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By Nicholas Fearn

An AWS tech stack can aid business growth and facilitate efficient operations, but misconfigurations have become all too common and stall this progress

Amazon Web Services (AWS) has become the lifeblood of millions of modern businesses, both big and small. But while this popular cloud platform enables them to manage and scale their operations with impressive speed, simplicity and affordability, it also represents a significant security and privacy risk if mismanaged by users.

An insecure or improperly configured AWS tech stack provides a gateway for cyber criminals to enter corporate systems and sensitive files. The biggest example of this occurred in 2019, when an ex-Amazon employee stole the data of 100 million Capital One customers simply by exploiting a misconfigured web application firewall in the financial service giant’s AWS tech stack.

The incident ended with a high-profile lawsuit in which the financial services giant had to pay a $190m (£140m) settlement to affected customers. Other big businesses impacted by similar incidents include Accenture, Facebook, LinkedIn, Pegasus Airlines, Uber and Twilio. So, what can organisations do to secure their AWS tech stacks?

One of the biggest risks of an insecure AWS tech stack is data theft and exfiltration by cyber criminals, according to Rik Turner, chief cyber security analyst at Omdia. He explains this can happen when S3 buckets, which contain large volumes of files and sensitive metadata, aren’t set up properly.

As a result, S3 bucket access rights can be granted to employees who don’t require them for their roles, leading to insider threats. Or, worse, these crucial storage objects can end up on the public internet for anyone to access and abuse.

Sensitive corporate and customer data exposed in this way can lead to businesses experiencing “enormous financial losses”, says Sylvester Kaczmarek, a professor at online higher education provider the Open Institute of Technology. Their finances take a hit through regulatory fines, customer lawsuits and expensive recovery efforts that can last for months. Reputational damage is often substantial, too.

Additionally, weak or reused user credentials, the absence of cyber security logging and monitoring capabilities, and weaknesses in cyber defences like firewalls leave AWS tech stacks dangerously exposed to data breaches, he adds.

Data breaches can also stem from poorly secured Relational Database Service databases, Elastic Compute Cloud (EC2) instances and application programming interfaces, explains Bob McCarter, chief technology officer of risk and compliance software provider Navex. Erroneous identity and access management policies, a lack of multi-factor authentication, unpatched software and open ports are common security issues affecting these AWS services.

Besides costly data breaches, the day-to-day operations of modern businesses can grind to a halt in the aftermath of an EC2 instance compromise. The latter results in “impaired performance”, and even “a complete malfunctioning” of critical applications and workloads, explains Turner.

These issues are largely the product of mistakes made by AWS users and not cyber attacks targeted at Amazon, according to Neil MacDonald, vice-president and distinguished analyst at Gartner. But he emphasises that mistakes can easily happen due to the “sheer size, complexity and rate of change of AWS deployments”, adding that they are “impossible” to monitor without using appropriate security tools from AWS or other technology companies.

It is, therefore, the responsibility of AWS users to take steps to protect the data they upload to AWS cloud resources. This is enshrined in the cloud security shared responsibility model, with the responsibility of cloud companies like AWS being to secure the infrastructure they sell to customers.

Best practices to secure AWS tech stacks

When it comes to securing AWS tech stacks, many effective best practices are laid out in the AWS Well-Architected framework. McCarter explains that it offers a comprehensive guide for access management, infrastructure management, data privacy, application security, and cyber threat monitoring and detection.

Crystal Morin, cyber security strategist at cloud security company Sysdig, is another vocal supporter of this framework. She says it’s great for handling the prevention, protection, detection and response sides of cyber security. “This model helps you think through how to prevent problems in the first place, ensure your workloads have security in place, and then have the right tools in place to detect and respond to cloud security threats if and when they do take place,” says Morin.

As well as adhering to AWS’s own security best practices, MacDonald points out that the Center for Internet Security also offers advice for creating and maintaining a secure AWS tech stack. He adds that many modern cyber security tools are aligned with the latest AWS best practices, whether provided by Amazon or an outside organisation.

Given that lots of AWS-related security incidents are caused by inadequate access controls, Jake Moore – global cyber security advisor at antivirus maker ESET – urges organisations to implement the principle of least privilege to ensure access rights are limited to those who require them for their roles. This should be enforced as part of a wider identity and access management strategy.

Of course, staff hiring, attrition and promotion can make it difficult to manage AWS access controls. Still, Moore says businesses can use cyber security monitoring tools to track these changes and ensure access controls are amended accordingly, minimising security incidents. In addition to investing in these tools, he urges organisations with AWS stacks to regularly audit their cyber security posture to ensure security gaps are identified and closed swiftly. Automated analysis tools can help with this.

To ensure cyber criminals can’t steal sensitive data stored on and travelling between AWS servers, OPIT’s Kaczmarek says organisations must encrypt data when it’s at rest and in transit. Utilising the AWS Key Management service will help protect data at rest. Meanwhile, tight network security configurations are the key to securing transit data and wider network traffic. These should apply for virtual private clouds, Security Groups and Network Access Control Lists, according to Kaczmarek.

Organisations operating AWS tech stacks can log all network traffic using AWS CloudTrail and monitor it using AWS CloudWatch, says Kaczmarek. He adds that these efforts can be complemented by using multi-factor authentication, implementing security patches when they’re issued and replacing manual processes with infrastructure as code. The previous step is paramount for “consistency and auditing”, he claims.

 

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Raconteur: AI on your terms – meet the enterprise-ready AI operating model
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
Nov 18, 2025 5 min read

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  • Raconteur, published on November 06th, 2025

What is the AI technology operating model – and why does it matter? A well-designed AI operating model provides the structure, governance and cultural alignment needed to turn pilot projects into enterprise-wide transformation

By Duncan Jefferies

Many firms have conducted successful Artificial Intelligence (AI) pilot projects, but scaling them across departments and workflows remains a challenge. Inference costs, data silos, talent gaps and poor alignment with business strategy are just some of the issues that leave organisations trapped in pilot purgatory. This inability to scale successful experiments means AI’s potential for improving enterprise efficiency, decision-making and innovation isn’t fully realised. So what’s the solution?

Although it’s not a magic bullet, an AI operating model is really the foundation for scaling pilot projects up to enterprise-wide deployments. Essentially it’s a structured framework that defines how the organisation develops, deploys and governs AI. By bringing together infrastructure, data, people, and governance in a flexible and secure way, it ensures that AI delivers value at scale while remaining ethical and compliant.

“A successful AI proof-of-concept is like building a single race car that can go fast,” says Professor Yu Xiong, chair of business analytics at the UK-based Surrey Business School. “An efficient AI technology operations model, however, is the entire system – the processes, tools, and team structures – for continuously manufacturing, maintaining, and safely operating an entire fleet of cars.”

But while the importance of this framework is clear, how should enterprises establish and embed it?

“It begins with a clear strategy that defines objectives, desired outcomes, and measurable success criteria, such as model performance, bias detection, and regulatory compliance metrics,” says Professor Azadeh Haratiannezhadi, co-founder of generative AI company Taktify and professor of generative AI in cybersecurity at OPIT – the Open Institute of Technology.

Platforms, tools and MLOps pipelines that enable models to be deployed, monitored and scaled in a safe and efficient way are also essential in practical terms.

“Tools and infrastructure must also be selected with transparency, cost, and governance in mind,” says Efrain Ruh, continental chief technology officer for Europe at Digitate. “Crucially, organisations need to continuously monitor the evolving AI landscape and adapt their models to new capabilities and market offerings.”

An open approach

The most effective AI operating models are also founded on openness, interoperability and modularity. Open source platforms and tools provide greater control over data, deployment environments and costs, for example. These characteristics can help enterprises to avoid vendor lock-in, successfully align AI to business culture and values, and embed it safely into cross-department workflows.

“Modularity and platformisation…avoids building isolated ‘silos’ for each project,” explains professor Xiong. “Instead, it provides a shared, reusable ‘AI platform’ that integrates toolchains for data preparation, model training, deployment, monitoring, and retraining. This drastically improves efficiency and reduces the cost of redundant work.”

A strong data strategy is equally vital for ensuring high-quality performance and reducing bias. Ideally, the AI operating model should be cloud and LLM agnostic too.

“This allows organisations to coordinate and orchestrate AI agents from various sources, whether that’s internal or 3rd party,” says Babak Hodjat, global chief technology officer of AI at Cognizant. “The interoperability also means businesses can adopt an agile iterative process for AI projects that is guided by measuring efficiency, productivity, and quality gains, while guaranteeing trust and safety are built into all elements of design and implementation.”

A robust AI operating model should feature clear objectives for compliance, security and data privacy, as well as accountability structures. Richard Corbridge, chief information officer of Segro, advises organisations to: “Start small with well-scoped pilots that solve real pain points, then bake in repeatable patterns, data contracts, test harnesses, explainability checks and rollback plans, so learning can be scaled without multiplying risk. If you don’t codify how models are approved, deployed, monitored and retired, you won’t get past pilot purgatory.”

Of course, technology alone can’t drive successful AI adoption at scale: the right skills and culture are also essential for embedding AI across the enterprise.

“Multidisciplinary teams that combine technical expertise in AI, security, and governance with deep business knowledge create a foundation for sustainable adoption,” says Professor Haratiannezhadi. “Ongoing training ensures staff acquire advanced AI skills while understanding associated risks and responsibilities.”

Ultimately, an AI operating model is the playbook that enables an enterprise to use AI responsibly and effectively at scale. By drawing together governance, technological infrastructure, cultural change and open collaboration, it supports the shift from isolated experiments to the kind of sustainable AI capability that can drive competitive advantage.

In other words, it’s the foundation for turning ambition into reality, and finally escaping pilot purgatory for good.

 

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OPIT’s Peer Career Mentoring Program
OPIT - Open Institute of Technology
OPIT - Open Institute of Technology
Oct 24, 2025 6 min read

The Open Institute of Technology (OPIT) is the perfect place for those looking to master the core skills and gain the fundamental knowledge they need to enter the exciting and dynamic environment of the tech industry. While OPIT’s various degrees and courses unlock the doors to numerous careers, students may not know exactly which line of work they wish to enter, or how, exactly, to take the next steps.

That’s why, as well as providing exceptional online education in fields like Responsible AI, Computer Science, and Digital Business, OPIT also offers an array of career-related services, like the Peer Career Mentoring Program. Designed to provide the expert advice and support students need, this program helps students and alumni gain inspiration and insight to map out their future careers.

Introducing the OPIT Peer Career Mentoring Program

As the name implies, OPIT’s Peer Career Mentoring Program is about connecting students and alumni with experienced peers to provide insights, guidance, and mentorship and support their next steps on both a personal and professional level.

It provides a highly supportive and empowering space in which current and former learners can receive career-related advice and guidance, harnessing the rich and varied experiences of the OPIT community to accelerate growth and development.

Meet the Mentors

Plenty of experienced, expert mentors have already signed up to play their part in the Peer Career Mentoring Program at OPIT. They include managers, analysts, researchers, and more, all ready and eager to share the benefits of their experience and their unique perspectives on the tech industry, careers in tech, and the educational experience at OPIT.

Examples include:

  • Marco Lorenzi: Having graduated from the MSc in Applied Data Science and AI program at OPIT, Marco has since progressed to a role as a Prompt Engineer at RWS Group and is passionate about supporting younger learners as they take their first steps into the workforce or seek career evolution.
  • Antonio Amendolagine: Antonio graduated from the OPIT MSc in Applied Data Science and AI and currently works as a Product Marketing and CRM Manager with MER MEC SpA, focusing on international B2B businesses. Like other mentors in the program, he enjoys helping students feel more confident about achieving their future aims.
  • Asya Mantovani: Asya took the MSc in Responsible AI program at OPIT before taking the next steps in her career as a Software Engineer with Accenture, one of the largest IT companies in the world, and a trusted partner of the institute. With a firm belief in knowledge-sharing and mutual support, she’s eager to help students progress and succeed.

The Value of the Peer Mentoring Program

The OPIT Peer Career Mentoring Program is an invaluable source of support, inspiration, motivation, and guidance for the many students and graduates of OPIT who feel the need for a helping hand or guiding light to help them find the way or make the right decisions moving forward. It’s a program built around the sharing of wisdom, skills, and insights, designed to empower all who take part.

Every student is different. Some have very clear, fixed, and firm objectives in mind for their futures. Others may have a slightly more vague outline of where they want to go and what they want to do. Others live more in the moment, focusing purely on the here and now, but not thinking too far ahead. All of these different types of people may need guidance and support from time to time, and peer mentoring provides that.

This program is also just one of many ways in which OPIT bridges the gaps between learners around the world, creating a whole community of students and educators, linked together by their shared passions for technology and development. So, even though you may study remotely at OPIT, you never need to feel alone or isolated from your peers.

Additional Career Services Offered by OPIT

The Peer Career Mentoring Program is just one part of the larger array of career services that students enjoy at the Open Institute of Technology.

  • Career Coaching and Support: Students can schedule one-to-one sessions with the institute’s experts to receive insightful feedback, flexibly customized to their exact needs and situation. They can request resume audits, hone their interview skills, and develop action plans for the future, all with the help of experienced, expert coaches.
  • Resource Hub: Maybe you need help differentiating between various career paths, or seeing where your degree might take you. Or you need a bit of assistance in handling the challenges of the job-hunting process. Either way, the OPIT Resource Hub contains the in-depth guides you need to get ahead and gain practical skills to confidently move forward.
  • Career Events: Regularly, OPIT hosts online career event sessions with industry experts and leaders as guest speakers about the topics that most interest today’s tech students and graduates. You can join workshops to sharpen your skills and become a better prospect in the job market, or just listen to the lessons and insights of the pros.
  • Internship Opportunities: There are few better ways to begin your professional journey than an internship at a top-tier company. OPIT unlocks the doors to numerous internship roles with trusted institute partners, as well as additional professional and project opportunities where you can get hands-on work experience at a high level.

In addition to the above, OPIT also teams up with an array of leading organizations around the world, including some of the biggest names, including AWS, Accenture, and Hype. Through this network of trust, OPIT facilitates students’ steps into the world of work.

Start Your Study Journey Today

As well as the Peer Career Mentoring Program, OPIT provides numerous other exciting advantages for those who enroll, including progressive assessments, round-the-clock support, affordable rates, and a team of international professors from top universities with real-world experience in technology. In short, it’s the perfect place to push forward and get the knowledge you need to succeed.

So, if you’re eager to become a tech leader of tomorrow, learn more about OPIT today.

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