Cloud Foundry Overview with Mike Dalessio

Podcast Wednesday, February 21 2018

Subscribe: Apple Podcasts | Android | RSS

Earlier this year we did several shows about Cloud Foundry, followed by several shows about Kubernetes. Both of these projects allow you to build scalable, multi-node applications–but they serve different types of users.

Cloud Foundry encompasses a larger scope of the application experience than Kubernetes. Kubernetes is lower level, and is actually being used within newer versions of Cloud Foundry to give Cloud Foundry users access to the Kubernetes abstractions.

Recording those shows gave me a wide understanding of how infrastructure is managed and how it has evolved. Today’s episode provides more context on Cloud Foundry–how the project got started, how people use it, and where Cloud Foundry is going. Today’s guest Mike Dalessio is a VP of engineering on Pivotal Cloud Foundry, and we had a great time talking about his work. Engineering leadership is a fine art, and conversations with engineering leaders are consistently interesting–this was no exception.

Transcript

Transcript provided by We Edit Podcasts. Software Engineering Daily listeners can go to weeditpodcasts.com/sed to get 20% off the first two months of audio editing and transcription services. Thanks to We Edit Podcasts for partnering with SE Daily. Please click here to view this show’s transcript.

Sponsors

Sponsoring today’s podcast is Datadog, a cloud-scale monitoring and analytics platform. Datadog integrates with more than 200 technologies, including Cloud Foundry, Docker, Kubernetes, and Kafka, so you can get deep visibility into every layer of your applications and infrastructure—in the cloud, on-premises, in containers, or wherever they run. With rich dashboards, machine learning-powered alerts, and distributed request tracing, Datadog helps teams resolve issues quickly and release new features faster. Start monitoring your dynamic cloud infrastructure today with a 14-day trial. Listeners of this podcast will also get a free T-shirt for trying Datadog! softwareengineeringdaily.com/datadog

When you’re building an application, you need it to be fast, secure—and always evolving. With Kubernetes Engine on Google Cloud Platform, developers can deploy fully-managed containerized apps quickly and easily. Google has been running production workloads in containers for over 15 years. We build the best of what we learn into Kubernetes, the industry-leading open source container orchestrator. Kubernetes Engine combines automatic scaling, updates and reliable, self-healing infrastructure with open-source flexibility to cut down development cycles and speed up time to market. Click to learn more about Kubernetes Engine, visit g.co/getgke.

Your enterprise produces lots of data, but you aren’t capturing as much as you would like. You aren’t storing it in the right place, and you don’t have the proper tools to run complex queries against your data. MapR is a converged data platform that runs across any cloud. MapR provides storage, analytics, and machine learning engines. Use the MapR operational database and event streams to capture your data. Use the MapR analytics and machine learning engines to analyze your data, in batch or interactively–across any cloud, on premise, or at the edge. MapR’s technology is trusted by major industries like Audi, which uses MapR for its connected vehicles. MapR also powers Aadhar, the world’s largest biometric system. To learn more about how MapR can solve problems for your enterprise, go to softwareengineeringdaily.com/mapr to find whitepapers, videos, and ebooks. Whether you are an oil company like Anadarko, a major FinTech provider like Kabbage, or a business in any other vertical, MapR can leverage the high volumes of data produced within your company. Go to softwareengineeringdaily.com/mapr and find out how MapR can help your business take full advantage of its data.