Shift Dev Conf API

Editor's Notes

• #2: Thank you I will speak you about ….. What do you do : 80% Access your Data – 20% execute functions
• #9: One of Cassandra's fault-tolerance strategies is replication. Replication is a matter of duplicating data across nodes. The number of replicas is called the Replication Factor. Let’s look at some examples… <click> (RF=1 appears) Let’s start with the simplest example: a replication factor of 1 – only a single copy It’s not something you would likely do in production, but it's a good place to start the discussion. <click> (data appears) Here we’re showing a write request Some data with a partition token of 59 <click> (data moves to node) The top-right node will serve as the coordinator <click> (data turns purple) Notice 59 falls in the purple range <click> (data move to the node) So the coordinator forwards the data to the purple node <click> (data clears) <click> (RF=2 appears) Let's increase the replication factor to 2 <click> (ring colors double) This doubles the range that each node is responsible for. For example, node 75 becomes responsible for the red range and the purple range <click> (data appears) Again our request to write partition with token 59 arrives. But this time the coordinator sends it to two nodes. <click> (data moves) <click> (data fades) Let's increase the replication factor to 3 <click> (RF=3 appears) This means that each node is responsible for 3 ranges <click> (3 ranges appear) Once again, the data arrives at the coordinator Where will the coordinator send the data this time? <click> (data moves) We see the data replicated to all three nodes <click> (data fades) So, in a nutshell, that's how replication works
• #10: Consistency level is different than replication factor. On a read, consistency level is how many replicas you read Each replica has a time stamp. The most recent replica wins In this example, imagine we have a replication factor of 3. <click> (shows write arrows) So when we write, we write 3 replicas of the data. <click> (shows CL=ONE) Now let's say we want to read from this cluster with a consistency level of 1. In this case, we only need to read from a single node to resolve the data. <click> (shows read arrows) Now, we can change the consistency level to quorum, <click> (CL=QUORUM appears) Which means we want to read a majority of the replicas. Since the replication factor is 3, quorum implies reading 2 replicas <click> (second read line appears) Notice, if the replicas disagree, the coordinator returns the data with the most recent time stamp <click> (CL clears) We can even specify a consistency level of ALL, <click> (CL=ALL appears) Which means we will read all replicas <click> (third read line appears) (pause to let people absorb)
• #14: ALEXANDRE Few logos: As we already told we are using Java why not using the last Java 12 Services are implemented and connected with Spring Everything is wrapped into a Spring boot 2.1 application Services are exposed as REST with Spring MVC Did you see our gray hairs and beards here, we do Java, we are serious people and do not play with the teenager language JavaScript
• #23: ALEXANDRE Show repository, stress its simplicity and blocking calls Show controller, same thing Show controller unit test, run tests