The Cloudcast

Aaron talks to Ken Hui (@kenhuiny - Solutions Architect, AWS) about advice on working from home. We've been working remotely for over 20 years and this may we offer some tips and tricks to stay productive. Stay safe everyone SHOW: 442SHOW SPONSOR LINKS:MongoDB Homepage - The most popular database for modern applicationsMongoDB Atlas - MongoDB-as-a-Service on AWS, Azure and GCPDatadog 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-cnotwSHOW NOTES:Wash your handsDon't touch your facePractice Social DistancingTopic 1 - No tech topic this week. We’re going to talk a bit today about working remotely. This may be new and unexpected to some of you. To talk about this I invited past guest and occasional co-host, Ken Hui.  Between Ken and I, we have worked together at a few different places in the past and probably have 20+ years working from anywhere. Welcome back Ken! For those that live under a rock and don’t know you, tell everyone a little about yourself and what you’re up to these days.Topic 2 - Let’s start with some basics. What are the first steps to both keep your sanity and be productive? (Making sure your calendar is public, your company has a standard for chat/video/etc, don’t they? You are available during business hours, etc.) Set up a dedicated work space, etc. Don’t use Slack to replace email….Topic 3 - At our last company together, Ken pushed hard for certain work from home inclusion rules, what were they? Video camera on, video camera off? People will always assume the worst.Topic 4 - Weekly report on work to a distributed team: this week, next week, GYR status, upcoming PTO, etc.Topic 5 - Have a start and stop time (that is friendly to your HQ)FEEDBACK?Email: show at thecloudcast dot netTwitter: @thecloudcastnet

Aaron Upright (@IAmAaronUpright, Co-founder of @ZenHubHQ) talks about the challenge of developer collaboration and project prioritization, integrating tools within GitHub, best practices for teams, and the importance of making tools that technical and non-technical team members can understand.SHOW: 441SHOW 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-shirtMongoDB Homepage - The most popular database for modern applicationsMongoDB Atlas - MongoDB-as-a-Service on AWS, Azure and GCPCLOUD NEWS OF THE WEEK - http://bit.ly/cloudcast-cnotwSHOW NOTES:ZenHub HomepageTopic 1 - Welcome to the show. Tell us a little bit about your background, and ultimately what led you to co-found ZenHub?Topic 2 - Let’s start by talking about what ZenHub delivers. We’re very interested in the potential of GitHub and the things it’s doing directy, but we’re also interested in this ecosystem that’s enhancing GitHub. Topic 3 - What are some best-practices around road mapping and prioritizing activities that could be shared?Topic 4 - What are some best-practices around allowing greater transparency of roadmaps with multiple teams? (what are the pros and cons)?Topic 5 - ZenHub is an example of a toolset that's built entirely around GitHub capabilities. Do you think we'll begin to see more companies just built around GitHub and move away from externally-connected toolsets? Topic 6 - Are most of your interactions with software companies, or are you also interacting with businesses whose primary focus is something other than being a software company?FEEDBACK?Email: show at thecloudcast dot netTwitter: @thecloudcastnet

Sunay Tripathi (@SunayTripathi, Founder and CTO, @MobiledgeX) talk about Edge Networking, why 5G will be a huge leap forward, evolving use cases beyond AR/VR, and creating a clean developer experience by abstracting away the mobile transport layerSHOW: 440SHOW SPONSOR LINKS:MongoDB Homepage - The most popular database for modern applicationsMongoDB Atlas - MongoDB-as-a-Service on AWS, Azure and GCPDatadog 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-cnotwSHOW NOTES:MobiledgeX websiteMobiledgeX Use CasesSeamsterTopic 1 - Welcome to the show. Tell everyone a little about yourself, you have been at the intersection of Network Virtualization, Cloud, and now Edge for quite some time.Topic 2 - Let’s start at the start. What is your definition of Edge and what are some of the historical problems you see there? In this instance we are talking about network edge devices and not edge computing, correct?Topic 3 - Tell us a little bit about device/identity security at the edge.Topic 4 - When I think about device based AR/VR, I think about gaming as the primary use case that I’m exposed to as a consumer but we are talking about much more than that. What are some of the prominent use cases you are seeing and are trying to solve for?Topic 5 - How does the increase in bandwidth at the transport layer, in particular worldwide 5G come in to play? Is this just a “bigger, faster pipe” or does it require a heavy implementation lift to adopt? How does world geography play into this? Some areas of the world are dominated with edge/handheld devices for almost all daily life now...Topic 6 - We don’t talk about PaaS as much on the podcast lately but would it be safe to characterize MobiledgeX’s technology as a development PaaS for edge devices?Topic 7 - Tells us about MobiledgeX’s upcoming initiative, Seamster. As I understand it this will bring vendors and developers together, correct?FEEDBACK?Email: show at thecloudcast dot netTwitter: @thecloudcastnet

Chris Riley (@hoardinginfo, DevOps Advocate, @Splunk) talks about the state of DevOps, the evolution of Incident Response with Machine Learning, Service vs. Site Reliability, and using Incident Response to increase quality of developmentSHOW: 439SHOW 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-shirtMongoDB Homepage - The most popular database for modern applicationsMongoDB Atlas - MongoDB-as-a-Service on AWS, Azure and GCPCLOUD NEWS OF THE WEEK - http://bit.ly/cloudcast-cnotwSHOW NOTES:VictorOps (now Splunk) BlogChris Riley at DevOps.comDevelopers Eating the World PodcastTopic 1 - Welcome to the show. Tell everyone a little about yourself, you’ve been active in the DevOps space for quite some time. Topic 2 - About a year ago we had your peer and good friend of the show, Josh Atwell, on to talk about the State of DevOps in 2019. What are your thoughts on changes over the last 12 months and where we headed in 2020?Topic 3 - One item in particular that has drawn my attention is your discussions on Incident Response and Machine Learning. Can you tell everyone a little bit about that and why you believe it will be valuable going forward?Topic 4 - This in a way feels almost like a transition into the next evolution of our model. First we had separate dev and ops and no one talked, then we put them together, then we had every device and app start spitting out logs and alerts and next thing you knew, we were drowning in data… The complexity of the systems has grown exponentially. Fair?Topic 5 - You recently did a post over on the Victor Ops blog about SRE and the meaning of the “S” in that blog. You propose more and more it should stand for Service Reliability Engineer vs. the more traditional Site Reliability Engineer, especially as we move into a subscription based model world. Can you explain to everyone your thoughts there?Topic 6 - When I think Incident Response, I think production environments. As part of VictorOps I’m sure you see a lot of use cases and have solved some pretty unique customer problems. How can this be applied outside of production, say for application testing or quality before hitting production? Is that a valid approach?FEEDBACK?Email: show at thecloudcast dot netTwitter: @thecloudcastnet

Peter Mattis (@PeterMattis, Co-founder/CTO of @CockroachDB) talks about the evolution of scalable SQL databases, the challenges of globally scalable data management, how Kubernetes has evolved to manage stateful applications, and lessons learned running Kubernetes and CockroachDB. SHOW: 438SHOW SPONSOR LINKS:MongoDB Homepage - The most popular database for modern applicationsMongoDB Atlas - MongoDB-as-a-Service on AWS, Azure and GCPDatadog 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-cnotwSHOW NOTES:CockroachLabs HomepageCockroachDB - Scalable, survivable, SQL database OperatorHub HomepagePeter Mattis on the Google Kubernetes PodcastTopic 1 - Welcome to the show. Before we dive into our discussion, tell us a little bit about your background in working on scalable technologies. Topic 2 - Today we’re going to mash together a couple of popular (and complex) topics - the growing use-cases on Kubernetes, and the growing need to synchronize data for anywhere access. Let’s start with the data side of the equation - tell us about the basics of your creation, CockroachDB, and the challenges it solves.Topic 3 - What are some of the use-cases that are driving more scalable SQL usage vs. more traditional SQL database models?Topic 4 - When Kubernetes first got started, the focus was on scalable stateless (cloud-native) applications. How are you beginning to see the trend towards companies becoming more comfortable with stateful applications (e.g. databases) on Kubernetes?Topic 5 - One of the new technologies that’s making it easier to get databases onto Kubernetes is “Operators”. CockroachLabs has been one of the leading platforms supporting this technology. Can you talk a little bit about your experience with Operators and how it images the way Kubernetes teams (developers or platform teams) about databases on Kubernetes.Topic 6 - What are some of the lessons learned from deploying CockroachDB onto Kubernetes?FEEDBACK?Email: show at thecloudcast dot netTwitter: @thecloudcastnet

Sam Charrington (@samcharrington, Host of TWIML & AI Podcast) talks about AI & ML trends in 2020, frameworks to understand usage patterns, hot new technology to explore, how long projects take to succeed, and the inherent bias built into every AI & ML model.SHOW: 437SHOW 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-shirtMongoDB Homepage - The most popular database for modern applicationsMongoDB Atlas - MongoDB-as-a-Service on AWS, Azure and GCPCLOUD NEWS OF THE WEEK - http://bit.ly/cloudcast-cnotwSHOW NOTES:TWIML Homepage (Podcasts, eBooks, etc.)eBook: The Definitive Guide to  ML PlatformsStudy Groups & Education TWIML Conference HomepageSam Charrington on The Cloudcast in 2019 (Eps.321) Topic 1 - Welcome back to the show. Let’s start with the broad set of TWIML activities that you’re working on these days. Topic 2 - You focus on AI & ML every week, across a lot of different domains and usages. It’s a broad scope. If you had to focus it on Enterprise/Business leaders, how do you structure a conversation around how to align business opportunity and technology choices?  Topic 3 - What are some of the most commonly used technologies being deployed around AI/ML systems? Any big shifts over the last couple of years? Topic 4 - You’ve been around Cloud Computing and DevOps communities, which required companies to go through some people/process change to achieve success. What are the people/process changes that you typically see with AI/ML environments?Topic 5 - If somebody asked you how they can put a timeline on when they’ll see value around their AI/ML, is that a realistic ask? What are the factors that go into achieving success in AI/ML projects?Topic 6 - What are some of the interesting usages of AI/ML that you’ve seen in use recently?Topic 7 - There has been quite a bit of discussion recently about bias in AI/ML algorithms. Can you explain what this means and how it could impact the system’s decision making?FEEDBACK?Email: show at thecloudcast dot netTwitter: @thecloudcastnet

SHOW: 436DESCRIPTION: Stephen Pinkerton (@spnktn, Product Manager @datadoghq) talks about the latest trends that Datadog has observed from monitoring serverless applications in the public cloud, adoption rates, as well as how serverless is deployed along with containers. SHOW SPONSOR LINKS:MongoDB Homepage - The most popular database for modern applicationsMongoDB Atlas - MongoDB-as-a-Service on AWS, Azure and GCPDatadog 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-cnotwSHOW NOTES:Datadog's State of Serverless ReportDatadog's Monitoring Lambda GuideTopic 1 - Welcome to the show; Tell us about your background, as you’ve worked for a number of interesting companies prior to Datadog. Topic 2 - Datadog recently released a report about trends in serverless usage. Before we dive into some of the highlights and insights, tell us about the scope of the report. Are you able to tell anything about the types of companies being monitored? (industries, size of company, etc.)Topic 3 - Highlights from the State of Serverless reportThe majority of functions are still fairly small, and don’t run very long (small memory footprint). Node.js and Python are the leading languages/frameworks being used (almost 90%)Nearly half of EC2 users have adopted LambdaEarly adopters of Containers (ECS) have adopted Lambda - 80%+Discuss which event-driven data sources are the most frequently usedTopic 4 - As you’re analyzing this usage data, what are some of the things you’re thinking about as a Product Manager for functionality that you can provide to help better monitor these rapidly changing environments?FEEDBACK?Email: show at thecloudcast dot netTwitter: @thecloudcastnet

SHOW: 435DESCRIPTION: James Higginbotham (@launchany; Founder, Author, API Architect) talks about frameworks for evaluating API usage, developer perspectives on APIs, versioning APIs and some thoughts on new trends in API usage. SHOW 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-shirtUpCloud - World’s fastest cloud serversUpCloud (promo) - Sign up for free, receive a $50 credit and try us out!MongoDB Homepage - The most popular database for modern applicationsMongoDB Atlas - MongoDB-as-a-Service on AWS, Azure and GCP[DONUT RUN DONATIONS] CLOUD NEWS OF THE WEEK - http://bit.ly/cloudcast-cnotwSHOW NOTES:James on The Cloudcast Eps.135 (“Building Better APIs for Business Success)LaunchAny HomepageRecent keynote: “APIs, Microservices, and Serverless: The Shape of Things to Come”Topic 1 - Welcome back to the show; It’s been a while, let’s reintroduce you to our audience. Tell us about the types of things you work on.Topic 2 - There are so many things going on with APIs these days, sometimes it’s hard to know where to start. Do you have a framework that you use to help companies think about APIs?  Topic 3 - Are there different perspectives that developers have if they are dealing with APIs for monolithic applications vs. microservices applications vs. external APIs? Topic 4 - What is some of thinking around dynamically changing environments (e.g. DevOps, Agile) and APIs (versioning, testing changes, etc.)?Topic 5 - What are some of the more critical things that you’re always reinforcing and educating people about APIs? Topic 6 - We’re seeing more companies emerge that just deliver APIs as part of an ecosystem of services. How has this changed application development?FEEDBACK?Email: show at thecloudcast dot netTwitter: @thecloudcastnet

SHOW: 434DESCRIPTION: Christian Posta (@christianposta, Field CTO @soloio_inc) talks about the trends that are shaping the Service Mesh space, including emerging standards, application patterns, and interactions with API gateways. SHOW SPONSOR LINKS:UpCloud - World’s fastest cloud serversUpCloud (promo) - Sign up for free, receive a $50 credit and try us out!MongoDB Homepage - The most popular database for modern applicationsMongoDB Atlas - MongoDB-as-a-Service on AWS, Azure and GCPDatadog 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-shirt[DONUT RUN DONATIONS] SHOW NOTES:Christian Posta’s blog (Service Mesh, Cloud-native apps content)Solo.io’s blog Christian on PodCTL podcast (discussing Istio)Topic 1 - Welcome to the show; you’ve been on PodCTL in the past. Tell us about your background, as you’ve been very active with application developers and distributed systems for quite a while.  Topic 2 - A few years ago, Service Mesh came onto the scene as a big deal (Istio, Linkerd, etc.) and people were trying to figure out what it was, what it did, etc. The technology has evolved quite a bit, but people are still oftentimes confused. How should we think about what a Service Mesh does (or doesn’t do)? Topic 3 - What are the most common use-cases when Service Mesh is being used? What are some of the places where Service Mesh is discussed, but probably shouldn’t be used? (API-Gateway, code in an application, etc.)Topic 4 - Sometimes we have a technology space that has lots of implementations (e.g. Kubernetes, Swarm, Mesos, etc.) that eventually converge into a single industry choice. But Service Mesh still has lots of implementations. Are they all really different? Will we see industry convergence around a standard? Do we need a standard?Topic 5 - What are some of the areas where you expect that we’ll see advancements in Service Mesh in 2020?Topic 6 -  What are some of the best ways for people to start either learning more about Service Mesh, or trying out the technology to see if it makes sense for them?FEEDBACK?Email: show at thecloudcast dot netTwitter: @thecloudcastnet

SHOW: 433DESCRIPTION: Gene Kim (@RealGeneKim, Author, DevOps Researcher) talks about his new book “The Unicorn Project”, the follow-on to “The Phoenix Project, and the newest trends shaping DevOps and business success. SHOW SPONSOR LINKS:MongoDB Homepage - The most popular database for modern applicationsMongoDB Atlas - MongoDB-as-a-Service on AWS, Azure and GCPDatadog 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-shirtUpCloud - World’s fastest cloud serversUpCloud (promo) - Sign up for free, receive a $50 credit and try us out![DONUT RUN DONATIONS] SHOW NOTES:The Unicorn Project (homepage)The Unicorn Project (resource guide)The Phoenix Project on The Cloudcast (Eps.79)The DevOps HandbookDevOps Enterprise Summit (event)Topic 1 - Welcome back to the show. It’s hard to believe it’s been 7 years since you were last on the show. Before we get into the Unicorn Project, let’s talk briefly about some of the other things you’ve been doing since The Phoenix Project (DevOps Handbook, DevOps Enterprise Summit, etc.) Topic 2 - Let’s do a Cliff Notes version of The Unicorn Project. It picks up 2-3 years after The Phoenix Project - what are the challenges now facing Parts Unlimited?Topic 3 - Without giving away the ending, there is a sense that the Unicorn Project team essentially says that DevOps is dead and they are going to do things a new way. Is that the message of the story?Topic 4 - The hero of this story (Maxine) is what I’d call a “25x engineer”. She’s portrayed as super-elite in her engineering skills. I’ve also noticed that the State of DevOps report is also now adding a focus on these super-elite teams. Is that a good thing to focus on, since so few teams identify like that? Topic 5 - This book talks about 5 “ideals”. How would you stack rank them in terms of ease or difficulty in achieving?THE FIRST IDEAL: Locality and SimplicityTHE SECOND IDEAL: Focus, Flow, and JoyTHE THIRD IDEAL: Improvement of Daily WorkTHE FOURTH IDEAL: Psychological SafetyTHE FIFTH IDEAL: Customer Focus Topic 6 - In Unicorn Project, you have a very broad set of characters. Do you do this so that a broad set of people can identify within these challenging environments? FEEDBACK?Email: show at thecloudcast dot netTwitter: @thecloudcastnet