The service mesh abstraction allows for a consistent model for managing and monitoring the different components of a microservices architecture. 

In the service mesh pattern, each service is deployed with a sidecar container that contains a service proxy. These sidecars are collectively referred to as the “data plane.” Each sidecar provides the service that it is deployed next to with a set of features such as security policy, rate limiting, and monitoring instrumentation.

The sidecars in the data plane communicate with a central module called a control plane. In the control plane, an engineer can operate across these individual services at scale, by pushing out updates to them.

Kubernetes has made it easier to manage large fleets of microservices, and has led to wider adoption of service mesh. Istio is one of the most popular service mesh products. In today’s show, Varun Talwar returns to the show to describe the state of the Istio project and the process of deploying Istio to a cluster. Varun is the CEO of Tetrate, a company building an enterprise-ready service mesh. Prior to Tetrate, Varun was at Google, where he helped found the gRPC and Istio projects.

The PlayStation is a line of game consoles created by Sony. PlayStation devices include the PS2, PS3, PS4, and the PSP mobile system. Tony Godar worked as an engineer in the PlayStation ecosystem for 15 years, and he joins the show to give a retrospective on his time in the console industry.

Developing hardware and software for game consoles differs significantly from the world of web development. Tony describes the culture of the game development world, and the challenges involved in the domains of software tooling, custom operating systems, and streaming media. In 2010, the PS3 was hacked by notorious tinkerer George Hotz, a previous guest on the show, an event which Tony also discusses.

We also discuss the world of modern gaming and VR technology. Tony currently works as an engineer at MelodyVR, a company that makes virtual reality live music experiences.

Large software companies have become a target for criticism. Google, Facebook, Amazon and other prominent technology giants find themselves under a kind of scrutiny that is reminiscent of banks in 2008 and oil companies in the early 1900s. Across the planet, there is a growing sentiment that “big tech” has too much power, and that they are abusing that power in order to dominate markets, censor speech, and manipulate politics.

Tyler Cowen is the author of Big Business: A Love Letter to an American Anti-Hero. He is also the host of the popular podcast Conversations with Tyler and an economist at George Mason University. In Big Business, Tyler explores the modern relationships between consumers and businesses, including the large technology companies.

Tyler joins the show to discuss his new book. In previous episodes with Tyler, we also talked about his previous books as well as the effects of technology on American society and the philosophical approaches software engineers can bring to their careers.

In this episode Will Larson, author of An Elegant Puzzle: Systems of Engineering Management, speaks with Uma Chingunde of Stripe and Jeff Meyerson of Software Engineering Daily about engineering management. Will was also featured on SE Daily recently.

An Elegant Puzzle is an excellent resource on management techniques and strategies for scaling software organizations. Will’s writing draws from his experiences working at Uber and Stripe.

Data-as-a-service businesses offer paid access to data sets. These data sets can be useful for building products or training machine learning models. 

There has been steady growth in the tools and practices around processing and storing data. But access to data sets remains a bottleneck for widespread development of machine learning applications in a large set of domains. 

SafeGraph is a company focused on the problem of data-as-a-service. Today, SafeGraph’s primary product is reliable, up-to-date location information on places. The data for these points-of-interest needs be acquired, verified, cleaned, made accessible through an API, and intelligently priced. 

In previous episodes with SafeGraph, we have explored the basic premise of data businesses and why they are important platforms for building futuristic data products that are impossible for entrepreneurs to build today. SafeGraph CEO Auren Hoffman returns to the show to discuss the data as a service business model.

Software-as-a-service has existed as a category for more than a decade. Infrastructure-as-a-service has existed for just as long. Data-as-a-service is much more undeveloped. Auren recently published the “Data-As-A-Service Bible: Everything You Wanted To Know About Running A DaaS Business”. This was a very useful article, as it breaks down a category of software that is almost entirely unexplored.

Data-as-a-service businesses offer paid access to data sets. These data sets can be useful for building products or training machine learning models. 

There has been steady growth in the tools and practices around processing and storing data. But access to data sets remains a bottleneck for widespread development of machine learning applications in a large set of domains. 

SafeGraph is a company focused on the problem of data-as-a-service. Today, SafeGraph’s primary product is reliable, up-to-date location information on places. The data for these points-of-interest needs be acquired, verified, cleaned, made accessible through an API, and intelligently priced. 

In previous episodes with SafeGraph, we have explored the basic premise of data businesses and why they are important platforms for building futuristic data products that are impossible for entrepreneurs to build today. SafeGraph CEO Auren Hoffman returns to the show to discuss the data as a service business model.

Software-as-a-service has existed as a category for more than a decade. Infrastructure-as-a-service has existed for just as long. Data-as-a-service is much more undeveloped. Auren recently published the “Data-As-A-Service Bible: Everything You Wanted To Know About Running A DaaS Business”. This was a very useful article, as it breaks down a category of software that is almost entirely unexplored.

A large sales organization has hundreds of sales people. Each of those sales people manages a set of accounts who they are trying to close sales deals on. Sales people are overseen by managers who ensure that the sales people are performing well. Directors and VPs ensure the scalability and health of the overall sales organization.

The sales lifecycle mostly takes place within a piece of software called a CRM: customer relationship management. This tool documents the interactions between sales people and accounts. CRMs have been around for many years, and although CRM software is a useful repository of data, it does not fulfill all the needs of a salesperson.

People.ai is a system of machine learning tools built around the sales tooling ecosystem. People.ai helps a sales organization avoid manual data entry, understand areas of potential improvement, and decide on who the highest value sales lead to pursue might be. Andrey Akselrod is the CTO At People.ai and he joins the show to discuss the potential applications of machine learning in the domain of sales, and the engineering work that his company has done.

A large sales organization has hundreds of sales people. Each of those sales people manages a set of accounts who they are trying to close sales deals on. Sales people are overseen by managers who ensure that the sales people are performing well. Directors and VPs ensure the scalability and health of the overall sales organization.

The sales lifecycle mostly takes place within a piece of software called a CRM: customer relationship management. This tool documents the interactions between sales people and accounts. CRMs have been around for many years, and although CRM software is a useful repository of data, it does not fulfill all the needs of a salesperson.

People.ai is a system of machine learning tools built around the sales tooling ecosystem. People.ai helps a sales organization avoid manual data entry, understand areas of potential improvement, and decide on who the highest value sales lead to pursue might be. Andrey Akselrod is the CTO At People.ai and he joins the show to discuss the potential applications of machine learning in the domain of sales, and the engineering work that his company has done.

During 2015, Uber was going through rapid scalability. The internal engineering systems were constantly tested by the growing user base. Over the next two years, the number of internal services at Uber would grow from 500 to 2000, and standardizing the monitoring of all these different services became a priority.

After working with a variety of available tools, Uber’s engineering team decided that something new needed to be built internally. Jaeger is an open source distributed tracing tool that provides observability features throughout Uber’s microservices architecture.

Yuri Shkuro is an engineer at Uber, where he works on Jaeger and other infrastructure projects. He joins the show to discuss the history of engineering at Uber, the architecture of Jaeger, and the requirements for building and scaling a distributed tracing tool.

During 2015, Uber was going through rapid scalability. The internal engineering systems were constantly tested by the growing user base. Over the next two years, the number of internal services at Uber would grow from 500 to 2000, and standardizing the monitoring of all these different services became a priority.

After working with a variety of available tools, Uber’s engineering team decided that something new needed to be built internally. Jaeger is an open source distributed tracing tool that provides observability features throughout Uber’s microservices architecture.

Yuri Shkuro is an engineer at Uber, where he works on Jaeger and other infrastructure projects. He joins the show to discuss the history of engineering at Uber, the architecture of Jaeger, and the requirements for building and scaling a distributed tracing tool.