Name: Activate Evergreen Digital Transformation with People, Data, Automation and AI
Start: 2022-11-16T13:00:00Z
End: 2022-11-16T13:00:35.000Z
Location: BrightTALK
Rating: 0

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.

The SNIA Cloud Storage Technologies Initiative (CSTI) conducted a poll early in 2024 during a live webinar “Navigating Complexities of Object Storage Compatibility,” citing 72% of organizations have encountered incompatibility issues between various object storage implementations. These results resulted in a call to action for SNIA to create an open expert community dedicated to resolving these issues and building best practices for the industry.  

Since then, SNIA CSTI partnered with the SNIA Cloud Storage Technical Working Group (TWG) and successfully organized, hosted, and completed the first SNIA Cloud Object Storage Plugfest (multi-vendor interoperability testing), co-located at SNIA Developer Conference (SDC), September 2024, in Santa Clara, CA. Participating Plugfest companies included engineers from Dell, Google, Hammerspace, IBM, Microsoft, NetApp, VAST Data, and Versity Software. Three days of Plugfest testing discovered and resolved issues and included a Birds of a Feather (BoF) session to gain consensus on next steps for the industry. Plugfest contributors are now planning two 2025 Plugfest events in Denver in April and Santa Clara in September.

This webinar will share insights into industry best practices, explain the benefits your implementation may gain with improved compatibility, and welcome your client and server cloud object storage team to join us in building momentum. Join us on November 21st where we’ll discuss:  
• Implications on client applications
• Complexity and variety of APIs 
• Access control mechanisms 
• Performance and scalability requirements
• Real-world incompatibilities found in various object storage implementations
• Missing or incorrect response headers
• Unsupported API calls and unexpected behavior

More information:
• SNIA CSTI https://www.snia.org/groups/csti
• SDC'24 https://www.sniadeveloper.org/
• Cloud Object Storage Plugfest (Sept. 2024)  https://www.sniadeveloper.org/cloud-object-storage-plugfest

Building Community to Tackle Cloud Object Storage Incompatibilities

Join us for an insightful webinar on the transformative impact of AI on networking. This session will delve into the various use cases of AI, the nature of traffic for different workloads, and the network impact of these workloads. We will explore the multiple networking challenges posed by AI and how Ethernet is evolving to meet these demands. Special focus will be given to congestion issues during model training, the role of Ultra Ethernet Consortium (UEC), and the specific requirements related to training large language models (LLMs) and other use cases.

Learning Objectives:
- Understand the different types of Network Topologies typically used with AI workloads.
- Identify the nature of traffic for various AI workloads and their impact on networks.
- Learn about the challenges Ethernet faces with AI workloads and the solutions being implemented.
- Explore a specific use case to see how Ethernet addresses bandwidth and congestion issues.

Don’t miss this opportunity to stay ahead in the rapidly evolving field of AI and networking. Register now to secure your spot and gain valuable insights from industry experts!

Ethernet in the Age of AI: Adapting to New Networking Challenges

Traditional application hosting strategies are increasingly redundant. As user expectations for instant access and seamless experiences grow, businesses are facing challenges like increased latency and security risks that hinder performance and harm customer satisfaction. 

Edge computing emerges as a transformative strategy that addresses these challenges by bringing computing resources closer to the end-user. This decentralization reduces latency and opens new avenues for enhanced security and scalability, allowing enterprises to host their applications more effectively alongside existing on-premises and cloud infrastructures.

In this session, Harri Gollipalli (Senior Software Development Manager at PayPal) will dive into the organizational approach to adopting edge computing. Join the session to get practical strategies for deploying edge solutions, enhancing security frameworks, and significantly improving application performance—all critical elements for staying competitive in a rapidly changing market.

Key Takeaways
- Enhanced Security: Learn how edge computing can reinforce your enterprise's security posture.
- Efficient Deployment: Gain insights into deploying applications at the edge for optimal performance.
- Improved Performance: Explore techniques to reduce latency and elevate the overall customer experience.
- And more...

Strategic Edge Computing: Elevating Security and Performance for Enterprises

As the digital landscape expands, edge computing emerges as a pivotal technology, pushing data processing to the frontier of the network to drive real-time insights and actions. However, the integration of edge computing with cloud infrastructure presents unique challenges and opportunities, especially in terms of security and seamless operations. This presentation aims to explore edge computing innovations, focusing on the strategies and technologies that ensure secure and fluid integration with cloud services.

This session will start by examining the current state of edge computing and its integral role in supporting IoT, AI, and real-time analytics applications across various industries. We will navigate through the architectural considerations for integrating edge computing with cloud platforms, highlighting the importance of creating a cohesive environment that leverages the strengths of both technologies.

We will then address security in edge-to-cloud integration. We will dissect the unique security challenges posed by distributed computing models and discuss strategies to safeguard data integrity, confidentiality, and availability. This includes the adoption of advanced encryption methods, secure access controls, and robust identity management systems, as well as the implementation of consistent security policies across the edge and cloud.

Join us in exploring how your organization can navigate the complexities of edge-to-cloud integration, harnessing the power of edge computing innovations to drive competitive advantage in a connected world.

Bridging the Gap: Enhancing Security in Edge-to-Cloud Integration for Next-Generation Computing

The rapid expansion of edge computing has introduced new cybersecurity challenges, particularly in decentralized and distributed environments. This presentation explores the emerging role of Generative AI (GenAI) in addressing these challenges and potentially reshaping the landscape of edge security.

We'll examine the current state of threat detection and response in edge computing, discussing its unique vulnerabilities and the limitations of traditional security approaches. The session will then delve into how GenAI technologies are being applied to enhance real-time threat detection, enable predictive analytics, and facilitate automated responses.

Through a series of case studies and theoretical models, we'll explore the potential benefits and limitations of GenAI in edge security. We'll discuss the broader implications of this technology for the future of cybersecurity, including ethical considerations and potential areas for further research and development.

Key Takeaways:
- Understand the specific security challenges unique to edge computing environments.
- Gain insights into the current and potential applications of GenAI in cybersecurity.
- Evaluate the effectiveness of GenAI-powered solutions in real-time threat detection and response.
- Hear real-world case studies of GenAI in action across various industries.

About the Speaker
Inna Ushakova is a pioneering tech entrepreneur who has built two successful and recognized companies, Scalarr and AI EdgeLabs, in the fields of AI-driven fraud prevention and cybersecurity.

Leveraging GenAI for Advanced Threat Detection and Response in Edge Computing

Edge computing plays a crucial role in industrial automation, particularly in enhancing communications. Here’s how:

1. REDUCED LATENCY:  By processing data closer to the source, edge computing minimizes the need to send data to a centralized cloud or data center. This significantly reduces latency, allowing for near-real-time decision-making and control.

2. IMPROVED RELIABILITY: Industrial environments often have connectivity challenges, such as network interruptions or bandwidth limitations. Edge computing ensures that essential operations can continue even if the connection to the central cloud is disrupted, enhancing system reliability and uptime.

3. EFFICIENT BANDWIDTH USAGE: Edge computing reduces the amount of data that needs to be transmitted to the cloud by filtering, aggregating, and analyzing data locally. Only the most relevant or summarized data is sent, which optimizes bandwidth usage and reduces communication costs.

4. ENHANCED SECURITY: Sensitive data can be processed and stored locally at the edge, minimizing the risk of exposure during transmission to the cloud. This decentralized approach can improve data security and compliance with regulations, especially in industries with stringent data protection requirements.

5. SCALABILITY: As industrial operations grow and more devices are connected (through IoT expansion), edge computing can help manage the increased data load without overwhelming central systems. It allows for scalable deployment of resources where they are needed most, at the edge of the network.

6. SUPPORT FOR REAL-TIME ANALYTICS AND AI: Edge computing enables the deployment of AI and machine learning algorithms directly at the production site. This capability supports real-time analytics and decision-making, improving process efficiency and productivity without relying on distant cloud resources.

Tune into this session to learn more.

The Value of Industrial Communications in Edge Computing

As organizations grow more reliant on real-time decision-making and data processing, edge AI has emerged as a critical technology to drive business value by enhancing speed, automation, and intelligence at the edge. Yet, the road to successfully deploying AI at the edge is complex,
 
This session will take you through a comprehensive exploration of edge AI, focusing on practical business outcomes and real-world use cases across industries like healthcare, manufacturing, and smart cities. 
 
By the end of this session, you will not only gain the technical knowledge to optimize edge AI for real-time data processing and decision-making but also understand how to drive tangible business value—from improving operational efficiency to reducing latency and delivering measurable ROI on your AI investments.
 
3 Key Takeaways:
1. Drive Business Outcomes with Edge AI: Learn how to harness the power of edge AI to deliver measurable business value, such as improved operational efficiency, cost reduction, and faster decision-making.
2. Overcome Industry-Specific Challenges: Explore solutions to key industry challenges, from regulatory compliance in healthcare to cost optimization in manufacturing, ensuring your edge AI strategy aligns with business goals.
3. Implement Scalable Edge Infrastructure: Gain actionable insights into building a scalable edge-to-cloud architecture, managing data flows securely, and deploying AI models in real-time with a future-proof infrastructure.
 
Who Should Attend: This session is ideal for CIOs, CTOs, and IT leaders focused on leveraging edge AI to drive business outcomes, enhance real-time decision-making, and optimize infrastructure. It also caters to IT architects, engineers, AI/ML practitioners, and industry professionals in sectors like healthcare, manufacturing, and IoT, who are looking for practical strategies to overcome specific industry challenges while deploying scalable, secure edge AI solutions.

Maximizing Business Impact and ROI with AI at the Edge: Harnessing Analytics, CI/CD, and Scalable Infrastructure

In today's rapidly evolving technological landscape, the convergence of DevOps and Edge Computing presents a powerful opportunity for innovation, particularly in distributed environments. This session explores how organizations can leverage the combined strengths of DevOps and edge computing to drive faster, more reliable, and secure deployments at the edge. Edge computing enables data processing closer to where it is generated, and when combined with DevOps practices such as automation and continuous integration, it opens the door to transformative possibilities across industries.

Key aspects covered include the low latency and real-time processing capabilities of edge computing and how DevOps can streamline infrastructure management at the edge. The session also addresses the challenges of deploying applications in resource-constrained, distributed environments and offers best practices to overcome these obstacles. Real-world case studies in smart cities, industrial IoT, and retail will demonstrate the practical benefits of DevOps at the edge.

Key Takeaways:
- Synergy of DevOps and Edge Computing.
- Overcoming challenges in edge environments.
- Real-world applications and future trends.

DevOps Meets the Edge: Accelerating Innovation in Distributed Environments

This presentation examines the critical role of storage solutions in optimizing AI workloads, with a primary focus on storage-intensive AI training workloads. We will highlight how AI models interact with storage systems during training, focusing on data loading and checkpointing mechanisms. We will explore how AI frameworks like PyTorch utilize different storage connectors to access various storage solutions. Finally, the presentation will delve into the use of file-based storage and object storage in the context of AI training: 
 
Attendees will:
- Gain a clear understanding of the critical role of storage in AI model training workloads
 - Understand how AI models interact with storage systems during training, focusing on data loading and checkpointing mechanisms
- Learn how AI frameworks like PyTorch use different storage connectors to access various storage solutions.
- Explore how file-based storage and object storage is used in AI training

The Critical Role of Storage in Optimizing AI Training Workloads

As generative AI copilots/ virtual assistants become widely available, companies are often struggling with justifying licensing and training costs, and in measuring ROI. In this session, Metrigy's Irwin Lazar, president and principal analyst, will share insights gathered from hundreds of end-user organizations. 

Attendees will learn: 
- How to measure ROI for generative AI collaboration tools. 
- How best to train users. 
- How generative AI apps are changing collaboration application deployments - How to translate time savings into measurable business value.

Realizing ROI for Generative AI in Collaboration

The “If you deploy it, they will use it” approach doesn’t work when it comes to UCC. Too many IT professionals focus exclusively on the architecture and design for UCC solutions, without taking into account the role of end user usage, adoption, and training to drive the overall success of a UCC. solution. This session we will focus on why end user adoption and training are so important, key findings from a usage and adoption study, and steps to drive adoption in order to get the most out of your UCC solution.

Key Takeaways 
- Why usage and adoption are even more important than the UCC technology itself
- How to develop a UCC end user adoption strategy
- Best practices for UCC training and adoption
- How to overcome some of the roadblocks to driving user adoption

Rethinking Unified Comms User Adoption

Unlocking a Sustainable Future for Data Storage

In a world of surging data demands, how can we reduce the environmental toll of storage solutions? Discover the power of the circular economy to reshape the storage industry for a greener tomorrow with this webinar, featuring Jonmichael Hands (Co-Chair SNIA SSD SIG and Board Member, Circular Drive Initiative) and Shruti Sethi (Sr. PM at Microsoft and Leadership Team, Open Compute Project-Sustainability).

Key Highlights:

- Circular Drive Initiative: Rethink the lifecycle of storage devices—from design to end-of-life—to unlock significant environmental benefits.
- Media Sanitization Best Practices: Securely erase data to enable reuse, extend device life, and cut down on e-waste. Explore techniques like:
- - Cryptographic erase
- - Block erase
- - Overwrite methods
- Compliance & Transparency: Learn how standards like IEEE 2883-2022 and ISO/IEC 27040:2024 guide secure data disposal, with organizations like SERI R2 and ADISA leading the charge in setting industry benchmarks.
- Carbon Accounting in Storage: Understand how tracking and reducing carbon emissions in storage aligns with global sustainability goals.

This session is your roadmap to driving real change by adopting circular economy principles, embracing advanced sanitization methods, and leveraging carbon accounting to reduce the industry’s environmental footprint.

Advancing Sustainable Storage: The Impact of the Circular Economy, Media Sanitization Policies, and Carbon Accounting

How can businesses effectively evaluate the diverse range of Low Code/No Code platforms available and identify the best fit for their specific needs and objectives?

Join serial entrepreneur and GTM expert Chaitra Vedullapalli, CISO and cybersecurity leader Cherie Griffith-Dunn, and IT executive Dexter Hardy as they discuss how organizations can effectively evaluate these technologies through various lenses, including: cost savings, time to market, employee productivity, and more.

Navigating the Low Code/No Code Landscape: Key Considerations for Your Business

The key to optimal SAN performance is managing performance impacts due to congestion. The Fibre Channel industry introduced Fabric Notifications as a key resiliency mechanism for storage networks in 2021 to combat congestion, link integrity, and delivery errors. These functions have been implemented by the ecosystem and have enhanced the overall user experience when deploying Fibre Channel SANs. This webinar explores the evolution of Fabric Notifications and the available solutions of this exciting new technology. In this webinar, you will learn the following:
• The state of Fabric Notifications as defined by the Fibre Channel standards.
• The mechanisms and techniques for implementing Fabric Notifications.
• The currently available solutions deploying Fabric Notifications.

The Evolution of Congestion Management in Fibre Channel

Organizations often operate data centers in multiple locations and are often geographically distributed to provide scale and disaster recovery capabilities. As with any fabric topology, scalability, data integrity and security are key requirements. This webinar will discuss how Fibre Channel can be effectively deployed in these applications using optical transport technology.  Topics to be covered:
• Optical Transport 101: A brief survey of optical networking (DWDM) technology 
• Fibre Channel transport via OTN 
• Robustness: Optical transport protection options: Resiliency against fiber outages
• Security: Optical transport OTN encryption: No-overhead layer 1 encryption that can be combined with IPSec or other higher-layer security protocols

Fibre Channel Data Center Interconnects (DCI): 64G FC and More

Just like a well-constructed burger requires carefully layering the right ingredients, securing multi-cluster deployments demands a thoughtful, layered approach. In this webinar, we'll deconstruct the multi-cluster burger, peeling back each layer to reveal security strategies for the infrastructure, applications, data, networking, observability, and overall security of components.

Key Takeaways
- Clarity on the different components or "layers" that make up a typical multi-cluster architecture.
- Insights into adopting a layered approach to security in multi-cluster and hybrid environments. They'll learn the importance of implementing security controls and best practices at each layer.
- Strategies for enforcing consistent security policies, access controls, and governance across all clusters and components in a multi-cluster setup.
- Need for centralized monitoring, logging, and observability tools to gain end-to-end visibility into the security posture and health of the entire stack.

Unwrapping Multi-Cluster Security: One Layer At A Time

One of the great challenges when implementing cybersecurity protection mechanisms is deciding between building a solution with a collection of "best-of -breed" solutions from various vendors or using a solution that can provide multiple layers of security using one overarching platform. There are good reasons to go in either direction. So how do you decide which is best for your specific needs? 

The presentation will provide useful insight to help you make that decision. It will provide useful information and consideration elements that can allow you to make the appropriate choice between various security products or a composite platform solution. 

Join this discussion to learn:
- How to evaluate various cybersecurity products.
- What is the difference between "best-of-breed" components and a platform solution.
- Cost and manpower considerations associated with the different solutions.
- The ability to use both of the options together for optimal protection.
- The various environments where each of the options would be considered the better solution.
- Creating a rational and defensible argument for your decision.

Best-of-Breed or a Platform Solution: Which is the Better Play?

Network infrastructure outages occur due to various factors like natural disasters, intentional attacks, and network failures. These outages are likely to result in the unavailability of critical network elements, impacts on services, and disruption of traffic flows. In order to protect themselves, companies should aim to implement strategies that both enable them to resist and tolerate failure and to recover mission critical communication elements within a business acceptable timescale. However, achieving this whole commitment can become a huge feat, dependent on the scope and age of the infrastructure, engagement with network providers, local distribution across multiple types of connectivity and services as well as the resources and network capacity necessary to manage the organizations “technology estate”.

Companies should ask themselves (as a starter) what strategy they are planning for and how they can best achieve this strategy within their technology structure. 

Tune into this session presented by our business continuity, disaster recovery, cyber resilience and major incident expert Steve Yates as he brings to light tips to redefine network infrastructure strategies in the “new world” as well as areas that companies must consider when considering resources and timescales for restoration of critical network services. Viewers are encouraged to privately share their major concerns in advance if they wish to gain the most from this session.

Viewers will come away from this session with the following takeaways:
- Become aware of common challenges they may encounter. 
- Form an understanding of redefining strategic direction.
- Ensure your organization embraces a joined-up thinking approach when delivering infrastructure resilience.

Redefining Network Infrastructure Strategies: What is the Key?

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Leading Change: A Leader's Guide to Successful Transformation

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Best Practices to Accelerate Your Digital Transformation

Making Data Work: Detect and Deliver Value via Data and Advanced Analytics

New Frontiers in SQL: Using Real-time Data and Document Databases in a Data Mesh

Leadership, Digital Transformation and Partnership with Fintechs

Optimising Healthcare Outcomes with AI and Advanced Technologies

How to Hyper-Perform with Human Artificial Intelligence

Accelerating Value-Driven Metaverse Adoption

Accelerating Digital Transformation

Too often, many organizations fail to harvest measurable business value due to legacy ways of working and measuring progress, siloed technologies and teams, a stagnant ecosystem of partnerships or other issues. Your ability to generate sustainable growth depends on mastering the interplay between people, data, automation and AI. This is a core operational challenge for many companies going forward -- and also the most important opportunity across industries.

In an evergreen enterprise, all of this happens naturally, organically, automatically. It does so because the business and its ecosystem are fed by a liquid asset that flows everywhere and energizes everything: data. The DNA of these companies intertwines the best of people working with machines to make smarter, faster moves based on human knowledge with AI, machine learning with creative inspiration, and automation with intuition.

Join Deloitte Consulting's Jim Rowan (AI & Data Operations Practice Leader) and and Sanghamitra Pati (US-India AI & Data Operations Offering Leader), to dig into the common challenges that businesses face on the path to sustainable, value-driving AI and data operations; and map out an evolved -- and ever evolving -- ecosystem model for the evergreen enterprise.

Activate Evergreen Digital Transformation with People, Data, Automation and AI

Artificial Intelligence

Machine Learning

Digital Transformation

Business Value

Automation

evergreen enterprise

data operations

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
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practices for avoiding virtual machine sprawl and other common virtualization pitfalls as well as how you can make the most of your virtualization environment.

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Activate Evergreen Digital Transformation with People, Data, Automation and AI

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