29 March 2026 9:54 am
AWS Bahrain Disruption Exposes Cloud Fragility Today

AWS Bahrain Disruption Exposes Cloud Fragility Today

Mar 27, 2026

Bahrain, trade center, skyscraper, Manama, Bahrain World Trade Centre, City, WTC, Bahrain, Manama  by IrinaKar via pixabay

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AWS Bahrain Disruption Exposes Cloud Fragility: What this Means for Middle East’s Cloud Infrastructure

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The disruption has prompted enterprises to reassess cloud resilience strategies amid rising geopolitical risks, highlighting vulnerabilities in infrastructure reliance.

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By Pavneet Kaur –

Adrone-related AWS outage in Bahrain is forcing enterprises to rethink cloud resilience, multi-region strategy and infrastructure risk across the Middle East.

The recent AWS disruption, triggered by drone activity near critical infrastructure, has disrupted services and pushed enterprises to shift workloads across regions. For many organisations, this is a stark reminder that cloud computing infrastructure is still deeply physical.

In an official statement to ITP.NET, AWS ensured that the team is working with authorities, while securing their personnel and empowering affected customers with migration efforts.

“The AWS Bahrain Region has been disrupted as a result of the ongoing conflict. We are working closely with local authorities and prioritizing the safety of our personnel throughout our recovery efforts. We continue to support affected customers, helping them to migrate to alternate AWS Regions, with a large number already successfully operating their applications from other parts of the world. As this situation evolves and, as we have advised before, we request those with workloads in the affected regions continue to migrate to other locations.”

Behind every cloud platform are data centres tied to specific geographies, dependent on power, connectivity and regional stability. When a Bahrain data centre disruption occurs, the impact extends far beyond a single facility, affecting applications, platforms and users across the region.

Cloud disruption in the Middle East is a concentration problem

The bigger issue exposed by this AWS cloud disruption is not downtime, but infrastructure concentration risk. Across the Middle East cloud market, many enterprises rely heavily on a single hyperscaler or a single region, particularly AWS Bahrain, which has become a core hub for startups, fintech platforms and government workloads.

This centralisation improves efficiency and latency. It also creates a single point of failure.

When a cloud outage in Bahrain happens, multiple organisations face simultaneous disruption, highlighting the risks of over-reliance on a single cloud region.

Geopolitical risk is now a cloud computing risk

Unlike typical outages caused by software failures or power issues, this AWS outage in Bahrain was linked to regional instability.

That shifts the conversation. For CIOs and IT leaders, geopolitical risk is now directly tied to cloud infrastructure strategy. As the Middle East accelerates investments in AI, digital services and cloud adoption, physical threats to infrastructure are becoming part of the risk landscape.

“The lesson is straightforward: enterprises must diversify both geographically and across providers,” says Dmitrii Gartung, CEO, OneSun Capital – an eco-conscious industrial robotics and automation software provider.

Distributing your nodes across multiple countries is only half the strategy — if all those nodes sit within the same cloud ecosystem, a platform-level failure can take everything down simultaneously. The practical steps for CIOs are clear. First, implement true multi-cloud architecture — not just multi-region within one provider, but across independent providers. Second, consider supporting smaller, independent data centre operators rather than concentrating everything with hyperscalers. Large cloud providers are obvious high-value targets; smaller operators present a lower risk profile. Third, invest in high-availability cluster design with geographic distribution built in from the start, not bolted on as an afterthought.

Over-reliance on a single cloud region or provider is, frankly, a sign of taking shortcuts during deployment. Convenience should never come at the cost of resilience — especially in a region where infrastructure risks are real and evolving.”

Cloud strategy can no longer focus only on cost, scalability and performance. It must now account for regional security risks, infrastructure exposure and operational continuity.

Levent Ergin, Chief Strategist for Agentic AI, Regulatory Compliance & Sustainability at Informatica from Salesforce also adds to this:

Resilience is a shared responsibility, and in practice, failover, recovery, and validation sit firmly with the customer.

The immediate step for CIOs is to revisit how resilience is defined and operationalised within their organisations. This starts with making SLAs more explicit about shared responsibility and ensuring they go beyond infrastructure uptime to prioritise data integrity, portability, and recoverability.

Equally important is moving from static SLAs to actively tested ones. Defining recovery objectives on paper is not enough; organisations need to regularly test failover and recovery scenarios under real-world conditions to ensure they actually work when needed.

Cloud resilience depends on architecture, not just providers

Hyperscalers like AWS are built with redundancy, but enterprise cloud resilience depends on how systems are designed. Many organisations still operate on a single-region cloud deployment model, assuming uptime rather than engineering for failure. Best practices like multi-region cloud deployment, disaster recovery planning and multi-cloud strategy are often discussed, but not always implemented due to cost or complexity.

The Bahrain disruption highlights a critical gap.

When systems are not designed for failover, cloud migration becomes reactive instead of seamless, increasing downtime and operational risk.

From cloud-first to resilience-first strategy

The AWS Bahrain disruption signals a broader shift in enterprise thinking. The next phase of digital transformation in the region will move from cloud-first to resilience-first.

This includes:

  • Adopting multi-region cloud architecture to avoid regional outages
  • Exploring multi-cloud strategies to reduce vendor concentration risk
  • Strengthening disaster recovery and business continuity planning
  • Mapping dependencies across cloud, SaaS and third-party services

Echoing these observations is Santiago Pontiroli, Lead TRU Researcher at Acronis:

Multi-availability and multi-region architectures improve resilience, but only if they are deliberately designed. The main benefit is that data can survive localized failures. Cloud providers replicate across zones and regions, so loss of data is rarely the issue. The challenge is that availability of data does not automatically translate into availability of operations. If dependencies such as identity systems, control planes, or application layers are not designed to fail over, the business can still be disrupted even when the data is intact.

There is also a trade-off between resilience and complexity. Multi-region setups require planning around replication, consistency, failover logic, and cost. In many environments, replication is not fully implemented because of cost or operational overhead, which limits the actual resilience achieved.

Another factor is recovery time. Moving workloads between regions is technically feasible, but it is not always immediate. If replication is not already in place, migration can introduce downtime and operational friction. In practice, the benefit is clear: higher resilience. But the drawback is equally clear: without proper architecture, multi-region becomes an assumption of safety rather than a guarantee.

For governments and regulated industries in the Middle East, this is already driving conversations around sovereign cloud and data localisation.

For enterprises, it is quickly becoming a priority.

The bigger takeaway for Middle East enterprises

The AWS outage in Bahrain will likely be resolved without long-term impact.

But its significance lies elsewhere. It exposes how fragile cloud infrastructure can become when physical, regional and geopolitical risks intersect. The cloud remains powerful, scalable and essential.

Ergin puts it directly, “What this situation underscores is the need for a fundamental shift in mindset. Resilience can no longer be viewed purely through the lens of protecting against infrastructure-level failures, whether that’s power, networking, or even regional or geopolitical disruption. Instead, the focus needs to move towards ensuring that data itself can be reliably replicated and recovered, using metadata, lineage, and robust integration pipelines to maintain a strong recovery posture.”

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Pavneet Kaur

Pavneet is the Editor of ITP.NET, where she leads content strategy and writes across its five brands. A technology writer by choice and passion, she breaks down complex trends in AI, cybersecurity, cloud,… 

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AI and Jobs in the Emerging and Developing Countries

AI and Jobs in the Emerging and Developing Countries

Mar 26, 2026

Artificial intelligence is poised to be a major economic catalyst in the MENA region’s emerging and developing economies, with the potential to add $320 billion to the region’s economy by 2030.  However, this digital transformation presents a double-edged threat.  ERF

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AI and Jobs in the Emerging and Developing Countries

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What if artificial intelligence could become the most powerful driver of inclusive growth and job creation across emerging markets? Our latest report by Jeffrey D. Sachs, University Professor and Director of the Center for Sustainable Development, Columbia University outlines how artificial intelligence is redefining economic growth and job creation across emerging markets and developing economies.  […]
PUBLISHED BY FII Institute – March 24, 2026

Download Publication

What if artificial intelligence could become the most powerful driver of inclusive growth and job creation across emerging markets?

Our latest report by Jeffrey D. Sachs, University Professor and Director of the Center for Sustainable Development, Columbia University outlines how artificial intelligence is redefining economic growth and job creation across emerging markets and developing economies (EMDEs), replacing outdated labor-intensive manufacturing models with a dynamic, AI-powered framework driven by productivity, skills, and service-sector expansion. The analysis reveals how AI can unlock trillions in value by boosting export competitiveness in agriculture, mining, and manufacturing while simultaneously fueling large-scale employment in healthcare, education, construction, tourism, and the rapidly growing creative economy. With a strong focus on human capital, smart urbanization, and innovative financing models such as education bonds and diaspora contributions, the report presents a bold, future-ready blueprint for inclusive and sustainable development, positioning AI not as a disruptor, but as a catalyst for long-term prosperity and global economic transformation.

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Prototype Driverless Taxi Unveiled in Astana Event

Prototype Driverless Taxi Unveiled in Astana Event

Mar 26, 2026

Astana cityscape featuring the iconic Bayterek Tower and modern architecture under cloudy skies. by Valeria Drozdova via pexels

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Prototype Driverless Taxi Unveiled in Astana

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@gov.kz

As part of the Nauryz celebrations in Astana, a demonstration run of a driverless vehicle developed at the Daulet Serikbayev East Kazakhstan Technical University (EKTU) was held. In the future, this prototype could become part of the city’s driverless taxi system.

The presentation took the form of a public demonstration for residents and visitors to Kazakhstan’s capital. According to the Astana City Administration, the vehicle’s software and test route were developed by specialists from the Luban Workshop, which opened at EKTU in Ust-Kamenogorsk in late 2023 with support from China’s Tianjin Vocational Institute.

The project is being implemented as part of an initiative to develop engineering competencies and introduce new technologies, ranging from alternative fuels to AI systems in the transport sector.

At the same time, an agreement was signed to establish the Kazakhstan Engineering Center for the Application and Development of Intelligent Automotive Technologies.

The demonstration run was organised by the Ministry of Artificial Intelligence and Digital Development in collaboration with the capital’s city administration and the IT company Astana Innovations.

The test took place at one of the city’s festive venues. Visitors were able to observe the autonomous vehicle in real time and assess its potential for use in an urban environment.

According to the organisers, the prototype demonstrated the potential for integrating AI technologies into Smart City systems, including navigation, data processing, and interaction with infrastructure.

Authorities view driverless transport as one of the key areas in the development of urban mobility. In the future, such solutions may be integrated into Astana’s infrastructure, including the launch of autonomous taxis.

 

It was previously reported that Kazakhstan plans to launch pilot projects for driverless taxis in the capital as early as 2026.

At the same time, work is under way to prepare road infrastructure. Digital “passports” for highways are being developed, which are expected to enable the future use of driverless trucks.

Dmitry PokidaevDmitry Pokidaev
Generative AI-Powered Forecasting for Urban Growth

Generative AI-Powered Forecasting for Urban Growth

Mar 25, 2026

Aerial view of wind turbines in a vast desert landscape under a clear blue sky. by Kelly via pexels

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Generative AI-powered forecasting for sustainable urban development

 

by Japan Advanced Institute of Science and Technology

edited by Sadie Harley, reviewed by Robert Egan

construction site

Researchers introduce a novel generative AI-driven framework, MMCN (Memory-aware Multi-Conditional generation Network), for forecasting future urban layouts by jointly considering building density, building height, transportation networks, and historical development patterns.

Leveraging a generative architecture-enhanced diffusion model with multi-conditional control, semantic prompt fusion, and spatial memory embedding, MMCN offers a novel approach to modeling complex urban evolution. This framework provides a powerful tool to explore sustainable urban development, demonstrating AI’s transformative potential in urban design.

Environmental sustainability in urbanization has become a critical global concern as cities expand at unprecedented rates. Urban design faces the challenge of making long-term decisions about infrastructure, building development, transportation networks, and land use, all of which shape the future structure and sustainability of cities.

These decisions are inherently complex, as urban growth emerges from the interaction of multiple factors, including building density, building height, road networks, and historical development patterns, which evolve together over time. Traditional urban design methods often struggle to capture these interconnected dynamics, making accurate forecasting of urban development impossible.

In response to this challenge, artificial intelligence (AI) has emerged as a promising tool for modeling complex spatial patterns and supporting data-driven urban planning. Yet, many existing generative AI-based models produce fragmented predictions because they may have difficulty effectively integrating multiple urban development factors or maintaining spatial continuity across large areas.

To address these limitations, researchers at the Japan Advanced Institute of Science and Technology (JAIST) and Waseda University, Japan, developed a novel AI-driven framework called the Memory-aware Multi-Conditional generation Network (MMCN).

The research team was led by Associate Professor Haoran Xie (JAIST and Waseda University) and included Doctoral Student Xusheng Du from JAIST and Professor Zhen Xu from Tianjin University, China, among others.

Their study was published in Sustainable Cities and Society.

Explaining the motivation behind the study, Dr. Xie said, “We aimed to bridge the gap between current AI capabilities and the practical needs of urban planners by developing a predictive model capable of forecasting future urban layouts while simultaneously considering multiple urban development factors and historical evolution patterns, as inspired by the actual decision-making workflow from professional planners.”

The MMCN model relies on multi-temporal spatial data, including building layouts, building density, building height, and transportation networks, which were standardized into 512 × 512-pixel patches for model training. In particular, this model adopted the urban layout data of Shenzhen due to it being the most rapidly developing city in China.

The network architecture combines a diffusion model with a multi-conditional control mechanism, allowing diverse urban factors to guide the generation process. A semantic prompt fusion module encodes information from each input type, while a spatial memory embedding component preserves contextual information from neighboring regions, ensuring continuity across patches.

Multiple conditional generation branches integrated with the diffusion model form the core generative model, enabling the production of realistic, coherent urban layouts that remain consistent with historical patterns.

Data training uses denoising and edge-stitching loss functions to enhance reconstruction accuracy and smooth transitions across patch boundaries. This approach allows MMCN to model complex interactions among urban variables and generate spatially consistent forecasts of urban development.

Experimental results demonstrated the framework’s effectiveness. MMCN outperformed baseline methods such as Pix2Pix, CycleGAN, and Instruct-Pix2Pix, achieving a Structural Similarity Index (SSIM) of 0.885 and a Boundary Intersection over Union (IoU) of 0.642, indicating strong structural fidelity and spatial continuity.

Qualitative analysis further confirmed that MMCN generates realistic, coherent urban layouts with continuous road networks and well-organized building clusters, whereas baseline models often produce fragmented roads, duplicated structures, or disconnected patterns.

These findings highlight the importance of combining multi-factor conditioning, spatial memory mechanisms, and learning from historical patterns within a unified generative framework. Additional cross-city experiments using data from Shanghai and Tianjin in China further demonstrated the model’s ability to produce stable and consistent urban layout predictions under diverse spatial conditions.

Beyond technical performance, MMCN offers practical benefits for urban design. By simulating potential growth scenarios, the framework allows planners to evaluate the long-term consequences of development strategies, supporting more informed and sustainable decisions. This aligns with the Sustainable Development Goals, particularly those focused on creating resilient and inclusive cities.

Looking ahead, the researchers envision several enhancements. Integrating climate models could enable assessment of environmental impacts, while including socio-economic data, could support more comprehensive forecasts.

“Interactive planning tools built on MMCN could facilitate community and stakeholder engagement in urban design, promoting collaborative planning,” said Dr. Xie. He added, “Expanding the dataset to include cities with diverse morphologies would improve the model’s generalizability, making it applicable across different urban contexts worldwide.”

In conclusion, MMCN represents a significant advancement in AI-assisted urban design, offering a novel approach to forecasting urban layout evolution by integrating multiple spatial factors and historical patterns.

By producing accurate, spatially coherent predictions, it provides a powerful tool for guiding cities toward more resilient, livable, and sustainable futures in an increasingly urbanized world.

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More information

Xusheng Du et al, AI-driven urban evolution forecasting: A unified memory-aware multi-conditional generation framework for sustainable development planning, Sustainable Cities and Society (2026). DOI: 10.1016/j.scs.2026.107272

Key concepts

Machine learning methodologies  AI in built environment

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Provided by Japan Advanced Institute of Science and Technology
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World Engineering Day for Sustainable Development 2026

World Engineering Day for Sustainable Development 2026

Mar 25, 2026

Scientist in lab coat handling samples in a research facility, focusing on sustainable practices. by ThisIsEngineering via pexels

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World Engineering Day for Sustainable Development 2026 features Omantel as an official partner

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Contributed by: Presswire

24 March, 2026

Presswire associated0

[PRESSWIRE] London, UK – 24 March, 2026 — Omantel has been named as an official partner for World Engineering Day for Sustainable Development (WED) 2026, the annual initiative highlighting the essential role that engineers and engineering plays around the world.

As a pioneer in telecommunications, Omantel plays a key role in developing inclusive and more environmentally friendly communications technology not just in Oman, but further afield.

“Technology must create real value for people and the communities it serves,” says Lujaina Al Kharusi, VP of Governance, Regulatory and Compliance at Omantel. “Engineering is fundamental to that progress, enabling stronger connectivity, smarter services and resilient digital infrastructure. Sustainable development, however, depends on how responsibly and collaboratively these capabilities are applied. As Oman advances its digital transformation in line with Vision 2040, our responsibility is to build intelligent networks that support inclusive growth and long-term economic resilience. We are proud to partner with World Engineering Day 2026 to recognise the engineers who turn innovation into meaningful impact for society.”

World Engineering Day launched in Jakarta, Indonesia, on 4 March 2026, marking the start of a year-long campaign of events, films, features and news. The focus of this year’s theme is “Smart engineering for a sustainable future through innovation and digitalisation”.

An official International Day, as proclaimed by UNESCO, WED is operated by the World Federation of Engineering Organisations (WFEO), the global body that spans members from more than 100 countries and represents over 30 million engineers worldwide.

WED 2026 provides governments, UN-associated organisations, policymakers, educators and leaders in the public and private sectors with the opportunity to raise awareness of the importance of engineering. All campaign content will be produced by SJH Studios – the official media partner and broadcaster for WED – and hosted on the official WED website at http://www.worldengineeringday.net.

Seng-Chuan Tan, President of the WFEO, says: “World Engineering Day brings together engineers, governments, academia, industries and individuals to exchange ideas, drive innovation and take meaningful action. Collaboration is essential – we must work together to transform innovative ideas into real-world impact. When we bring together different voices, perspectives and expertise, we create stronger, more sustainable solutions.”

Ludovica Bellomaria, SJH Group Director, Operations, says: “World Engineering Day is a unique opportunity for organisations to share the best of what the industry has to offer, so we’re excited to have Omantel providing their expertise in telecommunications as an official partner.”

To view Omantel’s WED content, visit: https://worldengineeringday.net/partner/omantel/

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