Build AI agents for business intelligence with Amazon Bedrock AgentCore: In this post, we show you how OPLOG developed three AI agents using the Strands Agents SDK, deployed them to Amazon Bedrock AgentCore, and integrated Amazon Bedrock with Anthropic’s… dlvr.it/TSfd7c

OPlog - mgyk｜麦焼き🍳 xfolio.jp/portfolio/oicgohan… #クロスフォリオ 以前描いていたﾝﾋﾟ絵をまとめました 見たいと仰ってくださった方有難う御座います！

This exporter is implemented as an oplog processor plugin, a fully open system for extending Golem's behavior by observing agents. And it has exactly-once delivery semantics!

We’ve been listening to the community for a long time, and today we’re excited to share what’s coming in Meteor 4.0. Meteor is dropping MongoDB in favor of Semantic Memory - After years of schema debates, migration headaches, and oplog nightmares, we made a decision: databases are over. Meteor 4.0 ships with a built-in AI layer that stores your data as semantic embeddings. No collections. No documents. No queries. You just describe what you need and the framework figures it out. Meteor.remember(“the user’s last order”), that’s your new data layer. Meteor 4.0 ships with first-class PHP support - We know. We know. But the data doesn’t lie: PHP powers 77% of the web, and we’re not here to fight the market. You’ll be able to write your Meteor methods in PHP with full DDP compatibility. jQuery Legacy Mode is back - By popular demand, Meteor 4.0 ships with a meteor add jquery@1.x official package. Blaze jQuery 1.11 is a stack that simply works, and we’re done pretending otherwise. Migration guide and beta release: April 1st.

ugm_fess tim kkn kami lagi butuh member baru 😜 WTB: ddv oplog gacor! kriteria: bisa konten foto/vid, ngerti edit (davinci/premiere) 🎬 benefit: gear ready (drone kamera), sponsor ada, udah lolos DPKM 😜 lokasi sulawesi | slot agro & medika msh open!! comment y ntar gweh dm

here it is. i implemented the complete "Google File System" paper in rust. [repo in replies] raw TCP, custom framing, bincode serialization. pipelined writes through replica chains with serial-ordered commits. record append with overflow detection and cross-replica padding. COW snapshots that fork chunks on first write, not on snapshot. operation log with rotation, checkpointing, and crash recovery. shadow masters that replicate the oplog live and catch up from disk when they reconnect. namespace locking so concurrent file ops don't step on each other. lazy GC that hides deleted files, sweeps after a retention window, then cleans chunkservers via heartbeat. re-replication when a server goes down. two-phase chunk rebalancing, copy first, confirm via heartbeat, then delete. reading the paper was the easy part. making all the pieces not break each other was THE project.

Meteor 3.4 focused on the client: faster builds, smaller bundles, better DX. Meteor 3.5 is turning attention to the server. Change Streams replacing Oplog = lower CPU and memory usage for your running apps. The performance era of Meteor is just getting started.

Update from the 2025 VascuPitch winner, Karan Chawla, MD! @LoyolaVascular #OpLog

Debezium connectors with Kafka in snapshot mode initially, and then in oplog/binlog streaming mode. Once the connector fully catches up and reaches 100% real‑time binlog/oplog processing, we can begin switching the application nodes one by one to point to the new AWS database

Hey Dhanian great overview! 👏 One tiny but important nit: replicas don't directly read from the primary's log file (binlog/WAL/oplog/etc.). The primary writes changes → log → ships log entries (or diffs) to replica → replica writes them to its own relay log (MySQL/MariaDB) or oplog (MongoDB) → replica's SQL/applier thread then reads its local relay/oplog and applies the changes to its data files. So it's not reading the primary's log file over the network in real time it's receiving a stream/copy and replaying locally. Helps avoid tons of network I/O on every read and allows for better buffering/retry. Rest of the post is spot on especially calling out lag vs consistency trade-offs!"

Meteor 3.5-beta is here and it’s all about SCALABILITY! 🚀 The game-changer? @MongoDB Change Streams support is officially in testing. 🌊 Why this matters: 40% More Connections: Benchmarks show a massive jump in concurrent users (from 1200 to 1680 VUs). No More OOM: Say goodbye to "Out of Memory" crashes during high traffic spikes. Efficiency: Moving away from heavy Oplog tailing to a modern, request-based streaming architecture. Meteor.js continues to prove it’s the king of real-time reactivity, now with the professional-grade stability your production apps need. 🛠️ Check out the full benchmarks and technical breakdown: forums.meteor.com/t/meteor-3… #MeteorJS #JavaScript #NodeJS #MongoDB #OpenSource #WebDev

Dimostrazione di quanto sia difficile lavorare con me: Il mio capo in un meeting: <<...PostgreSQL ha un meccanismo simile a MongoDB, solo che invece di chiamarlo OpLog lo chiama "WAL"...>> Io: <<Quindi posso usare l'espressione "Avete scassato la WAL"?!😁>> Tutti: "..."

No worries! I have manually written Mongo oplog streamers to do the same thing previously. Extremely fun and I hope you had a good time building it!

Local-First & P2P web apps with WebAuthN hardware secured signing the @orbit_db oplog, #DIDs and also #UCAN's via #WebAuthN varsic envelops! Why all of this is necessary and relates with @storachanetwork ? medium.com/@seidenwege/orbit…

Jujutsu を使い始めて 2週間ほど。Git と比べてリポジトリを壊さない安心感がすごい。 force push が必要になる変更は最初から弾かれる。一方でローカルでは何をやっても `jj undo / restore` で必ず元に戻せる。 ファイルは保存したら必ず履歴に残るので、Git のように add や commit し忘れ、stash の迷子もない。 一度 Git を直接触って履歴ごとファイルをふっとばして焦ったけど、`jj op restore` で oplog で操作前に戻したらブランチごと復活した。