– Virtual FXT
– Avere and Big Data Analytics
– What comes next for Avere
Enjoy the podcast!
Here the transcript of the interview:
Enrico: Hi everyone, and welcome to a new episode of Juku Beats. Today I’m here with Bernhard Behn, technical marketing at Avere Systems. Hi, Bernhard. How are you?
Bernhard: Hello, Enrico. How are you?
Enrico: First of all I’m just curious to know what means technical marketing? What do you do in your role at Avere?
Bernhard: Yes sure, no problem. Technical marketing is really bridging the worlds between technical product knowledge and how to market our product, and make it useful for our customers. A lot of what I do is customer use case validation, application validation, and all the various different environments to ensure the best fit and performance of our solution in these customer scenarios.
Enrico: Good. Avere is very well known for it’s performance and [virtualization 00:00:54] features of it’s appliances which enable to [inaudible 00:00:58] performance from capacity. In the last few years you also added some management features for the [inaudible 00:01:09]. Lately you also have added a vehicle appliance [inaudible 00:01:14], which is theoretically strange for an iperformance appliance like yours. Can you explain how it fits in the overall architecturally? What are the primary use cases for that appliance?
Bernhard: Yes, absolutely. The overall architecture of what Avere is shooting for here is what we’re calling the Hybrid Cloud NAS. Hybrid Cloud NAS, the idea here is that everybody today has some component of on premises computer and on premises storage and now with the advent of cloud computing and cloud storage, those are additional resources that are quote unquote unlimited from a provisioning stand point, but they’re also somewhat difficult to use because they’re remote, the computer’s remote and the storage uses a different API. As part of the Avere technology umbrella, the addition of the virtual FXT as we call it for Amazon EC2, is to enable data access to the applications that are running in the cloud and allow the usage of the cloud based storage that these cloud service providers offer.
In the end, our goal is to enable our customers to take their application and data, and choose where they want to store it and where they want to run their applications. The Avere edge filer is the glue that’s going to be able to provide that experience to applications running in the cloud now that we have the addition of this virtual FXT. It is an edge filer that runs within the cloud that your applications can access their data as it’s cached there.
Enrico: Really interesting. Avere has already proven to be a very powerful solution for many computer intensive applications, and it is true at this point both for local and remote hybrid cloud environments. Do you see a potential for these appliances in big data analytics and if yes, what are you doing in this space to enable it’s adoption?
Bernhard: That’s a great question, Enrico and absolutely there’s a potential for our technology and big data analytics. In fact, that’s really what we’ve been involved with for the past six years before the hype and buzz words of big data analytics really bubbled to the top. We’ve been involved with all kinds of compute tasks that involve analysis of data, be it genomic sequencing, oil and gas exploration. You have processing of video data. You have processing of financial market data for simulation. These are all big data analytics uses that most of our customers have cooked up in house as part of their intellectual property of their applications.
Now with the cloud we’re starting to see more general purpose big data analytic platforms such as Splunk and Hadoop and all these other types of technologies that are being launched to more generically consumed big data. It’s in that space that we’re really trying to push forward with our experience running under custom applications that [users 00:04:34] have run and now trying to push our technology to sit as part of this more generic infrastructure that lives in the cloud for big data analytics. In terms of integration, not integration but in terms of being able to run with the applications like Splunk and Hadoop, and the next generation genomic sequencing, those are all excellent big data analytics workflows that are now moving towards the cloud that we can help with.
Enrico: Really, really interesting. Looking at the progression of your solution in the last three four years. In the beginning it was cache and accelerator, then you added a lot of feature for data migration, protection and objects [inaudible 00:05:20], and lately the vehicle FXT. Can you tell something about what are you cooking in your labs? What’s up next for the next months?
Bernhard: Absolutely. Really, you’re absolutely right. We started out as acceleration and added features, and now that we have these cloud based features to use, cloud storage and service cloud compute with our edge filer, really the next movement that we’re seeing is a lot more people moving their workloads into the cloud and also testing out and playing with the various cloud service providers out there. You have a lot of big names beyond Amazon web services that are out there pitching cloud compute and cloud storage services. It’s our belief that users are going to really start to leverage all of these different cloud providers for the various different strengths, perhaps geographical advantages and what not, and we want to be the ones that are enabling them to utilize all those vast resources in the most straight forward and simple way for their legacy enterprise compute applications that they were running in house.
Enrico: Great. Thank you. I would like to add more but this is a five minutes and three question podcast. Thank you very much for your time, Bernhard, and see you soon.
Bernhard: Yes, thank you Enrico and it was a pleasure talking to you.