- Paper Insights #1 - Moving Beyond End-to-End Path Information to Optimize CDN Performance
- Affiliation: Google
- Learning Goals: Content Delivery Networks
- Paper Insights #2 - A Comparison of Software and Hardware Techniques for x86 Virtualization
- Affiliation: VMWare
- Learning Goals: Microprocessors, Instruction Sets, Virtual Memory, Classical Virtualization, Software Virtualization, Hardware Virtualization
- Paper Insights #3 - Memory Resource Management in VMware ESX Server
- Affiliation: VMWare
- Learning Goals: Memory, Virtual Memory, Virtualized Memory
- Paper Insights #4 - Firecracker: Lightweight Virtualization for Serverless Applications
- Affiliation: Amazon Web Services
- Learning Goals: Serverless, OS Virtualization, Lambda, Cloud Security
- Paper Insights #5 - The Design and Implementation of a Log-Structured File System
- Affiliation: University of California, Berkeley
- Learning Goals: File, File Systems, FAT File System, Log-Structured File System
- Paper Insights #6 - F2FS: A New File System for Flash Storage
- Affiliation: Samsung
- Learning Goals: Flash Memory, Solid State Drives
- Paper Insights #7 - Rethink the Sync
- Affiliation: University of Michigan
- Learning Goals: Inter-Process Communication, Speculative Execution, Journaling File System, Commit Buffering, File System Consistency
- Paper Insights #8 - The Google File System
- Affiliation: Google
- Learning Goals: Network File System, Distributed File System
- Paper Insights #9 - CacheSack: Admission Optimization for Google Datacenter Flash Caches
- Affiliation: Google
- Learning Goals: Distributed Flash Cache
- Paper Insights #10 - MapReduce: Simplified Data Processing on Large Clusters
- Affiliation: Google
- Learning Goals: Batch Processing, MapReduce, Shuffle
- Paper Insights #11 - Apache Flink™: Stream and Batch Processing in a Single Engine
- Affiliation: Apache
- Learning Goals: Stream Processing, Data Flow Graph
- Paper Insights #12 - The Dataflow Model: A Practical Approach to Balancing Correctness, Latency, and Cost in Massive-Scale, Unbounded, Out-of-Order Data Processing
- Affiliation: Google
- Learning Goals: Stream Processing, Event-Time Processing
- Paper Insights #13 - Delta Lake: High Performance ACID Table Storage over Cloud Object Stores
- Affiliation: Databricks
- Learning Goals: Databases, ETL, Data Storage Formats, Cloud Data Stores
- Paper Insights #14 - Bigtable: A Distributed Storage System for Structured Data
- Affiliation: Google
- Learning Goals: SQL v/s NoSQL Databases, B-Trees, Log-Structured Merge Trees, Distributed Wide-Column NoSQL Database, Bloom Filters
- Paper Insights #15 - Dynamo: Amazon's Highly Available Key-value Store
- Affiliation: Amazon
- Learning Goals: Distributed Hash Tables, Consistent Hashing, Quorum Systems, Vector Clocks, Merkle Trees, Distributed Key-Value Database
- Paper Insights #16 - Cassandra - A Decentralized Structured Storage System
- Affiliation: Facebook
- Learning Goals: Failure Detectors, Gossip Protocols
- Paper Insights #17 - The Eternal Tussle: Exploring the Role of Centralization in IPFS
- Affiliation: Protocol Labs
- Learning Goals: Kademlia Protocol, InterPlanetary File System
- Paper Insights #18 - Practical Uses of Synchronized Clocks in Distributed Systems
- Affiliation: Massachusetts Institute of Technology
- Learning Goals: Clock Synchronization, Network Time Protocol, At Most Once Delivery, Authentication Tokens, Cache Consistency, External Consistency
- Paper Insights #19 - Kafka: A Distributed Messaging System for Log Processing
- Affiliation: LinkedIn
- Learning Goals: Message Queues, PubSub, At Least Once Delivery
- Paper Insights #20 - Paxos Made Simple
- Affiliation: Massachusetts Institute of Technology
- Learning Goals: Consensus, FLP Impossibility, Paxos, Leader Election, Distributed Logs
- Paper Insights #21 - ZooKeeper: Wait-free coordination for Internet-scale systems
- Affiliation: Yahoo
- Learning Goals: Distributed Logs, Consistency Models, Linearizability, Sequential Consistency, Consensus, Atomic Broadcast, Coordination Kernel, Leader Election, Distributed Locks
- Paper Insights #22 - A New Presumed Commit Optimization for Two Phase Commit
- Affiliation: DEC Research Lab
- Learning Goals: Distributed Transactions, 2PC, 3PC
- Paper Insights #23 - Amazon Aurora: Design Considerations for High Throughput Cloud-Native Relational Databases
- Affiliation: Amazon Web Services
- Learning Goals: Correlated Failures, Replication, Distributed SQL Database
- Paper Insights #24 - Spanner: Google's Globally-Distributed Database
- Affiliation: Google
- Learning Goals: CAP Theorem, Distributed SQL Database, Strict Serializability, TrueTime, Paxos, 2PC
- Paper Insights #25 - Eliminating Receive Livelock in an Interrupt-driven Kernel
- Affiliation: Digital Equipment Corporation
- Learning Goals: I/O, Networking, Rate Limiting
- Paper Insights #26 - CliqueMap: Productionizing an RMA-Based Distributed Caching System
- Affiliation: Google
- Learning Goals: Software RDMA, In-Memory Caching
- Paper Insights #27 - Don't Settle for Eventual: Scalable Causal Consistency for Wide-Area Storage with COPS
- Affiliation: Princeton University
- Learning Goals: Logical Clocks, Causal Consistency
- Paper Insights #28 - TAO: Facebook's Distributed Data Store for the Social Graph
- Affiliation: Facebook
- Learning Goals: Eventual Consistency, Distributed Graph Databases
- Paper Insights #29 - Mesos: A Platform for Fine-Grained Resource Sharing in the Data Center
- Affiliation: University of California, Berkeley
- Learning Goals: Cluster Computing, High-Performance Computing, Task Scheduling
- Paper Insights #30 - Autopilot: Workload Autoscaling at Google Scale
- Affiliation: Google
- Learning Goals: Scaling
- Paper Insights #31 - F1 Query: Declarative Querying at Scale
- Affiliation: Google
- Learning Goals: Query Processing, Big Data
- Paper Insights #32 - Napa: Powering Scalable Data Warehousing with Robust Query Performance at Google
- Affiliation: Google
- Learning Goals: Data Warehouse, Distributed Analytical Database
- Paper Insights #33 - Photon: Fault-tolerant and Scalable Joining of Continuous Data Streams
- Affiliation: Google
- Learning Goals: Streaming Joins
- Paper Insights #34 - CRDTs: Consistency without Concurrency Control
- Affiliation: National Institute for Research in Computer Science and Automation
- Learning Goals: Commutative Operations
- Paper Insights #35 - Microsecond Consensus for Microsecond Applications
- Affiliation: VMWare Research
- Learning Goals: Consensus, Hardware RDMA
- Paper Insights #36 - Orca: A Distributed Serving System for Transformer-Based Generative Models
- Affiliation: Seoul National University
- Learning Goals: GPU, Model Serving, Distributed Machine Learning
- Paper Insights #37 - The Honey Badger of BFT Protocols
- Affiliation: University of Illinois, Tsinghua University, Cornell University
- Learning Goals: Blockchain, Byzantine Faults, Consensus
- Paper Insights #38 - Availability in Globally Distributed Storage Systems
- Affiliation: Google
- Leaning Goals: Availability