Name: Overcoming Obstacles to Cloud Innovation
Start: 2022-12-12T16:00:00Z
End: 2022-12-12T16:00:36.000Z
Location: BrightTALK
Rating: 5

The Enterprise Architecture channel  presents the next generation of Enterprise IT: recognizing the strategic importance of digital transformation and the data center to make companies more nimble and competitive. These presentations will help demanding IT and BizOps professionals achieve flexibility, scalability and performance with reduced risk and complexity.

Modern infrastructure is a dynamic ecosystem where workloads move fluidly across cloud regions, edge nodes, and on-premises systems. Traditional management methods are no longer sufficient to handle the scale, speed and complexity of these environments. As organizations adopt AI-driven architectures and face increasing regulatory demands, the need for intelligent, autonomous cloud management has become critical. 

At the same time, zero-trust security models are reshaping how businesses protect their systems requiring constant validation of every user, device and transaction. This is a challenge that adds significant operational strain. 

Join Ekambar Kumar Singirikonda, Director of DevOps Engineering at Toyota, to discover actionable strategies for building resilient, predictive, and cost-efficient hybrid infrastructures that align with business priorities.

Key Takeaways:
- Learn how to unify cloud, edge, and on-prem systems with intelligent orchestration platforms that optimize workloads for performance, cost, and compliance.
- Discover how to implement zero-trust security at scale without disrupting operations or user experience.
- Explore AI-driven architectural patterns, including predictive resource management, policy-based orchestration, and self-healing systems.
- Understand strategies to reduce hybrid infrastructure complexity through automation frameworks and unified management tools.
- Gain a roadmap for transitioning from manual oversight to predictive, business-aligned infrastructure operations.

Simplify Hybrid Infrastructure with Autonomous Cloud and Zero-Trust Strategies

Modern CIOs are pivotal drivers of business transformation. As AI reshapes industries, organizations have to embed intelligence into every aspect of their operations to remain competitive. From automating processes and enhancing decision-making to elevating customer experiences, AI's potential to drive change is huge —but unlocking its value requires strategic leadership and a clear roadmap.

This session will explore how CIOs can leverage AI as a catalyst for enterprise-wide transformation, aligning initiatives with business goals and delivering measurable outcomes. 

Join Ekambar Kumar Singirikonda, Director of DevOps Engineering at Toyota, to uncover how to embed AI into your enterprise DNA and lead with confidence in the AI era.

Key Takeaways:
- Discover strategic AI integration techniques that embed AI across enterprise functions to achieve measurable business impact.
- Understand how to evolve as a modern CIO, building executive influence and aligning AI initiatives with business objectives.
- Explore frameworks for evaluating emerging technologies and demonstrating ROI.
- Gain practical approaches to foster innovation, manage change, and upskill teams for AI adoption.
- Learn how to structure multi-year transformation plans that balance innovation with operational stability.

Harnessing AI to Drive Enterprise Transformation and Leadership Excellence

CIOs face a dual mandate with AI: they oversee the infrastructure that sustains trust in data and AI systems, but they must also narrate that infrastructure persuasively. Technical excellence means little if boards see only cost centres and regulators see only opacity. The session addresses how to measure and communicate AI value in terms that resonate beyond IT.

Effective measurement requires distinguishing two forms of transparency that executives often conflate. Data lineage describes how information flows through systems: origins, transformations, dependencies. Data provenance records the documented history of specific values: who created or modified them, when, under what parameters. Lineage answers architectural questions relevant to planning and change management; provenance answers forensic questions relevant to audit and dispute resolution. Metrics derived from each capability speak to different audiences. Time to audit readiness concerns board risk committees; value reconstruction time concerns legal and compliance; data preparation hours concern COOs and budget owners.

The session presents a metrics framework that translates governance capabilities into business language. Participants will examine how lineage coverage, provenance depth, error detection time, and downstream impact incidents can be reported in ways that demonstrate value rather than merely documenting activity. The goal is not dashboards for their own sake, but communication that builds confidence among stakeholders who will never examine the underlying systems directly.

Key Takeaways:
- Lineage and provenance serve different purposes and speak to different audiences.
- Metrics must translate technical capabilities into business outcomes.
- Time-based metrics (audit readiness, error detection, value reconstruction) communicate operational value.
- Governance framed as enabling rather than defensive builds broader organizational support.

Measuring AI Value: Metrics That Speak to Boards and Regulators

Modernization presents a critical yet complex opportunity for enterprises striving to balance innovation with operational excellence. Technology leaders often find themselves performing a precarious trapeze act—innovation attracts funding, but operational failures dominate headlines, exposing organizations to significant risks. With 79% of application modernization projects failing and 88% of transformations falling short, the stakes have never been higher.

This session uncovers the root causes of modernization failures, with a focus on applications and data—the foundation of enterprise transformation. Attendees will gain practical strategies to navigate these challenges, ensuring their initiatives align with business goals and deliver tangible results.

Join Jeffrey Tefertiller, Founder of Service Management Leadership, to explore proven approaches that can significantly improve your chances of modernization success.

Takeaways:
- Identify the key reasons behind modernization project failures.
- Align application and data strategies with overarching business objectives.
- Apply actionable frameworks to mitigate risks in transformation initiatives.
- Examine real-world examples of successful modernization efforts.
- Gain insights to future-proof your enterprise technology landscape.

Driving Modernization Success in 2026

Technology initiatives fail most when organisations scale complexity before they’re ready. Teams are asking CIOs to fund ‘enterprise-grade’ platforms for data, AI, security and more before they’re even clear on data ownership, platform priorities and use cases. In turn, organisations invest in high-ticket technologies that teams don’t adopt, yielding unsatisfactory outcomes.

This session introduces a practical framework for starting small and scaling smart when implementing complex enterprise capabilities. Focusing on the real-world example of data catalog and data quality, we’ll explore how starting with small, user-driven solutions allows teams to get to what really matters - ownership, definitions, quality metrics and operational decisions. Rather than focusing on which technology to choose, it’s about sequencing - knowing what can be built first, what can be delayed and understanding when scaling makes the most sense.

The framework has a broad application that CIOs can use for any initiative where tooling, behaviour change and governance need to evolve together. Join Inigo Antolin, Head of Data Management and Governance at the British Council, to receive a practical mental model to reduce risk, preserve optionality and scale with confidence rather than hope.

Key Takeaways:
- Why scaling enterprise platforms too early results in wasted resources and lost trust.
- How starting small can strengthen decision-making across ownership, definitions and quality.
- Discover the Start Small, Scale Fast framework that you can apply across all new tech initiatives.
- How to use constraints as a strategic advantage rather than a limitation.

Start Small, Scale Fast: Hard Lessons from Data Catalog & Data Quality

In today’s evolving IT landscape, selecting the right storage architecture is critical for optimal performance, scalability, data governance, and cost-efficiency. Furthermore, AI workloads have uniquely influenced how we meet these demands from our storage infrastructure. This webinar provides a technical deep dive into three fundamental storage deployment models – on-premises, cloud, and hybrid – examining their architectures and operational trade-offs through the lens of two key concepts: indirection (accessing data through mapping layers that provide flexibility and abstraction) and redirection (rerouting data requests to enable failover, load balancing, and optimized performance). 

We are going to take some of the key stages of AI lifecycle development as sample use-cases (such as data ingestion, preparation, training, inferencing, and retrieval) and compare how each storage model can serve these use-cases across varying access patterns, data volumes, and performance requirements.

Attendees will gain a practical framework for aligning AI workloads with the most suitable storage architecture, balancing cost, scalability, and latency. Whether you are building AI infrastructure from scratch or optimizing existing deployments, this session will help you make informed decisions for AI-ready storage.

Learning Objectives and Key Takeaways:

• Introduction to the 3 different types of storage deployment models – on-prem, cloud, and hybrid
• Trade-offs for each deployment model
• Importance of indirection and redirection
• Understand how AI-specific data types and access patterns (e.g., embeddings, checkpointing) influence storage performance and design
• Evaluate trade-offs in latency, scalability, security, and cost when choosing storage for different stages of the AI pipeline
• Gain a decision-making framework for selecting the right storage model based on workload characteristics and infrastructure goals

AI Meets Storage: Comparing On-Prem, Cloud, and Hybrid Architectures Across the AI Lifecycle

As AI workloads continue to scale, the physical infrastructure supporting them must evolve to deliver the performance, reliability, and efficiency required by modern data-intensive applications. This webinar will focus on the interconnect foundations of AI infrastructure, including storage. There will be an emphasis on the form factors, connectors, cables, and transceivers standards that enable scalable and interoperable systems.

We’ll explore how SNIA’s SFF Technical Work Group is contributing to the development of physical layer standards that support high-performance interconnects and storage devices used in AI environments. Topics will include the importance of transceiver innovation and the need to evolve; the role that form factors like EDSFF play; and how innovative cabling and connector designs support the adoption of high-speed signaling technologies like PCIe 8.0 and beyond.

This session is ideal for architects, engineers, and technologists who want to understand how physical infrastructure standards are enabling the next generation of AI systems.

Key Concepts:
• Transceiver development for out-of-box signaling 
• Connectors and cables for high-speed inbox signaling
• Copper vs. optical and the challenges of both
• SSD form factor innovations and their impact on density and thermal design

Accelerating AI Infrastructure: The Role of 400G and PCIe 8.0 in Next-Gen Interconnects

Storage security changes and adaptations are a fact of life to deal with the ever-changing threat and regulatory landscapes. A black swan event, a new standard, or a regulation often serves as a catalyst for organizations to review their controls and practices. The recent publication of NIST Special Publication 800-88 Rev. 2, Guidelines for Media Sanitization, is drawing attention to storage security, but it is not the only development worth noting. SNIA, Open Compute Project (OCP), Trusted Computing Group (TCG), and IEEE are developing or have developed standards and specifications that could be important going forward. One central theme underlying several of the activities is in storage sanitization (i.e., controlled eradication of data).

This session brings together a unique panel of experts who have served as editors of some of the most important storage sanitization standards. These experts also have broad knowledge of storage security. As a panel, they will provide insight into these new developments as well as observations on what organizations are experiencing. A moderator will engage the panel with thought-provoking questions, but participants are also encouraged to bring their own questions.

Join us to understand: 
• Changes to storage sanitization and what that means to organizations
• Primary drivers for storage security
• Difference between Storage Sanitization and Data Sanitization
• Interplay and interdependencies for storage security standards/specifications

The Storage Security Shake-Up: Adapt Now or Get Left Behind

Magnetic RAM, Resistive RAM, Ferroelectric RAM, and other new memory technologies have been pushed to the forefront by issues with Moore’s Law scaling, but the ancillary benefits they bring to computing will provide significantly more important longer-term benefits.  In this session, analysts Jim Handy and Tom Coughlin will explain how these new nonvolatile technologies will help accelerate and cost-reduce inference through compute-in-memory engines while standard computing will also see lower costs and higher performance by bringing inexpensive persistence closer to, and even within the processor chip itself.  The session will also address ways that new frameworks like CXL will help provide persistence-friendly structures at all levels of the computing hierarchy.

How New Memories Will Accelerate Both Inference and General-Purpose Compute

Smarter data management is the key to unlocking the full potential of next-generation data infrastructure for AI. This webinar explores how the SNIA Cloud Data Management Interface (CDMI™) standard enables government labs, HPC centers, and organizations leveraging the power of AI/ML to reimagine and innovate their infrastructure to meet next-generation data management demands. CDMI is a mature ISO standard (ISO/IEC: 17826:2022) with over 15 years of development and implementation, and is purpose-built for cloud data management. CDMI's extensive capabilities enhance key aspects of AI operations by transforming data management challenges into streamlined, intelligent workflows. 

CDMI 3.0 (in development now) will further extend the standard with:
• Automated resource discovery that accelerates AI workload efficiency
• Portable data movement that enables preservation of metadata fidelity during data migration, data replication, and data archival, including graph relationships and knowledge graph
• MCP-based data management that enhances AI accuracy while improving access speed

Building on a proven, standards-based foundation, CDMI enables true machine-readable data management. CDMI 3.0 will further improve how teams discover resources, orchestrate AI agents, and protect data across complex cloud environments while establishing the infrastructure for automated, self-describing data ecosystems with full auditability that drive future innovation. 

Read the SNIA CDMI 3.0 white paper https://www.snia.org/educational-library/introduction-cloud-data-management-interface-cdmitm-30-2025

Intelligent Data Management: Shaping the Future for AI Workloads

Join us for an insightful webinar and demonstration as we explore the foundational process of training machine learning models, with a special focus on computer vision applications. This session will guide participants through the essential stages of model development—from data preparation to algorithm selection—highlighting how these steps influence performance and accuracy.
Through practical demonstrations and conceptual discussions, attendees will gain a deeper understanding of how vision models are built and validated, and how these techniques can be extended to broader predictive analytics. We’ll also examine common challenges and share strategies to overcome them, emphasizing the value of simplicity, modular design, and thoughtful evaluation.

Key Takeaways:
• Core steps in the model training lifecycle
• Why data quality is critical to success
• Understanding inferencing and metrics for model validation
• Shifting from engineering mindset to modeling intuition
• Avoiding common pitfalls in training workflows
• Embracing parsimony and modularity in design
• Using checkpoints to monitor and refine progress

From Data to Decisions: Understanding How AI Models Learn

Storage networking consumers are fully aware of the classic benefits of Fibre Channel as a dedicated storage networking solution that provides reliable and lossless data transfer as well as high availability and redundancy.  What is less known is that Fibre Channel supports several Upper Layer Protocols (ULPs) including SCSI, FICON, NVMe, Avionics and RDMA. In this webinar, we explore the FC-4 layer of the Fibre Channel architecture that provides the services used by the various ULPs deployed in Fibre Channel products. Join us for an exploration into:

• The history of Fibre Channel’s versatility 
• Fibre Channel architectural layers
• Overview of the current FC-4 transports: FCP, FC-SB, FC-NVMe, FC-RDMA

Attendees of the webinar will become well versed in the scope and capabilities of Fibre Channel and develop a well-rounded understanding of the technology.

Versatility of Fibre Channel: Multi-Protocol Magic

Edge computing is transforming AI deployment by processing data locally rather than in distant cloud data centers. This session explores how distributed intelligence enables both sustainability and capabilities that centralized architectures cannot provide.

Through two contrasting deployments—precision agriculture in resource-constrained environments and real-time manufacturing optimization in advanced facilities—we demonstrate how edge computing addresses fundamentally different challenges using the same architectural principles. Both achieve 50-70% energy reduction with compelling ROI, while solving problems where cloud computing fails due to latency, connectivity, bandwidth, or data sovereignty requirements.

Beyond the case studies, attendees learn decision frameworks for edge versus cloud architecture, strategies for deploying AI in environments with limited infrastructure, and how to build business cases that balance sustainability goals with operational performance. The session provides actionable guidance for organizations seeking to scale AI deployments while reducing their environmental footprint and enabling new capabilities.

Edge AI from Farm to Factory: Building Sustainable Intelligence across the world

This webinar will explain the process of model inferencing and deployment options. We will discuss how trained models are used to make predictions and the considerations for deploying models. Attendees will understand the challenges and strategies for optimizing model performance, covering:
 
• What is model inferencing  
• Model inferencing process 
• How inferencing deployment differs in Gen AI and visual inspection
         - Inferencing deployment software options 
          - Inferencing hardware considerations (e.g., on the edge, on-prem, etc.)
• Deploying AI models for production best practices and lessons learned 
• Strategies for maintaining model performance post-deployment

AI Model Inferencing and Deployment Options

On-premises enterprise data centers have been in decline since the creation of co-lo’s and the cloud, but a new age is emerging with the advent of AI. While most AI is served by the mega data centers mushrooming in “data corridors”, some applications require the low latency response times that edge computing was designed to provide. The industry readily builds large numbers of small processing centers at the edge to serve things like 5G cell service. But constructing AI data centers close to every high demand user is financially impractical and subject to local restrictions due to their enormous demands on power and water.

Tune into this session presented by industry thought leader Bob McFarlane to learn how reviving enterprise data centers as edge facilities may be the answer to acquiring virtually instant response times. Despite significantly greater power and cooling demands, they are unlikely to reach the levels that concern local citizens, enabling them to be renovated or built where necessary without pushback. Companies with significant AI demands may need to start planning and budgeting for high capacity, high reliability infrastructures with costs and staffing beyond anything they have previously experienced.

Learning Objectives:
- Understand the key elements of Edge Computing, and how they relate to AI applications.
- Learn the limitations AI services providers confront in constructing edge facilities.
- Learn to identify AI applications that require the fast response times of the “edge”.
- Prepare for the challenges your organization may face in utilizing AI in critical applications.

Will Enterprise Data Centers Become ‘The Edge’ for AI?”

As breakthrough technologies like AI mature, they inevitably evolve from centralized to decentralized architectures. With global edge computing spending projected to reach $378 billion by 2028, organizations that continue relying solely on centralized AI risk falling behind in both efficiency and performance. The pervasive waste and expense of centralized generative AI models have underscored the urgent need for intelligence at the edge.

While edge computing concepts have existed since the 1990s with content delivery networks, today's businesses face the complex challenge of transforming their architectures to process data closer to its source. This session explores how leading organizations are navigating this transition, reducing latency and costs while competing with decades of established centralized cloud infrastructure.

Join Alan Morrison (Advanced Data Technologies Consultant and Writer) to discover how decentralized AI and edge computing are revolutionizing data processing across industries.

Key Takeaways:

- Understand why centralized AI approaches are becoming unsustainable and how edge computing addresses these limitations
- Learn practical strategies for implementing edge intelligence from organizations already succeeding with this approach
- Discover the economic benefits of processing data at the edge versus transmitting everything to centralized systems
- Gain insights into market growth projections and how to position your infrastructure investments accordingly
- Identify the architectural transformation challenges of edge computing and how to overcome them

Decentralized AI: The Future of Edge Computing

Today’s enterprise workflows don’t live in one place — they move across edge devices, cloud infrastructure, and on-prem systems in milliseconds. Some start at the edge — like sensor data or customer interactions — while others finish there, after running through cloud analytics or AI inference. The result is a constantly shifting architectural boundary where speed, security, and compliance collide.

This session looks at how to design cross-architectural workflows that maintain consistency, security, and data integrity from end to end. We’ll unpack how different architecture types — edge-native, hybrid, and multi-cloud — impact data handling, governance, and latency. And we’ll dive into the new layer of complexity AI introduces: model hallucinations, prompt injections, and evolving regulatory constraints when sensitive customer data moves from edge to cloud.

Join Eugina Jordan, CEO of YOUnifiedAI, as she breaks down how to architect distributed systems that are both intelligent and compliant — not in theory, but in practice.

Key takeaways:

- Understand how modern workflows traverse edge, cloud, and on-prem environments — and where control points break down
- Design architectures that protect customer data and maintain compliance even when processing happens across geographies
- Implement AI workflows that minimize hallucination risks and prevent prompt-injection attacks at the edge
- Balance performance with governance — using architecture, not just policy, to enforce trust
- Build an operational model that lets security, data, and AI teams collaborate on a single distributed workflow

Building Secure AI Workflows Across Edge, Cloud & AI Without Breaking Trust

Is your team developing AI solutions at pace with business demand? Modern cloud architectures have enabled a scale and flexibility for production AI not possible less than a decade ago. However, data science teams are seeing increased demand for new models often exceeding their capacity. 

In this session, we'll share why Agile AI is necessary for modern data science teams and practical learnings on how to leverage the cloud to:
- Increase time to value
- Decrease time to production
- Ensure the success of your models over the long term

Plus, we'll share multiple DataRobot customer stories and examples of Agile AI across the AI lifecycle.

Leveraging the Cloud for Agile AI Development

As a Service models have gained significant traction across businesses of all sizes and industries. Leaders are seeking solutions that accelerate cloud adoption and support agility while also allowing transformation at whatever pace works best. Many business leaders don’t want to change the way they operate, they just want to consume differently. They want to pay only for what they use – running applications and the business without worrying about how or where everything is being hosted.

As a Service is not a lease, capital purchase or cloud contract. It’s a way to use the latest technologies, with expert management, to the extent and capacity required.

Join Insight’s Kent Christensen as he unpacks the top benefits of as a service, from the financial to operational – and how to determine the right use cases for your business. Discover a new way to consume on-premises infrastructure that’s like the public cloud; a best-of-both worlds offering that will accelerate cloud adoption and drive impact across your organization.

Accelerating Cloud Transformation with As a Service

From the digital core to the data fabric, the data landscape has evolved dramatically over the past decades. We have witnessed the rise in complex data-driven applications, providing solutions to challenges which were previously thought to be unsolvable. Data fabrics will accelerate the development of these type of solutions, to create a seamless experience across disparate data technologies and their varied connection mechanisms. Most importantly, data fabrics will provide the protective umbrella-like cover for effective data management across an organization and when done right, simplify data partnerships across multiple organizations.
 
Join Dr. Pragyansmita Nayak for this data management-focused session to:
1. Define Data Fabric. 
2. Understand its critical role in the data management ecosystem.
3. Gain insight into how it enables data-driven solutions.

Data Fabric 101

The impact of the business need for faster cycles and increasing flexibility is driving DevOps and Cloud ideas throughout the IT value stream.  This has significant meaning for the compute side of the world.  We will explore the  “Environments on Demand” and how it impacts the IT Value Stream.  We will examine key elements of DevOps and cloud that help address the new world and optimize the investment.

In this session, we will discuss: 

1. Accelerating Change – Driving Forces (eg. Change Drivers, Industry Impact)
2. DevOps and Cloud – The Foundation (eg. Continuous Flow, Pipeline, Cloud Services)
3. Environments on Demand – Key Elements (eg. Infrastructure as Code (IAC), Automation, Integration & Ephemeral)
4. Environments on Demand – Real World Scenarios

Presented by: 
Terry Brennan, Managing Director, Orasi

DevOps and Cloud: Driving Environments On Demand and Optimizing Investments

AI brings unprecedented opportunities to businesses, but also incredible responsibility. Its direct impact on people’s lives has raised considerable questions around AI ethics, data governance, trust and legality. In fact, Accenture’s 2022 Tech Vision research found that only 35% of global consumers trust how AI is being implemented by organizations. And 77% think organizations must be held accountable for their misuse of AI.  

As machine learning and AI become more ubiquitous, businesses will need to find ways of overcoming these questions, deploying AI systems that empower employees and fairly impact customers and society.   

Join Monark Vyas (Managing Director – Applied Intelligence, Accenture) to explore how to leverage Responsible AI practices to design and deploy AI systems that engender trust and allow your business to flourish.    

Topics for discussion include:  
- Why AI and Machine Learning systems need to be built responsibly  
- The principles of responsible AI   
- How to put them into practice  
- And more...

Responsible AI: Scaling AI with Confidence

Today’s cloud teams have a lot on their hands. Some are working to modernize and migrate legacy applications to the cloud, others are struggling to keep up with the fast pace of change with cloud resources and services, all while managing a multi-cloud world, with workloads spanning on-prem data centers, private clouds, and public clouds. 

Join us for an introduction to VMware AriaTM, a new multi-cloud management solution, and a deep dive into cloud cost optimization. 

 Learn how VMware Aria Cost powered by CloudHealth (formerly CloudHealth):
• Gives business visibility into multi-cloud usage and costs
• Delivers recommendations for cost and usage optimization
• Governs your multi-cloud environment with policy-based alerts and automation
• Helps businesses implement FinOps best practices

Cost Optimization in a Multi-Cloud World: Drive Accountability with FinOps

Cloud technology has experienced massive growth, driven by the explosion of remote and hybrid workforces. Cloud computing provides a myriad of benefits for companies like increased growth, improved efficiency and faster workflows. But with this technology rapidly evolving, it is essential to stay on top of the new trends to ensure your company is gaining the most leverage from its cloud use and practicing a forward-thinking approach.

Tune into this panel discussion to hear top experts in the field discuss the key cloud computing trends to keep an eye on for this coming year and suggest how companies can practically apply these technologies while avoiding the trap of immediately jumping on a new cloud technology simply because it's another buzzword. 

Key discussion points:
- The multi-cloud strategy and its many benefits.
- The growing role AI and machine learning capabilities in cloud services.
- The increased adoption of cloud-native apps and how companies can best leverage them.
- The green cloud computing frameworks and how it emphasizes the environmental sustainability of cloud computing.

Moderated by: Simon Ratcliffe, Mentor and Adviser, Ensono
Alicia Howard, Product Manager, VMware Aria Cost powered by CloudHealth

What's on the cloud's horizon for 2023?

This fireside chat provides a behind-the-scenes look at how the Arsenal Football Club is leveraging a cloud solution to create a single namespace interface, collaborate on media assets regardless of where they are stored, and improve overall workflows, all while maintaining a high level of confidence that critical security and access measures are not compromised.

Fireside chat with Arsenal Football Club: Winning with the Cloud

Using cloud and cloud-migration to accelerate business growth and explore new ways to innovate and quickly implement new services emphasizes the need to adopt the mindset of security-by-design and zero trust. Without a solid foundation of cyberprotection, businesses open a gateway for cyberattacks and cybercriminals to cause severe and irreparable damage. 

The core and foundation of true cybersecurity is validated digital identities (eID): The prerequisite of all other cybersecurity measures. Validated digital identities must be the one and only authorized way to identify and gain access across all user groups, services, and devices. 

For more than 15 years, Denmark has provided public access to the eID-solution MitID. 3rd. generation is now available delivering one unified system giving both citizens, employees, public authorities, and businesses easy access to validated digital identities. Bjarke Alling has been closely involved in the development of the solution and will share insights into how it is used and how validated digital identities can be implemented. 

Takeaways: 
1.) How the Danish solution for validated digital identities works 
2.) What the Danish solution for validates identities gives access to 
3.) How to adopt validated digital identities as the foundation of a truly cybersecure cloud infrastructure 

About the speaker:
Bjarke Alling is co-founder and acting Group Managing Director of cybersecurity company Liga. He is a current member and prior co-chair of the National Danish Cyber Security Council, former chair of their IT-security committee, member of the board at The Danish ICT Industry Association (ITB), and member of the board of D-Mærket (D-Seal)

Building a Cybersecure Cloud Infrastructure with Validated Digital Identities

Whether they know it or not, most companies' IT infrastructure is multi-cloud. Even when using a single cloud strategy to drive digital transformation, companies have workloads hosted in AWS, Office365 for the desktops, Salesforce for CRM, SAP Concur for travel and expenses. It doesn’t get more multi-cloud than that. 

The challenges are many:
·       How does a company manage all these different SaaS, PaaS and IaaS environments?
·       How do they keep security guardrails consistent?
·       What about keeping track of cloud native innovations?
·       And, most of all, how do they control costs?

In this session, join Jeroen Mulder (Principal Consultant at Fujitsu) as he discusses the principle of the single pane of glass view in managing business environments across cloud propositions, from security and cost management perspective. Attendees will come away with a deeper understanding of how to keep their company safe and financially sound on the road to digital transformation.

Containing Cloud Costs

The decentralized cloud (dcloud) is emerging as a cost-effective alternative to conventional public cloud services. 

Research universities, for example, love the convenience of cloud services, but find it hard to afford to store all the data they have to collect and maintain. 

As storage and compute become less tightly coupled, price-sensitive, early adopter customers have been storing their big data via services that harness the power and cost advantages of the dcloud: newly capable peer-to-peer data networks such as the Interplanetary File System (IPFS) and the cloud-friendly infrastructure that’s already being built on top.

Other early adopter organizations such as the Chrome development unit of Alphabet, Netflix and Opera have been using IPFS-based storage as a simpler, cheaper and in some other ways more suitable alternative for certain classes of data storage. Tape and other “cold storage” methods are under replacement threat as a result. 
 
This talk will provide an overview of dcloud (a.k.a., services that use the dgraph/dweb/web3)  or P2P data network cloud storage alternatives for enterprise, what the pros and cons are of these new services, and how they promise to expand the storage options available to mainstream companies.

Speaker bio:
Alan Morrison is an independent consultant and freelance writer on data tech and enterprise transformation. He is a contributor to Data Science Central with over 35 years of experience as an analyst, researcher, writer, editor and technology trends forecaster, including 20 years in emerging tech R&D at PwC.

The Rise of Decentralized Cloud Storage

Content may be king, but API traffic makes up most requests between a user and an application. APIs provide data and personalization critical to users' experience but don't benefit from caching in the traditional sense. Instead, accelerating APIs needs global reach and an architecture that can quickly sync read-replicas to minimize latency and failures. In this webinar, we'll cover best practices to help improve the performance and availability of APIs regardless of the backend technology stack.

Global Data Replication for Improved API Performance and Availability

There’s a reason only 32% of global data is currently being put to work. Though projections expect 180 zettabytes of data will be created by 2025, these deep troves of information are often locked up, behind skills gaps, data gravity problems, and incomplete hybrid architectures. Even when the data is accessible, diverse teams struggle to collaborate to create, refine, understand, govern, and innovate with their data. Meanwhile, costs are always a factor. Amidst all these challenges — is there a better way?

In this session, Faction CTO Matt Wallace will explore:

 - How a multi-cloud approach solves data gravity and skills gravity
 - How multi-cloud creates huge cost and innovation advantages over “multiple clouds”
 - What the future of data warehouses, data lakes, and innovation looks like
 - How a fluid, hybrid multi-cloud approach can give you the best of all worlds - and what pitfalls to avoid that drive up cost and complexity

Unleash Innovation with Multi-Cloud

Microservices architectures can be a game-changer for business agility and incremental application modernization. 

Join the session to discover the following key takeaways:

- Learn best practices for building microservices leveraging a real-time data layer
- How DevOps teams can easily manage, administer and deploy Redis clusters on Kubernetes
- The key capabilities of cloud-native Redis Enterprise that make it the ideal data platform for real-time microservices-based applications

Overcoming the Challenges of Deploying a Microservices Data Layer on Kubernetes

Today there is a large gap in quality and access to pediatric healthcare between major cities in rich countries and rural areas in those same countries as well as the entire developing world. We have the power to help repair those gaps and raise the standards of children’s healthcare across the globe, through the development and deployment of pediatric cardiology, orthopedic, neurology, oncology and radiology and Artificial Intelligence (AI) applications. 

Born out of his early commercial work in cloud computing and inspired by a student in his Stanford cloud computing class, Timothy Chou formed BevelCloud to transform children’s healthcare globally by creating privacy-preserving real-time pediatric applications based on access to 1,000,000 healthcare machines in all 500 children’s hospitals in the world. 

In this talk, Timothy Chou describes how his team have constructed a widely distributed, privacy-preserving edge cloud service that optimizes communication and collaboration in pediatric healthcare to drive better outcomes for patients across the globe. He’ll discuss the benefits and challenges of using central architectures for AI in medicine and highlight real-time collaboration and privacy-preserving federated learning applications.  

Join the session to discover: 
- How software can do good in the world and transform children’s healthcare globally. 
- The challenges central architectures have to advance AI in pediatric medicine. 
- An introduction to a new edge cloud service.

A Moon-Shot Mission: Transforming Pediatric Healthcare with AI

With concerns about the environment constantly on the forefront, businesses should seek to do their part and reduce waste while maintaining efficiency and optimizing costs. The green cloud covers the many environmental benefits provided by cloud use such as reduced data center carbon footprint. Green cloud computing can even reduce costs when properly applied, making it a no-brainer for cloud-invested companies to explore. Tune into this panel discussion to hear experts in the field discuss some practical, real-life tips to making your cloud infrastructure more environmentally friendly:

• How to select a green cloud service provider.
• The action steps to help “green” your data center such as optimizing infrastructure and tracking usage.
• The newer technologies like machine learning that can replace the older more wasteful ones.
• How the green cloud can ultimately speed up digital transformation efforts.

Enhance sustainability and reduce costs with green cloud computing

Cloud infrastructure today is all built by composition. A disparate mix of hardware and software that must be composed into a final solution that is complex to build and costly and fragile to operate. But does it have to be this way?
Join SoftIron CTO Kenny Van Alstyne in this session to explore and understand the transformative technology that underpins SoftIron’s HyperCloud - the world’s first complete technology for building clouds.

Don’t miss out on this opportunity to discover this groundbreaking new technology. 

Join us in this webinar to learn:
- The drawbacks with how clouds have traditionally been composed
- How rethinking the “silos” of compute network and storage can be transformative
- How the concepts like “state and statelessness” can empower a new cloud architecture 
- How fragmented  lifecycle management can be transformed into holistic fleet management deep in the the fabric of the technology
- How this enables HyperCloud to be deployed in as little as half a rack and half a day, yet to scale to almost infinity with just generalist IT skills, and with a fraction of the management overhead

Not Your Average Cloud: Transforming Cloud Technology With HyperCloud

Cloud is quickly becoming the tech enabler of choice to disrupt markets and sectors with differentiated products and services. Savvy business leaders are waking up to the Cloud arms race and utilising its innovative power to re-shape operations and gain competitive edge whilst at the same time harnessing opportunities to embed long term sustainability.

We’re no longer in the decade of lift and shift. If businesses aren’t using Cloud to innovate and drive sustainable outcomes in the next, they’ll simply be left behind. Cloud coupled with industry leading knowledge and insight holds real potential for businesses to be successful in both strategy and ambition whilst future-proofing at speed and scale.

In this session, Bijit Sikdar, Klairi Liis and Jason Sutherland explore the Current state of cloud Adoption & Maturity, Challenges & Mitigation approaches, the industry-centric thinking and trends driving accelerated adoption to the Cloud; with innovation, global issues and emerging challenges such as sustainability management at the heart of shaping solutions using Cloud products and services.

Meet our Panel of experts in the field:

Jason Sutherland (Director - Cloud CoE: Innovation & Strategy Lead, PwC)
Bijit Sikdar (Director - Cloud CoE: Multi Cloud Pre-Sales Architect, PwC)
Klairi Liis (Director - Consulting: Cloud Transformation and Sustainability Tooling, PwC)

Cloud Revolution: Accelerating Innovation to Future-Proof Business and Society

When we speak of innovation we invariably default to conversations about technology and how and where it can change our organisations, but true innovation requires creative, original thinking to create the innovative ideas in the first place. It is said that the definition of insanity is repeating the same process and expecting a different result. The same applies to how we think. We need a different approach to enable innovation.

Join us in this webinar to explore how different approaches to organisational thinking can unlock potential within your organisation and release the potential for greater innovation.

The Future of Innovation: Changing the Mindset

Accelerating Cloud Innovation in 2023

Organizations are looking for new ways to accommodate accelerating cloud growth and edicts. Business agility, competitive differentiation, and the desire to grow overall are the driving factors for cloud adoption. Cloud approaches are necessary in order for the business to evolve, but the transition isn’t easy. Many CIOs are tasked with adopting a cloud strategy but are equally challenged with keeping core business operations going. This puts a tremendous burden on IT as well as lines of business. In this keynote session, ESG Senior Analyst Paul Nashawaty will discuss the skill gaps that make it difficult for organizations to tackle cloud projects, how most organizations are adopting a distributed approach to cloud adoption, why application portability is important, and how the market is evolving to adapt to this new way of doing business.

Overcoming Obstacles to Cloud Innovation

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Network Infrastructure

Enterprise Cloud

Welcome to the virtualization community on BrightTALK! Whether it affects servers, storage, networks, desktops or other parts of the data center, virtualization provides real benefits by reducing the resources needed for your
infrastructure and creating software-defined data center components. However, it can also complicate your infrastructure. Join this active community to learn best
practices for avoiding virtual machine sprawl and other common virtualization pitfalls as well as how you can make the most of your virtualization environment.

Virtualization

Cloud computing has exploded over the past few years, delivering a previously unimagined level of workplace mobility and flexibility. The cloud computing community on BrightTALK is made up of thousands of engaged professionals learning from the latest cloud computing research and resources. Join the community to expand your cloud computing knowledge and have your questions answered in live sessions with industry experts and vendor representatives.

The data center management community focuses on the holistic management and optimization of the data center. From technologies such as virtualization and cloud computing to data center design, colocation, energy efficiency and monitoring, the BrightTALK data center management community provides the most up-to-date and engaging content from industry experts to better your infrastructure and operations. Engage with a community of your peers and industry experts by asking questions, rating presentations and participating in polls during webinars, all while you gain insight that will help you transform your infrastructure into a next generation data center.

Data Center Management

The storage community on BrightTALK is made up of thousands of storage and IT professionals. Find relevant webinars and videos on storage architecture, cloud storage, storage virtualization and more presented by recognized thought leaders. Join the conversation by participating in live webinars and round table discussions.

Storage

Network infrastructure professionals understand that a reliable and secure infrastructure is crucial to enabling business execution. Join the network infrastructure community to interact with thousands of IT professionals. Browse hundreds of on-demand and live webinars and videos to learn about the latest trends in network computing, SDN, WAN optimization and more.

As an IT professional, many of the problems you face are multifaceted, complex and don’t lend themselves to simple solutions. The information technology community features useful and free information technology resources. Join to browse thousands of videos and webinars on ITIL best practices, IT security strategy and more presented by leading CTOs, CIOs and other technology experts.

Overcoming Obstacles to Cloud Innovation

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Enterprise Architecture