#Cisco Data

[nrgnews-it]

Nexus: The Dawn of IoT Consciousness – The Revolution Illuminating Big Data Chaos

[jcmarchi]

AI-powered incident management: Risk analysis and remediation

New Post has been published on https://thedigitalinsider.com/ai-powered-incident-management-risk-analysis-and-remediation/

AI-powered incident management: Risk analysis and remediation

Date: Friday, April 25 2025 @ 1PM ET / 10AM PT / 6PM BST | Location: Online

Unlock smarter, faster, and more scalable incident management.

IT teams are under increasing pressure to detect, investigate, and resolve incidents faster than ever. But with siloed data, manual processes, and escalating complexity, teams struggle to keep up, leading to slow resolutions, poor customer experiences, and costly downtime.

Join us and BigPanda where we’ll explore how AI is transforming incident management to accelerate investigations, surface relevant insights, and dynamically scale workflows.

Why attend?

🚨 Siloed data and institutional knowledge make it hard to get a complete picture of incidents.

📉 L1 NOC and service desk teams lack context, leading to unnecessary escalations and slow response times.

🔄 Manual processes and poor communication create inefficiencies, massive bridge calls, and poor documentation.

By attending, you’ll learn how organizations are saving an average of 30 minutes per task during incident investigations.

What you’ll walk away with:

We’ll walk you through real-world use cases and practical strategies to optimize ITSM workflows using AI. You’ll discover how to:

✅ Augment team knowledge – Equip responders with AI-driven insights, including impact assessment, priority scoring, and change risk analysis, so they can resolve incidents faster and more effectively.

✅ Streamline incident processes – Reduce manual, broken workflows by ensuring the right teams are engaged at the right time, improving internal communication and collaboration.

✅ Prevent future incidents – Analyze operational and ITSM data to detect recurring issues, measure gaps, and implement proactive fixes before they escalate.

Hosted by:

Katie Petrillo Senior Director, Product Marketing at BigPanda

As the senior director of product marketing, Katie is an experienced go-to-market leader with a deep understanding of IT Operations, Incident Management, and Cybersecurity markets and buyers. At BigPanda, Katie leads a team of product marketers, and uses customer and market insights to tell compelling stories for customers, prospects, and internal audiences.

Travis Carlson Senior Product Manager – AI Products at BigPanda

Travis Carlson leads product management for AI Products at BigPanda and is known for his ability to quickly study, thoroughly understand, and think critically about extraordinarily complex systems. He’s doing this at BigPanda as he drives the GTM development and release of BigPanda’s generative AI technology, Biggy AI. He’s previously developed products at Cisco and VMware, and has an MBA from MIT.

[cybersecuritycue]

Cisco Data Breach Confirmation to Authenticity of Data After Second Leak

On October 14, 2024, Cisco faced a significant cybersecurity challenge as a hacker group, led by an individual known as IntelBroker, leaked sensitive data allegedly obtained from the company. Now, the Cisco data breach confirmation has arrived. The data breach incident raised concerns about the security of Cisco’s systems and its customer-facing resources. Cisco has since confirmed the…

[peterbordes]

Understanding Cisco Nexus: The Backbone of Modern Data Centers

[xcalable24]

C9300L-48T-4X-A Cisco Catalyst 9300L 48P DATA NTWK ADVANTAGE 4X10G UPLINK

[puspendratalks]

CCIE Data Center V3.0 Training and Certification- CCIE HUB Technology

The CCIE data center is a reputed networking certification. It is recognized as a network engineer's proof of skill, knowledge, and expertise. It offers deep technical knowledge to make a professional ready to take on the data center assignment challenges in the industry.

The CCIE certification is recognized globally as the pattern and the program is continuously upgraded by Cisco. The program quality, tested methods, and the relevance of the program to the core industry practices make it a desirable course for someone looking for a jump in their IT career.

[radiantindia]

Cisco Catalyst 3000 Series: High-Performance Switching Solutions

Learn about Cisco Catalyst 3000 series switches, their advanced features, pricing insights, deployment scenarios, and where to buy in India through Radiant Info Solutions.

[dclessonsonline]

The Benefits of Cisco ACI in the Data Center

Data centres are evolving every day to implement new and efficient strategies for faster usage. Now data centres all over the world are adapting Cisco ACI technology. These Cisco ACI data centres ensure efficiency, scalability, and security. They have revolutionized the way data centres work and give people a valuable service for guiding and taking a very important part in the operation of a company. The Cisco ACI labs help improve the agility and security of the company. In this article, we will look at the benefits of Cisco ACI labs in data centres.

Automation Cisco ACI is a holistic software-defined networking (SDN) approach that helps them achieve faster processing and proper traffic distribution, which improves the service quality of data centres. The main and most important feature of the Cisco ACI data centre is automation, which eliminates the possibility of human error and thus delays the process. Automation has greatly increased the operational capacity of data centres. Giving them agility and precision and enabling them to manage better. This error-free operation of Cisco ACI Labs has great application usage, which ensures consistency and error-free network configuration.

Simplified Operations Humans have achieved a lot more precision and efficiency after the development of artificial intelligence, as computers have the capability to do the same work with great precision and without a break. Automating things in Cisco ACI data centres can handle large amounts of data at once and thus help provide faster and better service to customers. They have greatly reduced the use of human interaction and human errors. They have simplified the whole process of how these data centres used to work. This has not only helped people get their problems solved but also increased overall employment as they have more scalability and great precision.

Enhanced Security Security is the top concern for any data centre. There is always a great risk that a hacker might intrude into their workload and access the secret information of the company, threatening the overall foundation of the company. In the modern era of Cisco ACI data centres, they have induced technology to decrease the spread of threats in their program. They have used the micro-segmentation process, thus limiting the spread of hacks from one system to another so that the problem can be solved in the individual system only.

Conclusion Cisco ACI labs have transformed how data centres used to work and secure their systems. The automation technology has increased their working performance and made the process easier much safer and more efficient to work on. Increasing the service quality that they provide. Cisco ACI data centres have adopted the latest technology that will help them in the long term by decreasing the chances of human intervention and making the system much more efficient and error-proof.

Microsegmentation and enhanced network configuration have proven that Cisco ACI data centers are much better than traditional ones. DC Lessons has launched its course on Cisco ACI training on its online platform with the best-experienced teachers. Grab your certification now to get started.

For more information about Cisco Aci Data Center please visit the website.

[jcmarchi]

DevAI Raises $6M to Revolutionize Enterprise IT with Network Intelligence Agents

New Post has been published on https://thedigitalinsider.com/devai-raises-6m-to-revolutionize-enterprise-it-with-network-intelligence-agents/

DevAI Raises $6M to Revolutionize Enterprise IT with Network Intelligence Agents

In a major boost to enterprise IT, DevAI, a rising force in AI-powered IT solutions, has secured $6 million in an oversubscribed seed round led by Emergence Capital. The round also saw participation from Pear VC, Base10, and Benchstrength, following an earlier $1 million pre-seed investment from Pear VC.

DevAI is tackling a critical challenge in the $2.5 trillion IT software and services market: IT teams are bogged down by fragmented tools, unreliable system data, and an over-reliance on institutional knowledge. With enterprise IT professionals spending up to 80% of their time on KTLO (Keep the Lights On) activities—tasks essential to maintaining IT infrastructure but with minimal direct business impact—DevAI is stepping in with AI-driven solutions to optimize workflows and reduce downtime.

At the heart of DevAI’s offering is the DevAI Network Intelligence Engine, a system that aggregates insights from IT tools, industry best practices, and institutional expertise. The company’s first AI agent, Neo, is designed to streamline IT workflows, enhance security and compliance, and minimize time spent troubleshooting.

“IT professionals are the unsung heroes of modern enterprises, working around the clock to ensure IT systems stay online and networks are secure and performing their best,” says Susie Wee, cofounder and CEO of DevAI. “Our network AI agents give them the insights they need to proactively address issues and eliminate inefficiencies so they can focus on business priorities and innovation instead of constant firefighting.”

Wee, a former Cisco executive, is no stranger to transforming enterprise IT. She earned her Ph.D. from MIT and previously founded DevNet, Cisco’s developer program, which grew to over half a million members. She now brings that experience to DevAI, aiming to arm IT professionals with AI tools that capture institutional knowledge, enrich IT infrastructure data, and accelerate productivity.

Wee’s cofounder, Edwin Zhang, brings deep expertise in enterprise technology, cloud, and software platforms. He and Wee have collaborated for over a decade on award-winning enterprise solutions.

“Neo isn’t just another AI tool—it’s a tech buddy for IT professionals,” says Zhang. “Neo works alongside them, gathering information from across their systems, reducing the time they spend troubleshooting, and empowering them to solve complex problems faster.”

Addressing the Enterprise IT Knowledge Gap

Enterprise IT teams struggle with inconsistent “source of truth” systems, where different IT tools provide conflicting information on configurations, assets, and infrastructure. DevAI’s technology gathers and enriches data from multiple sources, creating an accurate and centralized repository of institutional knowledge. The solution enables IT teams to:

Reduce MTTI (Mean Time to Identify) and MTTR (Mean Time to Resolve) incidents, minimizing costly downtime.

Improve source of truth accuracy by consolidating and validating data from different IT tools.

Capture and retain institutional knowledge, preventing information loss when tenured IT professionals leave an organization.

Free up domain experts from repetitive tasks, allowing them to focus on strategic initiatives.

Investor Confidence in DevAI’s Market Potential

Emergence Capital’s backing signals confidence in DevAI’s ability to transform enterprise IT operations.

“We couldn’t be more excited to partner with Susie and the DevAI team to transform enterprise IT management, bringing much-needed automation and intelligence to an area ripe for innovation,” says Santi Subotovsky, General Partner at Emergence Capital. “When we talked to DevAI’s sophisticated enterprise customers and heard how DevAI aligns with their growing demand for smarter, AI-powered tools to reduce costs and enhance productivity, we were convinced DevAI was creating real value for enterprises.”

Mar Hershenson, founding managing partner at Pear VC, echoes this sentiment: “Susie founded DevNet and learned firsthand from the community the problem of managing complex enterprise networks. Using an agentic framework to optimize implementations and maintenance will allow these experts not only to spend time on more strategic matters but also increase network reliability.”

Real-World Impact: Partnering with Industry Leaders

Beyond investor support, DevAI is already working with major enterprises, including FedEx and Cigna, to refine its AI-driven solutions through real-world deployment.

Aryo Kresnadi, Technical Director at FedEx, emphasizes the importance of DevAI’s collaboration: “We need to architect our network to support our business today and for the next 5, 10, and 20 years. Working closely with DevAI has allowed us to design solutions for critical areas we have not been able to address to date.”

The Road Ahead: Scaling AI for Enterprise IT

With its fresh injection of capital, DevAI plans to expand its AI-powered agent solutions, onboard more enterprise partners, and enhance its platform’s capabilities. The company is building a thriving IT community, inviting enterprises to join as design partners to shape the next generation of AI-driven IT management.

[nitizsharmaglobaltech]

Data Center Energy Efficiency: Best Practices for Sustainability

As the demand for data centers grows, so does their energy consumption, leading to higher operational costs and environmental concerns. Energy efficiency is a critical factor for sustainable data center operations. 

By adopting advanced technologies and strategies, such as renewable energy, optimized cooling systems, and real-time energy monitoring, organizations can reduce their carbon footprint while boosting performance. 

For IT professionals, including those pursuing the CCIE Data Center certification, understanding these best practices is essential to stay ahead in the industry. This blog explores key strategies to achieve energy efficiency, ensuring cost-effectiveness and sustainability in modern data centers.

The Importance of Energy Efficiency in Data Centers

Cost Reduction: Lowering energy usage directly reduces operational expenses.

Environmental Responsibility: Promoting sustainability helps meet global environmental goals and reduces carbon footprints.

Enhanced Performance: Efficient energy use ensures consistent performance and minimizes equipment downtime.

Regulatory Compliance: Many regions have introduced energy efficiency standards for data centers, making compliance crucial.

Adopting Green Building Standards for Data Centers

LEED Certification: Leadership in Energy and Environmental Design (LEED) certification ensures environmentally responsible construction and operation.

Energy Star for Data Centers: This certification identifies facilities that meet strict energy performance criteria.

Efficient Building Design: Implementing energy-efficient lighting, insulation, and renewable energy integration supports green initiatives.

Optimizing Power Usage Effectiveness (PUE)

Definition: Power Usage Effectiveness (PUE) is the ratio of total facility energy to IT equipment energy.

Goal: Aim for a PUE close to 1.0, indicating efficient energy usage.

Regular Audits: Conduct energy audits to identify inefficiencies.

Efficient Equipment: Upgrade outdated hardware to more energy-efficient alternatives.

Load Balancing: Distribute workloads effectively to prevent overuse of specific servers.

Leveraging Renewable Energy Sources

Solar Power: Installing solar panels reduces dependence on non-renewable energy.

Wind Energy: Utilize wind farms to supply power.

Hydropower: Partner with hydropower facilities for clean energy.

Carbon Offsetting: Invest in renewable energy credits to offset carbon emissions.

Efficient Cooling Solutions for Data Centers

Optimizing Airflow: Use hot aisle/cold aisle configurations to improve cooling efficiency.

Sealing Gaps: Prevent air leaks to ensure efficient temperature management.

Raising Temperature Set Points: Modern equipment can operate efficiently at slightly higher temperatures, reducing cooling needs.

Liquid Cooling vs. Air Cooling

Liquid Cooling: Offers higher efficiency and a smaller footprint but involves higher initial setup costs and maintenance complexity.

Air Cooling: Easier to maintain and involves lower upfront costs but is less efficient and has higher energy consumption.

The Role of Virtualization in Reducing Energy Consumption

Server Consolidation: Virtualization reduces the number of physical servers required, cutting energy use.

Dynamic Resource Allocation: Allocate resources based on demand to avoid energy wastage.

Energy Savings: Virtualization can reduce energy consumption by up to 30%.

Harnessing Automation for Energy Optimization

AI-Driven Cooling: Use artificial intelligence to optimize cooling systems in real time.

Energy Monitoring Tools: Implement tools to automate power usage analysis and optimization.

Predictive Maintenance: Automation ensures timely maintenance, preventing energy losses due to equipment inefficiencies.

Monitoring and Managing Energy Consumption in Real-Time

IoT Sensors: Deploy sensors to track energy consumption across facilities.

Energy Management Platforms: Utilize software solutions to analyze and report energy usage.

Key Metrics Tracking: Monitor PUE, carbon emissions, and cost savings in real-time.

Case Studies: Success Stories in Sustainable Data Centers

Google’s Data Centers: Achieved a PUE of 1.10 through advanced cooling techniques and AI-driven optimization.

Microsoft’s Underwater Data Center: Leveraged ocean cooling to reduce energy costs.

Facebook’s Luleå Data Center: Operates on 100% renewable energy and employs natural cooling techniques.

Data Center Energy Challenges

High Energy Demand: Data centers require vast amounts of energy to power servers, storage devices, and networking equipment.

Cooling Requirements: Maintaining optimal temperatures to prevent overheating consumes a significant portion of energy.

Rising Operational Costs: Increased energy usage translates into higher costs, impacting the bottom line.

Environmental Impact: Excessive energy consumption contributes to carbon emissions, necessitating environmentally friendly practices.

Future Trends in Data Center Energy Efficiency

Edge Computing: Reducing energy by processing data closer to its source.

Advanced Cooling Solutions: Innovations like immersion cooling for better thermal management.

Energy Storage Systems: Deploying batteries and other storage systems for renewable energy integration.

Sustainable Building Materials: Using eco-friendly materials in construction.

Conclusion

Adopting energy-efficient practices in data centers is essential for achieving sustainability while minimizing operational costs. By implementing strategies like efficient cooling systems, virtualization, renewable energy integration, and proactive monitoring, organizations can significantly reduce their carbon footprint. 

These practices not only enhance energy efficiency but also align with global environmental goals. To manage and optimize energy-efficient data centers, specialized expertise is crucial. Enrolling in CCIE Data Center Training equips professionals with advanced skills to design, implement, and maintain sustainable data center infrastructures. Stay ahead in the industry by combining technical expertise with a commitment to sustainability.

[mariacallous]

Ever since OpenAI released ChatGPT at the end of 2022, hackers and security researchers have tried to find holes in large language models (LLMs) to get around their guardrails and trick them into spewing out hate speech, bomb-making instructions, propaganda, and other harmful content. In response, OpenAI and other generative AI developers have refined their system defenses to make it more difficult to carry out these attacks. But as the Chinese AI platform DeepSeek rockets to prominence with its new, cheaper R1 reasoning model, its safety protections appear to be far behind those of its established competitors.

Today, security researchers from Cisco and the University of Pennsylvania are publishing findings showing that, when tested with 50 malicious prompts designed to elicit toxic content, DeepSeek’s model did not detect or block a single one. In other words, the researchers say they were shocked to achieve a “100 percent attack success rate.”

The findings are part of a growing body of evidence that DeepSeek’s safety and security measures may not match those of other tech companies developing LLMs. DeepSeek’s censorship of subjects deemed sensitive by China’s government has also been easily bypassed.

“A hundred percent of the attacks succeeded, which tells you that there’s a trade-off,” DJ Sampath, the VP of product, AI software and platform at Cisco, tells WIRED. “Yes, it might have been cheaper to build something here, but the investment has perhaps not gone into thinking through what types of safety and security things you need to put inside of the model.”

Other researchers have had similar findings. Separate analysis published today by the AI security company Adversa AI and shared with WIRED also suggests that DeepSeek is vulnerable to a wide range of jailbreaking tactics, from simple language tricks to complex AI-generated prompts.

DeepSeek, which has been dealing with an avalanche of attention this week and has not spoken publicly about a range of questions, did not respond to WIRED’s request for comment about its model’s safety setup.

Generative AI models, like any technological system, can contain a host of weaknesses or vulnerabilities that, if exploited or set up poorly, can allow malicious actors to conduct attacks against them. For the current wave of AI systems, indirect prompt injection attacks are considered one of the biggest security flaws. These attacks involve an AI system taking in data from an outside source—perhaps hidden instructions of a website the LLM summarizes—and taking actions based on the information.

Jailbreaks, which are one kind of prompt-injection attack, allow people to get around the safety systems put in place to restrict what an LLM can generate. Tech companies don’t want people creating guides to making explosives or using their AI to create reams of disinformation, for example.

Jailbreaks started out simple, with people essentially crafting clever sentences to tell an LLM to ignore content filters—the most popular of which was called “Do Anything Now” or DAN for short. However, as AI companies have put in place more robust protections, some jailbreaks have become more sophisticated, often being generated using AI or using special and obfuscated characters. While all LLMs are susceptible to jailbreaks, and much of the information could be found through simple online searches, chatbots can still be used maliciously.

“Jailbreaks persist simply because eliminating them entirely is nearly impossible—just like buffer overflow vulnerabilities in software (which have existed for over 40 years) or SQL injection flaws in web applications (which have plagued security teams for more than two decades),” Alex Polyakov, the CEO of security firm Adversa AI, told WIRED in an email.

Cisco’s Sampath argues that as companies use more types of AI in their applications, the risks are amplified. “It starts to become a big deal when you start putting these models into important complex systems and those jailbreaks suddenly result in downstream things that increases liability, increases business risk, increases all kinds of issues for enterprises,” Sampath says.

The Cisco researchers drew their 50 randomly selected prompts to test DeepSeek’s R1 from a well-known library of standardized evaluation prompts known as HarmBench. They tested prompts from six HarmBench categories, including general harm, cybercrime, misinformation, and illegal activities. They probed the model running locally on machines rather than through DeepSeek’s website or app, which send data to China.

Beyond this, the researchers say they have also seen some potentially concerning results from testing R1 with more involved, non-linguistic attacks using things like Cyrillic characters and tailored scripts to attempt to achieve code execution. But for their initial tests, Sampath says, his team wanted to focus on findings that stemmed from a generally recognized benchmark.

Cisco also included comparisons of R1’s performance against HarmBench prompts with the performance of other models. And some, like Meta’s Llama 3.1, faltered almost as severely as DeepSeek’s R1. But Sampath emphasizes that DeepSeek’s R1 is a specific reasoning model, which takes longer to generate answers but pulls upon more complex processes to try to produce better results. Therefore, Sampath argues, the best comparison is with OpenAI’s o1 reasoning model, which fared the best of all models tested. (Meta did not immediately respond to a request for comment).

Polyakov, from Adversa AI, explains that DeepSeek appears to detect and reject some well-known jailbreak attacks, saying that “it seems that these responses are often just copied from OpenAI’s dataset.” However, Polyakov says that in his company’s tests of four different types of jailbreaks—from linguistic ones to code-based tricks—DeepSeek’s restrictions could easily be bypassed.

“Every single method worked flawlessly,” Polyakov says. “What’s even more alarming is that these aren’t novel ‘zero-day’ jailbreaks—many have been publicly known for years,” he says, claiming he saw the model go into more depth with some instructions around psychedelics than he had seen any other model create.

“DeepSeek is just another example of how every model can be broken—it’s just a matter of how much effort you put in. Some attacks might get patched, but the attack surface is infinite,” Polyakov adds. “If you’re not continuously red-teaming your AI, you’re already compromised.”

[lostlibrariangirl]

03.03.2025

Life is getting better.

After so many days in the hospital, my husband is very well, I am studying and exercising again... It feels like a rebirth 🐦‍🔥

I will start my new job this month, working with vulnerabilities (awareness, understanding root cases, extracting data from the management tools of the company, work closer to other internal Cybersecurity teams to help the department developers). I am not afraid, not because I am extremely courageous, but couldn't think about that until now 😄 the hospital situation was taking my whole time and effort.

I will continue my Ethical Hacker course with Cisco and started the AWS Cloud practitioner certification studies to get this one and the AI at least until July.

Thank God one phase is over! Let's to energize and go to the next one (a better one, I hope, 'cause I had enough hardcore mode in this first two months of 2025).

🌼 have a great week, guys!

[authortobenamedlater]

Seen these going around and decided to do one of my own!

I specifically did not include Commander Data because I knew he’d win 🤣