

The Cloudcast
Massive Studios
The Cloudcast (@cloudcastpod) is the industry's #1 Cloud Computing podcast, and the place where Cloud meets AI. Co-hosts Aaron Delp (@aarondelp) & Brian Gracely (@bgracely) speak with technology and business leaders that are shaping the future of business. Topics will include Cloud Computing | AI | AGI | ChatGPT | Open Source | AWS | Azure | GCP | Platform Engineering | DevOps | Big Data | ML | Security | Kubernetes | AppDev | SaaS | PaaS .
Episodes
Mentioned books

Jul 16, 2020 • 28min
Natural Language Understanding with AI for IT Support
Vaibhav Nivargi (CTO & Founder @Moveworks) talks about Natural Language Understanding (NLU), interacting with users using chatbots, and augmenting customer service with AI. SHOW: 458SHOW SPONSOR LINKS:Datadog Security Monitoring Homepage - Modern Monitoring and AnalyticsTry Datadog yourself by starting a free, 14-day trial today. Listeners of this podcast will also receive a free Datadog T-shirtstrongDM HomepageStart your free 14 day trial today at: strongdm.com/cloudcastCLOUD NEWS OF THE WEEK - http://bit.ly/cloudcast-cnotwPodCTL Podcast is Back (Enterprise Kubernetes) - http://podctl.comSHOW NOTES:Moveworks HomepageTopic 1 - Vaibhav, welcome to the show. Tell everyone a little about yourself and what got you started in the AI space?Topic 2 - We’ve done a number of AI/ML shows over the years, but we haven’t talked much about Natural Language Understanding or NLU. Let’s start there, can you give everyone an introduction?Topic 3 - Based on that, is the primary interaction with the end user through a chatbot or something similar? What are the primary use cases and tools you are seeing in the industry? Is this a Slack and/or Microsoft Teams integration? Unsolicited plug, I’m a customer in my day job… Topic 4 - We’ve been talking a lot on the show recently about the migration to SaaS based products. What is the model here? Is the AI central (cloud hosted) or private and in-house? Do you have the concept of a template AI and then each customer AI is an instance or is this a central AI that is called? How does it get customized and updated over time? What training is typically required and is this training on-going?Topic 5 - How do you prevent user frustration from “loops” or unanswered questions? I think of the voice automated telephone systems I’m not a fan of as an example. How would you handle language that isn’t built into the AI?FEEDBACK?Email: show at thecloudcast dot netTwitter: @thecloudcastnet

Jul 8, 2020 • 45min
2020 in Review - Midyear Edition
Aaron and Brian review the first half of 2020, which feels like it’s lasted 6 years. SHOW: 457SHOW SPONSOR LINKS:strongDM HomepageStart your free 14 day trial today at: strongdm.com/cloudcastDatadog Security Monitoring Homepage - Modern Monitoring and AnalyticsTry Datadog yourself by starting a free, 14-day trial today. Listeners of this podcast will also receive a free Datadog T-shirtCLOUD NEWS OF THE WEEK - http://bit.ly/cloudcast-cnotwPodCTL Podcast is Back (Enterprise Kubernetes) - http://podctl.comSHOW NOTES:Topic 1 - Back on March 18th, Aaron and Ken Hui did a show about “Working from Home Tips and Tricks”. Can you even remember your mindset back in March? Zoom becomes a verbTopic 1a - Is 2020 the Year of Virtual Desktops? Have you seen any last shifts happening about people being remote? [are companies going to allow people to work remote?]Topic 2 - We’re starting to see the major clouds start to carve out some unique personalities:AWS - Goes over $10B for the quarter, not a lot of big announcementsAzure - Lots of interesting growth around GitHub; pushing Teams hard with COVID; but had some scaling issues with COVID - also has made several acquisitionsGoogle - Getting very sales focused (CEO Kurian); pushing Anthos into other clouds (AWS now, Azure soon)Oracle - Are they becoming the low-cost bandwidth cloud?Topic 3 - Should anybody be running their own software anymore? MongoDB, Confluent, Datastax, Hashicorp, Red Hat, VMware (and many more) now have managed cloud-based versions of their core software.Topic 4 - 2001 Internet Crash drove a ton of new innovation. 2008 Financial Crash led to the public cloud, but also lots of “cost savings” innovation. What does 2020 potentially bring? Topic 5 - We have to talk about conferences and tradeshows. Do they return in 2021? What have we learned from the virtual ones in 2020?Topic 6 - Any insights / predictions about the rest of 2020? FEEDBACK?Email: show at thecloudcast dot netTwitter: @thecloudcastnet

Jun 24, 2020 • 32min
Building a Next-Generation of Serverless
Tim Zonca (@timzonca, CEO at @stackeryio) talks about the next evolution of the serverless developer experience, the maturity of customer adoption, how much customer appreciate not having to manage infrastructure, and how to manage the journey to serverless.SHOW: 456SHOW SPONSOR LINKS:Taos HomepageTaos - Gartner MQ - Cloud Professional ServicesStudio 3T - HomepageStudio 3T - 30 Day Free TrialDatadog Security Monitoring Homepage - Modern Monitoring and AnalyticsTry Datadog yourself by starting a free, 14-day trial today. Listeners of this podcast will also receive a free Datadog T-shirtCLOUD NEWS OF THE WEEK - http://bit.ly/cloudcast-cnotwPodCTL Podcast is Back (Enterprise Kubernetes) - http://podctl.comSHOW NOTES:Stackery HomepageStackery Cloudlocal FeaturesTopic 1 - Welcome to the show. You’ve had a pretty diverse career in terms of elements of making developers successful. Tell about your background and how you became CEO at Stackery almost a year ago.Topic 2 - It’s hard to believe that AWS Lambda launched about 5.5 years ago. Obviously the serverless ecosystem has grown and expanded quite a bit since then. Where do you see serverless in terms of both maturity of the technologies, and maturity of customer adoption?Topic 3 - Lets talk about what the Stackery platform brings to the serverless ecosystem. Topic 4 - As you talk to prospective customers, how much different is it to discuss not have to be burdened by underlying resources vs. previous conversations you’ve had about applications? How long does it usually take them to grasp the magnitude of the changes in development?Topic 5 - How much of a “traditional” developer experience still exists with serverless (write code, write tests, pipelines, etc.) and what are some immediate things they will see that’s different?Topic 6 - Having been at Puppet you obviously saw many DevOps transformations. What are some of the steps on a typical Serverless transformation for companies?FEEDBACK?Email: show at thecloudcast dot netTwitter: @thecloudcastnet

Jun 17, 2020 • 25min
MLOps, GPUs and AI Developers
Dillon Erb (@dlnrb, CEO @HelloPaperSpace) talks about what exactly is MLOps, Serverless AI platforms, and how developers can utilize GPUs for AI/ML.SHOW: 455SHOW SPONSOR LINKS:Datadog Security Monitoring Homepage - Modern Monitoring and AnalyticsTry Datadog yourself by starting a free, 14-day trial today. Listeners of this podcast will also receive a free Datadog T-shirtTaos HomepageTaos - Gartner MQ - Cloud Professional ServicesStudio 3T - HomepageStudio 3T - 30 Day Free TrialCLOUD NEWS OF THE WEEK - http://bit.ly/cloudcast-cnotwPodCTL Podcast is Back (Enterprise Kubernetes) - http://podctl.comSHOW NOTES:PaperSpace websiteCovid-19 BlogFighting Covid-19 with Data and AI blogTopic 1 - Dillon, welcome to the show, tell us a little bit about yourself and how you got involved in this space?Topic 2 - I’ve had a running joke on the show that a market doesn’t exist until you attach Ops to it. Today we’ll talk about MLOps. Give everyone an introduction for those not familiar.Topic 3 - What exactly is a Serverless AI Platform? How does this differ from traditional CI/CD platforms that our listeners would be used too? Is this abstracting away the infrastructure layer for MLOps teams?Topic 3a - Switching gears from Ops to Developers, what do you mean when you say that you make it easy for developers to use GPUs? What do developers need to know about hardware-level stuff like GPUs that they didn’t need to know with CPUs? Topic 4 - As with all things emerging tech, the use cases are constantly evolving. What are the early initial use cases that you are seeing? Are there unique things that emerge for gaming or media applications? Topic 5 - How does access to data models fit into all of this?Topic 6 - I noticed your company did some articles on Covid-19, can you explain what is going on there?FEEDBACK?Email: show at thecloudcast dot netTwitter: @thecloudcastnet

Jun 10, 2020 • 31min
Security Visibility from Observability Data
Marc Tremsal (@mtremsal, Director Product Management @datadoghq) talks about the intersection of observability and security, if SRE needs a DevSecOps transition, using security data for modeling, and tips to make immediate impacts on overall security.SHOW: 454SHOW SPONSOR LINKS:Studio 3T - HomepageStudio 3T - 30 Day Free TrialTaos HomepageTaos - Gartner MQ - Cloud Professional ServicesDatadog Security Monitoring Homepage - Modern Monitoring and AnalyticsTry Datadog yourself by starting a free, 14-day trial today. Listeners of this podcast will also receive a free Datadog T-shirtCLOUD NEWS OF THE WEEK - http://bit.ly/cloudcast-cnotwPodCTL Podcast is Back (Enterprise Kubernetes) - http://podctl.comSHOW NOTES:Datadog Security MonitoringTopic 1 - Welcome to the show. You’ve played a role in helping to design systems that secure some of the most critical environments in the world. Tell us a little bit about your background.Topic 2 - We’ve talked about monitoring, observability and in various ways “security”, but how do you see all those things beginning to come together more these days? Topic 3 - As we get into more distributed environments, especially for security (authentication, encryption, key-management, proxies, etc.), how should people think about a framework to have visibility and be able to take action across these distributed systems? Topic 4 - Is this visibility of security-related activities (or potentially security-associated) mostly useful for real-time security threats (e.g. “we’re being attacked”), or can it also be used for more long-term types of activities (planning, threat modeling, chaos engineering, etc.)?Topic 5 - Can you share with us any customer-centric stories of how this is helping companies deliver better services, or more uptime for their services?Topic 6 - What are some tips you can share with the audience today that would help them make immediate impacts to how them monitor for security? FEEDBACK?Email: show at thecloudcast dot netTwitter: @thecloudcastnet

Jun 3, 2020 • 27min
AI for the Mainstream
Venkat Rangan (Co-Founder & CTO @ Clari) talks about AI and application into more mainstream areas and revenue generation.SHOW: 453SHOW SPONSOR LINKS:Taos HomepageTaos - Gartner MQ - Cloud Professional ServicesStudio 3T - HomepageStudio 3T - 30 Day Free TrialDatadog Homepage - Modern Monitoring and AnalyticsTry Datadog yourself by starting a free, 14-day trial today. Listeners of this podcast will also receive a free Datadog T-shirtCLOUD NEWS OF THE WEEK - http://bit.ly/cloudcast-cnotwPodCTL Podcast is Back (Enterprise Kubernetes) - http://podctl.comSHOW NOTES:Clari websiteTopic 1 - Venkat, you have a very interesting background as a technologist in our industry. Give everyone a brief introduction and if you don’t mind also tell everyone a bit about being a member of the Forbes Technology Council. I believe you are our first guest from there.Topic 2 - Today we’re going to dig back into AI as a topic. Let’s start at the start. In your current role you have been involved in technology over the years and Clari has been around for awhile. What compelled you to focus on this space?Topic 3 - AI has suffered from a perception issue. It often is seen as unapproachable with a pretty high barrier to entry. We’ve spoken to companies in the past about specific industry or vertical applications (manufacturing for instance). Many architects and our listeners are practitioners vs. data scientists. How do we solve this problem and “bring AI to mainstream”Topic 4 - In order for that to happen, what does our industry need? Is it SaaS based, services from public clouds, etc?Topic 5 - Having been in field sales for years, it’s always been somewhere between complete and utter guesswork all the way to precision, rocket science level analysis. - What are your thoughts here and how can AI improve this situation?Topic 6 - What’s next for industry? What are the use cases both today and in the future?FEEDBACK?Email: show at thecloudcast dot netTwitter: @thecloudcastnet

May 27, 2020 • 32min
Continuous Reliability
Tal Weiss (@weisstal, Co-Founder/CTO of @OverOpsHQ) talks about the challenges of frequently deploying applications, understanding cloud-native patterns, and helping developers debug problems in production. SHOW: 452SHOW SPONSOR LINKS:Datadog Homepage - Modern Monitoring and AnalyticsTry Datadog yourself by starting a free, 14-day trial today. Listeners of this podcast will also receive a free Datadog T-shirtLogz.io Homepage - Start your free Logz.io trial here, and receive a t-shirt, on us!OpenObservability.io online event (May 27, 2020)strongDM HomepageStart your free 14 day trial today at: strongdm.com/cloudcastCLOUD NEWS OF THE WEEK - http://bit.ly/cloudcast-cnotwPodCTL Podcast is Back (Enterprise Kubernetes) - http://podctl.comSHOW NOTES:OverOps HomepageTopic 1 - Welcome to the show. You’ve been a software developer, an entrepreneur and worked on some pretty challenging technical areas - tell us a little bit about your background. What motivated you to start OverOps?Topic 2 - We are quickly moving to a world where software is no longer a “big bang” planning activity, but lots of continuous activities, loosely coordinated. What sort of challenges does that create for production applications? Topic 3 - OverOps talks about this concept of Continuous Reliability. What does this mean in a world where cloud-native patterns are teaching people that they should build systems that are designed around unreliable infrastructure?Topic 4 - How does OverOps begin to make it easier for developers to debug production problems, especially when there are many tools collecting lots and other information about systems? Topic 5 - Where do you see the most progress for companies that have these highly variable, fast-moving application environments improving the most? Is it the evolution of SRE teams, or visibility tools, or something else? Topics 6 - Any tips you can pass along to our audience for reaching continuous reliability?FEEDBACK?Email: show at thecloudcast dot netTwitter: @thecloudcastnet

May 20, 2020 • 33min
Network Security with Adaptive DDI
Andrew Wertkin (Chief Strategy Officer @ BlueCat) talks about Enterprise DNS, DDI (DNS, DHCP, IPAM), and the differences between Adaptive network security and public cloud security.SHOW: 451SHOW SPONSOR LINKS:Logz.io Homepage - Start your free Logz.io trial here, and receive a t-shirt, on us!OpenObservability.io online event (May 27, 2020)strongDM HomepageStart your free 14 day trial today at: strongdm.com/cloudcastDatadog Homepage - Modern Monitoring and AnalyticsTry Datadog yourself by starting a free, 14-day trial today. Listeners of this podcast will also receive a free Datadog T-shirtCLOUD NEWS OF THE WEEK - http://bit.ly/cloudcast-cnotwPodCTL Podcast is Back (Enterprise Kubernetes) - http://podctl.comSHOW NOTES:BlueCat WebsiteNetwork Disrupted PodcastTopic 1 - Andrew, tell everyone a little about yourself.Topic 2 - Our topic today is all about network security and foundations. Over the years, our networks have become complex and we have multiple infrastructure systems to maintain such as on-prem DHCP, VPC connections to public cloud, public facing, etc. Tell everyone a little bit about the challenge and your findings with customers in the industry.Topic 3 - I’ve heard Enterprise DNS and DDI (DNS, DHCP, IPAM), what’s the difference? Doesn’t everyone just use a spreadsheet still? :) What’s changed?Topic 4 - How has an era of new devices (VOIP, IoT, Edge, etc.) affected management and security approaches?Topic 5 - What are the tradeoffs and design considerations when it comes to all of the above (multiple clouds, multiple types of devices, multiple vendors with management tools). Are we talking about an overlay, a replacement tool? How does this unification happen? Aren’t there differences for instance in DNS implementations between vendors?Topic 6 - What’s next for industry? What are the use cases both today and in the future?FEEDBACK?Email: show at thecloudcast dot netTwitter: @thecloudcastnet

May 13, 2020 • 29min
Cloud BI for Everyone
Pedro Arellano (@DSSPedro, Head of Product Marketing, Looker) talks about the evolution of Business Intelligence (BI), how BI is used by more than data scientists, the importance of visualization, and creating new ways to correlate data sources.SHOW: 450SHOW SPONSOR LINKS:Datadog Homepage - Modern Monitoring and AnalyticsTry Datadog yourself by starting a free, 14-day trial today. Listeners of this podcast will also receive a free Datadog T-shirtstrongDM HomepageStart your free 14 day trial today at: strongdm.com/cloudcastLogz.io Homepage - Start your free Logz.io trial here, and receive a t-shirt, on us!OpenObservability.io online event (May 27, 2020)CLOUD NEWS OF THE WEEK - http://bit.ly/cloudcast-cnotwPodCTL Podcast is Back (Enterprise Kubernetes) - http://podctl.comSHOW NOTES:Looker HomepageData in the time of COVID-19How to choose the best chart for your data (Looker blog)Data scientists and the Art of Persuasion (HBR)Topic 1 - Welcome to the show. You’ve been around the data industry for a while, and were part of the Looker team that was acquired by Google Cloud in 2019. Tell us a little bit about your background, and what excites you about the Business Intelligence space. Topic 2 - We live in a world where we are presented with large amounts of data on a daily basis, but most of us aren’t data scientists. How does Looker’s approach to Business Intelligence appeal to the masses? Topic 3 - Usually BI requires a significant investment in ETL technologies to be able to bring together many different data sources. How does Looker overcome that, or apply “data models” across a variety of data sources. Topic 4 - Looker has always emphasized the visualization elements of data. Some data scientists live in spreadsheets or Jupyter notebooks. How important do you find it is to be able to visualize complex data, especially as it needs to be used to communicate across groups within a company? Topic 5 - Given that Looker allows many different types of data sources to be part of the analysis, do you do anything in working with customers to help them think about “new” data sources that could provide new correlations or viewpoints to their business? Topics 6 - What are some of the examples of new ways that you’re seeing companies use Cloud BI, either to enable new teams to have business insights, or collaborate better across teams?FEEDBACK?Email: show at thecloudcast dot netTwitter: @thecloudcastnet

May 6, 2020 • 34min
Making Microservices Work at Scale
Sarah Wells (@sarahjwells, Technical Director for Operations & Reliability at @FT) talks about how she's evolved her career with the changes at FT, how they chose to use microservices, how their internal culture has evolved and how they think about funding and maintaining service ownership. SHOW: 449SHOW SPONSOR LINKS:Logz.io Homepage - Start your free Logz.io trial here, and receive a t-shirt, on us!OpenObservability.io online event (May 27, 2020)strongDM HomepageStart your free 14 day trial today at: strongdm.com/cloudcastDatadog Homepage - Modern Monitoring and AnalyticsTry Datadog yourself by starting a free, 14-day trial today. Listeners of this podcast will also receive a free Datadog T-shirtCLOUD NEWS OF THE WEEK - http://bit.ly/cloudcast-cnotwPodCTL Podcast is Back (Enterprise Kubernetes) - http://podctl.comSHOW NOTES:Sarah Wells - DevClass Interview Challenge of Migrating 150 Services to Kubernetes (CNCF Talk - Video)Mature Microservices and How to Operate Them (InfoQ)FT colleagues Victoria Morgan Smith and her co-author Matthew Skelton on internal tech conferencesTopic 1 - Welcome to the show. We often speak with experts working on the technology-vendor side of the industry, but you’re building in a much different way. Tell us about your background, and introduce us to the work you’re doing today at the Financial Times. Topic 2 - For the last 4 years, you’ve been talking a lot (publicly) about building and using microservices. Give us some background on your journey, and some of the reasons why your teams have chosen this architecture. (experimentation, A/B testing)Topic 3 - You work in a world that reports on the financial success (or failures) of other companies, but how do you measure your own success? How do you put them in perspective/Topic 4 - Lets talk about service ownership. Who owns a service, how long do they own a service, do they ever go away? Topic 5 - Any tips or tricks that you’d be willing to share with our audience about driving successful culture within your team or across other teams? FEEDBACK?Email: show at thecloudcast dot netTwitter: @thecloudcastnet


