"Crowd Cloud" Brings Asia-Pacific Emerging Markets into the Cloud

Asaf Zamir

Asia-Pacific is at the forefront of the cloud revolution. According to the Cisco Global Cloud Index: Forecast and Methodology, 2015 – 2020, Asia Pacific is projected to generate 1.5 zettabytes of cloud traffic, or a trillion gigabytes. To put it into perspective, that’s equivalent to about 375 billion DVDs. Yet while developed APAC countries, such as Hong Kong and Singapore, are leading the way in cloud adoption, emerging markets in the region are trailing behind. The decentralized cloud – or the "Crowd Cloud" – will bring these markets into the 21st century by making the cloud accessible to all.

Growth of the Cloud in Asia-Pacific

Asia-Pacific is the fastest growing region in terms of hyperscale data center locations, and is expected to grow more rapidly over the next five years. Alibaba, the Chinese e-commerce company, announced its plans this year to open two more data centers in the region – one in Malaysia and another in Singapore. Meanwhile, Microsoft Asia Pacific has recorded triple-digit growth year-on-year for Azure in the first 10 months of 2016, providing cloud services to everything from IoT systems to monitor oyster farms to patient records for healthcare providers.

However, the very nature of centralized cloud services stymies growth in the cloud. These data centers are slow to build and costly to run. They are also vulnerable to cyber attacks, system failures and power outages. While Singapore and Hong Kong have made significant investments in the necessary cables, power and broadband for supporting the cloud, emerging APAC countries often lack the necessary infrastructure investment to support the cloud. For businesses, disruptions caused by systems failures can be costly; a recent outage of one of the largest cloud service providers in the US paralyzed a number of cloud-dependent businesses and cost S&P 500 companies $150 million USD.

The lack of competition between hyperscale cloud providers also means that costs are unnaturally high. The top 24 "hyperscale" companies operate over 300 data centers across the world, and account for almost 60 percent of cloud-hosted software services. By mid-2018, operational expenditure for cloud services will account for 80 percent of company’s IT budgets, according to Intel Security. This prices many businesses out of the cloud economy.

Crowd Cloud in an Emerging Market

The traditional model of centralized cloud services provided by a few hyperscale providers is outdated. To keep pace in the internet-based economy, Asia-Pacific emerging markets need to adopt a new model for the cloud: the "Crowd Cloud." Rather than storing and processing data in a centralized data center, the Crowd Cloud harnesses the unused processing power and data storage from millions of home and office computers worldwide. This will solve many of the issues in cloud scalability in Asia-Pacific emerging markets by bypassing the need for significant infrastructure investment in data centers, and creating a more secure and stable cloud network.

While there are already a number of decentralized solutions out there, these only provide solutions for a single vertical within the cloud – storage, computing (CPU), bandwidth, applications or payments – aimed towards niche markets, such as 3D graphics rendering or scientific research. Until now, there has not been a fully-integrated decentralized cloud service solution. The solution to this is through a decentralized infrastructure that utilizes a blockchain-based gateway to integrate between all these cloud components.

Within a new decentralized cloud ecosystem, it is necessary to have a standard cryptocurrency based on blockchain-Ethereum to govern exchanges automatically. By creating a running receipt of the cloud services used, it will enable the clearing and distributing of payments to Crowd Cloud providers. This could still include big players like Amazon Web Services, Microsoft Azure and Google Cloud, alongside individual – anyone who is a part of the Crowd Cloud.

The introduction of decentralized cloud services will revolutionize how emerging markets access the cloud. Rather than relying on infrastructure which is slow, costly to build and prone to failure, the Crowd Cloud will provide instant access to high-power computer processing (CPU), data storage and other cloud services. This will ensure that these emerging markets are not left by the wayside as demand for online services continues to grow in Asia-Pacific.

Related Links

Hot Topics

The Latest

Keys to Building a Partner Ecosystem That Scales

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

How AI Agents Are Reshaping DataOps for the Always-On Enterprise

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

AI Deepfakes: Rethinking Trust in the Workplace

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Nine in Ten Enterprises Plan Cloud Data Repatriation amid Rising Cloud Costs and Data Sovereignty Mandates

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Why ITOps Need Right-Sized AI, Not Bigger Models

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

The End of Reactive DevOps: AI-Driven Observability for Zero-Defect Digital Systems

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

5 Takeaways from the Observability Forecast for Media and Entertainment

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Why Moving Off the Cloud Is the Easy Part and What Comes Next Is Where Things Get Hard

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

MEAN TIME TO INSIGHT Podcast - Episode 24: Network Observability Tool Sprawl

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

Capacity Isn't a Guess: Observability-Driven Sizing for On-Prem Databases

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...

"Crowd Cloud" Brings Asia-Pacific Emerging Markets into the Cloud

Asaf Zamir

Asia-Pacific is at the forefront of the cloud revolution. According to the Cisco Global Cloud Index: Forecast and Methodology, 2015 – 2020, Asia Pacific is projected to generate 1.5 zettabytes of cloud traffic, or a trillion gigabytes. To put it into perspective, that’s equivalent to about 375 billion DVDs. Yet while developed APAC countries, such as Hong Kong and Singapore, are leading the way in cloud adoption, emerging markets in the region are trailing behind. The decentralized cloud – or the "Crowd Cloud" – will bring these markets into the 21st century by making the cloud accessible to all.

Growth of the Cloud in Asia-Pacific

Asia-Pacific is the fastest growing region in terms of hyperscale data center locations, and is expected to grow more rapidly over the next five years. Alibaba, the Chinese e-commerce company, announced its plans this year to open two more data centers in the region – one in Malaysia and another in Singapore. Meanwhile, Microsoft Asia Pacific has recorded triple-digit growth year-on-year for Azure in the first 10 months of 2016, providing cloud services to everything from IoT systems to monitor oyster farms to patient records for healthcare providers.

However, the very nature of centralized cloud services stymies growth in the cloud. These data centers are slow to build and costly to run. They are also vulnerable to cyber attacks, system failures and power outages. While Singapore and Hong Kong have made significant investments in the necessary cables, power and broadband for supporting the cloud, emerging APAC countries often lack the necessary infrastructure investment to support the cloud. For businesses, disruptions caused by systems failures can be costly; a recent outage of one of the largest cloud service providers in the US paralyzed a number of cloud-dependent businesses and cost S&P 500 companies $150 million USD.

The lack of competition between hyperscale cloud providers also means that costs are unnaturally high. The top 24 "hyperscale" companies operate over 300 data centers across the world, and account for almost 60 percent of cloud-hosted software services. By mid-2018, operational expenditure for cloud services will account for 80 percent of company’s IT budgets, according to Intel Security. This prices many businesses out of the cloud economy.

Crowd Cloud in an Emerging Market

The traditional model of centralized cloud services provided by a few hyperscale providers is outdated. To keep pace in the internet-based economy, Asia-Pacific emerging markets need to adopt a new model for the cloud: the "Crowd Cloud." Rather than storing and processing data in a centralized data center, the Crowd Cloud harnesses the unused processing power and data storage from millions of home and office computers worldwide. This will solve many of the issues in cloud scalability in Asia-Pacific emerging markets by bypassing the need for significant infrastructure investment in data centers, and creating a more secure and stable cloud network.

While there are already a number of decentralized solutions out there, these only provide solutions for a single vertical within the cloud – storage, computing (CPU), bandwidth, applications or payments – aimed towards niche markets, such as 3D graphics rendering or scientific research. Until now, there has not been a fully-integrated decentralized cloud service solution. The solution to this is through a decentralized infrastructure that utilizes a blockchain-based gateway to integrate between all these cloud components.

Within a new decentralized cloud ecosystem, it is necessary to have a standard cryptocurrency based on blockchain-Ethereum to govern exchanges automatically. By creating a running receipt of the cloud services used, it will enable the clearing and distributing of payments to Crowd Cloud providers. This could still include big players like Amazon Web Services, Microsoft Azure and Google Cloud, alongside individual – anyone who is a part of the Crowd Cloud.

The introduction of decentralized cloud services will revolutionize how emerging markets access the cloud. Rather than relying on infrastructure which is slow, costly to build and prone to failure, the Crowd Cloud will provide instant access to high-power computer processing (CPU), data storage and other cloud services. This will ensure that these emerging markets are not left by the wayside as demand for online services continues to grow in Asia-Pacific.

Related Links

Hot Topics

The Latest

Keys to Building a Partner Ecosystem That Scales

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

How AI Agents Are Reshaping DataOps for the Always-On Enterprise

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

AI Deepfakes: Rethinking Trust in the Workplace

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Nine in Ten Enterprises Plan Cloud Data Repatriation amid Rising Cloud Costs and Data Sovereignty Mandates

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Why ITOps Need Right-Sized AI, Not Bigger Models

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

The End of Reactive DevOps: AI-Driven Observability for Zero-Defect Digital Systems

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

5 Takeaways from the Observability Forecast for Media and Entertainment

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Why Moving Off the Cloud Is the Easy Part and What Comes Next Is Where Things Get Hard

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

MEAN TIME TO INSIGHT Podcast - Episode 24: Network Observability Tool Sprawl

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

Capacity Isn't a Guess: Observability-Driven Sizing for On-Prem Databases

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...