AMIS Oracle OpenWorld & CodeOne Review - Pillar 1 - Cloud Infrastructure (5 november 2018)

Editor's Notes

• #2: Fast data arrives in real time and potentially high volume. Rapid processing, filtering and aggregation is required to ensure timely reaction and actual information in user interfaces. Doing so is a challenge, make this happen in a scalable and reliable fashion is even more interesting. This session introduces Apache Kafka as the scalable event bus that takes care of the events as they flow in and Kafka Streams and KSQL for the streaming analytics. Both Java and Node applications are demonstrated that interact with Kafka and leverage Server Sent Events and WebSocket channels to update the Web UI in real time. User activity performed by the audience in the Web UI is processed by the Kafka powered back end and results in live updates on all clients. Fast data arrives in real time and potentially high volume. Rapid processing, filtering and aggregation is required to ensure timely reaction and actual information in user interfaces. Doing so is a challenge, make this happen in a scalable and reliable fashion is even more interesting. This session introduces Apache Kafka as the scalable event bus that takes care of the events as they flow in and Kafka Streams for the streaming analytics. Both Java and Node applications are demonstrated that interact with Kafka and leverage Server Sent Events and WebSocket channels to update the Web UI in real time. User activity performed by the audience in the Web UI is processed by the Kafka powered back end and results in live updates on all clients. Introducing the challenge: fast data, scalable and decoupled event handling, streaming analytics Introduction of Kafka demo of Producing to and consuming from Kafka in Java and Nodejs clients Intro Kafka Stream API for streaming analytics Demo streaming analytics from java client Intro of web ui: HTML 5, WebSocket channel and SSE listener Demo of Push from server to Web UI - in general End to end flow: - IFTTT picks up Tweets and pushed them to an API that hands them to Kafka Topic. - The Java application Consumes these events, performs Streaming Analytics (grouped by hashtag and author and time window) and counts them; the aggregation results are produced to Kafka - The NodeJS application consumes these aggregation results and pushes them to Web UI - The WebUI displays the selected Tweets along with the aggregation results - in the Web UI, users can LIKE and RATE the tweets; each like or rating is sent to the server and produced to Kafka; these events are processed too through Stream Analytics and result in updated Like counts and Average Rating results; these are then pushed to all clients; this means that the audience can Tweet, see the tweet appear in the web ui on their own device, rate & like and see the ratings and like count update in real time
• #6: Core acritical choices are optimized for Security and Performance. Our physical network design is flat and non-oversubscribed. Our secret saus is off box virutalzoation; As name suggests implemented Storage and Networking virutaizont is built out side server (unlike other clouds everything is on the hypervisor). It has two advantages a) No provider SW runs on your machine. Hence secure. And b) We can offer you bare metal server on-demand.
• #15: High Availability architectures require fault isolated building blocks.   We provide 3 physically close but fault isolated Availability Domains within a Region, allowing for synchronous replication and constant uptime for almost any disaster. Each Availability Domain is an Independent data center, with independent power and network. Multiple Regions with a high bandwidth network and easy connectivity to support recovery for truly catastrophic events.
• #17: Eye chart .. For the last four year, we have been budilgin .. Core service … Data services .. Next laryer services ...to help deploy your applciations faster. And a vibrant third party ecosystem Key takeaway – If you have an pplication that neds to be deployed in the cloud, we can do it the way you want to.
• #19: Clay Magouyrk, Senior Vice President, Software Development, Oracle
• #40: https://www.datamation.com/cloud-computing/slideshows/top-7-cloud-computing-companies-in-2018.html
• #46: The cloud edge is the point where people and devices connect to the network, making it both a crucial point for users’ interactions with applications in the cloud and a potential launch point for attacks. Our cloud edge is mature, proven, and fully scaled. The Oracle Cloud Infrastructure edge network is built to deliver the following advantages in a multicloud environment:  Ensure high-speed web traffic with minimal latency Defend against targeted application-layer attacks Protect against volumetric attacks on network infrastructure https://blogs.oracle.com/cloud-infrastructure/oracle-cloud-infrastructure-is-ready-for-any-and-all-workloads
• #51: https://map.internetintel.oracle.com/
• #52: https://twitter.com/InternetIntel
• #64: https://www.oracle.com/openworld/on-demand.html?bcid=5853085984001 Time: 43:25
• #77: https://static.rainfocus.com/oracle/oow18/sess/1523720875201001bowD/PF/Exadata%20OOW%202018_1540521672709001DFBX.pdf