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4m 41s - Adopting Microservices allows you to write your software in different programming languages so you could have some written in Node.js, some in Python, some in Go and some in Java.

5m 22s - Microservices bring lots of benefits, like teams owning their own release cycles and being responsible for their own uptime.

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5m 46s - Because each team does their own thing, the aggregate velocity would in many cases be slower the Java people had to figure out how to talk to the metrics system, as did the Node people and the Go people.

6m 05s - A hard-fought bug on one platform also has to be battled on another platform.

6m 19s - I hadnР Р†Р вЂљРІвЂћСћt expected the cost of multiple languages to be as high as it was.

7m 21s - Uber is in many different data centres around the world, to get the data closer to customers and for availability reasons.

7m 43s - At the front end we do TLS termination and we are trying to push that as close to the end users as we can, so weР Р†Р вЂљРІвЂћСћre using some cloud providers for that.

8m 03s - We then have the Node.js dispatch system, now called Marketplace, as Uber expands into other sorts of logistics beyond transportation.

8m 31s - Marketplace is gradually moving from Node.js to Go and Java.

8m 50s - This is the part of the system that actually has to be up so this is where we do aggressive failure testing and require the highest level of scrutiny about all the changes we make.

9m 14s - Uses Riak clusters to manage the state of all the jobs that are in progress.

9m 31s - Completed jobs are moved out of the Marketplace system and into various other business logic systems, a lot of which go through Kafka.

9m 58s - Various other queues also execute workflow to, for example, prompt you to get a receipt and rate the trip.

10m 27s - The map services compute the ETAs and routes for the trip.

These are some of the highest throughput systems and are mostly written in Java.

11m 07s - All the Kafka streams go to Hadoop for analytics processing.

12m 44s - Such a huge team and product growth rate would not be possible without being able to hire really good engineers.

It would be much more efficient if we hired more slowly, but the competition is fierce and we have to work hard to stay ahead.

13m 51s - One of the interesting things is that because we were adding people so quickly it wouldnР Р†Р вЂљРІвЂћСћt have been possible if we werenР Р†Р вЂљРІвЂћСћt building things as lots of tiny services.

14m 44s - Uber's culture is not always cohesive.

16m 14s - Uber has a team that manages the in-house build and deploy pipeline.

Uses Jenkins as well as in-house developed automation.

16m 44s - They also have an observability (metrics) team.

17m 10s - There are four different languages and many different client libraries, so logging is hard for the Kafka team.

17m 58s - There are a lot of flaws but the business is incredibly successful, which fixes a lot of problems.

21m 38s - Learnt from a lot of big companies like Google, Facebook, Twitter and Microsoft.

22m 10s - Ringpop, which most of the Marketplace systems are based on, is inspired by Microsoft Orleans and is in Github.

22m 46s - Currently working on interesting things around their RPC protocol, which will be open sourced.

23m 28s - Other systems that share the same design to support aggressive failure testing in production without other users noticing.

24m 36s - The failure testing is UberР Р†Р вЂљРІвЂћСћs version of NetflixР Р†Р вЂљРІвЂћСћs Simian Army, but Uber runs a lot of its own data centres as well as Amazon so itР Р†Р вЂљРІвЂћСћs had to build a lot of its own tooling.

25m 28s - There must not be any Nodes in the system that canР Р†Р вЂљРІвЂћСћt break - anyone should be able to take any Node down.

26m 16s - Caitie McCaffrey from Twitter and Sean T.

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