Pull Request Environments with Eric Silverman
42 min

The modern release workflow involves multiple stakeholders: engineers, management, designers, and product managers. It is a collaborative process that is often held together with brittle workflows. A developer deploys a new build to an ad hoc staging environment and pastes a link to that environment in Slack. Other stakeholders click on that link, then send messages to each other in Slack, or make comments on the pull request in GitHub.

This workflow is far from ideal. Collaborating around pull requests can be made easier with a dedicated set of tools for sharing and discussing those pull requests. This is the goal of FeaturePeek, a system for spinning up dedicated pull request environments, creating screenshots and comments, and reimagining the lifecycle of the release workflow.

Eric Silverman is a co-founder of FeaturePeek and he joins the show to discuss release management, the interactions between different stakeholders, and the development of his company. Much like the previous show about Postman, in which we explored how API management has become a ripe space for collaboration, the same is true of pull requests.

Sponsorship inquiries: sponsor@softwareengineeringdaily.com

The post Pull Request Environments with Eric Silverman appeared first on Software Engineering Daily.

Google Cloud Platform Podcast
Google Cloud Platform Podcast
Google Cloud Platform
2020 Year End Wrap Up
This week, four of the podcast’s greatest hosts come together to celebrate all of the fun and informative episodes we’ve been privileged to do this year! Join Mark Mirchandani, Jon Foust, Priyanka Vergadia, and Brian Dorsey as we talk about our favorite guests and shows, some cool things that happened this year, and what we’re looking forward to in 2021! Cool things of the week * A Giant List of Google Cloud Resources blog * Google Cloud 4 Words site Our favorite episodes * Jon’s Favorites * GCP Podcast Episode 212: Data Management with Amy Krishnamohan podcast * GCP Podcast Episode 237: NVIDIA with Bryan Catanzaro podcast * Priyanka’s Favorite * GCP Podcast Episode 240: reCAPTCHA Enterprise with Kelly Anderson + Spring ML Potholes with Eric Clark podcast * Mark’s Favorites * GCP Podcast Episode 242: NASA and FDL with James Parr and Madhulika Guhathakurta podcast * GCP Podcast Episode 217: Cost Optimization with Justin Lerma and Pathik Sharma podcast * GCP Podcast Episode 228: Fastly with Tyler McMullen podcast * Brian’s Favorites * GCP Podcast Episode 223: Voice Coding with Emily Shea and Ryan Hileman podcast * GCP Podcast Episode 233: Bare Metal Solution with James Harding and Gurmeet Goindi podcast * GCP Podcast Episode 212: Data Management with Amy Krishnamohan podcast Sound Effects Attribution * “Bad Beep” by RicherLandTV of Freesound.org * “Small Group Laugh 6” by Tim.Kahn of Freesound.org * “It’s Always Night in Space” by JamesSilvera of HDInteractive.com * “Easy Cheesy” by LoboLoco of FreeMusicArchive.org
36 min
Towards Data Science
Towards Data Science
The TDS team
58. David Duvenaud - Using generative models for explainable AI
In the early 1900s, all of our predictions were the direct product of human brains. Scientists, analysts, climatologists, mathematicians, bankers, lawyers and politicians did their best to anticipate future events, and plan accordingly. Take physics, for example, where every task we think of as part of the learning process, from data collection to cleaning to feature selection to modeling, all had to happen inside a physicist’s head. When Einstein introduced gravitational fields, what he was really doing was proposing a new feature to be added to our model of the universe. And the gravitational field equations that he put forward at the same time were an update to that very model. Einstein didn’t come up with his new model (or “theory” as physicists call it) of gravity by running model.fit() in a jupyter notebook. In fact, he never outsourced any of the computations that were needed to develop it to machines. Today, that’s somewhat unusual, and most of the predictions that the world runs on are generated in part by computers. But only in part — until we have fully general artificial intelligence, machine learning will always be a mix of two things: first, the constraints that human developers impose on their models, and second, the calculations that go into optimizing those models, which we outsource to machines. The human touch is still a necessary and ubiquitous component of every machine learning pipeline, but it’s ultimately limiting: the more of the learning pipeline that can be outsourced to machines, the more we can take advantage of computers’ ability to learn faster and from far more data than human beings. But designing algorithms that are flexible enough to do that requires serious outside-of-the-box thinking — exactly the kind of thinking that University of Toronto professor and researcher David Duvenaud specializes in. I asked David to join me for the latest episode of the podcast to talk about his research on more flexible and robust machine learning strategies.
37 min
Kubernetes Podcast from Google
Kubernetes Podcast from Google
Adam Glick and Craig Box
KubeCon NA 2020, with Stephen Augustus
Join us for all the news from KubeCon NA 2020, and a conversation with conference co-chair Stephen Augustus. Stephen is a Senior Open Source Engineer on the VMware Tanzu team, a chair of Kubernetes’ SIG Release, and a leader in many other parts of the project, past and present. Do you have something cool to share? Some questions? Let us know: * web: kubernetespodcast.com * mail: kubernetespodcast@google.com * twitter: @kubernetespod Chatter of the week * The kākāpō wins Bird of the Year * We’re off for 2 weeks. See you on December 8! News of the week * Cisco acquires Banzai Cloud * CNCF announces Cloud Native Survey 2020 results * Red Hat: New edge features, industrial AI/ML blueprint and AWS launch * CNCF End User Tech Radar for storage * New End User benefits * Envoy Mobile joins the CNCF * New sandbox projects * cert-manager * cdk8s * Kyverno * OpenKruise * Pravega * SchemaHero * Tinkerbell * k8ssandra from Datastax * Episode 98 with Sam Ramji * k0s from Mirantis * Solo.io announces Gloo Mesh Enterprise and rebrands products * Episode 55, with Idit Levine * Pinniped * Shipa launches Ketch * Kinvolk launches Headlamp * The SPIFFE book “Solving The Bottom Turtle” * Episode 45, with Andrew Jessup * Anthos Developer Sandbox * GKE ingress features * Ambassador Labs takes in $18m and launches v1.9 * Tanzu SQL: Postgres on Kubernetes * Lightning round: * Accurics extends Terrascan * AWS adds containers to Lightsail * Arrikto takes $10m in funding * Brobridge releases Gravity * CircleCI runner is GA * Cloud66 for agencies and multiple database support * Cloudflare Origin CA cert-manager plugin * Cloudical Vanillastack * Cloudify version 5.1 * Codefresh launches GitOps 2.0 features * Commvault backup-as-a-service * Diamanti Spektra 3.1 and customer portal * Dynatrace PurePath 4 * Elastisys Compliant Kubernetes * The Fairwinds Kubernetes Maturity Model * Garden takes “seed” funding * Gremlin adds soundproofing * Humio Operator * Instana adds observability tools on Kubernetes * Intuit runs TurboTax on Kubernetes * Kioxia announces a new storage offering * Kubecost adds features for monitoring outside a cluster * KubeMQ adds automatic network creation * Kubermatic updates KubeOne to v1.1 * Kubernative SINA * Kublr 1.19 * Lablup announced Backend.ai 20.09 RC * Magalix launches KubeAdvisor 2.0 * Mayadata launches Kubera Propel and Kubera Chaos * Mirantis adds extensions to Lens * Puppet Labs adds Relay to Puppet Enterprise * Reblaze announces Curiefense to add WAF to Envoy * Replicates wants to help you Troubleshoot * Styra adds new editions to DAS * Sysdig introduces Kubernetes-native network security (ZTNSK) and partners with IBM Cloud * TrilioVault for Kubernetes v2.0 * Zerto for Kubernetes * Google Open Source Live Kubernetes Links from the interview * KubeCon NA 2020 * Episode 117, with Constance Caramanolis * CNCF Twitch * SIG Friday: ping Stephen for the current link * Slack * CNCF Slack * Kubernetes Slack * Hallway Track * Kubernetes Podcast chat * CoreOS * CoreOS Tectonic * CoreOS acquired by Red Hat * Tectonic on Azure * SIG Azure * SIG Release * SIG PM (retired) * Kubernetes Enhancement Process * Receipts process KEP * Sidecar containers - KEP closed! * Production readiness review * Episode 10, with Josh Berkus and Tim Pepper * Release managers * Black Lives Matter announcement banner * Better announcements * Kubernetes Naming working group * Inclusive Naming project * Dan Kohn memorial * Stephen Augustus on Twitter and on the web
53 min
The Cloudcast
The Cloudcast
Cloudcast Media
eBPF & Cilium Cloud-native Networking
Dan Wendlandt (@danwendlandt, CEO/Co-Founder @Isovalent talks about the evolution of cloud networking, eBPF and Cilium for programmable infrastructure, and blurring the lines between networking, security and service-mesh.  *SHOW: *476 *SHOW SPONSOR LINKS:* * CloudAcademy -Build hands-on technical skills. Get measurable results.  * Get 50% of the monthly price of CloudAcademy by using code CLOUDCAST * Datadog Security Monitoring Homepage - Modern Monitoring and Analytics * Try Datadog yourself by starting a free, 14-day trial today. Listeners of this podcast will also receive a free Datadog T-shirt. * Learn more about Fauna: https://www.fauna.com/serverless * Try FaunaDB for Free: https://dashboard.fauna.com/accounts/register *CLOUD NEWS OF THE WEEK *- http://bit.ly/cloudcast-cnotw *PodCTL Podcast is Back (Enterprise Kubernetes) *- http://podctl.com *SHOW NOTES:* * Isovalent (homepage) * Cilium (homepage) * What is eBPF?  *Topic 1 *- Welcome to the show. We’ve been following your work for a while (Nicira, OpenShift networking, etc), but tell our audience a little bit about your background. *Topic 2* - A few years ago I wrote an article that said, “if you’re in networking, the #1 skill you should learn is Linux”. Why has there been so much shift from “traditional networking” to so many new capabilities being implemented in software, and specifically Linux? *Topic 3 *- Help us understand these two new concepts - eBPF and Cilium. It’s new packet filtering, it’s container networking, it’s multi-cluster networking, it can help with observability - lots going on here.  *Topic 4 *- What are some of the gaps in today’s networking/filtering/observability stacks that can improve with eBPF/Cilium?*   * *Topic 5 *- We’ve seen quite a few companies evolve from expertise in an open-source project to commercial offerings. What lessons have you learned from other companies that shape how Isovalent will both go-to-market and also engage with ecosystem partners?* * *Topic 6 *- What are some of the common use-cases or applications you see that highlight the value of the Isovalent stack?  *FEEDBACK?* * Email: show at thecloudcast dot net * Twitter: @thecloudcastnet
36 min
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