Pregel: A System For Large-Scale Graph Processing The Binary Breakdown podcast

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B2B marketing strategy grows ever more complex, with marketers needing to understand strategy, marketing technology, e-commerce, customer success, and more. This show covers it all, from a Business-to-Business perspective. From the creators and host of the award-winning The Agile Brand with Greg Kihlström podcast, comes B2B Agility™, a podcast focused on how B2B marketers and the brands they represent become category leaders and drive optimal results for the business and their customers. The show looks at B2B success in a variety of ways, all with a focus on the intersection of sales, marketing & technology.

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Pregel: A System for Large-Scale Graph Processing

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תוכן מסופק על ידי The Binary Breakdown. כל תוכן הפודקאסטים כולל פרקים, גרפיקה ותיאורי פודקאסטים מועלים ומסופקים ישירות על ידי The Binary Breakdown או שותף פלטפורמת הפודקאסט שלהם. אם אתה מאמין שמישהו משתמש ביצירה שלך המוגנת בזכויות יוצרים ללא רשותך, אתה יכול לעקוב אחר התהליך המתואר כאן https://he.player.fm/legal.

The article is a paper published in 2010 by researchers at Google that introduces Pregel, a large-scale graph processing system. Pregel is designed for processing graphs with billions of vertices and trillions of edges, and it uses a vertex-centric approach where vertices are assigned to individual machines and communicate with each other through message passing. The paper details the model of computation, the C++ API, and the implementation of Pregel, including fault-tolerance mechanisms for dealing with machine failures. It also explores applications of Pregel to various graph algorithms, including PageRank, shortest paths, bipartite matching, and semi-clustering, providing experimental results for shortest paths on graphs ranging in size from 10 million to 1 billion vertices. Finally, the paper discusses related work and future directions for Pregel, highlighting its strengths and potential areas for improvement.

https://15799.courses.cs.cmu.edu/fall2013/static/papers/p135-malewicz.pdf

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#Podcasting Education #The Binary Breakdown

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Pregel: A System for Large-Scale Graph Processing

The Binary Breakdown

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תוכן מסופק על ידי The Binary Breakdown. כל תוכן הפודקאסטים כולל פרקים, גרפיקה ותיאורי פודקאסטים מועלים ומסופקים ישירות על ידי The Binary Breakdown או שותף פלטפורמת הפודקאסט שלהם. אם אתה מאמין שמישהו משתמש ביצירה שלך המוגנת בזכויות יוצרים ללא רשותך, אתה יכול לעקוב אחר התהליך המתואר כאן https://he.player.fm/legal.

The article is a paper published in 2010 by researchers at Google that introduces Pregel, a large-scale graph processing system. Pregel is designed for processing graphs with billions of vertices and trillions of edges, and it uses a vertex-centric approach where vertices are assigned to individual machines and communicate with each other through message passing. The paper details the model of computation, the C++ API, and the implementation of Pregel, including fault-tolerance mechanisms for dealing with machine failures. It also explores applications of Pregel to various graph algorithms, including PageRank, shortest paths, bipartite matching, and semi-clustering, providing experimental results for shortest paths on graphs ranging in size from 10 million to 1 billion vertices. Finally, the paper discusses related work and future directions for Pregel, highlighting its strengths and potential areas for improvement.

https://15799.courses.cs.cmu.edu/fall2013/static/papers/p135-malewicz.pdf

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Anna: A KVS For Any Scale 19:01

לפני 21 ימים19:01

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19:01

This research paper introduces Anna , a key-value store (KVS) designed for scalable performance across diverse computing environments, from single multi-core machines to globally distributed cloud deployments. Anna achieves high performance and adaptability through a partitioned, multi-master architecture utilizing wait-free execution and coordination-free consistency . Its design is built upon coordination-free actors and lattice-based composite data structures , which allow for various consistency models and elastic scaling. The authors demonstrate that Anna effectively leverages multicore parallelism and scales smoothly, outperforming traditional KVS systems like Redis and Cassandra in specific scenarios while offering a wider range of consistency levels with minimal overhead. https://dsf.berkeley.edu/jmh/papers/anna_ieee18.pdf…

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Conflict-free Replicated Data Types 26:17

לפני 28 ימים26:17

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26:17

This academic paper introduces Conflict-free Replicated Data Types (CRDTs) , which are abstract data types designed for distributed systems where data is replicated across multiple locations. CRDTs allow any replica to be modified without needing immediate coordination with other replicas, ensuring high availability and low latency . The core concept is that CRDTs employ mathematically sound rules and specific concurrency semantics (like add-wins or last-writer-wins) to guarantee that replicas converge to the same state when they have received the same updates, even if updates occur concurrently. The paper explores various synchronization models for propagating updates between replicas, discusses key research findings related to preserving sequential semantics and handling concurrency, examines guarantees and limitations (including their relationship with the CAP theorem), highlights examples of applications where CRDTs are used, and outlines future research directions such as scalability and security. https://arxiv.org/pdf/1805.06358…

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CAP Twelve Years Later: How the "Rules" Have Changed 29:47

לפני 5 weeks29:47

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29:47

This content from InfoQ provides insights for software architects and developers through various formats like newsletters, articles, and conference information. It highlights topics in architecture, AI, data engineering, culture, methods, and DevOps . Featured pieces discuss Slack's cellular architecture, data stream processing patterns, cultivating resilience, and implementing EU Cyber Resilience Act requirements . A significant portion focuses on a detailed article examining the CAP theorem twelve years later, clarifying common misconceptions and discussing practical approaches for managing partitions and consistency in distributed systems. The text also mentions upcoming InfoQ Dev Summit and QCon events . https://www.infoq.com/articles/cap-twelve-years-later-how-the-rules-have-changed/…

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Raft versus Paxos: An Understandable Consensus Algorithm 33:14

לפני 6 weeks33:14

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33:14

Raft , a consensus algorithm designed for managing a replicated log in distributed systems. It aims to be more understandable than Paxos , a widely used but complex alternative, while achieving equivalent efficiency and safety. Raft separates key consensus elements like leader election , log replication , and safety , using techniques such as problem decomposition and state space reduction to enhance clarity. The document describes the algorithm's server states (leader, follower, candidate), time divided into terms , and communication through RPCs for leader election, log replication, and eventually log compaction and client interaction. A user study is presented as evidence of Raft's improved understandability compared to Paxos.…

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Neo4j Architecture: Graph Database Internals, Performance, and Optimization 17:42

לפני 7 weeks17:42

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17:42

This compilation of resources offers a comprehensive examination of Neo4j's graph database architecture. It explains how Neo4j differs from relational and document-oriented databases through its native graph storage. The materials describe how nodes, relationships, and properties are stored and indexed for efficient traversal and query processing. Transaction management, ACID compliance, performance optimization techniques like the Block format, and real-world applications are also addressed. The text concludes by acknowledging ongoing challenges such as migration, scaling, and machine learning integration, while also pointing towards future advancements like GPU acceleration. https://www.perplexity.ai/page/neo4j-graph-database-architect-ktv.ktumRLmdwxtqaUT.Gw…

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Sentry: Error Monitoring at Scale - Design Principles Analysis 15:48

לפני 8 weeks15:48

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Sentry is a large-scale, open-source error monitoring platform designed for modern distributed systems. It prioritizes actionable insights by focusing on exceptions and crashes, enriching errors with contextual data, and using features such as breadcrumbs and error grouping. Sentry's architecture employs modular and decoupled components like Relay for high-throughput event processing. Scalability and fault tolerance are achieved through horizontal scaling and cross-region replication, and dynamic sampling optimizes performance by balancing data fidelity with operational costs. User experience is enhanced through URL-driven state, role-based access control, and integrations with numerous development tools. Future developments aim to address challenges like ephemeral errors in serverless environments and explore quantum-safe cryptography. https://www.perplexity.ai/page/sentry-error-monitoring-at-sca-RRaPhaGbQ9Gn3j3DcddQKg…

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Istio Service Mesh: Architecture, Security, and Traffic Management 33:58

לפני 9 weeks33:58

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33:58

These excerpts offer a detailed look at Istio's service mesh architecture, a critical component for managing microservices in cloud-native environments. The architecture is divided into a control plane and data plane, emphasizing security through automated mTLS and traffic management with advanced load balancing techniques. Observability is achieved through comprehensive telemetry collection, although performance overhead remains a concern. Various deployment models, including multi-cluster and hybrid setups, are supported, but operational complexity necessitates careful migration strategies. Future research focuses on AI-driven optimizations and enhanced security measures, ensuring Istio remains relevant in evolving cloud ecosystems. https://www.perplexity.ai/page/istio-service-mesh-architectur-JZjsEh8qSHSQMjAHUCaWLg…

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CockroachDB: SQL for Global Scale Design Principles 14:33

לפני 10 weeks14:33

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14:33

CockroachDB is a distributed SQL database designed for global scalability and resilience. The database achieves this through a unique architecture built on a monolithic key-value store, Raft-based replication, and hybrid logical clocks. Transaction management is optimized for global workloads using a non-blocking commit protocol and multi-region capabilities. CockroachDB offers declarative data locality, enabling administrators to define data placement policies for performance and compliance. Performance optimization strategies, like follower reads and elastic scaling, help reduce latency and costs. Despite its strengths, challenges remain around write amplification and tradeoffs associated with global tables, but future development focuses on serverless architecture and AI-driven autotuning. https://www.perplexity.ai/page/cockroachdb-sql-for-global-sca-8wVC7NgaQAup2iEyCWw8Fw…

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Snowflake: Revolutionizing Cloud Data Warehousing and Analytics 17:21

לפני 11 weeks17:21

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Snowflake, a cloud-native data warehouse, revolutionizes modern analytics through its unique architecture and capabilities. The platform separates compute and storage layers, enabling independent scaling and optimized performance. Its three-layer design encompasses cloud services, a compute layer using virtual warehouses, and a storage layer leveraging cloud object storage. Snowflake's architecture ensures security, manages concurrency, and optimizes costs, outperforming cloud alternatives such as Azure Synapse and Redshift in several benchmarks. Emerging applications include genomics processing, real-time cybersecurity analytics, and multi-cloud data meshes. Despite limitations such as ETL complexity, Snowflake's future developments involve serverless GPU acceleration and integration with open table formats, solidifying its position in cloud data warehousing. https://www.perplexity.ai/page/snowflake-a-cloud-native-data-lkc22F_tRgKawFNhK.7Tdw…

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Kubernetes: Container Orchestration, Architecture, and Evolution 25:56

לפני 12 weeks25:56

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25:56

This collection of excerpts comprehensively examines Kubernetes, the leading container orchestration platform. It traces the historical evolution of container orchestration and highlights Kubernetes' architectural foundations, including its control plane and node components. Scalability mechanisms like horizontal pod autoscaling and cell-based architectures are explored, alongside the platform's security model, emphasizing role-based access control and network policies. The text further details Kubernetes' role in microservices orchestration, edge computing integrations, and CI/CD pipelines, with specific implementations like Argo CD and KubeEdge being noted. Finally, the documentation looks to the future, considering WebAssembly integration and quantum-safe cryptography, and concludes by underscoring Kubernetes' continued evolution and pivotal role in distributed systems. https://www.perplexity.ai/page/kubernetes-container-orchestra-AnzcSV82T.2kcKZAEOYSvw…

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Elasticsearch: Architecture, Applications, and Emerging Trends 18:13

לפני 13 weeks18:13

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18:13

This compilation of excerpts thoroughly examines Elasticsearch, focusing on its architecture, applications, and future trends. The core architecture and its integration within the Elastic Stack are highlighted, emphasizing scalability and real-time analytics. Various specialized applications are discussed, including maritime data storage, academic research portals, and healthcare blockchain systems. Advancements in query processing, machine learning operationalization, and security are analyzed, showcasing improved search efficiency and reduced system response times. The exploration concludes with emerging trends, such as AI-optimized hardware, decentralized search infrastructure, and environmental impact mitigation, solidifying Elasticsearch's role in modern data management. https://www.perplexity.ai/page/elasticsearch-a-comprehensive-pfqie_tbQLaK9e3liDI.8A…

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Ray: A Distributed Framework for Emerging AI Applications 19:40

לפני 14 weeks19:40

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This research paper introduces Ray, a distributed framework designed for emerging AI applications, particularly those involving reinforcement learning. It addresses the limitations of existing systems in handling the complex demands of these applications, which require continuous interaction with the environment. Ray unifies task-parallel and actor-based computations through a dynamic execution engine, facilitating simulation, training, and serving within a single framework. The system uses a distributed scheduler and fault-tolerant store to manage control state, achieving high scalability and performance. Experiments demonstrate Ray's ability to scale to millions of tasks per second and outperform specialized systems in reinforcement learning applications. The paper highlights Ray's architecture, programming model, and performance, emphasizing its flexibility and efficiency in supporting the evolving needs of AI. https://www.usenix.org/system/files/osdi18-moritz.pdf…

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Zanzibar: Google's Global Authorization System 27:21

לפני 15 weeks27:21

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27:21

This paper details Zanzibar, Google's globally distributed authorization system, designed to manage access control lists (ACLs) at a massive scale. Zanzibar uses a flexible data model and configuration language to handle diverse access control policies for numerous Google services, achieving high availability and low latency. The system maintains external consistency, respecting the causal order of ACL changes, and employs techniques like caching and request hedging to handle high request volumes and hot spots. The authors present the system's architecture, implementation, and lessons learned from years of operation, highlighting challenges and solutions in building a consistent, world-scale authorization system. The paper also explores related research in access control and distributed systems. https://www.usenix.org/system/files/atc19-pang.pdf…

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Google Mesa: A Geo-Replicated, Near Real-Time Data Warehouse 15:02

לפני 16 weeks15:02

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**Mesa** is a highly scalable, geo-replicated data warehousing system developed at Google to handle petabytes of data related to its advertising business. **Designed for near real-time data ingestion and querying**, it processes millions of updates per second and serves billions of queries daily. **Key features include strong consistency, high availability, and fault tolerance**, achieved through techniques like multi-version concurrency control and Paxos-based distributed synchronization. The paper details Mesa's architecture, including its storage subsystem using versioned data management with delta compaction, and its multi-datacenter deployment. Finally, it explores operational challenges and lessons learned in building and maintaining such a large-scale system. https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=bb1af5424e972c0c15f21e3847708e4d393abfae…

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Time, Clocks, and the Ordering of Events in a Distributed System 13:50

לפני 17 weeks13:50

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13:50

This paper, "Time, Clocks, and the Ordering of Events in a Distributed System," explores the challenges of defining and managing time in distributed systems. It introduces the concept of a "happened before" relation to partially order events and presents an algorithm for creating a consistent total ordering using logical clocks. The paper then extends this to physical clocks, analyzing synchronization and error bounds to prevent anomalous behavior arising from discrepancies between perceived and actual event orderings. The second paper, "Shallow Binding in Lisp 1.5," focuses on efficient variable access in the Lisp 1.5 programming language. It proposes a "rerooting" method for environment tree transformations to achieve shallow binding, allowing for context switching and concurrent processes within the same environment structure, all while maintaining program semantics. The method enhances efficiency without altering a program's meaning. https://www.microsoft.com/en-us/research/uploads/prod/2016/12/Time-Clocks-and-the-Ordering-of-Events-in-a-Distributed-System.pdf…

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Google: The Chubby lock service for loosely-coupled distributed systems 51:11

לפני 33 weeks51:11

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51:11

This document describes the development and implementation of Google's Chubby lock service, a highly available and reliable system that provides coarse-grained locking and storage for distributed systems. The authors discuss the design choices behind Chubby, including its emphasis on availability over performance, and the use of a file system-like interface for ease of use. The paper details Chubby's architecture, including its components, consensus protocol, and caching mechanisms. It also explores unexpected uses of Chubby, such as its popular role as a name service, and discusses the lessons learned during its development and deployment, such as the importance of considering developer habits and the need to scale the system effectively. https://static.googleusercontent.com/media/research.google.com/en//archive/chubby-osdi06.pdf…

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Megastore: Providing Scalable, Highly Available Storage for Interactive Services 18:19

לפני 33 weeks18:19

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18:19

The provided text describes the architecture and design of Megastore, a Google-developed storage system designed to meet the needs of interactive online services. Megastore blends the scalability of NoSQL datastores with the convenience of traditional relational databases, offering high availability and strong consistency guarantees. It achieves this by utilizing Paxos, a fault-tolerant consensus algorithm, to synchronize data replication across geographically distributed data centers. Megastore also implements a partitioning strategy, dividing data into entity groups that are replicated separately, which allows for high throughput and localized outages. The authors detail the features of Megastore's data model, including ACID transactions, indexes, and queues, and explain how these features are implemented within the system. They also provide details about Megastore's replication algorithm and its performance characteristics, as well as insights into the development and operational experience with the system. https://www.cidrdb.org/cidr2011/Papers/CIDR11_Paper32.pdf…

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Bigtable: A Distributed Storage System for Structured Data 15:26

לפני 33 weeks15:26

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15:26

The article, “Bigtable: A Distributed Storage System for Structured Data,” describes a large-scale distributed data storage system developed at Google, capable of handling petabytes of data across thousands of servers. Bigtable uses a simple data model that allows clients to dynamically control data layout and format, making it suitable for various applications like web indexing, Google Earth, and Google Finance. The authors detail the system's implementation, including its use of Google File System (GFS) for data storage, Chubby for distributed locking, and SSTables for data organization. The article concludes by evaluating Bigtable's performance and scalability through various benchmarks and discusses how it is used in real Google products. https://static.googleusercontent.com/media/research.google.com/en//archive/bigtable-osdi06.pdf…

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MapReduce: Simplified Data Processing on Large Clusters 14:15

לפני 33 weeks14:15

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14:15

MapReduce is a programming model that simplifies the process of processing large datasets on clusters of commodity machines. It allows users to define two functions: Map and Reduce , which are then automatically parallelized and executed across the cluster. The Map function processes key/value pairs from the input data and generates intermediate key/value pairs. The Reduce function merges all intermediate values associated with the same key to produce the final output. This paper, written by researchers at Google, describes the implementation of MapReduce on their large-scale computing infrastructure, highlighting its features, performance, fault tolerance, and real-world applications. The authors also discuss the benefits of using MapReduce, such as its simplicity, scalability, and flexibility, and compare it to other related systems. https://storage.googleapis.com/gweb-research2023-media/pubtools/4449.pdf…

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The Google File System 32:26

לפני 33 weeks32:26

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32:26

The source is a technical paper that describes the Google File System (GFS), a scalable distributed file system designed to meet Google's data processing needs. The paper discusses the design principles behind GFS, including its focus on handling component failures, managing large files, and optimizing for append-only operations. It also details the system architecture, consisting of a single master node and multiple chunkservers, as well as the implementation of various features, such as atomic record appends and snapshots. Finally, the authors present micro-benchmark results and real-world measurements from GFS clusters used at Google to illustrate the system's performance and scalability. https://static.googleusercontent.com/media/research.google.com/en//archive/gfs-sosp2003.pdf…

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TAO: Facebook’s Distributed Data Store for the Social Graph 18:46

לפני 33 weeks18:46

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18:46

Facebook developed a distributed data store called TAO to efficiently serve the social graph data. TAO prioritizes read optimization, availability, and scalability over strict consistency, handling billions of reads and millions of writes per second. TAO utilizes a simplified data model based on objects and associations, offering a specialized API designed for common social graph queries. The architecture involves a multi-layered caching system, with followers caching data and leaders communicating with the persistent storage layer in MySQL. TAO leverages a master/slave configuration to manage geographic distribution, ensuring data consistency across multiple regions while mitigating inter-region latency. The paper details the design, implementation, consistency model, performance characteristics, and a comparison with existing related work. https://www.usenix.org/system/files/conference/atc13/atc13-bronson.pdf…

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Scaling Memcache at Facebook 13:29

לפני 33 weeks13:29

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13:29

This document details how Facebook engineers scaled Memcached, a popular open-source in-memory caching solution, to accommodate the demands of the world's largest social network. The paper outlines the development of Facebook's Memcached architecture, starting with a single cluster of servers and progressing through geographically distributed clusters. It highlights key optimizations and mechanisms implemented at various scales, including reducing latency, handling failures, and maintaining data consistency across multiple regions. The document also provides insights into the characteristics of Facebook's Memcached workload, including fan-out, response size, and latency. https://research.facebook.com/publications/scaling-memcache-at-facebook/…

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Monarch: Google’s Planet-Scale In-Memory Time Series Database 20:26

לפני 33 weeks20:26

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20:26

This technical paper details the architecture and design of Monarch , a planet-scale in-memory time series database developed at Google. Monarch is used to monitor the performance and availability of massive, globally distributed systems like YouTube, Google Maps, and Gmail. The paper discusses the system's novel features, including its regionalized architecture , expressive query language , and support for sophisticated data types , such as distributions and exemplars. It also presents a comprehensive evaluation of Monarch's scalability , highlighting its ability to handle trillions of time series, ingest terabytes of data per second, and serve millions of queries per second. Finally, the paper outlines key lessons learned from the development and operation of Monarch over a decade. https://www.vldb.org/pvldb/vol13/p3181-adams.pdf…

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Gorilla: A Fast, Scalable, In-Memory Time Series Database 9:52

לפני 33 weeks9:52

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9:52

The provided text describes the architecture and functionality of Gorilla , Facebook's in-memory time series database. Gorilla was developed to address the challenges of monitoring and analyzing massive amounts of time series data generated by Facebook's vast infrastructure. The system prioritizes high availability for writes and reads, even in the face of failures, by using compression techniques, a unique data structure, and replication across geographically distributed datacenters. Gorilla achieves high performance through compression and in-memory data structures, enabling the development of new tools for time series correlation, visualization, and aggregation. The paper highlights the importance of prioritizing recent data over historical data in this context, and the trade-offs made to achieve high availability. https://www.vldb.org/pvldb/vol8/p1816-teller.pdf…

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Building a three-tier architecture on a budget 16:22

לפני 33 weeks16:22

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16:22

This document, an AWS blog post, guides users through the process of building a cost-effective, three-tier architecture using serverless technologies within the AWS Free Tier. It begins by explaining the benefits and capabilities of AWS serverless services and then provides a detailed walkthrough of how to construct each tier (presentation, business logic, and data) utilizing various free AWS services, including S3, CloudFront, Cognito, API Gateway, Lambda, and DynamoDB. The article concludes with tips on monitoring Free Tier usage to avoid unexpected charges and emphasizes the advantages of serverless architectures, particularly cost savings, scalability, and flexibility. https://aws.amazon.com/blogs/architecture/building-a-three-tier-architecture-on-a-budget/…

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The Binary Breakdown

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Saas Lens: Deploy multi-tenant SaaS workloads using AWS services 21:18

לפני 33 weeks21:18

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21:18

This whitepaper outlines the AWS Well-Architected Framework specifically for Software as a Service (SaaS) applications. It examines how to design and deploy multi-tenant SaaS workloads using AWS services, detailing best practices in operational excellence, security, reliability, performance efficiency, cost optimization, and sustainability. The whitepaper explores various architecture models like serverless SaaS, Amazon EKS SaaS, and hybrid deployments, focusing on the importance of tenant isolation and the complexities of managing and scaling a multi-tenant environment. https://docs.aws.amazon.com/pdfs/wellarchitected/latest/saas-lens/wellarchitected-saas-lens.pdf…

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The Binary Breakdown

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Streaming Media Lens 50:03

לפני 33 weeks50:03

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הפעל מאוחר יותר

50:03

This document is a white paper about the AWS Well-Architected Framework, particularly focusing on its application to streaming media workloads. It defines key components within a streaming media architecture, including ingest, processing, origin, delivery, and the client. The paper then outlines best practices for designing and implementing streaming media workloads according to the six pillars of the AWS Well-Architected Framework: operational excellence, security, reliability, performance efficiency, cost optimization, and sustainability. Finally, the document discusses specific scenarios, such as video-on-demand streaming, live streaming, and ad-supported content monetization, providing insights into the unique considerations for each scenario. https://docs.aws.amazon.com/pdfs/wellarchitected/latest/streaming-media-lens/wellarchitected-streaming-media-lens.pdf#streaming-media-lens…

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The Binary Breakdown

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1
Dynamo: Amazon’s Highly Available Key-value Store 17:43

לפני 33 weeks17:43

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17:43

This technical paper details the design and implementation of Dynamo, a highly available and scalable key-value storage system developed by Amazon.com. The paper outlines the challenges of maintaining reliability at a massive scale in an e-commerce environment and explains how Dynamo addresses these challenges by sacrificing consistency in favor of availability under certain failure scenarios. The authors explore the system architecture, including partitioning, replication, versioning, membership, and failure handling, and provide insights gained from running Dynamo in a live production environment. They also compare different partitioning strategies and highlight the tradeoffs between performance and durability. https://assets.amazon.science/ac/1d/eb50c4064c538c8ac440ce6a1d91/dynamo-amazons-highly-available-key-value-store.pdf…

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