Assertions vs Types: Design by Contract, Deterministic Simulation Testing, and Safety vs Availability (TigerBeetle Vol. 3)In this episode (volume 3), Kai talks with Alex about assertions, type systems, and design by contract, arguing it’s not “types vs assertions” but using both: types for cheap, structural guarantees and assertions where types become too costly or obscure logic. Alex defines assertions (in Zig) as a function that crashes the program on false, explains why disabling assertions in production is dangerous, and ties reliable assertion use to deterministic simulation/generative testing to exercise error paths. We discuss aiming for very high assertion density, repeating weak and strong assertions across call sites and callees to form an interlocking “net,” and note you don’t need special language features for DBC. We also cover safety vs availability tradeoffs, recovery/isolation boundaries (“let it crash” with recovery), TigerBeetle’s approach to correctness, a real cache/hash-table bug caught by an assertion, handling poison-pill failures via fix-forward and frequent releases, control plane vs data plane performance tactics for assertions, and why Alex doesn’t use AI to write TigerBeetle code.Chapters:00:00 Welcome and Intro01:33 Assertions Versus Types03:05 Silver Bullets Origins08:10 When Types Get Costly11:06 What Is an Assertion?12:40 Never Disable Assertions15:30 Testing and Error Paths19:52 Simulation Testing Harness22:50 Where to Assert Everywhere27:01 Redundant Contracts Benefits33:08 No Language Features Needed38:01 Visibility and Abstractions40:47 Boundaries and Integration44:01 Safety Versus Liveness Setup44:31 Safety vs Availability Tradeoffs46:16 Let It Crash Philosophy47:13 Isolation and Recovery Boundaries48:02 TigerBeetle vs IDE Priorities53:48 Always Assertions Pattern55:46 Cascading Failures in Clusters57:57 Fix Forward and Fast Releases01:02:27 Worst TigerBeetle Bug Story01:07:00 Control Plane vs Data Plane01:09:50 Assertion Performance Tactics01:15:18 AI Limits for Safety Systems01:18:55 Closing Advice on AssertionsFor memberships: join this channel as a member here:https://www.youtube.com/channel/UC_mGuY4g0mggeUGM6V1osdA/joinDon't forget to like, share, and subscribe for more insights!=============================================================================Like building stuff? Try out CodeCrafters and build amazing real world systems like Redis, Kafka, Sqlite. Use the link below to signup and get 40% off on paid subscription.https://app.codecrafters.io/join?via=geeknarrator=============================================================================Database internals series: https://youtu.be/yV_Zp0Mi3xsPopular playlists:Realtime streaming systems: https://www.youtube.com/playlist?list=PLL7QpTxsA4se-mAKKoVOs3VcaP71X_LA-Software Engineering: https://www.youtube.com/playlist?list=PLL7QpTxsA4sf6By03bot5BhKoMgxDUU17Distributed systems and databases: https://www.youtube.com/playlist?list=PLL7QpTxsA4sfLDUnjBJXJGFhhz94jDd_dModern databases: https://www.youtube.com/playlist?list=PLL7QpTxsA4scSeZAsCUXijtnfW5ARlrsNStay Curios! Keep Learning!

In this episode, Catherine, Co-Founder, and CEO of Kernel, reveals the magic behind Kernel's approach using uni-kernels and micro VMs, enabling browser startups in just milliseconds. We talk about the technical challenges of agent-based web interactions, how Cash App leverages Kernel for live QA of e-commerce sites, the intricacies of handling authentication, and the future potential of attaching virtual GPUs for optimal performance. Whether you're an AI developer or fascinated by the backbone of internet automation, don't miss this insightful conversation. Chapters:00:00 Introduction to AI Agent Challenges00:35 Welcome and Episode Overview01:58 Guest Introduction and Background02:39 The Problem Statement and Kernel's Origin07:21 Infrastructure for AI Agents16:09 Kernel's Technical Architecture20:33 Use Cases and Real-World Applications24:38 Challenges and Future Directions27:20 Running on Bare Metal: Optimizing Browser Instances28:02 Challenges in Infrastructure Optimization30:34 Headful Browsers and Human Interaction30:58 Recording and Debugging Browser Sessions33:42 Preventing Misuse of Browser Automation39:55 Handling Authentication and Secure Access44:57 Bot Detection and Good Actor Automations48:56 Future Developments and GPU Integration52:41 Conclusion and Final ThoughtsImportant links:- Homepage to go get a free account (no credit card required) and just try us out: https://www.kernel.sh/ - Our chromium on Unikernels OSS repo: https://news.ycombinator.com/item?id=43705144- The blog post where in it we benchmarked ourselves against all others and ranked the fastest browser infrastructure in the world: https://www.kernel.sh/blog/fast For memberships: join this channel as a member here:https://www.youtube.com/channel/UC_mGuY4g0mggeUGM6V1osdA/joinDon't forget to like, share, and subscribe for more insights!=============================================================================Like building stuff? Try out CodeCrafters and build amazing real world systems like Redis, Kafka, Sqlite. Use the link below to signup and get 40% off on paid subscription.https://app.codecrafters.io/join?via=geeknarrator=============================================================================Database internals series: https://youtu.be/yV_Zp0Mi3xsPopular playlists:Realtime streaming systems: https://www.youtube.com/playlist?list=PLL7QpTxsA4se-mAKKoVOs3VcaP71X_LA-Software Engineering: https://www.youtube.com/playlist?list=PLL7QpTxsA4sf6By03bot5BhKoMgxDUU17Distributed systems and databases: https://www.youtube.com/playlist?list=PLL7QpTxsA4sfLDUnjBJXJGFhhz94jDd_dModern databases: https://www.youtube.com/playlist?list=PLL7QpTxsA4scSeZAsCUXijtnfW5ARlrsNStay Curios! Keep Learning!

For memberships: join this channel as a member here:https://www.youtube.com/channel/UC_mGuY4g0mggeUGM6V1osdA/joinTigerStyle with matklad Vol. 2 Systems EngineeringChapters:00:00 Introduction to Alex and His Journey00:06 The Importance of Culture and Principles00:25 Weekly Releases and Quality Optimization00:45 Static Allocation Explained01:01 Alex's Passion for Programming01:25 Welcome and Introduction to the Show01:40 Alex's Background and Career Path04:01 Choosing the Right Language for Systems Programming07:12 Mental Models and Programming Philosophy20:19 Test-Driven Development and Quality42:00 Weekly Releases as a Force Multiplier44:49 Monoliths vs Microservices: The Core Idea47:05 The Importance of Engineering Process47:37 Designing a Scalable Chat Application49:36 Achieving Simplicity in System Design52:25 Static Allocation Explained01:13:59 Balancing Safety and Availability with Assertions01:27:08 The Passion Behind ProgrammingAbout matklad: https://matklad.github.io/aboutFor memberships: join this channel as a member here:https://www.youtube.com/channel/UC_mGuY4g0mggeUGM6V1osdA/joinDon't forget to like, share, and subscribe for more insights!=============================================================================Like building stuff? Try out CodeCrafters and build amazing real world systems like Redis, Kafka, Sqlite. Use the link below to signup and get 40% off on paid subscription.https://app.codecrafters.io/join?via=geeknarrator=============================================================================Database internals series: https://youtu.be/yV_Zp0Mi3xsPopular playlists:Realtime streaming systems: https://www.youtube.com/playlist?list=PLL7QpTxsA4se-mAKKoVOs3VcaP71X_LA-Software Engineering: https://www.youtube.com/playlist?list=PLL7QpTxsA4sf6By03bot5BhKoMgxDUU17Distributed systems and databases: https://www.youtube.com/playlist?list=PLL7QpTxsA4sfLDUnjBJXJGFhhz94jDd_dModern databases: https://www.youtube.com/playlist?list=PLL7QpTxsA4scSeZAsCUXijtnfW5ARlrsNStay Curios! Keep Learning!

For memberships: join this channel as a member here:https://www.youtube.com/channel/UC_mGuY4g0mggeUGM6V1osdA/joinExploring Cloud Databases, Scalability, and Simple Engineering with Sam Lambert, CEO of PlanetScaleIn this episode of The Geek Narrator podcast, we welcome Sam Lambert, CEO and Co-Founder of PlanetScale, known for creating the world's fastest and most scalable cloud database. Sam shares his insights on databases, operational excellence, and simple engineering. We discuss topics such as scalability, Postgres versus MySQL, and replication. Sam also talks about handling complexity in engineering, the unique features of Vites, and how PlanetScale achieves high availability. Don't miss this deep dive into the future of cloud databases. Like, share, and subscribe to support the channel!Chapters:00:00 Introduction and Episode Overview01:13 Meet Sam Lambert: Background and Career02:42 Balancing Work and Social Media05:48 The Philosophy of Simple Engineering14:21 The Slotted Counter Pattern at GitHub18:27 Postgres vs MySQL: Design Flaws and Philosophical Differences28:58 Sharding and Scaling with Vitess37:01 Database Branching and Schema Changes38:50 Common Practices in Startups39:07 Challenges with Data Branching40:45 Legal and Ethical Considerations42:31 Staging Environments vs. Dev Branches45:26 Trade-offs in Cloud Databases52:41 Replication and Durability01:00:02 Ensuring High Availability01:08:04 Backup Strategies and Testing01:10:41 Conclusion and Final ThoughtsLearn about PlanetScale: https://planetscale.com/For memberships: join this channel as a member here:https://www.youtube.com/channel/UC_mGuY4g0mggeUGM6V1osdA/joinDon't forget to like, share, and subscribe for more insights!=============================================================================Like building stuff? Try out CodeCrafters and build amazing real world systems like Redis, Kafka, Sqlite. Use the link below to signup and get 40% off on paid subscription.https://app.codecrafters.io/join?via=geeknarrator=============================================================================Database internals series: https://youtu.be/yV_Zp0Mi3xsPopular playlists:Realtime streaming systems: https://www.youtube.com/playlist?list=PLL7QpTxsA4se-mAKKoVOs3VcaP71X_LA-Software Engineering: https://www.youtube.com/playlist?list=PLL7QpTxsA4sf6By03bot5BhKoMgxDUU17Distributed systems and databases: https://www.youtube.com/playlist?list=PLL7QpTxsA4sfLDUnjBJXJGFhhz94jDd_dModern databases: https://www.youtube.com/playlist?list=PLL7QpTxsA4scSeZAsCUXijtnfW5ARlrsNStay Curios! Keep Learning!

For memberships: join this channel as a member here:https://www.youtube.com/channel/UC_mGuY4g0mggeUGM6V1osdA/joinSummary:In this captivating episode, we sit down with Joran Dirk Greef, the mastermind behind Tiger Beetle, a groundbreaking financial transactions database. Joran shares his journey of innovation, highlighting the challenges and triumphs of creating a system that is not only faster but also safer. Dive into the philosophy of Tiger Style, a unique methodology that emphasizes quality and performance, ensuring that software development is both efficient and effective. Joran's insights into trust, discipline, and the relentless pursuit of excellence offer valuable lessons for anyone in the tech industry. Whether you're a developer, entrepreneur, or tech enthusiast, this episode is packed with inspiration and practical wisdom. Don't miss out on this opportunity to learn from one of the leading minds in software engineering.Chapters:00:01:37 Introduction to Tiger Beetle 00:02:27 Philosophy of Tiger Style 00:03:38 Challenges in Software Development00:04:43 Importance of Trust and Quality 00:09:43 Static Allocation in Software 00:16:53 AI in Software Development 00:23:53 Business Philosophy and Innovation 00:31:53 The Future of Software DevelopmentFor memberships: join this channel as a member here:https://www.youtube.com/channel/UC_mGuY4g0mggeUGM6V1osdA/joinDon't forget to like, share, and subscribe for more insights!=============================================================================Like building stuff? Try out CodeCrafters and build amazing real world systems like Redis, Kafka, Sqlite. Use the link below to signup and get 40% off on paid subscription.https://app.codecrafters.io/join?via=geeknarrator=============================================================================Database internals series: https://youtu.be/yV_Zp0Mi3xsPopular playlists:Realtime streaming systems: https://www.youtube.com/playlist?list=PLL7QpTxsA4se-mAKKoVOs3VcaP71X_LA-Software Engineering: https://www.youtube.com/playlist?list=PLL7QpTxsA4sf6By03bot5BhKoMgxDUU17Distributed systems and databases: https://www.youtube.com/playlist?list=PLL7QpTxsA4sfLDUnjBJXJGFhhz94jDd_dModern databases: https://www.youtube.com/playlist?list=PLL7QpTxsA4scSeZAsCUXijtnfW5ARlrsNStay Curios! Keep Learning!

For memberships: join this channel as a member here:https://www.youtube.com/channel/UC_mGuY4g0mggeUGM6V1osdA/joinSummary:In this episode, host Kaivalya Apte interviews Ankit Sultana, a staff engineer at Uber with extensive experience in Apache Pinot, a real-time analytics platform. They discuss the high-level architecture, ingestion processes, and query mechanisms of Apache Pinot. Ankit provides a historical context, detailing the evolution of Apache Pinot from its origins at LinkedIn to its widespread adoption. They discuss the key components of Pinot, explaining the roles of Pinot servers, brokers, controllers, and the dependency on Zookeeper. Ankit also explained how data flows into Apache Pinot and the technicalities of its real-time ingestion and querying capabilities. Chapters:00:00 Introduction and Episode Overview03:30 Understanding Apache Pinot03:49 Apache Pinot's Historical Background05:20 Real-Time Analytics with Apache Pinot11:06 Apache Pinot's Architecture and Components17:05 Tenancy and Data Ingestion in Apache Pinot30:22 Understanding Real-Time Replication and Consumer Groups30:52 Pinot's Offset Tracking and Segment Creation31:59 Handling Server Restarts and Segment Transitions32:50 Dealing with Kafka Duplicates and Deduplication Features35:13 Ingestion Process and Mutable vs Immutable Segments39:18 Memory Management and Segment Flushing40:10 Advantages of Keeping Mutable Segments Longer42:21 Introduction to Pinot's Query Engines42:50 Single Stage Engine: Architecture and Optimizations54:49 Multi-Stage Engine: Flexibility and Challenges58:13 Conclusion and Next StepsImportant Links:* Good high-level overview on Pinot: https://www.youtube.com/watch?v=F8Q_pGIH9yY* Apache Pinot 101 by Tim: https://www.youtube.com/playlist?list=PLihIrF0tCXdfN6y-twj9KtWaXM1GH4RSe* Multistage Physical Optimizer, the new optimizer that we built at Uber and open-sourced: https://docs.pinot.apache.org/users/user-guide-query/multi-stage-query/physical-optimizer* Multistage Lite Mode: https://docs.pinot.apache.org/users/user-guide-query/multi-stage-query/multistage-lite-mode* Time Series Engine Talk at RTA Summit: https://www.youtube.com/watch?v=kgseiambgesFor memberships: join this channel as a member here:https://www.youtube.com/channel/UC_mGuY4g0mggeUGM6V1osdA/joinDon't forget to like, share, and subscribe for more insights!=============================================================================Like building stuff? Try out CodeCrafters and build amazing real world systems like Redis, Kafka, Sqlite. Use the link below to signup and get 40% off on paid subscription.https://app.codecrafters.io/join?via=geeknarrator=============================================================================Database internals series: https://youtu.be/yV_Zp0Mi3xsPopular playlists:Realtime streaming systems: https://www.youtube.com/playlist?list=PLL7QpTxsA4se-mAKKoVOs3VcaP71X_LA-Software Engineering: https://www.youtube.com/playlist?list=PLL7QpTxsA4sf6By03bot5BhKoMgxDUU17Distributed systems and databases: https://www.youtube.com/playlist?list=PLL7QpTxsA4sfLDUnjBJXJGFhhz94jDd_dModern databases: https://www.youtube.com/playlist?list=PLL7QpTxsA4scSeZAsCUXijtnfW5ARlrsNStay Curios! Keep Learning!

For memberships: join this channel as a member here:https://www.youtube.com/channel/UC_mGuY4g0mggeUGM6V1osdA/joinSummaryIn this conversation, Ian discusses the evolution and significance of Unikernels and NanoVMs, emphasizing their potential to enhance security and performance in cloud computing. He explains the historical context of operating systems, the limitations of traditional systems, and how Unikernels offer a streamlined alternative. Ian also highlights the unique features of NanoVMs, their integration capabilities, and the challenges faced in the ecosystem. The discussion concludes with insights into the future of Unikernels and the ongoing developments in the field.takeaways.Unikernels are a specialized type of operating system designed for cloud environments.The evolution of operating systems has led to the need for more efficient solutions like Unikernels.Unikernels can significantly reduce security vulnerabilities compared to traditional systems.NanoVMs provide a unique approach to Unikernels with a focus on performance and security.Integrations with existing tools and libraries are crucial for the adoption of Unikernels.The ecosystem around Unikernels is still developing, with many opportunities for growth.Unikernels eliminate the need for complex orchestration and management layers.The future of Unikernels includes tighter integrations with cloud services and improved developer experiences.Security features in Unikernels are designed to address modern threats effectively.The potential for Unikernels to transform application deployment is significant, with many untapped possibilities.Chapters00:00 Introduction to Unikernels and NanoVMs04:24 The Evolution of Operating Systems11:24 Understanding Unikernels vs. Traditional Systems17:20 Security Implications of Unikernels26:17 NanoVMs: Architecture and Unique Features38:44 Security Concerns in Unikernels41:05 Integration and Support for GPUs44:02 Cloud Support and Deployment45:51 Avoiding Bloat in Integrations51:54 Developer's Perspective on Unikernels59:18 Limitations and Future of UnikernelsImportant Links:https://ops.cityhttps://nanos.orghttps://repo.ops.cityhttps://nanovms.com/dev/tutorialsFor memberships: join this channel as a member here:https://www.youtube.com/channel/UC_mGuY4g0mggeUGM6V1osdA/joinDon't forget to like, share, and subscribe for more insights!=============================================================================Like building stuff? Try out CodeCrafters and build amazing real world systems like Redis, Kafka, Sqlite. Use the link below to signup and get 40% off on paid subscription.https://app.codecrafters.io/join?via=geeknarrator=============================================================================Database internals series: https://youtu.be/yV_Zp0Mi3xsPopular playlists:Realtime streaming systems: https://www.youtube.com/playlist?list=PLL7QpTxsA4se-mAKKoVOs3VcaP71X_LA-Software Engineering: https://www.youtube.com/playlist?list=PLL7QpTxsA4sf6By03bot5BhKoMgxDUU17Distributed systems and databases: https://www.youtube.com/playlist?list=PLL7QpTxsA4sfLDUnjBJXJGFhhz94jDd_dModern databases: https://www.youtube.com/playlist?list=PLL7QpTxsA4scSeZAsCUXijtnfW5ARlrsNStay Curios! Keep Learning!

For memberships: join this channel as a member here:https://www.youtube.com/channel/UC_mGuY4g0mggeUGM6V1osdA/joinSummaryIn this conversation, Philipp discusses the innovations behind CedarDB, a database system designed from scratch to optimize performance for modern hardware. He explains the foundational principles of compiling SQL to machine code, the importance of parallel processing, and the challenges of maintaining Postgres compatibility. The discussion also covers the system's approach to handling transactional and analytical workloads, data ingestion processes, query optimization strategies, and future developments including schema evolution and disaggregated storage.Takeaways:- CedarDB is built from the ground up to utilize modern hardware effectively.- The system compiles SQL directly to machine code for performance.- Parallel processing is a key feature, allowing efficient use of multiple cores.- CedarDB aims to be Postgres compatible while innovating on performance.- Transactional workloads are handled efficiently without sacrificing analytical capabilities.- Data ingestion is optimized for both row-oriented and columnar formats.- The system uses optimistic concurrency control to manage write conflicts.- Query optimization leverages statistics to improve join performance.- Future developments include schema evolution and disaggregated storage.- CedarDB is designed to be flexible and adaptable for various workloads.Chapters00:00 Introduction to CDRDB and Background of Philipp05:36 Compiling SQL to Machine Code for Performance11:25 General Purpose vs. Analytical Databases16:51 Transactional Workloads and Hybrid Storage Engine54:29 Understanding B-Tree and Columnar Storage01:02:18 Data Duplication and Memory Efficiency01:08:43 Indexing Strategies and B-Tree Optimization01:15:57 Handling Write Conflicts and Transaction Management01:24:10 Query Optimization and Join Strategies01:33:28 Future Developments in Schema Evolution and StorageImportant Links:CedarDB: https://cedardb.com/The Umbra research project: https://umbra-db.com/SQL Query Compilation: http://www.vldb.org/pvldb/vol4/p539-neumann.pdfOptimistic B-Trees: https://cedardb.com/blog/optimistic_btrees/Our B-Tree storage engine: https://cedardb.com/blog/colibri/For memberships: join this channel as a member here:https://www.youtube.com/channel/UC_mGuY4g0mggeUGM6V1osdA/joinDon't forget to like, share, and subscribe for more insights!=============================================================================Like building stuff? Try out CodeCrafters and build amazing real world systems like Redis, Kafka, Sqlite. Use the link below to signup and get 40% off on paid subscription.https://app.codecrafters.io/join?via=geeknarrator=============================================================================Database internals series: https://youtu.be/yV_Zp0Mi3xsPopular playlists:Realtime streaming systems: https://www.youtube.com/playlist?list=PLL7QpTxsA4se-mAKKoVOs3VcaP71X_LA-Software Engineering: https://www.youtube.com/playlist?list=PLL7QpTxsA4sf6By03bot5BhKoMgxDUU17Distributed systems and databases: https://www.youtube.com/playlist?list=PLL7QpTxsA4sfLDUnjBJXJGFhhz94jDd_dModern databases: https://www.youtube.com/playlist?list=PLL7QpTxsA4scSeZAsCUXijtnfW5ARlrsNStay Curios! Keep Learning!

Read more about Kafka Diskless-topics, KIP by Aiven:KIP-1150: https://fnf.dev/3EuL7mvSummary:In this conversation, Kaivalya Apte and Alexis Schlomer discuss the internals of query optimization with the new project optd. They explore the challenges faced by existing query optimizers, the importance of cost models, and the advantages of using Rust for performance and safety. The discussion also covers the innovative streaming model of query execution, feedback mechanisms for refining optimizations, and the future developments planned for optd, including support for various databases and enhanced cost models.Chapters00:00 Introduction to optd and Its Purpose03:57 Understanding Query Optimization and Its Importance10:26 Defining Query Optimization and Its Challenges17:32 Exploring the Limitations of Existing Optimizers21:39 The Role of Calcite in Query Optimization26:54 The Need for a Domain-Specific Language40:10 Advantages of Using Rust for optd44:37 High-Level Overview of optd's Functionality48:36 Optimizing Query Execution with Coroutines50:03 Streaming Model for Query Optimization51:36 Client Interaction and Feedback Mechanism54:18 Adaptive Decision Making in Query Execution54:56 Persistent Memoization for Enhanced Performance57:12 Guided Scheduling in Query Optimization59:55 Balancing Execution Time and Optimization01:01:43 Understanding Cost Models in Query Optimization01:04:22 Exploring Storage Solutions for Query Optimization01:07:13 Enhancing Observability and Caching Mechanisms01:07:44 Future Optimizations and System Improvements01:18:02 Challenges in Query Optimization Development01:20:33 Upcoming Features and Roadmap for optdReferences:- NeuroCard: learned Cardinality Estimation: https://vldb.org/pvldb/vol14/p61-yang.pdf- RL-based QO: https://arxiv.org/pdf/1808.03196- Microsoft book about QO: https://www.microsoft.com/en-us/research/publication/extensible-query-optimizers-in-practice/- Cascades paper: https://15721.courses.cs.cmu.edu/spring2016/papers/graefe-ieee1995.pdf- optd source code: https://github.com/cmu-db/optd- optd website (for now): https://db.cs.cmu.edu/projects/optd/For memberships: join this channel as a member here:https://www.youtube.com/channel/UC_mGuY4g0mggeUGM6V1osdA/joinDon't forget to like, share, and subscribe for more insights!=============================================================================Like building stuff? Try out CodeCrafters and build amazing real world systems like Redis, Kafka, Sqlite. Use the link below to signup and get 40% off on paid subscription.https://app.codecrafters.io/join?via=geeknarrator=============================================================================Database internals series: https://youtu.be/yV_Zp0Mi3xsPopular playlists:Realtime streaming systems: https://www.youtube.com/playlist?list=PLL7QpTxsA4se-mAKKoVOs3VcaP71X_LA-Software Engineering: https://www.youtube.com/playlist?list=PLL7QpTxsA4sf6By03bot5BhKoMgxDUU17Distributed systems and databases: https://www.youtube.com/playlist?list=PLL7QpTxsA4sfLDUnjBJXJGFhhz94jDd_dModern databases: https://www.youtube.com/playlist?list=PLL7QpTxsA4scSeZAsCUXijtnfW5ARlrsNStay Curios! Keep Learning!#database #queryoptimization #sql #postgres

For memberships: join this channel as a member here:https://www.youtube.com/channel/UC_mGuY4g0mggeUGM6V1osdA/joinSummaryIn this conversation, Nitish Tiwari discusses Parseable, an observability platform designed to address the challenges of managing and analyzing large volumes of data. The discussion covers the evolution of observability systems, the design principles behind Parseable, and the importance of efficient data ingestion and storage in S3. Nitish explains how Parseable allows for flexible deployment, handles data organization, and supports querying through SQL. The conversation also touches on the correlation of logs and traces, failure modes, scaling strategies, and the optional nature of indexing for performance optimization.References:Parseable: https://www.parseable.com/GitHub Repository: https://github.com/parseablehq/parseableArchitecture: https://parseable.com/docs/architecture Chapters:00:00 Introduction to Parseable and Observability Challenges05:17 Key Features of Parseable12:03 Deployment and Configuration of Parseable18:59 Ingestion Process and Data Handling32:52 S3 Integration and Data Organisation35:26 Organising Data in Parseable38:50 Metadata Management and Retention39:52 Querying Data: User Experience and SQL44:28 Caching and Performance Optimisation46:55 User-Friendly Querying: SQL vs. UI48:53 Correlating Logs and Traces50:27 Handling Failures in Ingestion53:31 Managing Spiky Workloads54:58 Data Partitioning and Organisation58:06 Creating Indexes for Faster Reads01:00:08 Parseable's Architecture and Optimisation01:03:09 AI for Enhanced Observability01:05:41 Getting Involved with ParseableFor memberships: join this channel as a member here:https://www.youtube.com/channel/UC_mGuY4g0mggeUGM6V1osdA/joinDon't forget to like, share, and subscribe for more insights!=============================================================================Like building stuff? Try out CodeCrafters and build amazing real world systems like Redis, Kafka, Sqlite. Use the link below to signup and get 40% off on paid subscription.https://app.codecrafters.io/join?via=geeknarrator=============================================================================Database internals series: https://youtu.be/yV_Zp0Mi3xsPopular playlists:Realtime streaming systems: https://www.youtube.com/playlist?list=PLL7QpTxsA4se-mAKKoVOs3VcaP71X_LA-Software Engineering: https://www.youtube.com/playlist?list=PLL7QpTxsA4sf6By03bot5BhKoMgxDUU17Distributed systems and databases: https://www.youtube.com/playlist?list=PLL7QpTxsA4sfLDUnjBJXJGFhhz94jDd_dModern databases: https://www.youtube.com/playlist?list=PLL7QpTxsA4scSeZAsCUXijtnfW5ARlrsNStay Curios! Keep Learning!#database #s3 #objectstorage #opentelemetry #logs #metrics