll want to make sure your architecture doesn’t drift or get more complex to the point that things start to break, you lose control, and you have to slow down your engineering velocity. AO keeps your applications in check whether monolith or microservices. Architectural Observability Gives You Better Systems My readers may recall that I have been focused on the following mission statement, which I feel can apply to any IT professional: “Focus your time on delivering features/functionality that extends the value of your intellectual property. Leverage frameworks, products, and services for everything else.” - J. Vester Architectural observability adheres to my mission statement perfectly. By moving from plain vanilla observability to architectural observability, we can shift left for more reliable, more resilient, and better-performing systems. This shift affords us more time to spend on the business problems that our teams understand best. As John F. Kennedy once said: “The best time to repair the roof is when the sun is shining.” Architectural observability should be placed on the same level (or higher) as APM. With AO, teams can truly understand their architecture, have a broader and more insightful view of their applications than with APM alone, and fix problems earlier. Have a really great day! In my previous article, Managing Architectural Tech Debt , I talked about understanding and managing architectural technical debt. Architectural technical debt is the often ignored, but ironically, one of the most damaging , categories of technical debt. Managing Architectural Tech Debt architectural the most damaging In this article, I want to dive deeper into one way to manage architectural technical debt (and technical debt as a whole)— architectural observability (AO) . AO is a new category of observability that I believe is just as important, if not more so, as application performance management (APM). I believe we need to shift left observability—to the architectural stage—where we can not just see symptoms, but fix core problems. architectural observability (AO) Let’s take a look. APM Is (Half) the Answer You already know that APM is important. Gartner defines it as “software that enables the observation and analysis of application health, performance and user experience.” And IDC reports that companies using APM solutions see a 2.5x improvement in mean time to resolution (MTTR) and a 50% reduction in the number of incidents. IDC reports APM and observability: Helps to ensure better user experiences by monitoring, in real-time, performance and responsiveness. Can help identify defects. Can provide data to teams, such as usage patterns, bottlenecks, and overall health to keep systems healthy. Helps to ensure better user experiences by monitoring, in real-time, performance and responsiveness. Can help identify defects. Can provide data to teams, such as usage patterns, bottlenecks, and overall health to keep systems healthy. Overall, APM has become a necessary tool for troubleshooting and fixing issues in enterprise environments. APM has become table stakes. And APM works! In my current role, we use APM to observe the usage of our APIs to understand the breakdown of URI (uniform resource identifier) requests across all of our consumers. When our APIs are not functioning as expected, we lean to APM in order to gain visibility into performance bottlenecks. In cases where an alert is triggered, the same interface can be utilized for initial troubleshooting efforts in order to help pin down the root cause. But even though APM works, there’s a problem. APM identifies the symptoms of the defects, but not the actual defects themselves . It’s up to the team to track down why the problems are occurring. And with the pressure we often feel in prod to “just fix the problem as fast as you can,” I often see that while symptoms may be addressed, teams don’t have the time (or organizational support) to find and fix the actual core problems. but not the actual defects themselves why Imagine taking aspirin because you get a headache every night, but never taking the time to figure out why you keep having headaches. To find—and address—the why of our defects, we need architectural observability . why architectural observability Architectural Observability: Getting to the Real Answers We need to shift our processes left, stop focusing on symptoms, and instead focus on the root cause of these problems and actually reduce the number of incidents caught with APM. root cause of these problems That’s where architectural observability comes in. Architectural observability is the ability to analyze an application’s architecture (both statically and dynamically), understand how it works, observe changes, and identify and fix architectural technical debt. Architectural observability Architectural observability is the next step in observability tools. Architectural observability gives you visibility into your application architecture, helping you solve problems (not just identify symptoms) earlier in the SDLC by identifying architectural issues. You probably already have the data you need to implement AO—it uses the same data sources as APM (for example, OpenTelemetry (OTel). But AO takes that data and applies a layer of intelligence that focuses on analyzing the architecture and the sources of architectural technical debt. For example, an AO tool might analyze: Architectural complexity - The interdependence and relationships of services within the architecture, the number of flows in a service, identifying multi-hop flows and circular flows. Architectural complexity - The interdependence and relationships of services within the architecture, the number of flows in a service, identifying multi-hop flows and circular flows. Architectural complexity Dependency mappings - Relationships among services including circular dependencies. Dependency mappings - Relationships among services including circular dependencies. Dependency mappings Architectural drift - What has changed since your last release, what new domains/services were added, what new dependencies and flows were introduced. Architectural drift - What has changed since your last release, what new domains/services were added, what new dependencies and flows were introduced. Architectural drift Technical debt - Such as resource exclusivity, service dependencies, duplicate services that should be merged, and complexity. Technical debt is a huge problem in the industry. 70% of organizations say that technical debt is a major obstacle to innovation. Technical debt - Such as resource exclusivity, service dependencies, duplicate services that should be merged, and complexity. Technical debt is a huge problem in the industry. 70% of organizations say that technical debt is a major obstacle to innovation. Technical debt major obstacle to innovation. Database-related issues - Examine if multiple services are accessing tables. Database-related issues - Examine if multiple services are accessing tables. Database-related issues Architectural observability is proactive and strategic. Where APM tools alert on the leaks in the roof when it is already raining, AO identifies architectural issues that can lead to those leaks, way before they actually occur. Using Tools to Gain Architectural Observability Used well, AO doesn’t just help you find issues earlier, but helps you: Truly discover and understand your architecture and its relationships and dependencies. Prevent issues caused by architectural changes. Make systems more resilient and scalable by continually monitoring, modernizing, and strengthening your architecture. Minimize technical debt. Truly discover and understand your architecture and its relationships and dependencies. Prevent issues caused by architectural changes. Prevent Make systems more resilient and scalable by continually monitoring, modernizing, and strengthening your architecture. Minimize technical debt. I love that last one. As I pointed out in my last article , architectural debt is a foe of mine that I have been battling for over a decade. my last article Architectural observability is a new field and is starting to gain traction as something teams must have. There aren’t many tools yet built around the concept, but let’s look at how your team might use one of the first AO tools—vFunction—to gain AO. Once you’ve connected to your applications (through the OTel connector or similar), the tool analyzes your system (in this case with vFunction, it’s using AI to understand and analyze your architecture). Then you get a report on the current state of your architecture. You’ll see details such as: A visualization of the architecture across your entire app portfolio A map of services and entry points, cross services APIs, and external APIs Exclusivity of database tables (Kafka, Redis, MongoDB) and other resources Complexity scores And more… A visualization of the architecture across your entire app portfolio A map of services and entry points, cross services APIs, and external APIs Exclusivity of database tables (Kafka, Redis, MongoDB) and other resources Complexity scores And more… And you can use architectural observability to monitor your architecture not just in the present state, but dynamically as it changes. Changes to your architecture (a.k.a., architectural drift)? You’ll know right away. Add a dependency impacting resiliency? You’ll catch it before migrating. Did you create a circular flow? Did you significantly increase the complexity of your system? Find out early. Changes to your architecture (a.k.a., architectural drift)? You’ll know right away. Add a dependency impacting resiliency? You’ll catch it before migrating. Did you create a circular flow? Did you significantly increase the complexity of your system? Find out early. Incurring even more technical debt? You can’t hide from it now. more With architectural observability, you now have hard proof of how architectural debt is affecting your systems and how, by using AO, you can identify and prioritize the actual problems in your systems early and often, rather than only addressing the symptoms in production. AO makes applications more resilient, more scalable, and helps your team move faster. And AO can help proactively. Is your team moving from a monolith to a microservice? AO can give you a plan to move your architecture forward. With AO, you could analyze your monolith, understand how its domains and functionality are structured and connected, and then get actionable steps on how to modularize and move the functionality to microservices. And once you have a distributed architecture (microservices or distributed monoliths), you’ll want to make sure your architecture doesn’t drift or get more complex to the point that things start to break, you lose control, and you have to slow down your engineering velocity. AO keeps your applications in check whether monolith or microservices. Architectural Observability Gives You Better Systems My readers may recall that I have been focused on the following mission statement, which I feel can apply to any IT professional: “Focus your time on delivering features/functionality that extends the value of your intellectual property. Leverage frameworks, products, and services for everything else.” - J. Vester “Focus your time on delivering features/functionality that extends the value of your intellectual property. Leverage frameworks, products, and services for everything else.” - J. Vester Architectural observability adheres to my mission statement perfectly. By moving from plain vanilla observability to architectural observability , we can shift left for more reliable, more resilient, and better-performing systems. This shift affords us more time to spend on the business problems that our teams understand best. architectural observability As John F. Kennedy once said: “The best time to repair the roof is when the sun is shining.” Architectural observability should be placed on the same level (or higher) as APM. With AO, teams can truly understand their architecture, have a broader and more insightful view of their applications than with APM alone, and fix problems earlier. Have a really great day!

From Observability to Architectural Observability—Shifting Left for Resiliency

Republic, a blockchain technology firm focusing on financial investment into the web3 industry, has announced that its Republic Note dividend pool has surpassed $1 million. This milestone marks a significant step towards the company's goal of distributing dividends to Note holders. This achievement represents a significant step towards the company's goal of distributing dividends to Note holders and highlights the growing interest in alternative investment models. The Republic Note, launched as an innovative venture digital asset, offers investors exposure to a diversified portfolio of high-growth startups, blockchain projects, and established companies through a single investment. The dividend pool, which now exceeds $1 million, is a key feature of this digital asset. The Note dividend pool grows when Republic is able to sell eligible investments it has made for cash, and places a portion of them into an interest-bearing account dedicated to the Note. Once the Note dividend pool hits $2 million, dividends will be paid out to Note holders. This unique approach to dividend distribution sets the Republic Note apart in the digital asset landscape. Dividends will be paid in the form of USDC on the Avalanche token network to anyone holding Note tokens in their wallet when the $2 million threshold is crossed. While the $1 million milestone is significant, industry experts caution that it's still early days for the project. Republic's portfolio, which includes stakes in well-known companies such as SpaceX, Avalanche, Carta, and Gumroad, is designed with long-term growth in mind. The company has expressed optimism about the future growth of the dividend pool. Currently, the primary contributors to the Note's dividend pool are Republic's two main investment arms: U.S. Retail and Capital. As the company expands, it plans to diversify the sources of potential returns for Note holders, potentially accelerating the growth of the dividend pool. The Republic Note has attracted over $32 million from a global community of investors. Unlike traditional venture capital investments, it's accessible to investors regardless of net worth or accreditation status, subject to eligibility based on jurisdiction. The Note is available for trading on the INX platform, operating on a 24/7 basis. In addition to the potential financial benefits, Republic has been offering exclusive perks to Note holders. These include access to VC Files episodes featuring prominent figures like Ryan Hoover and Kamal Ravikant, special deals and offers, and even NFC-chipped merchandise. Republic, headquartered in New York City with operations across several countries, reports a community of over 3 million members who have collectively invested more than $2.6 billion in various private ventures. The company's ecosystem comprises an enterprise-focused Digital Merchant Bank and a retail-focused Global Marketplace. As the digital asset and alternative investment landscapes continue to evolve, initiatives like the Republic Note are drawing attention from both investors and industry observers. However, as with all investments, potential participants are advised to conduct thorough research and consider their risk tolerance before making financial decisions. The achievement of this $1 million milestone in the dividend pool marks an interesting chapter in the story of digital assets and alternative investments. As Republic continues to grow and develop its Note offering, many in the industry will be watching closely to see how this innovative model performs in the long term. Don’t forget to like and share the story! Vested Interest Disclosure: This author is an independent contributor publishing via our business blogging program. HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR. Republic , a blockchain technology firm focusing on financial investment into the web3 industry, has announced that its Republic Note dividend pool has surpassed $1 million. This milestone marks a significant step towards the company's goal of distributing dividends to Note holders. This achievement represents a significant step towards the company's goal of distributing dividends to Note holders and highlights the growing interest in alternative investment models. Republic The Republic Note, launched as an innovative venture digital asset, offers investors exposure to a diversified portfolio of high-growth startups, blockchain projects, and established companies through a single investment. The dividend pool, which now exceeds $1 million, is a key feature of this digital asset. The Note dividend pool grows when Republic is able to sell eligible investments it has made for cash, and places a portion of them into an interest-bearing account dedicated to the Note. Once the Note dividend pool hits $2 million, dividends will be paid out to Note holders. This unique approach to dividend distribution sets the Republic Note apart in the digital asset landscape. Dividends will be paid in the form of USDC on the Avalanche token network to anyone holding Note tokens in their wallet when the $2 million threshold is crossed. While the $1 million milestone is significant, industry experts caution that it's still early days for the project. Republic's portfolio, which includes stakes in well-known companies such as SpaceX, Avalanche, Carta, and Gumroad, is designed with long-term growth in mind. The company has expressed optimism about the future growth of the dividend pool. Currently, the primary contributors to the Note's dividend pool are Republic's two main investment arms: U.S. Retail and Capital. As the company expands, it plans to diversify the sources of potential returns for Note holders, potentially accelerating the growth of the dividend pool. The Republic Note has attracted over $32 million from a global community of investors. Unlike traditional venture capital investments, it's accessible to investors regardless of net worth or accreditation status, subject to eligibility based on jurisdiction. The Note is available for trading on the INX platform, operating on a 24/7 basis. In addition to the potential financial benefits, Republic has been offering exclusive perks to Note holders. These include access to VC Files episodes featuring prominent figures like Ryan Hoover and Kamal Ravikant, special deals and offers, and even NFC-chipped merchandise. Republic, headquartered in New York City with operations across several countries, reports a community of over 3 million members who have collectively invested more than $2.6 billion in various private ventures. The company's ecosystem comprises an enterprise-focused Digital Merchant Bank and a retail-focused Global Marketplace. As the digital asset and alternative investment landscapes continue to evolve, initiatives like the Republic Note are drawing attention from both investors and industry observers. However, as with all investments, potential participants are advised to conduct thorough research and consider their risk tolerance before making financial decisions. The achievement of this $1 million milestone in the dividend pool marks an interesting chapter in the story of digital assets and alternative investments. As Republic continues to grow and develop its Note offering, many in the industry will be watching closely to see how this innovative model performs in the long term. Don’t forget to like and share the story! Vested Interest Disclosure: This author is an independent contributor publishing via our business blogging program. HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR. Vested Interest Disclosure: This author is an independent contributor publishing via our business blogging program . HackerNoon has reviewed the report for quality, but the claims herein belong to the author. #DYOR. Vested Interest Disclosure: business blogging program business blogging program

Republic's Digital Asset Dividend Pool Reaches $1 Million Mark

প্রজাতন্ত্রের ডিজিটাল সম্পদ লভ্যাংশ পুল $1 মিলিয়ন চিহ্নে পৌঁছেছে

Der Dividendenpool für digitale Vermögenswerte von Republic erreicht die Marke von 1 Million US-Dollar

El fondo de dividendos de activos digitales de Republic alcanza la marca del millón de dólares

Le pool de dividendes d'actifs numériques de Republic atteint la barre des 1 million de dollars

रिपब्लिक का डिजिटल एसेट डिविडेंड पूल $1 मिलियन के आंकड़े तक पहुंचा

リパブリックのデジタル資産配当プールが100万ドルに到達

Republic의 디지털 자산 배당금 풀이 100만 달러에 도달

Pool de dividendos de ativos digitais da Republic atinge marca de US$ 1 milhão

Дивидендный пул цифровых активов Республики достиг отметки в 1 миллион долларов

Republic'in Dijital Varlık Temettü Havuzu 1 Milyon Dolara Ulaştı

Nhóm cổ tức tài sản kỹ thuật số của Cộng hòa đạt mốc 1 triệu USD

Republic 数字资产股息池达到 100 万美元

Golden Celestial Ratio (GCR): A Comprehensive Guide to the Divine Ecosystem

গোল্ডেন সেলেস্টিয়াল রেশিও (GCR): ডিভাইন ইকোসিস্টেমের একটি ব্যাপক নির্দেশিকা

Golden Celestial Ratio (GCR): Ein umfassender Leitfaden zum göttlichen Ökosystem

Proporción áurea celestial (GCR): una guía completa del ecosistema divino

Ratio Céleste Doré (GCR) : Un guide complet de l'écosystème divin

स्वर्णिम आकाशीय अनुपात (जीसीआर): दिव्य पारिस्थितिकी तंत्र के लिए एक व्यापक मार्गदर्शिका

黄金比（GCR）：神の生態系への総合ガイド

황금 천체 비율(GCR): 신성한 생태계에 대한 종합 가이드

Proporção Celestial Áurea (GCR): Um Guia Abrangente para o Ecossistema Divino

Золотое небесное сечение (GCR): подробное руководство по божественной экосистеме

Altın Gök Oranı (GCR): İlahi Ekosistem İçin Kapsamlı Bir Kılavuz

Tỷ lệ thiên thể vàng (GCR): Hướng dẫn toàn diện về hệ sinh thái thần thánh

黄金天体比例（GCR）：神圣生态系统的综合指南

Global startup funding has hit its lowest level in five years, according to Crunchbase. Rather than prioritizing rapid growth, founders are now concentrating on achieving profitability quickly. Merging traditional VC approaches with venture lending could provide a flexible solution for cash-strapped businesses, says Andrey Lebedev. As a venture partner at U.S.-based VC funds, such as Amadeo Global, he is working on ad-hoc financing strategies for innovative companies. Venture capital has become expensive for tech founders who don’t want to give away substantial equity, says Lebedev. “Also, high interest rates have made it more challenging for venture funds to invest in startups,” he added. Lebedev emphasizes a shift in focus for startups. “Tech companies are looking to diversify financing sources, including bank loans and fintech platforms,” he said. In Europe, for example, state programs provided around 60 billion euros in 2023 to tech founders. In contrast, venture-funded platforms are more prominent in the U.S. Another popular strategic tool – venture debt – supports sustainable growth and long-term success for startups and their investors. The Future of Venture Debt After SVB “SVB's failure in March 2023 raised concerns about the future of venture debt, a product SVB had championed,” Lebedev said. Venture debt is designed specifically for startups and high-growth companies that have already secured VC equity funding. It provides these companies with access to additional capital without diluting the ownership stakes of their founders and investors. “However, SVB's demise was not due to the inherent flaws of venture debt but rather it was a result of a classic bank run, exacerbated by the high concentration of its customer base in startups and VC funds,” Lebedev noted. Despite this setback, venture debt remains a compelling and vital financing tool for startups.” Typically, venture debt is used to extend the runway between equity rounds, finance capital expenditures, or provide a buffer during periods of uncertainty. Despite SVB’s collapse, the fundamental advantages of venture debt remain intact. The demand for non-dilutive capital solutions continues to grow, driven by startups' need for flexible financing options that support their growth without compromising ownership and control. “As the market evolves, we can expect increased diversification, innovation, and risk management to further bolster the appeal of venture debt,” Lebedev said. Moreover, other financial institutions and specialized venture debt providers are well-positioned to fill the void left by SVB. The Hybrid Model: A New Approach Amadeo’s hybrid venture-credit model combines venture debt with mezzanine financing. This approach allows for shorter investment horizons (2-3 years) compared to traditional venture capital (5-7 years), and with similar return expectations. “Mezzanine financing and debt financing options, including securitization via options, provide control over loan repayment and offer a more attractive proposition for startups and investors alike,” Lebedev said. Similar investment firms use the DSE (Deposit, Account, Control) system, which facilitates automatic loan repayments by debiting money from a company's account upon receipt.  While this system is relatively new to the U.S., similar mechanisms have long been in use globally, says Lebedev. He compares the U.S. venture financing environment with Europe’s. “Advanced payment systems and financial discipline offer unique advantages to investors,” he said. “In the U.S., credit ratings and reputational risks play a significant role in business development, making the hybrid venture-credit model more appealing as it provides a structured approach to funding.” The Evolution of Venture Financing Lebedev believes that the hybrid venture-credit model is the future of startup investment. “This model effectively addresses the need for flexible funding and rapid business expansion, without significant equity dilution for founders,” he said. As technology advances and AI-driven financial analysis becomes more prevalent, funds that adopt these innovative practices gain a competitive edge. SVB’s collapse precipitated a wave of innovation and new entrants into the venture debt space. New players are often more agile and better equipped to understand the unique needs of startups, providing customized solutions that can offer even greater value. “Amadeo’s hybrid venture-credit model offers a compelling alternative to traditional venture capital, providing flexible and growth-oriented funding solutions,” Lebedev added. This innovative approach has the potential to steer the evolution of venture financing, more effectively catering to the needs of startups and small businesses in a tough economic environment. Global startup funding has hit its lowest level in five years, according to Crunchbase. Rather than prioritizing rapid growth, founders are now concentrating on achieving profitability quickly. Global startup funding has hit its lowest level in five years, according to Crunchbase. Rather than prioritizing rapid growth, founders are now concentrating on achieving profitability quickly. Global startup funding has hit its lowest level in five years, according to Crunchbase . Rather than prioritizing rapid growth, founders are now concentrating on achieving profitability quickly. according to Crunchbase according to Crunchbase Merging traditional VC approaches with venture lending could provide a flexible solution for cash-strapped businesses, says Andrey Lebedev. As a venture partner at U.S.-based VC funds, such as Amadeo Global, he is working on ad-hoc financing strategies for innovative companies. Venture capital has become expensive for tech founders who don’t want to give away substantial equity, says Lebedev. “Also, high interest rates have made it more challenging for venture funds to invest in startups,” he added. Lebedev emphasizes a shift in focus for startups. “Tech companies are looking to diversify financing sources, including bank loans and fintech platforms,” he said. In Europe, for example, state programs provided around 60 billion euros in 2023 to tech founders. In contrast, venture-funded platforms are more prominent in the U.S. Another popular strategic tool – venture debt – supports sustainable growth and long-term success for startups and their investors. The Future of Venture Debt After SVB The Future of Venture Debt After SVB “SVB's failure in March 2023 raised concerns about the future of venture debt, a product SVB had championed,” Lebedev said. Venture debt is designed specifically for startups and high-growth companies that have already secured VC equity funding. It provides these companies with access to additional capital without diluting the ownership stakes of their founders and investors. “However, SVB's demise was not due to the inherent flaws of venture debt but rather it was a result of a classic bank run, exacerbated by the high concentration of its customer base in startups and VC funds,” Lebedev noted. Despite this setback, venture debt remains a compelling and vital financing tool for startups.” Typically, venture debt is used to extend the runway between equity rounds, finance capital expenditures, or provide a buffer during periods of uncertainty. Despite SVB’s collapse, the fundamental advantages of venture debt remain intact. The demand for non-dilutive capital solutions continues to grow, driven by startups' need for flexible financing options that support their growth without compromising ownership and control. “As the market evolves, we can expect increased diversification, innovation, and risk management to further bolster the appeal of venture debt,” Lebedev said. Moreover, other financial institutions and specialized venture debt providers are well-positioned to fill the void left by SVB. The Hybrid Model: A New Approach The Hybrid Model: A New Approach Amadeo’s hybrid venture-credit model combines venture debt with mezzanine financing. This approach allows for shorter investment horizons (2-3 years) compared to traditional venture capital (5-7 years), and with similar return expectations. “Mezzanine financing and debt financing options, including securitization via options, provide control over loan repayment and offer a more attractive proposition for startups and investors alike,” Lebedev said. Similar investment firms use the DSE (Deposit, Account, Control) system, which facilitates automatic loan repayments by debiting money from a company's account upon receipt.  While this system is relatively new to the U.S., similar mechanisms have long been in use globally, says Lebedev. He compares the U.S. venture financing environment with Europe’s. “Advanced payment systems and financial discipline offer unique advantages to investors,” he said. “In the U.S., credit ratings and reputational risks play a significant role in business development, making the hybrid venture-credit model more appealing as it provides a structured approach to funding.” The Evolution of Venture Financing The Evolution of Venture Financing Lebedev believes that the hybrid venture-credit model is the future of startup investment. “This model effectively addresses the need for flexible funding and rapid business expansion, without significant equity dilution for founders,” he said. As technology advances and AI-driven financial analysis becomes more prevalent, funds that adopt these innovative practices gain a competitive edge. SVB’s collapse precipitated a wave of innovation and new entrants into the venture debt space. New players are often more agile and better equipped to understand the unique needs of startups, providing customized solutions that can offer even greater value. “Amadeo’s hybrid venture-credit model offers a compelling alternative to traditional venture capital, providing flexible and growth-oriented funding solutions,” Lebedev added. This innovative approach has the potential to steer the evolution of venture financing, more effectively catering to the needs of startups and small businesses in a tough economic environment.

Shaping the Future of Startup Funding With a New Hybrid Venture-Credit Model

একটি নতুন হাইব্রিড ভেঞ্চার-ক্রেডিট মডেলের মাধ্যমে স্টার্টআপ ফান্ডিং এর ভবিষ্যত গঠন করা

Die Zukunft der Startup-Finanzierung mit einem neuen hybriden Venture-Credit-Modell gestalten

Dando forma al futuro de la financiación inicial con un nuevo modelo híbrido de riesgo y crédito

Façonner l’avenir du financement des startups avec un nouveau modèle hybride de crédit-risque

नए हाइब्रिड वेंचर-क्रेडिट मॉडल के साथ स्टार्टअप फंडिंग के भविष्य को आकार देना

新しいハイブリッドベンチャークレジットモデルでスタートアップ資金調達の未来を形作る

새로운 하이브리드 벤처-신용 모델로 스타트업 자금 조달의 미래 형성

Moldando o futuro do financiamento de startups com um novo modelo híbrido de crédito de risco

Формирование будущего финансирования стартапов с помощью новой гибридной модели венчурного кредитования

Yeni Hibrit Girişim-Kredi Modeli ile Startup Finansmanının Geleceğini Şekillendirmek

Định hình tương lai của nguồn tài trợ khởi nghiệp với mô hình tín dụng mạo hiểm kết hợp mới

通过新的混合风险信贷模式塑造初创企业融资的未来

Defusing Emotionally Charged Conversations: 4 Steps to Success

The Snowflake Hack and Its Domino Effect

স্নোফ্লেক হ্যাক এবং এর ডমিনো প্রভাব

Der Snowflake-Hack und sein Dominoeffekt

El truco del copo de nieve y su efecto dominó

Le Snowflake Hack et son effet domino

स्नोफ्लेक हैक और इसका डोमिनो प्रभाव

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