Neo4j’s support for public cloud platforms has grown tremendously in 2018, as well as customer’s utilization of Docker and Kubernetes approaches.
In this session we will give an overview of the options for how Neo4j can be run quickly and easily. We will provide:
- An Amazon AWS run-down of options and tradeoffs
- Google Cloud rundown of options and tradeoffs
- How running neo4j in Docker or Kubernetes is different, and how it works
- Examples of how to automate your neo4j instances, such as for Continuous Integration pipelines
- How other Neo4j tooling (like Desktop and Bloom) interact with graphs in the public cloud
We will also cover the different modes of running Neo4j, to show how the same techniques apply whether you’re a user of Community Edition, Enterprise Edition, whether single node or running in a clustered configuration.
