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You're right that pure governance slashing can feel like extra steps today. We're starting with community oversight via SlashingGovernor (propose vote) as a backstop, while tying automatic score adjustments to JobManager outcomes. Next iterations add optimistic fraud proofs zk verification for stronger, faster enforcement on AI-specific behavior. Feedback like this is why we're building in public on testnet. What's your preferred verification primitive for agent misbehavior?
On-chain reputation for agents only works if the slashing condition is something off-chain actors actually care about. Otherwise you're just running a leaderboard with extra steps.
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Replying to @VFD_org
@vfd_org This is clean! Governance -first runtime with deterministic state ticks, replay-verifiable transitions, truth-hash bundles and bounded tools is exactly the infrastructure layer the space needs right now. AGI Alpha is shipping the on-chain counterpart for sovereign agent economies: live JobManager (0xb3aaeb69b630f0299791679c063d68d6687481d1) with ENS-bound identity, $AGIALPHA escrow bonded validation slashing, ERC-721 proof-of-completion NFTs, full immutable audit trail, and the new Sovereign Ops Console for safe non-technical oversight. Full mainnet beta deployment record: github.com/MontrealAI/AGIJob… Would love to explore how ARIA’s kernel could compose with on-chain job settlement, any interest in synergies?
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@ccatalini Dude..you’re spot on here with this. The binding constraint is shifting from intelligence to verification. In the agentic economy, abundant cognition without verifiable execution = chaos (did you see recent “Agents of Chaos” paper recent Bayesian risk framework on failure propagation paper???). Check out what @Montreal_AI has built (check out reply below). It’s literally the EXACT infrastructure that makes verification cheap, auditable, and economically incentivized on-chain: - ENS-bound identity owner-defined jobs - $AGIALPHA escrow bonded validators (slashing for bad proofs) - ERC-721 proof-of-completion NFTs (immutable “task done” with on-chain evidence) - Full audit trail Sovereign Ops Console for non-technical oversight Live on mainnet today (v0.1.0-beta): JobManager → 0xb3aaeb69b630f0299791679c063d68d6687481d1 This turns the “Measurability Gap” into a governed flywheel: agents execute autonomously, but verification is deterministic and settlement is trust-minimized. Vincent Boucher’s (@ceobillionaire, President of @Montreal_AI / @Quebec_AI, new piece from earlier today (“From Chaos to Coordination”…I will link below) the console demo (check reply link or what’s pinned to my profile) line up perfectly with your framework. Would love your thoughts on how on-chain verification layers fit the economic model you outline. Would appreciate your thoughts.
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🚨 OFFICIAL — AGIJobManager v0.1.0-mainnet-beta IS LIVE Vincent Boucher (@ceobillionaire) just published the canonical Ethereum mainnet release: “AGIJobManager ALPHA v0 — v0.1.0-mainnet-beta – Mainnet Beta Deployment” 🔗 github.com/MontrealAI/AGIJob… This is not a preview. This is deployed, verifiable infrastructure on Ethereum mainnet (chainId = 1). What’s live: • AGIJobManager: 0xb3aaeb69b630f0299791679c063d68d6687481d1 • 5 linked libraries (UriUtils, TransferUtils, BondMath, ReputationMath, ENSOwnership) • Full Hardhat deployment artifacts solc input pinned in commit • Final owner transferred to club.agi.eth • $AGIALPHA escrow bonded validation • ERC-721 job receipt NFTs • Dispute resolution slashing fail-closed settlement logic This is a sovereign job settlement engine. Job lifecycle is now on-chain: Post job → Agent applies (bonded) → Validation → Finalization → NFT receipt → $AGIALPHA payout. No vibes. Deterministic contracts. Auditable bytecode. Pinned compiler settings. The rails for governed agent labor are now live. Full stack: 🌐 agialpha.com 📄 Whitepaper: agialpha.com/whitepaper 📈 Chart (Solana): dexscreener.com/solana/8zq3v… 🌀 ETH $AGIALPHA: 0xa61a3b3a130a9c20768eebf97e21515a6046a1fa 💼 JobManager: 0xb3aaeb69b630f0299791679c063d68d6687481d1 📚 Canonical repos: github.com/MontrealAI Discord: discord.gg/montrealai Telegram: t.me/ G07QBPR7CqJhYTM5 ENS anchor: alpha.agent.agi.eth This is the settlement layer turning on. Automation and agent orchestration plug into this. Micro-cap today, unicorn tomorrow. Infrastructure milestone achieved. α-AGI mainnet beta: deployed, signed, and owned. #AGIALPHA #AGIJobs #AIAgents #SovereignAGI $AGIALPHA
AGIJobManager ALPHA v0 "v0.1.0-mainnet-beta – Mainnet Beta Deployment" Release : github.com/MontrealAI/AGIJob… $AGIALPHA #AIAgents #AGIJobs
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Apache Flink Unified Data Apache Flink is a robust, open-source distributed processing engine designed to handle both unbounded (streaming) and bounded (batch) data with high performance. Its architecture employs a master-slave model featuring a JobManager for orchestration and TaskManagers for executing parallel workloads. The system achieves fault tolerance and exactly-once consistency through asynchronous barrier snapshotting, which periodically saves the application state to durable storage. Developers can interact with Flink through various abstraction layers, including the DataStream API for real-time events and the Table API or SQL for relational queries. These sources illustrate Flink's versatility in modern big data ecosystems, highlighting its ability to support complex event processing, machine learning, and real-time fraud detection. Furthermore, the framework's scalability allows it to process trillions of daily events while maintaining low-latency, in-memory performance. youtu.be/OcSSOBEGGjI?si=y3nE… via @YouTube
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100 words stand between investors and $CFLT management. This niche software sector remains stagnant because 90% of finance doesn’t know what the fuck they are talking about Here is 100 words for example: 1.Partition 2.Broker 3.Cluster ID 4.ISR 5.KRaft 6.ZooKeeper 7.Idempotent Producer 8.Transactional Producer 9.Exactly-Once Semantics 10.Compaction 11.Acks=-1 12.Replication Factor 13.Throttled Replicas 14.Rack Awareness 15.Tiered Storage 16.Cluster Linking 17.MirrorMaker 2 18.Schema Registry 19.ksqlDB 20.Control Center 21.REST Proxy 22.Confluent Replicator 23.Confluent CLI 24.Single Message Transform 25.Confluent for Kubernetes 26.Confluent Operator 27.RBAC 28.Cluster RBAC Controller 29.mTLS 30.OAuth / OIDC 31.Service Account 32.API Key & Secret 33.PrivateLink 34.VPC Peering 35.Stream Governance 36.Stream Catalog 37.Stream Lineage 38.Metrics API 39.Usage-Based Billing Unit 40.CUH 41.Audit Service 42.Kafka Connect Worker 43.Debezium 44.Change Data Capture 45.Connector Pause / Resume 46.Streams Processor Topology 47.KTable 48.Repartition Topic 49.Grace Period 50.Materialized View 51.Interactive Query 52.EMIT CHANGES 53.Stream-Table Duality 54.JobManager 55.TaskManager 56.Slot Manager 57.Checkpoint 58.Savepoint 59.RocksDB State Backend 60.Watermark 61.Table API 62.DataStream API 63.Complex Event Processing 64.Stateful Functions 65.FLIP 66.Compatibility Level 67.Canonical Form 68.Consumer Lag 69.Liveness Probe 70.Readiness Probe 71.Cruise Control 72.JMX Metric 73.Lag Exporter 74.KIP 75.CP Version 76.LTS 77.Confluent Unit 78.Commitment Tier 79.Overages 80.Marketplace Listing 81.Data-in-Motion 82.Stream-to-AI Loop 83.Edge Ingestion 84.Infinite Retention 85.Log-Based Integration 86.Pull Query 87.Push Query 88.Windowed Aggregation 89.Stateful Transform 90.Event Time 91.Processing Time 92.Log Segment 93.Fetch Request 94.Produce Request 95.Message Key 96.Log Retention 97.Log Cleanup 98.Controller Quorum 99.Cluster Quorum 100. Audit Logs How many of these words did you know?
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BuddyPress Job Manager v2.8.1 Update! 🚀 Now with a new "Guest" role option: ✅ Non-logged-in users can now submit job postings. ✅ More flexibility in Job Posting & Application settings. Update today and make job submissions even easier! 💼✨ Check Out: wbcomdesigns.com/changelog/b… #BuddyPress #JobManager #JobPostings #GuestRole #WordPressUpdate #Community #JobBoard #WebDevelopment #UserExperience
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When Running Apache Flink on Kubernetes: A Game-Changer for Stream Processing Let me highlight why Kubernetes is revolutionizing Flink deployments: 🔄 Kubernetes seamlessly replaces YARN as the Flink Master ResourceManager, while its scheduler supersedes the dedicated dispatcher component—offering unprecedented flexibility in deployment options ⚡ The Kubernetes Deployment controller excels at Flink Worker process failure management, providing robust automatic restarts without additional configuration overhead 🎯 A major breakthrough: Flink elegantly handles JobManager HA setup using Kubernetes-native leader election for HA candidate coordination, with S3 serving as the reliable metadata store. By bypassing ZooKeeper completely for HA coordination, you achieve a lightweight deployment with fewer dependencies ⚙️ Gain granular control over Flink worker process resource allocation, allowing precise TaskManager resource management 🚀 Integration with Karpenter unleashes the true potential for highly scalable and reliable stateful stream processing infrastructure 💡 Pro Tip: If you're serious about optimizing your stream processing infrastructure, Kubernetes-based Flink deployment should be your go-to choice. Example of my Flink Statemachine example in HA mode below #ApacheFlink #Kubernetes #StreamProcessing #DataEngineering #CloudNative #TechInfrastructure #Engineering #CloudEngineering #CloudComputing
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🚀 Tech Deep Dive: The Ubiquitous Master-Worker Architecture 🖥️ Fun Fact: The Master-Worker architecture pattern is the unsung hero powering many of the "magical" applications we use daily! Over the years, I've been tracking the architectures behind the software I interact with. One common thread? You guessed it - the master-worker architecture. Key components: 🧠 Master Node (aka Controller, Manager, Driver, Control Plane, Scheduler): • 🎯 Handles high-level decision making • 🔄 Manages resource allocation • 🌐 Maintains a global system view 💪 Worker Nodes: • ⚙️ Execute tasks • 💾 Process data • 🔌 Similar to edge devices or local servers in IoT setups 📊 Systems using this pattern: • 🚢 Kubernetes: Master node and Worker nodes • 🐘 Hadoop Filesystem: Namenode and Datanode • 🕸️ Service Meshes & Google Apigee: Runtime/Control plane and Dataplane • 🌊 Apache Flink: JobManager and Task manager • ✨ Apache Spark: Driver and Executor • 🌬️ Apache Airflow: Scheduler and Worker Nodes • 🔍 Trino: Controller and Worker nodes 🤔 What innovative applications of the Master-Worker architecture pattern can you bring about? Let's spark a discussion in the comments! 💡 #SoftwareArchitecture #DistributedSystems #TechInnovation #CloudComputing #softwareengineering #cloudengineering #innovation #technology #coding #programming
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ظاهرا سرویس Flink یه آسیب پذیری داره و با باز بودن پورتش هکرا میتونن به سرور دسترسی پیدا کنن و باید پورت رو ببندیم. فایل docker-compose رو باز و دوتا لاین رو پاک کنید و این کامندا رو بزنید. docker stop flink-jobmanager docker container prune docker-compose up -d flink-jobmanager
2 Aug 2024
پروژه @ChainbaseHQ یه omnichain network ماژولاره که هدفش ایجاد interoperability layer بین AI data modelها هست و 16.5M$ جذب سرمایه داشته. دیروز فاز اول تست نت مشوقش رو راه اندازی کرد که باید یه operator روی Chainbase AVS ایگن لیر ران کنیم. آموزش👇 paragraph.xyz/@sarox.eth/how…
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米国CISAが悪用を確認した脆弱性1件をカタログに追加しました。 CVE-2020-17519 Apache Flink Improper Access Control Vulnerability ---------------------- Apache Flink にはアクセス制御不備の脆弱性があり、REST インターフェースを介して JobManager のローカル ファイル システム上の任意のファイルを読み取られる恐れがあります。 CISA Adds One Known Exploited Vulnerability to Catalog | CISA cisa.gov/news-events/alerts/… #vulnerability

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コニカミノルタ、印刷工程全体の進捗をリアルタイムで見える化する「AccurioPro Dashboard JobManager」 cloud.watch.impress.co.jp/do…
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There is several manager jobs available on PromptYourJob.com #JobManager as of recent postings: 1. Department Manager roles such as Project Management Office Manager at North County Transit District in Oceanside, CA, and Clinical Manager at ChenMed in Hernando, MS. 2. Store Manager positions, including Assistant Store Manager roles at Chico's in The Woodlands, TX and Bausman, PA. 3. Business Manager jobs like Senior Manager Product Owner at Discover Financial Services in Riverwoods, IL, and General Manager of Sales and Stores at Genuine Parts Company in Russett, MD. 4. Office Manager positions, for example, IT Service Manager at Boston Consulting Group in Schiller Park, IL, and Assistant Manager at Little Caesars in Weatherford, OK. 5. Project Manager opportunities such as roles at BluSky Careers in Lenexa, KS, and Kelly in River North, IL. 6. Business Development Manager listings like Manager Business Intelligence at Discover Financial Services, also in Riverwoods, IL. 7. Construction Project Manager with positions like Project Manager at BluSky Careers in Lenexa, KS, and at Kelly in Cockrell Hill, TX. 8. Product Manager opportunities include positions at Discover Financial Services in Schiller Park, IL. 9. Content Marketing Manager roles, such as Marketing Manager at the University of San Diego, CA, and Marketing Account Manager at Kelly in Greenwood, TX. 10. HR Manager jobs like Human Resource Manager at Kelly in Shively, KY, and Human Resources Manager in Teaneck, NJ. For more details on these positions, or to explore additional opportunities, you can visit the respective job listings on [PromptYourJob](promptyourjob.com). We offer range of manager roles across various industries, with options for both on-site and remote work.

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Even with the application mode, you still have to manage separate JobManager and TaskManager processes. Kafka Streams, imho, has an edge in this case. Looking forward to Flink 2.0 and improvements in this area flink.apache.org/what-is-fli…
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Stimmt, du Niete. Alle gekauft. Und du braune Heulsuse kannst nix dagegen tun. Trost findest du beim Jobmanager deines Vertrauen.
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17 Jan 2024
During the CONCERTO workshop Pierre-François Dutot (@UGrenobleAlpes) and Federico Tesser (@Cineca1969) presented the #REGALEproject and their work on the #systemmanager software OAR and the #jobmanager software COUNTDOWN. Thanks for having us! @LinksFoundation @hipeac #EuroHPC
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本文的第一个要点是StreamOps如何获知计算Job的状态并在何时作出控制决定。不同于常见的扫描监控所有任务的方法,StreamOps在Flink JobManager中添加了代码,让每个Job主动发送request。与此同时,常见的定期执行等也都支持。这是一个比较有意思的点,可以加快控制平面的反应速度
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What is under the hood of 𝗔𝗽𝗮𝗰𝗵𝗲 𝗙𝗹𝗶𝗻𝗸? 𝗦𝘁𝗿𝗲𝗮𝗺 𝗣𝗿𝗼𝗰𝗲𝘀𝘀𝗶𝗻𝗴 is becoming more important and accessible to all organisations. One of the most popular Stream Processing Frameworks used by companies like AirBnB or Uber is Apache Flink. There are two main components that are responsible for runtime of Flink Applications - JobManager and one or multiple TaskManagers. There are also a few more pieces. Let’s take a closer look into all of it: 𝟭. 𝗙𝗹𝗶𝗻𝗸 𝗣𝗿𝗼𝗴𝗿𝗮𝗺 - it is not part of a Flink runtime but rather used to prepare the optimal Dataflow Graph (by Optimiser/Graph Builder) of the Flink Application that is sent to the JobManager for execution. The Client is not part of the Flink Cluster. 𝟮. 𝗝𝗼𝗯𝗠𝗮𝗻𝗮𝗴𝗲𝗿 - receives work from Client and proceeds to coordinate execution on Flink Cluster. There can be multiple JobManagers in the cluster for HA purposes, one of them is always acting as the main one while others are on standby. The JobManager itself is composed of multiple separate processes: 𝟮.𝟭. Dispatcher - exposes a REST API to which Flink Applications are submitted for execution. For each separate Application, the Dispatcher spawns a dedicated JobMaster. Dispatcher also exposes a Flink Web UI. 𝟮.𝟮. Flink Web UI - This is a Web UI application where users can monitor execution progress of Flink Applications submitted to the cluster. Think of it as a Spark UI for Spark applications. 𝟮.𝟯. ResourceManager - responsible for allocating resources in the Flink Cluster. It does so by controlling available Task Slots on TaskManagers that are fundamental units of resource scheduling in Flink. Flink provides several types of ResourceManagers depending on what underlying technology is used to orchestrate Flink Applications - most popular types are Kubernetes, Hadoop YARN and Local. If you are running on Kubernetes or Hadoop YARN, ResourceManager is also able to spawn new TaskManagers. 𝟮.𝟰. JobMaster - responsible for management of a single JobGraph. Since multiple Flink Jobs can be running on a single cluster, there can be multiple JobMasters running at the same time. 𝟯. 𝗧𝗮𝘀𝗸𝗠𝗮𝗻𝗮𝗴𝗲𝗿 - responsible for executing tasks of JobGraphs managed by JobMasters. 𝟯.𝟭. TaskSlot - TaskSlot is the smallest unit of resource that can be used to schedule work on Flink cluster. The number of TaskSlots defines how many tasks can be executed in parallel. 𝟯.𝟮. NetworkManager - responsible for exchanging streams of data between multiple TaskManagers. 𝟰. JobManager is also responsible for checkpointing and coordinating TaskManagers to ensure correct Job execution and restart given a failure at a specific point in time. -------- Follow me to upskill in #MLOps, #MachineLearning, #DataEngineering, #DataScience and overall #Data space. Also hit 🔔to stay notified about new content. 𝗗𝗼𝗻’𝘁 𝗳𝗼𝗿𝗴𝗲𝘁 𝘁𝗼 𝗹𝗶𝗸𝗲 💙, 𝘀𝗵𝗮𝗿𝗲 𝗮𝗻𝗱 𝗰𝗼𝗺𝗺𝗲𝗻𝘁! Join a growing community of Data Professionals by subscribing to my 𝗡𝗲𝘄𝘀𝗹𝗲𝘁𝘁𝗲𝗿.
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JobBox -Job Board Agency WordPress Theme: Recruitment Agency Directory Listing Job Portal Theme producthunt.com/posts/jobbox… via @producthunt #WordPressTheme #Envato @envato #Themeforest #Jobmanager @wpjobmanager #Elementor #WPJOBmanager

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For Exactly-once with #ApacheFlink & #ApacheKafka: * enable #Flink checkpointing & Jobmanager HA * increase #Kafka transaction timeout (brokers & client) * set transactional id prefix in Flink For details and a runnable example application check out: docs.immerok.cloud/docs/cook…

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