# Concurrency Published articles for Concurrency. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Java 27 Reaches GA With The G1 Garbage Collector By Default Everywhere DevFeed: [Java 27 Reaches GA With The G1 Garbage Collector By Default Everywhere]() Original publisher: [Read original article]() Author: Michael Larabel Published: 2026-09-15T13:39:00Z Content type: news Language: en Sources: [Phoronix]() Topics: [Java](), [openjdk](), [releases](), [Concurrency](), [Post-Quantum](), [TLS (Transport Layer Security)]() Tags: [availability](), [concurrency](), [desktop-linux](), [java](), [linux-benchmarking](), [linux-hardware-benchmarks](), [linux-hardware-reviews](), [linux-how-to](), [linux-performance](), [linux-server-benchmarks](), [open-source-graphics](), [openjdk](), [phoronix](), [phoronix-test-suite](), [post-quantum](), [release](), [structured-concurrency](), [tls](), [ubuntu-benchmarks](), [ubuntu-hardware]() ### AI overview OpenJDK 27 has reached general availability. Its G1 garbage collector is now enabled by default across environments, replacing Serial as the default in constrained environments after improvements in throughput, latency, and memory usage. The release also includes post-quantum hybrid key exchange for TLS 1.3, preview features for lazy constants and structured concurrency, compact object headers by default, and an incubating Vector API. ### Source excerpt Oracle christened Java 27 today with the OpenJDK 27 release reaching general availability (GA) status... ## How automated testing improves development of complex features DevFeed: [How automated testing improves development of complex features]() Original publisher: [Read original article]() Author: Dan Lew Published: 2026-09-15T13:16:49Z Content type: opinion Language: en Sources: [Dan Lew Blog]() Topics: [Testing](), [coding](), [Concurrency](), [Database]() Tags: [automated](), [concurrency](), [database](), [regression](), [testing]() ### AI overview The author contrasts manual testing with automated testing while developing job cancellation in a work queue. Automated tests help expose concurrency and regression risks, cover corner cases, and simulate mid-execution cancellation more reliably. ### Source excerpt It's hard for me to overstate how much my coding has improved since embracing automated testing. And yet, I used to think of it as a waste of time! This post is for my former self, demonstrating why I embrace the practice now. Allow me to demonstrate with ## How Solaris' Turnstile Influenced the Modern System Designs of Web Browsers and Language Runtimes DevFeed: [How Solaris' Turnstile Influenced the Modern System Designs of Web Browsers and Language Runtimes]() Original publisher: [Read original article]() Author: Olimpiu Pop Published: 2026-09-15T06:06:00Z Content type: article Language: en Sources: [InfoQ]() Topics: [systems](), [Programming](), [Kernel](), [observability](), [browsers](), [web browsers]() Tags: [architecture](), [architecture-design](), [architectures](), [blocking](), [concurrency](), [development](), [efficiency](), [kernel](), [locking](), [memory](), [news](), [observability](), [operating-systems](), [solaris](), [storage](), [systems](), [turnstile-system-design]() ### AI overview The article examines how Solaris innovations influenced modern systems engineering. It discusses the Slab Allocator, OpenZFS, DTrace, Zones, and turnstiles, focusing on how turnstiles reduce per-lock memory overhead while supporting priority inheritance for contended locks. ### Source excerpt Sun's Solaris influenced modern systems engineering, with key innovations like the Slab Allocator for efficient memory management, OpenZFS for advanced storage, and DTrace for observability. Its turnstile mechanism addressed issues with mutexes, promoting lean locking designs that are reflected in contemporary programming languages and web browsers, enhancing performance and memory efficiency. By Olimpiu Pop ## How to operate shared platforms safely at agent scale DevFeed: [How to operate shared platforms safely at agent scale]() Original publisher: [Read original article]() Author: Candace Shamieh; T Zhang; Gabriele Baldoni Published: 2026-09-15T00:00:00Z Content type: article Language: en Sources: [Datadog | The Monitor blog]() Topics: [Platform Engineering](), [Loop Engineering](), [AI Agent](), [sdlc](), [Latency](), [Low Latency](), [Concurrency](), [Software]() Tags: [agent](), [agent-observability](), [agentic-workflows](), [agents](), [ai](), [ai-agent](), [ci](), [concurrency](), [latency](), [low-latency](), [operational](), [performance](), [platform-engineering](), [platforms](), [queue](), [recovery](), [timeout]() ### AI overview This Datadog article explains how platform teams can operate shared platforms safely as AI agent workloads scale across teams. It discusses modeling demand across agent trajectories, planning capacity across dependencies such as CI queues and sandbox pools, handling contention and recovery behavior, and preserving control across system boundaries. ### Source excerpt Learn how Datadog models agent demand, allocates capacity under contention, and preserves control as AI agent workloads scale across shared platforms. ## Java News Roundup: New OpenJDK JEPs, CDI 5.0, Spring, Open Liberty, RefactorFirst, ADK for Kotlin DevFeed: [Java News Roundup: New OpenJDK JEPs, CDI 5.0, Spring, Open Liberty, RefactorFirst, ADK for Kotlin]() Original publisher: [Read original article]() Author: Michael Redlich Published: 2026-09-14T20:15:00Z Content type: news Language: en Sources: [InfoQ]() Topics: [Java](), [Concurrency](), [JDK 27](), [releases](), [Jakarta EE](), [Gradle](), [Groovy]() Tags: [2026](), [architecture-design](), [concurrency](), [development](), [gradle](), [groovy](), [jakarta-ee](), [java](), [java-news-roundup-sep07-2026](), [jdk-27](), [jdk-28](), [kotlin](), [micronaut](), [news](), [open-jdk](), [open-liberty](), [refactorfirst](), [releases](), [spring-framework](), [tornadovm]() ### AI overview A Java news roundup for September 7, 2026, covers new OpenJDK proposals for ahead-of-time compilation and structured concurrency, Jakarta CDI 5.0 and ADK for Kotlin 1.0, Open Liberty, TornadoVM, RefactorFirst, Micronaut, Groovy 6.0, and Gradle 9.8. It also reports current JDK 27 and JDK 28 early-access builds and describes improvements in TornadoVM 6.1.0. ### Source excerpt This week's Java roundup for September 7th, 2026, features news highlighting: new JEPs for ahead-of-time compilation and structured concurrency; GA releases of Jakarta CDI 5.0 and ADK for Kotlin 1.0; the September 2026 edition of Open Liberty; point releases of TornadoVM and RefactorFirst; a maintenance release of Micronaut; and first releases candidates of Groovy 6.0 and Gradle 9.8. By Michael Redlich ## Resolve Amazon Aurora PostgreSQL lock contention with Database Insights: Part 2 DevFeed: [Resolve Amazon Aurora PostgreSQL lock contention with Database Insights: Part 2]() Original publisher: [Read original article]() Author: Sameer Kumar Published: 2026-09-14T16:02:16Z Content type: tutorial Language: en Sources: [AWS Database Blog]() Topics: [Amazon Aurora](), [Amazon CloudWatch](), [PostgreSQL](), [Concurrency](), [Monitoring](), [Database](), [Amazon EC2](), [Architecture & Design](), [Amazon Web Services](), [AWS CloudFormation]() Tags: [advanced-300](), [amazon-aurora](), [amazon-cloudwatch](), [amazon-ec2](), [aws](), [aws-cloudformation](), [concurrency](), [monitoring](), [performance](), [postgresql](), [rds-for-postgresql](), [simulation](), [technical-how-to]() ### AI overview This tutorial explains how to diagnose and resolve lock contention in Amazon Aurora PostgreSQL using Amazon CloudWatch Database Insights. It demonstrates Lock Analysis and the Lock Tree visualization for identifying blocking sessions, then covers immediate fixes, configuration changes, optimistic concurrency control, asynchronous processing, SKIP LOCKED, and row splitting. ### Source excerpt Part 1 showed how row lock contention degrades Amazon Aurora PostgreSQL throughput. In Part 2, use Amazon CloudWatch Database Insights and its Lock Tree to pinpoint blocking sessions, then resolve contention with query termination, timeout parameters, and architectural patterns such as SKIP LOCKED and row splitting that restore throughput. ## Troubleshooting row lock contention in Amazon Aurora PostgreSQL: Part 1 - Understanding row lock contention in PostgreSQL DevFeed: [Troubleshooting row lock contention in Amazon Aurora PostgreSQL: Part 1 - Understanding row lock contention in PostgreSQL]() Original publisher: [Read original article]() Author: Sameer Kumar Published: 2026-09-14T16:02:08Z Content type: tutorial Language: en Sources: [AWS Database Blog]() Topics: [Amazon Aurora](), [PostgreSQL](), [Concurrency](), [Monitoring](), [Transactions](), [Amazon CloudWatch](), [Amazon RDS](), [Architecture & Design](), [Extension]() Tags: [advanced-300](), [amazon-aurora](), [amazon-cloudwatch](), [amazon-rds](), [architecture](), [availability](), [concurrency](), [database](), [database-performance](), [extension](), [locks](), [monitoring](), [postgresql](), [production](), [rds-for-postgresql](), [technical-how-to](), [transactions](), [troubleshooting]() ### AI overview This first part of a two-part series explains row lock contention in PostgreSQL and Amazon Aurora PostgreSQL. It covers how concurrent transactions competing for the same rows can reduce throughput and cause timeouts despite healthy CPU and I/O, then introduces PostgreSQL locking internals and monitoring techniques using system views, functions, the pgrowlocks extension, and log_lock_waits. The article notes that the same behavior and investigation approach apply to Amazon RDS for PostgreSQL. ### Source excerpt Row lock contention can collapse database throughput during a flash sale even when CPU and I/O look healthy. In Part 1 of this series, learn how PostgreSQL row locking works and how to monitor lock contention in Amazon Aurora PostgreSQL and Amazon RDS for PostgreSQL using system views, the pgrowlocks extension, and the log_lock_waits parameter. ## Back to the Basics. Threads. DevFeed: [Back to the Basics. Threads.]() Original publisher: [Read original article]() Author: Daniel Beach Published: 2026-09-14T12:19:11Z Content type: tutorial Language: en Sources: [Data Engineering Central]() Topics: [Concurrency](), [Rust](), [Concurrent Programming](), [Programming](), [Python]() Tags: [concurrency](), [programming](), [python](), [rust](), [threads]() ### AI overview An introductory, applied discussion of threads and concurrency, focusing on Rust and briefly recalling Python ProcessPools for parallel data and file processing. ### Source excerpt staying grounded in an agentic world ## Speeding Up Azure Durable Functions with Fan-Out/Fan-In and a Higher Concurrency Limit DevFeed: [Speeding Up Azure Durable Functions with Fan-Out/Fan-In and a Higher Concurrency Limit]() Original publisher: [Read original article]() Author: Michael Li Published: 2026-09-14T12:00:32Z Content type: tutorial Language: en Sources: [Atomic Object]() Topics: [Azure](), [Concurrent Programming](), [Code]() Tags: [apis](), [azure](), [azure-functions](), [batch](), [concurrency](), [development-practices](), [file](), [storage]() ### AI overview An Azure Durable Functions batch job was accelerated by combining fan-out/fan-in orchestration with a higher function-host concurrency limit. Together, the changes reduced a representative run from about 710 seconds to about 240 seconds. ### Source excerpt For one of our projects, we run a nightly job that generates a batch of files. It's a long process: pulling records from an upstream system, calling several APIs to gather info about each one, generating a file per record, and writing the results back to storage. For a small batch, this works fine, but [...] The post 2 Changes Made Our Azure Durable Functions 3X Faster appeared first on Atomic Spin. ## How to Prevent Race Conditions in Django DevFeed: [How to Prevent Race Conditions in Django]() Original publisher: [Read original article]() Author: Mari Published: 2026-09-11T21:50:46Z Content type: tutorial Language: en Sources: [freeCodeCamp Programming Tutorials: Python, JavaScript, Git & More]() Topics: [Concurrency](), [Database](), [SQLite](), [Docker]() Tags: [backend](), [concurrency](), [database](), [django](), [how-to](), [postgresql](), [python](), [race-condition](), [sqlite](), [transactions]() ### AI overview A Django tutorial that demonstrates a credit-spending race condition and explains how database transactions and row locks prevent concurrent requests from using the same credit. ### Source excerpt Let's say you have enough credit left to generate one more image in an AI app. You submit a request in one browser tab, then submit another in a second tab before the first finishes. The app accepts b ## Netflix Reworks Conductor for 420 Million Monthly Workflow Executions and 10X Larger Workflows DevFeed: [Netflix Reworks Conductor for 420 Million Monthly Workflow Executions and 10X Larger Workflows]() Original publisher: [Read original article]() Author: Leela Kumili Published: 2026-09-11T14:17:00Z Content type: news Language: en Sources: [InfoQ]() Topics: [Orchestration](), [Amazon S3](), [Kafka](), [Apache Iceberg]() Tags: [amazon-s3](), [apache-iceberg](), [apache-kafka](), [architecture-design](), [asynchronous-architecture](), [cassandra](), [cloud-architecture](), [concurrency](), [development](), [devops](), [distributed-systems](), [elasticsearch](), [java-operator-sdk](), [kafka](), [latency](), [microservices](), [netflix](), [netflix-conductor-4-workflow](), [news](), [orchestration](), [s3](), [scalability](), [windows-workflow-foundation](), [workflow](), [workflow-bpm](), [workflow-foundation]() ### AI overview Netflix reworked Conductor 4.0 to scale workflow orchestration to roughly 200,000 definitions and 420 million monthly executions. The redesign raises supported workflow size to 30,000 tasks and reports a roughly 40% reduction in p99 evaluation latency by loading only task data needed for each decision. ### Source excerpt Netflix has reworked its Conductor workflow orchestration engine to handle larger workloads, increasing supported workflow size from about 2,500 to 30,000 tasks and reducing p99 workflow evaluation latency by about 40%. Conductor 4.0 separates workflow metadata from task data, moves evaluation to asynchronous processing, and introduces dynamic worker allocation and concurrency controls. By Leela Kumili ## A Bootiful Podcast: Netflix's Paul Bakker DevFeed: [A Bootiful Podcast: Netflix's Paul Bakker]() Original publisher: [Read original article]() Author: joshlong Published: 2026-09-10T00:00:00Z Content type: article Language: en Sources: [Spring]() Topics: [Concurrency](), [Concurrent Programming](), [Tooling]() Tags: [ai](), [batch](), [boot](), [cloud](), [complexity](), [concurrency](), [event-driven](), [java](), [microservices](), [netflix](), [podcast](), [reactive](), [serverless](), [spring](), [tooling](), [web-applications]() ### AI overview A podcast interview with Netflix's Paul Bakker on scaling Java, adopting newer JDKs to reduce costs, and using virtual threads and structured concurrency instead of reactive complexity. It also previews AI-powered tooling and Project Valhalla's future. ### Source excerpt Hi, Spring fans! This week's interview is a must-watch if you care about where Java is headed next. This week, I talk to Netflix's Paull Bakker! We dig into Netflix's real-world playbook for scaling Java, cutting costs with newer JDKs, and replacing reactive complexity with virtual threads and structured concurrency. Plus, there's a sneak peek at the exciting future of Java, from AI-powered tooling to the upcoming Valhalla era. ## Building async Python applications with Tortoise ORM and Amazon Aurora DSQL DevFeed: [Building async Python applications with Tortoise ORM and Amazon Aurora DSQL]() Original publisher: [Read original article]() Author: Lasita Bhattacharya Published: 2026-09-09T15:27:43Z Content type: tutorial Language: en Sources: [AWS Database Blog]() Topics: [DSQL](), [Concurrency](), [AWS IAM](), [Database](), [CRUD]() Tags: [advanced-300](), [amazon-aurora](), [concurrency](), [database](), [dsql](), [how-to](), [iam](), [orm](), [postgresql](), [python](), [rideshare](), [serverless](), [technical-how-to]() ### AI overview A tutorial for building a high-concurrency asynchronous Python rideshare application with Tortoise ORM and Amazon Aurora DSQL. It covers UUID-based models, IAM-authenticated asyncpg connections, OCC retry handling, and asynchronous CRUD operations. ### Source excerpt Build a high-concurrency async Python rideshare application with Tortoise ORM and Amazon Aurora DSQL. This post walks through the key adaptations: UUID primary keys, IAM-authenticated asyncpg connections with a connection-pool patch, individual DDL execution, and optimistic concurrency control (OCC) retry logic. ## Java Weekly, Issue 662 DevFeed: [Java Weekly, Issue 662]() Original publisher: [Read original article]() Author: baeldung Published: 2026-09-06T09:25:19Z Content type: article Language: en Sources: [Baeldung]() Topics: [IntelliJ IDEA](), [Concurrency](), [Tooling](), [Cryptography](), [elasticsearch]() Tags: [concurrency](), [cryptography](), [elasticsearch](), [intellij-idea](), [java](), [no-ads](), [no-after-post](), [no-before-post](), [no-optins](), [tooling](), [weekly-review](), [weekly-review-no-ads-no-after-post-no-before-post-no-optins]() ### AI overview A Java ecosystem roundup led by a hands-on look at Project Loom in IntelliJ IDEA, covering virtual threads, scoped values, structured concurrency, and related tooling. It also links to Java and Spring articles, podcasts, release announcements, code-review commentary, and IntelliJ IDEA Conf 2026. ### Source excerpt The three Loom pillars and, more importantly, the tooling. Plus IntelliJ IDEA Conf 2026 getting close. The post Java Weekly, Issue 662 first appeared on Baeldung. ## How Databases Keep Their Sanity with Concurrency Control DevFeed: [How Databases Keep Their Sanity with Concurrency Control]() Original publisher: [Read original article]() Author: ByteByteGo Published: 2026-09-03T15:31:17Z Content type: article Language: en Sources: [ByteByteGo]() Topics: [Databases](), [Concurrency]() Tags: [article](), [concurrency](), [concurrency-control](), [databases]() ### AI overview The article introduces how databases handle bugs related to concurrency control, but the supplied evidence does not provide the specific methods or findings discussed. ### Source excerpt So how do we handle such bugs? This is what we are going to try to answer in this article. ## Goroutine Leak Profiles DevFeed: [Goroutine Leak Profiles]() Original publisher: [Read original article]() Author: Vlad Saioc Published: 2026-09-02T00:00:00Z Content type: article Language: en Sources: [The Go Blog]() Topics: [Go Language](), [Concurrency](), [debugging](), [Tooling]() Tags: [bugs](), [concurrency](), [debugging](), [go](), [performance](), [production](), [testing](), [tools]() ### AI overview Go 1.27 introduces a goroutine leak profiler for detecting goroutines blocked permanently in running programs, including production systems. ### Source excerpt Go 1.27 includes new goroutine leak profiles. ## How to Size GPUs for AI Inference and TCO Without Overspending DevFeed: [How to Size GPUs for AI Inference and TCO Without Overspending]() Original publisher: [Read original article]() Author: Elizabeth Goodman Published: 2026-09-01T15:00:00Z Content type: tutorial Language: en Sources: [NVIDIA Developer](), [NVIDIA Technical Blog]() Topics: [AI Inference](), [GPU](), [Inference Performance](), [Large Language Model](), [cloud-infrastructure](), [Optimization]() Tags: [agentic-ai-generative-ai](), [ai-factory](), [ai-inference](), [concurrency](), [cost](), [data-center-cloud](), [gpu](), [inference-performance](), [latency](), [llm](), [mlops](), [quantization]() ### AI overview A practical guide to sizing GPU infrastructure for AI inference workloads while balancing latency, concurrency, model choice, deployment strategy, and total cost of ownership. ### Source excerpt The surge in AI adoption is transforming everything from chatbots to content generation. Still, a common pain point remains: How can organizations confidently... ## Announcing rustup 1.29.1 DevFeed: [Announcing rustup 1.29.1]() Original publisher: [Read original article]() Author: The Rustup Team Published: 2026-09-01T00:00:00Z Content type: release Language: en Sources: [Rust Blog]() Topics: [releases]() Tags: [bug](), [cli](), [concurrency](), [docs](), [http](), [releases](), [rust](), [toolchain](), [update](), [windows]() ### AI overview Rustup 1.29.1 improves concurrent update and component-install operations, adds local HTTP documentation serving, and changes several installation behaviors. The release also fixes Windows-related installation issues and updates target terminology. ### Source excerpt The rustup team is happy to announce the release of rustup version 1.29.1. Rustup is the recommended tool to install Rust, a programming language that empowers everyone to build reliable and efficient software. What's new in rustup 1.29.1 The headlines of this release are: Concurrency in certain rustup operations has been improved: When running rustup update, rustup will first check for possible updates in parallel. pr#4752 When running rustup component add with multiple components, they will be installed concurrently. pr#4790 Implicit installation of the active toolchain in rustup-init and rustup invocations has been deprecated where deemed unnecessary and will now produce a warning. pr#4840 Please see our blog post for more details regarding this change. rustup doc now supports the --serve flag which allows serving the docs over local HTTP. This should help users with containerized browser and/or rustup setups. pr#4986 Installing i686-pc-windows-* host toolchains on 64-bit Windows now requires --force-non-host. pr#4935 rustup-init will no longer leave unexpected files on disk after cancelled installations. pr#4996 A bug has been fixed which might cause Windows installation to fail when using rustup-init.sh. pr#4756 "Target triple" has been renamed to "target tuple" across the project to reflect the new terminology. pr#4743 pr#4827 pr#4834 Please note that this is not a breaking change in the CLI since the existing options such as --target are not using this terminology. In addition, rustup now officially supports aarch64-pc-windows-gnullvm as a host platform. pr#4523 Further details are available in the changelog! How to update If you have a previous version of rustup installed, getting the new one is as easy as stopping any programs which may be using rustup (e.g. closing your IDE) and running: $ rustup self update Rustup will also automatically update itself at the end of a normal toolchain update: $ rustup update If you don't have it already, you can get rustup ## How LlamaIndex uses Temporal to scale reliable document orchestration DevFeed: [How LlamaIndex uses Temporal to scale reliable document orchestration]() Original publisher: [Read original article]() Author: Adrian Lyjak Published: 2026-09-01T00:00:00Z Content type: article Language: en Sources: [Temporal Blog]() Topics: [llamaindex](), [Orchestration](), [RabbitMQ](), [Concurrency]() Tags: [api](), [concurrency](), [llamaindex](), [orchestration](), [rabbitmq](), [scale](), [temporal](), [temporal-voices]() ### AI overview This article explains how LlamaIndex moved document-processing workloads from RabbitMQ to Temporal. It describes the complexity of processing documents page by page and reports that Temporal helped the team improve durability and concurrency while processing tens of millions of pages per day for the Batch API. ### Source excerpt Learn how LlamaIndex moved from RabbitMQ to Temporal to make LlamaParse more durable, improve concurrency, and process tens of millions of pages per day. ## Hyperloop B: the coroutine engine behind Appwrite 2.0 DevFeed: [Hyperloop B: the coroutine engine behind Appwrite 2.0]() Original publisher: [Read original article]() Author: Luke B. Silver Published: 2026-08-31T00:00:00Z Content type: article Language: en Sources: [Appwrite Blog]() Topics: [Appwrite](), [Coroutines](), [Concurrency](), [PHP](), [Benchmark]() Tags: [architectures](), [backend](), [benchmark](), [concurrency](), [coroutine](), [coroutines](), [cpu](), [memory](), [php](), [platform](), [process](), [redis]() ### AI overview The article explains Hyperloop B, a coroutine-based engine behind Appwrite 2.0. It describes how yielding during I/O lets one process serve many concurrent requests, reporting 7x higher requests per second and 6x lower memory use on an I/O-bound benchmark. ### Source excerpt Hyperloop B is the Swoole coroutine engine behind Appwrite 2.0. Here is what it is, the concurrency problem it solves, and the 7x I/O throughput it buys. ## Performance Progression of Percona Server for MySQL 8.4 DevFeed: [Performance Progression of Percona Server for MySQL 8.4]() Original publisher: [Read original article]() Author: Bogdan Degtyariov Published: 2026-08-27T13:07:20Z Content type: article Language: en Sources: [Blog - Percona]() Topics: [MySQL](), [benchmarking](), [Benchmark](), [Scalability](), [configuration](), [cpu](), [Hardware]() Tags: [2026](), [benchmark](), [benchmarking](), [benchmarks](), [concurrency](), [configuration](), [cpu](), [data](), [database](), [hardware](), [intel](), [latency](), [load](), [measurement](), [mysql](), [percona](), [percona-server-for-mysql](), [performance](), [processors](), [run]() ### AI overview This article investigates read/write performance changes across Percona Server for MySQL 8.4 versions released in 2026. It describes benchmark scope, database and buffer-size combinations, configuration, and CPU-frequency controls, while excluding features, security patches, latency percentiles, and resource-utilization measurements. ### Source excerpt 1. Purpose and scope This performance investigation aims to look into the read/write performance of Percona Server for MySQL 8.4 and how it changed between versions released in 2026: 8.4.8-8 released on 12 March 2026 8.4.10-10 released on 30 June 2026 8.4.11-11 released on 20 August 2026 We want to see if there are improvements ... Continued The post Performance Progression of Percona Server for MySQL 8.4 appeared first on Percona. ## Python 3.15 Preview: Sampling Profiler DevFeed: [Python 3.15 Preview: Sampling Profiler]() Original publisher: [Read original article]() Author: Bartosz Zaczyński Published: 2026-08-26T14:00:00Z Content type: tutorial Language: en Sources: [Real Python]() Topics: [cpu](), [Processes](), [dashboards]() Tags: [concurrency](), [cpu](), [graphs](), [processes](), [profile](), [python](), [tracing](), [tutorial]() ### AI overview A tutorial previewing Python 3.15's new low-overhead sampling profiler. It covers profiling scripts, modules, threads, async tasks, and live processes, with CPU/I/O/GIL modes and outputs such as flame graphs, heatmaps, and a terminal dashboard. ### Source excerpt Explore Python 3.15's new sampling profiler and learn low-overhead profiling of scripts, threads, and live production processes. ## 【etcd】Lease 与 KeepAlive：TTL、checkpoint 与 Leader 切换 DevFeed: [【etcd】Lease 与 KeepAlive：TTL、checkpoint 与 Leader 切换]() Original publisher: [Read original article]() Author: Liao Tonglang Published: 2026-08-26T00:00:00Z Content type: tutorial Language: zh Sources: [土法炼钢 - 系统与基础设施]() Topics: [etcd](), [Raft](), [Kubernetes](), [Remote Procedure Call (RPC)]() Tags: [api](), [checkpoint](), [client](), [concurrency](), [distributed](), [etcd](), [follower](), [k8s](), [keepalive](), [kubernetes](), [lease](), [lessor](), [primary](), [raft](), [ttl](), [v3](), [v3-5-33](), [watch]() ### AI overview This article explains etcd v3.5.33 lease behavior, focusing on the lessor's primary, demote, and promote roles, the KeepAlive renewal path that normally bypasses Raft, lease checkpointing, and TTL changes during leader transitions. It also discusses implications for Kubernetes Node Leases and distributed locks. ### Source excerpt 钉 etcd v3.5.33 lessor 的 primary/demote/promote、KeepAlive 不经 Raft 的 Renew 路径、LeaseCheckpoint 与 Promote 时 TTL 展期，以及 Leader 切换对 Node Lease 的排障落格。 ## 【etcd】Txn 与并发语义：compare/mod 与 Jepsen 边界 DevFeed: [【etcd】Txn 与并发语义：compare/mod 与 Jepsen 边界]() Original publisher: [Read original article]() Author: Liao Tonglang Published: 2026-08-26T00:00:00Z Content type: tutorial Language: zh Sources: [土法炼钢 - 系统与基础设施]() Topics: [etcd](), [version](), [Raft](), [API]() Tags: [bug](), [compare](), [concurrency](), [distributed](), [etcd](), [jepsen](), [kubernetes](), [mvcc](), [raft](), [serializable](), [txn](), [v3-5](), [v3-5-33](), [version]() ### AI overview This article examines etcd v3.5.33 transaction semantics, including compare operations, nested transactions, MVCC visibility, ReadIndex behavior, and Raft-based atomic application. It distinguishes the design goals of the KV transaction path from the Lease session-lock path and carefully limits Jepsen evidence to etcd 3.4.3 rather than claiming an independent 3.5.33 rerun. ### Source excerpt 钉 etcd v3.5.33 Txn 的 compareToPath、MOD/CREATE/VERSION 比较与写 Txn 的 Raft 单槽 apply，并对照 Jepsen 3.4.3 的 strict-serializable 与 Lease 锁不安全子集。 [Next page]()