AI Agent Migrates 1TB of Elasticsearch Data to OpenSearch 3.x in 33 Minutes

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A team recently demonstrated an AI-assisted database migration that moved one terabyte of production data from Elasticsearch 7.10 on Amazon OpenSearch Service to OpenSearch 3.x in just 33 minutes. The entire process was orchestrated by an AI agent using Kiro connected to Migration Assistant for Amazon OpenSearch Service, running on Amazon EKS, with no manual configuration or human intervention required. The agent independently handled infrastructure decisions, set snapshot throttling to 800 MB/s, calculated optimal parallelization across 480 concurrent reindex pods, and configured EKS auto mode to provision EC2 instances on demand. Migration Assistant is an open-source tool that supports migrations from Elasticsearch, self-managed OpenSearch, and Apache Solr versions 6.x through 9.x to both Amazon OpenSearch Service domains and Serverless collections. The demo highlights AI agents' growing capability to autonomously manage complex, multi-layered database migration tasks that have traditionally required senior engineering oversight.

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Perl Weekly Challenge 386: Base Conversion and Repeating Decimal Comparison

The 386th Perl Weekly Challenge presents two mathematical programming tasks for participants to solve. The first task requires writing a function that converts a string representation of a number in any given base back into a standard integer, essentially reversing the previous week's challenge. The second task asks programmers to determine whether two non-negative rational numbers expressed as repeating decimals are equal. The recommended approach for the second task involves converting each repeating decimal into a standard fraction using algebraic manipulation, then comparing the two fractions. Perl's built-in bigrat module is suggested as a convenient tool for handling rational number arithmetic with automatic fraction reduction.

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ProgrammingDEV Community ·

Developer Revives Abandoned Weave Scope with Multi-Platform Docker Support

Weave Scope, a once-popular open-source tool for real-time container cluster monitoring and visualization, was archived and left unmaintained after its original developers at Weaveworks stepped away. The tool's dependency tree had frozen, locking it exclusively to x86_64 architectures and making it incompatible with modern ARM-based systems such as AWS Graviton, Apple Silicon, and Raspberry Pi. Developer Mario Ezquerro used an AI coding assistant called Antigravity to audit dependencies, refactor Dockerfiles, and modernize the build pipeline to support both linux/amd64 and linux/arm64 targets. The revived project has been published to a new GitHub repository and multi-architecture Docker images are now available on Docker Hub. Ezquerro says the entire modernization effort was completed in a single afternoon, highlighting the potential for developers to rescue other abandoned open-source projects with relatively little effort.

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ProgrammingDEV Community ·

Google Launches Gemini 3.7 Flash at Half the Price, Targeting AI Agent Workflows

Google released Gemini 3.7 Flash on August 13, 2024, just three weeks after its predecessor, 3.6 Flash, with a focus on coding and multi-step agent workflows. The model is priced at $0.75 per million input tokens and $3.75 per million output tokens through end of 2026 — half the original 3.6 Flash price — before doubling on January 1, 2027. On benchmarks, 3.7 Flash outperforms 3.6 Flash on FrontierCode 1.1 Main (43.6% vs 34.4%) and DeepSWE v1.1 (65.3% vs 49.0%), among others. Google highlights improvements in multi-step planning, tool-call accuracy, intent clarification, and instruction-following — capabilities that directly reduce costly retries and human interventions in agent loops. Analysts note that for agentic use cases, the true cost of a model extends beyond token pricing to include retries, failed edits, and human resets, making reliability as important as raw price.

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ProgrammingDEV Community ·

Engineering student builds AI-assisted typing trainer with 31 sub-levels and bigram tracking

A first-year engineering physics student has launched WorkThoseKeys, a free typing trainer built using Lovable, a prompt-based AI app builder, without writing code by hand. The tool features 31 sub-levels across eight stages, introducing one finger at a time before combining them, with each level structured around warmup, weak points, integration, and a progress check. Unlike most typing trainers, it tracks per-bigram error rates — identifying which letter pairs a user struggles with — and separates keyboard layout settings from content language. The app also includes an AI coach that translates typing data into plain-language advice, and a book mode that lets users type real public-domain literature, from short poems to the full text of Moby-Dick. All features are available for free with no sign-up required, though users can log in with Google to save stats and streaks.

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