On the eve of Mobility Field Day 14 and a three and a half hour long presentation by HPE/Juniper, I’m sitting once again as a Tech Field Day Delegate in my hotel in San Jose writing about HPE from a different perspective amongst celebrations of Telas Cybertrucks carrying Mexican Flags blast their Musica Española in celebration of Cinco de Mayo. All bringing me back to my days living in Puebla Mexico where the true Cinco de Mayo all began.
But let’s focus more on Greenlake.. and not the Greenlake that integrates with Aruba Central. The Greenlake that handles the HPE Private Cloud AI. The Cloud and Server farms side of the coin with some AI buzzwords mixed in. The one thing that continues is the long expanse of names including the HPE branding at the beginning.
I’m actually a big fan of HPE, I’ve been buying their servers for years and have several sites running Aruba switching and Wi-Fi APs. I’ve also anxiously been watching the Athonet acquisition and their Private 5G product lineup and hoping to see something come from that.
Then enter the AI Infrastructure Field Day 3 and HPE came with a completely different structure of gear than my Mobility, Wi-Fi, and Edge Field Day experiences of the past.
When it came to AIIFD3, HPE was the culmination of all the vendor presentation all wrapped up into one. They were the most complete across the field of having a product line that can handle the loads being thrown at it by AI. Unlike many of the other companies presenting, just one guy showed up and was had quite the time getting there with his flight, but it was worth it.
Data to AI Inferencing Pipeline
The biggest common denominator, I noticed at AIIFD3, was how to get Data from the Edge, where it is being collected, to the AI servers and GPUs for AI Inferencing and is actually useful. It is all about the Infrastructure, servers and networking, not the AI itself.
I’ve attended a couple Field Day events focused specifically on the Edge. The Edge, where the data is collected, how do we get the data to where it is needed when it is needed? Enter HPE Private AI Cloud.
During their AIIFD3 presentation, HPE showcased that you should:
Leave your data where it is then connect your data to the inferencing cluster
This is what everyone wants, but doing it is not so simple. That is the problem everyone at AIIFD3 was trying to solve. HPE seems to have the best view of that.
It comes down to a Task and Workflow problem. This leads to so many improvements by bringing the AI Infastructure into a Private Cloud instead of pushing it out to the Public Cloud.
After all the AIIFD3 presentation, I feel HPE has the best all around control of the full stack. The acquisition of Juniper/Mist and Athonet help bring that along. HPE is becoming a powerhouse that can stack up against the behemoths of Cisco world. I’m excited to see if HPE can truly deliver on this full stack approach across all their product lines.
Is the AI Private Cloud the right move for HPE? Time will tell, but from looking at the view of the AI Infrastructure view we got at AIIFD3, my bets are on them having the best shot. Now to see what they announce at Mobility Field Day 14 that fits along with this overarching footprint.
You can watch the whole coverage of the event here. Plus be sure to join me and my fellow delegate starting at 7:30am PDT with HPE/Juniper Networks talking all about AI, Wi-Fi, and a ton more stuff at Mobility Field Day 14.