TIDB THE LARGE SCALE RELATIONAL DATABASE SOLUTION PRODUCT REVIEW 2022 Piloting tomorrow’s creativity https://www.iconic.inc Iconic Data Japan (IDJ) is a multi-national data services company that new database solution that is targeted primarily to clients that need to handle very large databases, with very large frequency of queries. If those two problems describe your business then this database category. (Large Databases and Fast Queries) Executive Summary SUMMARY 3 AUDIENCE TIDB STANDOUT FEATURES: TIDB IS A GOOD SOLUTION FOR THOSE THAT CAN TAKE ADVANTAGE OF IT’S FEATURES Clients with large databases

#IstioCon Moving large scale consumer e-commerce Infrastructure to Mesh Rajath Ramesh Principal Software Engineer @Carousell Harshad Rotithor Software Architect @Carousell #IstioCon About Carousell

#IstioCon Performance tuning and best practices in a Knative based, large-scale serverless platform with Istio 张龚, Gong Zhang, IBM China Development Lab 庄宇, Yu Zhuang, IBM China Development Lab #IstioCon The envoy mem release fix included in Istio 1.6.0+ resolved this issue. o Istiod MEM bumped with large numbers of Knative Services (#25532) Mem usage optimization of pilot resolved this issue. • Tune

10 Problems Large Companies Have Managing C++ Dependencies and How to Solve Them Augustin Popa, Microsoft C++ TeamIntroduction Augustin Popa Senior Product Manager, Microsoft C++ Team @augustin_popa vulnerabilities 7. Centralize common tasks 8. Produce SBOMs 9. Global, reproducible builds 10. Break large migrations down into smaller milestonesDemo Intro: Cataclysm: Dark Days Ahead vcpkg + CMake + Visual usable binaries •Build times: 2nd biggest pain point for C++ (ISO C++ surveys) •Scales poorly with large projects or many distributed teamsProblem 2: Build times are too long when building from source Solution

Futures/Promises to Lazy Continuations Evolving an Actor Library Based on Lessons Learned from Large-Scale Deployments Benjamin Hindman @benh CppCon 2021prologue ● past life at UC Berkeley, Twitter

represent performance in large projects well. 11How will we compare performance? ● Benchmarks at this low level are not too reliable, and also don’t represent performance in large projects well. ● Dynamic performance? ● Benchmarks at this low level are not too reliable, and also don’t represent performance in large projects well. ● Dynamic instruction count is more reliable on modern CPUs. ● We’ll use simple examples compiler. 13“… machine code … can range from 10s to 100s of megabytes in size, which is often too large to fit in any modern CPU instruction cache. As a result, the hardware spends a considerable amount

ever-growing digital datasets that have been in the making for over three decades; breakthrough large language models (LLMs) that – in effect – found freedom with the November 2022 launch of OpenAI’s where computers are ingesting massive datasets to get smarter and more competitive. Breakthroughs in large models, cost-per-token declines, open-source proliferation and chip performance improvements are Models *As of 4/25, ‘Large-Scale AI Models’ are generally defined as those with a training compute of 1023 FLOPs or greater, per Epoch AI. Source: Epoch AI (5/25) Number of New Large-Scale AI Models (Larger

Guarantees of sends and commits 23. Message Redelivery and Undelivered Messages 24. Message Expiry 25. Large Messages 26. Paging 27. Queue Attributes 28. Scheduled Messages 29. Last-Value Queues 30. Message know nothing of each other. This allows you to create flexible, loosely coupled systems. Often, large enterprises use a messaging system to implement a message bus which loosely couples heterogeneous transaction. Apache ActiveMQ Artemis also supports the sending and acknowledgement of message as part of a large global transaction - using the Java mapping of XA: JTA. The Publish-Subscribe Pattern Delivery

44 1.45 1.46 1.47 1.48 1.49 1.50 1.51 1.52 1.53 1.54 1.55 1.56 1.57 Message Expiry Large Messages Paging Queue Attributes Scheduled Messages Last-Value Queues Message Grouping Extra know nothing of each other. This allows you to create flexible, loosely coupled systems. Often, large enterprises use a messaging system to implement a message bus which loosely couples heterogeneous transaction. Apache ActiveMQ Artemis also supports the sending and acknowledgement of message as part of a large global transaction - using the Java mapping of XA: JTA. Durability Messages are either durable

44 1.45 1.46 1.47 1.48 1.49 1.50 1.51 1.52 1.53 1.54 1.55 1.56 1.57 Message Expiry Large Messages Paging Queue Attributes Scheduled Messages Last-Value Queues Message Grouping Extra know nothing of each other. This allows you to create flexible, loosely coupled systems. Often, large enterprises use a messaging system to implement a message bus which loosely couples heterogeneous transaction. Apache ActiveMQ Artemis also supports the sending and acknowledgement of message as part of a large global transaction - using the Java mapping of XA: JTA. Durability Messages are either durable