When I started the AWS Podcast back in 2011, it was driven by a desire to help educate and inform about a radical change taking place in how IT was being delivered and consumed. From humble beginnings, it became a regular part of the listening “diet” of thousands of people in over 100 countries. It was always exciting to hear from listeners in far-flung lands about how they were adopting cloud, and developing applications in new and powerful ways.
When I moved to Pivotal, many listeners reached out to me to ask if I would continue with a podcast, and I am really happy to say YES!
The work we do at Pivotal spans so many interesting areas, that I am sure a lot of former listeners will be keen to add this new podcast to their rotation. Whether you are interested in Platform-as-a-Service, Big Data, Data Science Agile, Cloud, Software Architecture—there is something in this podcast for you!
Different people like to consume information through a variety of different media.
We are fortunate today to have so many choices—video, audio, written word and so many delivery mechanisms such as broadcast, narrowcast, subscription, etc.
As a general rule, most people have a thirst for knowledge. And in my experience, technically-oriented people have a significant thirst!
One way to quench some of that thirst is to find easy to consume, useful information sources. Podcasts fit the bill wonderfully! They are totally portable, consumable in your own timeframe and fit wonderfully into those “slack times” such as a commute, a walk, or even mowing the lawn!
So today we are launching the All Things Pivotal Podcast. This is a regular podcast that covers all aspects related to the work Pivotal does with customers, the types of technological advancements we are contributing to and the kinds of businesses that are evolving based on Pivotal Software technologies. You can grab the feed from iTunes or right here: http://pivotal.io/podcasts.
The podcast will be regular, and run around 15-20 minutes per episode. There will be longer “deep dives” and interviews with experts in their field, as well as more general conversations about topics of relevance and interest. Being at the intersection of Cloud, Big Data and Agile—there are no shortage of interesting topics to discuss!
I am really excited to be able to produce this podcast for you, and hope it becomes a regular part of your podcast listening rotation!
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Welcome to the All Things Pivotal Podcast. The podcast at the intersection of agile, cloud, big data. Stay tuned for regular updates, technical deep dives, architecture discussions and interviews . Please share your feedback with us by email email@example.com.
Hello, everybody and welcome to episode number one of the Pivotal Software podcast. Fantastic to have you with us. My name’s Simon Elisha, I’m CTO and field engineering manager of Pivotal Software in Australia and New Zealand and I’m really excited to have you join us for this brand new podcast episode number one, coming to you from beautiful Melbourne, Australia, where it is sunny, clear and gorgeous, as it is not often.
What is this podcast going to be about? Well, it’s going to be all about Pivotal Software and many of you might say, ‘Well, what is Pivotal? What does Pivotal do? How does it fit in?’ So, I thought for these first episodes we might try and talk a little bit about what Pivotal is and more importantly, what customers would talk to Pivotal about and what they do with the components. In the future we’ll go into far more depth on a lot of things, but I thought it would be nice to have a little overview. So, here we go.
Pivotal is really the company that’s at the intersection of big data, platform as a service and agile development and it really helps companies turn themselves into great software companies. Now, we see a lot of organizations changing the way go to market, changing the way they move into the market, to having a very much more software-focused approach, because they recognize that software components can give them the differentiation they need from their competition.
We also have a far more digitally savvy work force and certainly a far more digitally-focused user base than ever before and consumer base, of course; so people are looking to primarily consume things via digital channels to interact with their organizations digitally and this requires a different level of interaction, a different level of software. What this has done has allowed a new generation of developers to come through and to really shift the way that we deliver platforms and processes. These developers who work in agile teams and they need a platform that supports this agile development methodology so that they can work continuously, they can deliver updates very quickly and they can also scale and grow their applications, importantly without down time. We live in a global, 24/7 world and there’s no time for downtime any more. This changes the way that software has to be developed and importantly, how it’s deployed and operated.
They also want to see an easy way to get access to these huge data sets that organizations either have or create as they operate and to be able to do really detailed analytics on top of that and drive iteration of their software based on customer behavior and customer needs to create this really interesting and tight feedback loop between customer behavior and the software creator for those customers. Now, that is a topic worthy of many podcasts and we’ll talk a lot about that in the future, but that’s just taste as a theme, if you like, of what we try and talk about.
Now, how was Pivotal founded? Where did it come from? It’s an organization that is backed by EMC, VMWare and General Electric. It’s led by Paul Maritz, who many of you may know from his amazing leadership work at VMWare, EMC and Microsoft. It’s an organization that’s designed to create an agile organization to serve agile customers. So, what do customers actually talk to Pivotal about? Well, there’s a few different dimensions that I wanted to share with you. Firstly, they love to talk about platform as a service and obviously Pivotal has a piece of software called ‘Pivotal Cloud Foundry’. Pivotal Cloud Foundry is a platform that makes it easier to deploy and operate your applications. What this means from a business perspective is that you can move faster and with much lower risk, because you can integrate changes more frequently and make those changes smaller. Also, from an operational perspective, it simplifies the way applications are run, managed and troubleshooted, as well as how they’re scaled over time.
Another nice component here is it makes you cloud-agnostic. So, when you’re using Pivotal Cloud Foundry you can choose where to run your workloads, be that on VMWare infrastructure, Amazon Web Services, Google Cloud, OpenStack, or providers that have not even emerged yet. The beauty of platform as a service is it’s an extensible architecture; it allows you to plug in different components as you go along. This is open source software, but with enterprise support. What this means is that we have rapid iteration and frequent updates, the ability to develop the software very quickly, the platform very quickly, feeding in all the contributions from the broad community, but curating this and delivering this with full enterprise support for large customers that require that level of expertise and that support.
It also helps to develop, to simplify I should say, the developer’s life, allowing the deployment of applications to be very quick, very easy and very reliable and very repeatable. Many of you will be familiar with the need to automate your deployment life cycle and this feeds directly into that, making it very efficient. We’ll have many deep dives in that into the future.
Another topic that customers like to talk to us about is big data, fast data and data lakes; it’s a whole bunch of different kinds of data. This is really around the ability to capture more information than ever, at lower cost and accessing it in the correct way and primarily this is trying to avoid a lot of the complicated and expensive ETL activity; so, the extract, transform and load type of activities that you might be familiar with, which typically are complicated, brittle and tend to break down at scale.
Now, there are many dimensions to this kind of data and data-use case. It could be in-memory data grids to provide super-low-latency data access; this is a great example for financial trading houses, anything that’s got real time interaction where the data has to remain in memory, it has to be reliable and it has to be actionable. It could be for massive petabyte-scale data sets that are accessed via Hadoop; so, providing a low-cost and very flexible storage environment that allows organizations to store and access information far more cost-effectively than before.
Now, it could be those same data sets, but being accessed using ANSI-compliant SQL, so an interface that we’re all very familiar with, using something called HAWQ software, that we’ll talk about in depth later. So, the ability to access these new data sets using traditional and familiar mechanisms and methods. It could be massively parallel processing databases. These are a family of databases that allow you to grow the database implementation and maintain linear performance as you grow the footprint.
In a traditional database environment, you’re often constrained by the size of the box or boxes that can operate on that particular data set. MPP databases work around this by being dramatically horizontally scalable, that means that we can scale lineally as the requirements of the platform grow from a storage perspective, from a data access perspective, from a number of queries as a perspective. It could be real-time streaming and eventing, so the ability to take in massive amounts of information to ingest in real time, huge live streams of information, correlate that information with other components and then generate events that need to be actioned or need to be recognized in real time; this is not a huge area of innovation. Or, it could simply be replacing existing data warehouses or maintaining those data warehouses where they’re proving too inflexible and too expensive. A huge area of depth and again, something really interesting to talk about, what really happens in that space.
Another really interesting topic that people like to talk about is data science to find insights into the data that they have and this is a relatively new space and an often misunderstood space, if I can put it that way. But basically data science is an evolution beyond business intelligence. It’s very much a use-case driven iterative and agile exploration of granular data with the intent to derive insights and then operationalize those insights with new applications. So, if you think about big data emphasizing volume, diversification, low-latency and ubiquity, data science really applies predictive modeling, machine-learning, parallelized and in-database algorithms, different MapReduce techniques and ways of automating analysis of these large data sets on an ongoing basis.
So, it’s a fascinating area and we have an area called the ‘Pivotal Data Labs’ that has data scientists that do this kind of work. We’ll dive into what some of that data science looks like, again, in another episode. Another thing that organizations talk to us about is how to learn to build new cool applications in better, more efficient ways. As I mentioned earlier, organizations and customers are demanding different kinds of applications and different ways of interacting with the organizations that they work with, or that they want to engage with from a commercial perspective.
We have an organization called ‘Pivotal Labs’ and Pivotal Labs is a highly-disciplined agile practice that focuses on test-driven development, peer programming, short development cycles and continuous verification and integration of code. What this means is that they are able to dramatically improve software quality, flexibility and reduce costs. They write code every day and they try and deliver code to their clients every day so they can get to market fast. It really is a fascinating way of developing software, taking the agile framework, the agile methodology and taking it to its extreme. To have two people working at the same console, one keyboard, one screen, one mouse, but two people dealing with problems, solving issues, trying to find solutions, working together in tandem during the day, creates a real quantifiable efficiency and a really interesting way developing software that many people are starting to look at and say, ‘Hey, this is the way we should be doing it.’
We’ll dive very deeply into some of that in the future. It is a fascinating area and I know many of you listeners come from a development background and would be interested to hear how it’s done. Also, I’ll share with you a little bit of the insight into the offices and the work space that they use to facilitate this kind of engagement, because it’s pretty cool, I have to say.
The final area is that of open source software. Pivotal is a big believer in open source software and a big supporter of open source software and we have a few domains that we’re working in that place. Now, obviously Cloud Foundry is a community-sponsored and led by Pivotal Software and so Cloud Foundry is open source software and the Pivotal Cloud Foundry product is the enterprise version of that software. So, we’re very heavily engaged in assisting that community, contributing massive amounts of development resource into that community and helping foster it to be an open, thriving ecosystem.
We also provide the Spring Application Framework for Java; so, many Java developers out there will be very familiar with this framework. This is something that comes under the Pivotal banner. Also, things like Groovy, Grails, Redux, RabbitMQ, Open Chorus, Apache Tomcat and Apache Server, all things that we provide to customers and support for customers in the day-to-day operations. So, we’ll dive deeply into all of the areas that we spoke about. We’ll explore some of the powerful things that customers can do. We’ll learn about some modern architecture patents and we’ll get a view of what applications of the future are starting to look like.
A little about me, your host. As I mentioned, I’m CTO and Senior Manager of Field Engineering for Australia and New Zealand at Pivotal. I’m very passionate about IT that makes a difference to the way that business operates and competes. I’m definitely a geek at heart. I love knowing how things work, but I also love talking about the ‘so-what’ of technology and capabilities. ‘If we can do this, what does it actually mean?’ Now, I started my career more years back than I care to share as a software developer in the mainframe world and I moved to client server and web-based technology and I developed a soft spot over time for scalable distributed systems. In fact, if you’ve ever visited Australia, you’ve used one of my systems, which is the boarder-control system that I architected a long time ago now, but is a great example of a interesting distributed system problem, built with technology from a long time ago that I would love to build in modern technology these days, let me tell you.
I look forward to sharing regular time with you, exploring the depths of cloud, agile and big data. We’ll be having some interviews, we’ll be having overviews, we’ll be having deep dives. The durations of the podcasts will differ from week to week, depending on what the subject matter is; typically they’ll be about 15 to 20 minutes, some will be longer if we’re doing a really in-depth deep dive, or having a really interesting interview. But we try and make them bite-size and easy for you to consume. Of course, we’d love to get your feedback about the podcast and suggestions, or things you’d like to hear about. So, please email us at firstname.lastname@example.org. That’s email@example.com, with any ideas or suggestions.
If you’ve enjoyed the podcast, obviously we are new, we are just fresh, please let others know that it exists and that they can subscribe and listen to it on a regular basis. Until then, keep on building. See you later.
Thanks for listening to the All Things Pivotal Podcast. If you enjoyed it, please share it with others. We love hearing your feedback, so please send any comments or suggestions to firstname.lastname@example.org.
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