Optimizing
We track 15 posts about Optimizing from 9 engineering blogs. Most active: William Kennedy, SitePoint, Etsy. Latest post: Sep 22, 2026.
Companies writing about Optimizing
Recent posts
Optimizing Gemini 3.8 Flash for Autonomous Coding Agents: Thinking Levels and Tool Fallbacks (opens on the source site)
Build a TypeScript harness that routes Gemini 3.8 Flash thinking levels by task complexity while enforcing Zod schema validation and tool-call retries. Continue reading Optimizing Gemini 3.8 Flash for Autonomous Coding Agents: Thinking Levels and Tool Fallbacks on SitePoint.
Optimizing GitHub Actions for Agent PRs: Speculative Test Slicing and AST Impact Analysis (opens on the source site)
Fix CI saturation from high-frequency agent pull requests with AST change-impact analysis and speculative test slicing in GitHub Actions. Continue reading Optimizing GitHub Actions for Agent PRs: Speculative Test Slicing and AST Impact Analysis on SitePoint.
From hours to minutes: Optimizing Red Hat Developer Hub performance testing with immutable LDAP images (opens on the source site)
Red Hat ·
At Red Hat, our CI/CD pipelines are the heartbeat of our development process. However, as we scaled the Red Hat Developer Hub performance testing framework, we hit a wall. Our environment setup time was ballooning, turning what should have been a seamless verification step into a long waiting game. For performance engineering in catalog-dependent applications, deployment and catalog population speed directly dictate your feedback loops. The post From hours to minutes: Optimizing Red Hat Developer Hub performance testing with immutable LDAP images appeared first on Red Hat Developer.
AI Infra Summit: NVIDIA Vera Rubin and DSX Platform Advancements Showcase Energy Efficiencies of Optimizing Tokens Per Watt for AI Factories (opens on the source site)
Nvidia ·
Ian Buck, vice president of hyperscale and high-performance computing at NVIDIA, Tuesday spoke on AI factory efficiency at the AI Infra Summit, the Santa Clara Convention Center event that has morphed into a Coachella of infrastructure tech. Before a packed audience — with more than 8,000 attendees this year, up from 3,500 last year — […]
How we saved 100 terabytes of memory by optimizing 1.1.1.1’s DNS cache (opens on the source site)
Five Rust-level memory optimizations to the DNS cache layout of Big Pineapple cut per-entry memory by 56%, freeing approximately 100 TB of memory across Cloudflare's fleet.
Optimizing Redshift Write Patterns: Tackling Tombstones and Ghost Rows (opens on the source site)
Amazon Redshift is a core part of our analytics platform, powering dashboards, data quality checks, ad-hoc analytical workloads, and downstream reporting on a shared cluster. Because everything runs on the same cluster, the size and health of our tables directly affects every workload. At Wealthfront, data drives every decision we make, which means any performance... Read more
Optimizing ML Workload Network Efficiency (Part I): Feature Trimmer (opens on the source site)
Guangtong Bai | Staff Software Engineer, Product ML Infrastructure*; Shantam Shorewala | Software Engineer II, Product ML Infrastructure*; Chi Zhang | Staff Software Engineer, AI Platform*; Neha Upadhyay | Software Engineer II, AI Platform*; Haoyang Li | Director, Product ML Infrastructure*These authors contributed equally to this article.BackgroundAt Pinterest, our online ML serving systems employ a root-leaf architecture. On a high level, the architecture looks as follows:Figure 1: Root-leaf Architecture of Online ML Serving Systems at PinterestIn the diagram, “Client Service” is…
Optimizing Third-Party Content Delivery: A Deep Dive into Preconnect’s Performance and Call Cost Implications (opens on the source site)
This document details how preconnect improves web performance, especially for Bazaarvoice's third-party content, by accelerating connection setups and reducing LCP. Crucially, internal testing confirmed preconnect operations are not counted as API calls, validating a "no count, low cost" model—a key insight for our developer blog.
Optimizing Databases on Kubernetes: Kubernetes Backup and Recovery with CNPG and ZFS Snapshots (opens on the source site)
Introduction: In the final episode of the Optimizing Databases on Kubernetes series, Jérôme Petazzoni dives into advanced backup and recovery techniques for PostgreSQL, showcasing how CNPG (Cloud Native PostgreSQL) and ZFS snapshots ensure durability and fast recovery in production environments. This episode focuses on safeguarding data with comprehensive backup strategies, point-in-time recovery, and rapid database cloning, while leveraging ZFS’s efficiency for optimized storage performance. Comprehensive Backup Strategies: Exploring backups with CNPG, including write-ahead logs (WAL) and…
Optimizing Databases on Kubernetes Ep.4: Kubernetes Storage: Benchmarking ZFS, Cloud Disks, and Local Paths (opens on the source site)
Introduction: In Episode 4 of the Optimizing Databases on Kubernetes series, Jérôme Petazzoni benchmarks the performance of various Kubernetes storage classes, including cloud block storage, ZFS, and Rancher’s Local Path provisioner. This episode dives into the practical aspects of measuring transactions per second, storage efficiency, and durability, offering insights into selecting the right storage solution for database workloads. Through detailed performance comparisons, Jérôme highlights how features like ZFS compression can optimize resource usage and boost database throughput.
Optimizing Databases on Kubernetes Ep.3: Exploring Kubernetes Storage with OpenEBS and ZFS (opens on the source site)
Introduction: In Episode 3 of the Optimizing Databases on Kubernetes series, Jérôme Petazzoni introduces ZFS, a versatile file system renowned for its features like compression, deduplication, and snapshots. Leveraging ZFS with Kubernetes, Jérôme demonstrates how to create efficient and flexible storage solutions, complete with automated setup and configuration using tools like OpenEBS LocalPV. This episode showcases the potential of ZFS to optimize storage performance and reliability in containerized environments. Overview of ZFS: Exploring the features of this advanced file system, from…
Optimizing Databases on Kubernetes Ep.2: Automating Database Maintenance with Kubernetes and CNPG (opens on the source site)
Introduction: In this episode, Jérôme Petazzoni explores how Kubernetes and CNPG (Cloud Native PostgreSQL) work seamlessly to manage database operations during node maintenance. With real-world demonstrations, Jérôme highlights the power of Kubernetes’ automation features, such as failover mechanisms and pod disruption budgets, ensuring minimal downtime and maximum reliability for database applications. Automated Failover with CNPG: How Kubernetes handles database switchover during node drains. Pod Disruption Budgets (PDBs): Ensuring critical pods remain unaffected during maintenance.
Optimizing Databases on Kubernetes Ep.1: Provisioning a Cluster and Configuring PostgreSQL on Kubernetes (opens on the source site)
Introduction: In this introductory episode, Jérôme Petazzoni walks through the critical steps of provisioning a Kubernetes cluster tailored for running databases like PostgreSQL. Leveraging his extensive experience, Jérôme demonstrates practical tools and techniques to establish a scalable, cost-efficient database infrastructure while laying the groundwork for future optimizations covered in this series. Provisioning Kubernetes Clusters: A step-by-step guide to creating a reliable cluster using Linode. Setting Up PostgreSQL with CNPG: Deploying production-ready PostgreSQL clusters with…
Enhancing Cloud Usage Forecasting, Monitoring & Optimizing (opens on the source site)
Etsy ·
In 2020, Etsy concluded its migration from an on-premise data center to the Google Cloud Platform (GCP). During this transition, a dedicated team of program managers ensured the migration's success. Post-migration, this team evolved into the Etsy FinOps team, dedicated to maximizing the organization's cloud value by fostering collaborations within and outside the organization, particularly with our Cloud Providers. Positioned within the Engineering organization under the Chief Architect, the FinOps team operates independently of any one Engineering org or function and optimizes globally…
Enhancing Cloud Usage Forecasting, Monitoring & Optimizing (opens on the source site)
Etsy ·
In 2020, Etsy concluded its migration from an on-premise data center to the Google Cloud Platform (GCP). During this transition, a dedicated team of program managers ensured the migration's success. Post-migration, this team evolved into the Etsy FinOps team, dedicated to maximizing the organization's cloud value by fostering collaborations within and outside the organization, particularly with our Cloud Providers. Positioned within the Engineering organization under the Chief Architect, the FinOps team operates independently of any one Engineering org or function and optimizes globally…
Related topics
This page is generated automatically from the engineering blogs we follow. Every post links to its source, where it was published. See all sources.