accidental, not the essential, difficulties.”Solutions to Accidental Difficulties • High-level languages • The most a high-level language can do is to furnish all the constructs the programmer imagines essence, or are they remainders of our accidental difficulties?”Silver bullets? • Ada and other high-level language advances • Object-oriented programming • Artificial intelligence • Expert systems • servers, but I need more servers so I need… • an Infrastructure as a Service platform, but for high availability I need… • another rack of servers, but to pay for it I need…Always ask yourself • Am I solving

Kinds of scanning policies • Elaborate scanning report Content Trust • Digital signature High Availability • HA support Helm Chart Support • Helm Chart repository • Same mechanism and user experiences

Consistency нет! ❋ Как и у любой системы с асинхронной репликацией ❋ Но можно включить › Availability (почти) есть! ❋ Можно отключать один ДЦ, если ZK в 3-х датацентрах, а реплики минимум в 2-x

We ❤ Web. But… We need: • Better offline support • Access to all device APIs • Home screen availability • Push notifications • App monetization • App store discovery • … Hybrid "Promise" 100%

Decentralized Performance High High, less than Web2 Query Capability Powerful Powerful, less than Web2 Open Source Code Open or Not, mostly NOT Open Data Resiliency Normal High Data Openness Closed Open Underlying Nodes Many Few Performance Low High Query Capability Low High Open Source Code Open Open Hot Data Capacity Low High Data Resiliency High High Data Openness Open Open Trustlessness Yes

request of Pod. However, in many cases, some nodes have low resource requests but high load, while some nodes have high resource requests but low load. Dynamic-Scheduler Node1 Node2 Kube-scheduler 5)*10+(1-0.4)*10=11 (1-0.5)*10+(1-0.6)*10=9 Assigned to Node1 DeScheduler If the pod is enabled high-load automatic migration Node2 Real Load Level Pod1 Pod2 Pod3 Node3 Real Load Level Pod2 Node1 Node1 Real Load Level Pod1 Pod1 migrate to Node1 Pod2 migrate to Node3 Descheduler Node2 load is high How to expand horizontally more quickly and flexibly HPA-controller Supporting horizontal scaling

computationally intensive tasks, using Javascript is very poor. Therefore, we plan to use Rust to provide high performance 2); Photo / image / chart Rust FFI Rust FFI (Foreign Function Interface) refers to performance, memory safety, and concurrency features, Rust has become an ideal choice for building high-performance mobile applications. - Cross-Platform Support: Rust's cross-platform capabilities allow effort and improves code maintainability. - High Performance: Rust provides performance comparable to C and C++. This makes Rust a powerful tool for developing high-performance mobile applications. 利用 Rust

objects retired to it are destroyed before the the completion of destruction of Container. • Problem: High setup overhead of constructing/destroying per custom domain hazard pointers. • Even worse if many 2018: Global cleanup deprecated. Still supported for testing and microbenchmarking. • 2020: One user: High frequency of retiring objects. Unsharded list grew out of control. • 2020: Sharded cohorts without Proposal for C++26: Minimal useful subset of TS2. • Why minimal? High confidence in proposal. Require less committee time. • Cohorts: • High confidence in usefulness based on Folly experience. • Why not C++26

from system-wide real-time clock  std::steady_clock: guarantees it never goes backwards  std::high_resolution_clock: has shortest possible tick period  C++20 adds:  utc_clock, tai_clock, gps_clock cout << put_time(t, "%H:%M:%S");22 Clocks  Time execution time: // Get start time. auto start { high_resolution_clock::now() }; // Execute code to benchmark. double d { 0 }; for (int i { 0 }; i < ++i) { d += sqrt(sin(i) * cos(i)); } // Get end time and calculate the difference. auto end { high_resolution_clock::now() }; auto diff { end – start }; // Convert difference into milliseconds.

to Raw Text Log Files High Compression (column store + LZ4) • Typically 100x faster than MySQL on Single Server • Semi-Linear Scalability to 100s of nodes High Performance © 2018 Percona