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Getting the most out of your containerized database
- 1. Containerized DBs In a Machine Data Environment (or how you get the most out of your containerized database) DevOps Gathering, 24th March 2017 @claus__m
- 2. About ~2yrs at Crate.io DevRel/Field Engineering/Support/ Integrations/… Crate.io Founded in 2013, ~25 people and growing Offices San Francisco, Berlin, Dornbirn (AT) Talk to me about Rust, Raspberry Pis, Tech! @claus__m
- 4. Source: HPE Jun 2016 http://www.slideshare.net/penumuru/harness-the-power-of-big-data-with-oracle-63438438/9 @claus__m
- 5. Machine Data Characteristics Millions of data points/second Streaming in from sensors, devices, logs, etc. Data diversity Structured & unstructured JSON, Blobs Real-time query performance Monitoring & alerting Complex queries of big data volumes With Terabytes of historic data Growth Adding sources often means exponential growth @claus__m
- 6. Machine Data Internet of Things Sensors, cameras, ... Wearables, Gadgets Location data, interaction data, ... Logs & Monitoring data Component health monitoring, access logs, ... Industry 4.0, Digitization Production line insights, automation, ... Vehicles Location data, health data, ... @claus__m
- 7. Clickdrive.io Fleet management & vehicle tracking Vehicle health and tracking data High ingest rate 2,000 data points per car, per second In-depth & real-time analysis Predictive maintenance, accident reconstruction, route/driver efficiency @claus__m
- 8. Roomonitor Smart apartments Monitoring & control climate, occupancy, noise, access Better efficiency, safer environment Alerts: AC/heating on with window open, noisy neighbors, ... @claus__m
- 9. Skyhigh Networks Cloud access security broker (CASB) Access logging for cloud services Large data volumes & ingest Billions of events per day from 600+ customers, 10s of thousands of concurrent TCP connections Machine data is the fingerprint of fraud Unsupervised learning to find anomalies @claus__m
- 11. Microservices Containers Isolation by default Flexibility Building blocks Horizontally scalable Mostly Stateful containers Databases? @claus__m
- 13. Consumer Visualizer An Example Sensor Sensor Produces data Consumer Receives and enriches data Visualizer Draws stuff @claus__m
- 14. LOAD BALANCER V C Deploy! S U S S C V C V Load balancer For TLS, reverse proxying, load balancing High availability 3 instances A few sensors One user to actually use it @claus__m
- 15. Go Live More users! More sensors and users Data storage Slow and fast Monitoring & Analytics Two different subsystems LOAD BALANCER V C S S U S S U NoSQL DBMessage Queue SQL DB U S S C V C MONITORING V S ANALYTICS @claus__m
- 16. But ... Even more users? Horizontal scaling? Maintenance & bug hunting? Mostly via scheduled downtimes Reporting? Kafka? Elasticsearch? Security? Access control? Expertise? Knowledge transfer? LOAD BALANCER V C S U S S U NoSQL DBMessage Queue SQL DB U S S C V C MONITORING V S ANALYTICS S @claus__m
- 20. Yay! @claus__m
- 21. CrateDB Shared nothing Partitioning & auto-sharding Replication (Almost) Zero config Multi model: Structured & unstructured SQL @claus__m
- 22. CrateDB Fundamentals Disk-based index with in-memory caching Fast and efficient OS caching Shards: Units of data Concurrency by distributing shards Distributed query execution engine “Push down” queries @claus__m
- 23. Postgres Wire Protocol ANTLR4 Parser Distributed Query Planner Query Execution Engine Elasticsearch Lucene CLIENT @claus__m
- 24. A better setup! Horizontal scalability Scale out everything Reduced tech stack Get to know it quicker Live reporting Use ad-hoc queries on production data Flexibility Schema Evolution not required @claus__m LOAD BALANCER V C S S U S S U U S S C V C MONITORING V S ANALYTICS
- 25. A better setup! No single point of failure As highly available as your service Reduced network traffic Better reliability No queue Work with real data DB isolation Accessible only from the host @claus__m LOAD BALANCER V C S S U S S U U S S C V C MONITORING V S ANALYTICS
- 26. Live Demo Docker Swarm Orchestration across platforms Eden Server (Rust!) RESTful web service Eden Client (Rust!) ARM application for reading temperature data from BMP180 Grafana To draw up a nice dashboard @claus__m LOAD BALANCER G E ME Pi E E
- 28. An Open Stack for Machine Data w/ CrateDB Ad-hoc analysis with SQL Instant reporting on production data Integrates well Legacy SQL applications included Horizontally scalable Container native, highly availability @claus__m