Living here, I’ve “discovered”—everyone in Denver knows these places—some fantastic restaurants beyond the usual NFL city/convention center adjacent chains (Cheesecake Factory, Bubba Gump’s, Ruth’s Chris) that won’t break the bank or your diet.

Weather aside—you’ve been warned—I’m looking forward to a couple of Red Hat Conference sessions on observability and sustainability, two areas that are getting increasing attention in the open source community.

Serverless observability with OpenTelemetry. Daniel Oh’s talk on how to observe serverless functions with OpenTelemetry, Jaeger (distributed tracing), Knative , and Kubernetes should be a good one on instrumentation—the bane of “legacy” observability approaches, now championed and heavily supported by commercial Full Stack Observability purveyor, Cisco, now with added Splunk. I’m looking forward to seeing how OpenTelemetry works in serverless and exactly what sorts of differentiated metrics there are to be collected.

Update on Red Hat’s vision for sustainability and the Kepler project. I’m particularly excited for this session on IT sustainability. Sustainability in computing is becoming increasingly crucial, and we simply need to find ways to make our systems more efficient. This session focuses on Red Hat’s vision for Kepler, a Kubernetes tool that helps enterprises understand and reduce their energy consumption.

This aligns perfectly with our recent research­: The Role of ESG Programs in IT Decision Making, Enterprise Strategy Group, September 2022) which highlights the importance of translating broad environmental, social, and governance and sustainability goals into actionable steps. Kepler, with its focus on real-world power use metrics for reporting and reduction, exemplifies this approach to operationalizing sustainability. Red Hat, along with IBM and Intel, have been major contributors to this Cloud Native Computing Foundation project that leverages eBPF to gather energy related system stats and exports them as Prometheus metrics. I want to see how Red Hat envisions the future.

AnsibleFest Keynote: Automation, AI, and the next enterprise IT revolution. Revolution is not a word to be thrown around lightly, but when it comes to the impact that AI and automation can have on IT, Enterprise Strategy Group’s own research concurs that the future of IT involves automation and AI to accelerate operations anywhere from 25 to 100% over the next few years. Ansible plays a key role in automation for many organizations, so it will be interesting to hear how Red Hat envisions Ansible in the revolutionary era of AI.

Plus, it’s an industry trade show so it’s obligatory to speak about artificial intelligence. I wonder if Jensen Huang, CEO of Nvidia, is going to turn up on the main stage?

Mile-high oxygen bar. The event planners had enough foresight to include the oxygen bar on the daily agenda. Folks, the air is thinner here. The sun is brighter. Seriously, people. Stay hydrated and if need be stay oxygenated. Altitude sickness can ruin your day.

Dining Tips

I’m a Denver transplant. Here are a couple of insider meal tips for your stay in the Mile High City.

• The most Denver place to eat: Sams No. 3. Do not miss the green chili. Seriously, it’s one of the best things about Denver. You can walk there easily from the convention center.
• A good place for dinner away from the show: Rioja, a cozy modern Mediterranean spot in Larimer Square, a neighborhood that can be interesting even if you don’t eat here.
• A good place to go if you’re not paying: Uchi, a very modern sushi restaurant. Yes, there is one in Austin, too. It’s really great sushi despite being thousands of miles from any coast.

I am looking forward to seeing you at the show and I hope you enjoy the Mile High City.

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To learn more about these trends, download the free infographic, Operationalizing Encryption and Key Management.

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To learn more about these trends, download the free infographic, Generative AI for Cybersecurity: An Optimistic but Uncertain Future.

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Source: Enterprise Strategy Group Research Report, The State of DataOps: Unleashing the Power or Data, January 2024.

For most organizations, data is no longer only one of many elements that contribute to the success of business initiatives. On the contrary, data increasingly is the business, wielding formidable influence and power across numerous factors, including the ability to rapidly make informed business decisions. In turn, organizations are investing significant resources into the development of DataOps strategies that formalize parts and processes inherent to the data pipeline and help to build collaboration between stakeholders across the ecosystem. Data-centric challenges are extensive within any team connected to the organization’s data pipeline, including data producers, engineers, developers, and users. These challenges ultimately drive the adoption and use of technologies and processes designed to satisfy both common and unique data requirements.

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Why so long in the sector? Reason number one: Networks have never been more essential. Just look at our tech-heavy economy and you quickly realize that without reliable, high-performing networks, at the local, wide area, data center and internet levels, everything grinds to a halt. Networks are the plumbing of the modern world, and just like the physical plumbing in our homes and businesses, they are often taken for granted because they just work. But when something doesn’t work, networks typically get the first blame. And while networks do have their fair share of culpability, the reality is that problem sources are more commonly elsewhere in the stack—in the apps, servers, storage, endpoint or, in no small percentage of cases, with Layer8—the user themselves.

Reason number two: When there is a problem and there is no obvious cause—such as a server or switch on fire—then the network can be an excellent place from which to start the process of isolation and identification. Just like a traffic map for a busy metro area, viewed in Google Maps or Waze, you can use the network to quickly recognize where things are working smoothly and where they are not, so you can zoom in on the most likely source of issues, accelerating and focusing efforts to restore normal function.

Reason number three: It’s never dull. There is so much change to keep up with. Networking technology has largely settled in at Layers 2-4, converging around Ethernet and TCP/IP, and this is a good thing. No one wants to go back to the days of FDDI, Token Ring, IPX and Banyan Vines, when interoperability was a massive challenge. But this convergence does not mean the fun is over. There is still innovation due to the relentless growth in network speeds and capacity, and we continue to see evolution and change in other parts of the stack. Witness the continued, rapid development of wireless access, such as WiFi 6, 6+, 7, and Private LTE and 5G. Look for some fresh insights coming from Enterprise Strategy Group on this topic very soon.

And we can’t forget the fascinating work going on to support purpose-built generative AI (GenAI) infrastructure, including the use of both traditional networking technologies and specialized tech developed for storage networking such as RoCE—RDMA over Converged Ethernet—and Infiniband. I’ll be tracking the latter under the general heading of “Networking for AI.” I’ll be writing more on this very soon as well.

Of course, the change does not stop there. Personally, I’m fascinated by a number of ongoing developments in the sector, and hope to spend time studying and covering the following issues and challenges:

• Convergence of networking and network security. In my view, this is an absolute necessity in today’s connected world, lately manifesting using integrated functions, SASE, SSE and multipurpose monitoring and analytics techniques.
• Multi-cloud, hybrid networking. This freight train has been heading toward us for a long time, bringing major complexity headaches, but also opportunities to rethink network strategies.
• Network-as-a-Service. Part of a broader move toward a subscription basis for acquiring and licensing network technology, but also a great alternative for modernizing and hardening enterprise networks.
• AI for Networking. GenAI and natural language processors are already working their way into network management tools for diagnostic and troubleshooting workflows, but can they also make a difference in planning, configuration and overall network automation?
• Network Observability. Making sure that proactive, effective visibility exists across complex, hybrid networks, and is fully integrated with cross-domain observability stacks continues to be a priority for most but also a struggle for many.

There’s more, but that should be enough to get me off and running. As I renew old contacts and make new ones across the networking sector, I’ll have my head up and ears open for feedback. What excites you about networking and network management today? What areas of change are you most interested in? I’d love to hear and discuss.

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Despite these risks, generative AI holds great cybersecurity potential. Generative AI could help improve security team productivity, accelerate threat detection, automate remediation actions, and guide incident response. These prospective benefits are so compelling that many CISOs are already experimenting with GenAI or building their own security LLMs. At the same time, security professionals remain anxious about how cybercriminals may use GenAI as part of attack campaigns and how they can defend against these advances.

Have organizations embraced GenAI for cybersecurity today, and what will they do in the future? To gain further insight into these trends, TechTarget’s Enterprise Strategy Group surveyed 370 IT and cybersecurity professionals at organizations in North America (US and Canada) responsible for cyber-risk management, threat intelligence analysis, and security operations, with visibility into current GenAI usage and strategic plans.

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