FoundationDB Summit 2019
| title | author | length |
|---|---|---|
| Restoring FDB after Catastrophic Accidents | Brandon Burton, Matthew Zeier | 15m |
A multi-petabyte FoundationDB deployment recovers from three real incidents using FDBDR, Linux filesystem snapshots and EBS snapshots, proving an end-to-end… | ||
| FoundationDB and Node.js: Year in Production | Steve Korshakov | 16m |
Company moves entire backend to FoundationDB and builds a Node.js library fdb.openland that provides distributed locks, work queues, an entity/record-like… | ||
| Scale & Security for Data Workloads on IBM Cloud | Jason McGee | 08m |
IBM moves its entire cloud stack onto Kubernetes and runs 16,000+ clusters and over 10,000 database instances to host mission‑critical workloads, including The… | ||
| New Snowflake Capabilities and What They Mean for FoundationDB | Torsten Grabs | 11m |
Snowflake adds table change stream and scheduled tasks that let an append-only staging table feed incremental merge logic into target tables while all task… | ||
| Unlucky Simulation | Andrew Noyes | 08m |
Replacing the fair PRNG with a coverage-guided fuzzer as the source of scheduling choices produces drastically better results: the existing fair RNG runs… | ||
| How We Saved 5x Migrating from Aurora to FoundationDB | Rick Branson, Ray Jenkins | 24m |
Segment migrates a Persona identity-resolution service from Aurora to FoundationDB and reports a 5x cost reduction while keeping serializable isolation and… | ||
| VMware Network Insight's Configuration-Store Layer | Gaurav Agarwal | 19m |
VMware Network Insight's Configuration-Store Layer - Gaurav Agarwal, VMware
This talk introduces the heterogeneous infrastructure stack in an enterprise… | ||
| Evaluation of FoundationDB in Financi... | Alok Madhukar, Rishabh Maheshwari, Subramaniam Ramamoorthi | 21m |
Evaluation of FoundationDB in Financial Services - Alok Madhukar, Rishabh Maheshwari & Subramaniam Ramamoorthi, Goldman Sachs
Within Goldman Sachs we have an… | ||
| Build Anything with FoundationDB | Ryan Worl | 25m |
Starts from an empty key value store and shows how to model a relational schema using the tuple layer, primary and secondary indexes that store the primary key… | ||
| Time Series and FoundationDB: Millions of Writes/s and 10x Compression in 2000 Lines of Go | Richard Artoul | 15m |
Prototype demonstrates building a time series engine on FoundationDB that achieves millions of writes/s, 10x compression, and fits in 2,000 lines of Go. It… | ||
| NuGraph: GraphDB as a Cloud Service Built Upon JanusGraph and FoundationDB | Jun Li, Hieu Nguyen | 19m |
eBay builds NuGraph, a JanusGraph-based GraphDB using FoundationDB as the storage backend and demonstrates a production triple‑region deployment holding 1.3… | ||
| Retrofitting a Foundation for CouchDB | Adam Kocoloski | 24m |
CouchDB is being refactored to run on FoundationDB: bindings exist, core persistence moves under CouchDB 4.0, and a working prototype implements documents… | ||
| A ZooKeeper Layer for FoundationDB | Paul Hemberger | 20m |
A proof‑of‑concept replaces ZooKeeper by mapping ZK nodes to the FoundationDB Directory Layer, emulates ZK watches by appending ordered notifications into a… | ||
| Building a Performant Configuration-Store Layer | Guarav Agarwal | 19m |
Uses a deterministic prefix derived from the transaction read-version masked+bit-reverse buckets to spread appends across storage servers and shows production… | ||
| FoundationDB as a Storage Engine for Irmin | Andreas Garnæs | 17m |
irmin-fdb implements Irmin storage on FoundationDB and ships OCaml FoundationDB bindings so Irmin (an OCaml Git-like DB) can use FoundationDB as a horizontally… | ||
| Rearchitecting CouchDB Secondary Indexes on Top of FoundationDB | Garren Smith | 18m |
Rewrites CouchDB secondary indexes to run on FoundationDB by making Mango indexes update in the same document transaction (so queries after a write see the… | ||
| A New Radix-Tree Based Memory Storage Engine | Mengran Wang | 17m |
A radix-trie based in-memory engine for FoundationDB replaces the BST and cuts per-process memory by about 25% less memory on Wavefront workloads and ~20% on… | ||
| Performance Profiling in FoundationDB | Diego Didona | 18m |
Benchmarks use perf (perf trace -s, perf record, perf report, perf script) to pinpoint a client-side bottleneck where a single networking/library thread… | ||
| Flow: An Introduction | Markus Pilman | 19m |
Flow is the custom language that implements FoundationDB’s actor-based concurrency model inside C++ and is compiled by a C# actor compiler into C++ that runs… | ||
| FoundationDB as Datastore for Training Deep Learning Models | Kannan Dorairaj | 05m |
Axstrm uses FoundationDB as the datastore and orchestration layer for a swim-tracking mobile app that stores extensive sensor and image data, spins out… | ||
| Orientation and Community Update | Alex Miller | 13m |
Quick orientation to the schedule and concrete community changes: the conference runs as a one‑and‑a‑half track split between ballroom 5 (case studies +… | ||
| FoundationDB Roadmap: Past and Future | Evan Tschannen | 17m |
2019 brings a 6.1→6.2 cycle with over 200 release notes and ~3,000 commits and a practical doubled scalability limit (from ~200 disk clusters to over 400 in… | ||
| Using FoundationDB and the FDB Record Layer to Build CloudKit | Scott Gray | 20m |
CloudKit runs on FoundationDB and the FDB Record Layer and uses per-app, per-user contiguous record-store key ranges so millions of databases move and… | ||
| Meta-Data Caching and Record Store Scalability | Alec Grieser | 06m |
A Record Layer cache uses a tiny, proxy-served metadata version key (12 bytes) added in FoundationDB 6.1 and set only via a version stamped value to detect… | ||
| Managing FoundationDB at Scale | John Brownlee | 21m |
Apple runs hundreds of clusters with over 100,000 FoundationDB processes and manages them on Kubernetes using fdb_monitor, configMaps, anti-affinity and a… | ||
| FoundationDB Record Layer: Open Source Structured Storage on FoundationDB | Nicholas Schiefer | 18m |
Apache-licensed library that implements a relational-like layer on FoundationDB using protocol buffers and transactionally maintained indexes, with an… | ||
| Redwood Storage Engine Update | Steve Atherton | 21m |
Redwood is a B+ tree storage engine for FoundationDB that ships in recent 6.2 patches and targets higher I/O throughput and smaller on-disk footprints. It… | ||
| Consistent Caching in FoundationDB | Xin Dong, Neelam Goyal | 11m |
Proposes a native cache that holds hot key ranges in memory and increases replication factor for those ranges to throw more CPUs at load; introduces ephemeral… | ||
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