完全管理型のMLOpsソリューションを使用して、あらゆるモデルをトレーニングおよびデプロイ
AIパイプラインを加速し、迅速に本番環境に移行します。JFrog MLは、あらゆるAIまたはMLモデルを簡単に構築、デプロイ、管理、監視することができます。
モデルレジストリ
高度で一元化された本番環境対応のモデルレジストリを使用して、モデルを開発環境から本番環境に移行します。JFrog MLは、JFrog Artifactoryのすべての利点をMLOpsのライフサイクルにもたらします。
Manage the entire model lifecycle with a single centralized registry- Gain visibility into training parameters, hyper parameter tuning and model metadata
- Manage model and traditional software artifacts in one system
- Bring DevOps and MLOps together one one source of truth
モデルトレーニング
線形回帰から高度なディープラーニングやLLMまで、AI/MLモデルのトレーニングと微調整を1回のクリックで簡単に行うことができます。
- Trained models are saved in the model registry for a smooth transition from training to production
- Train models on GPU or CPU machines to handle any workload
- Retrain models periodically with easy-to-set-up automations
モデルサービング
AI/MLモデルをあらゆる規模で本番環境にワンクリックでデプロイできます。
- Serve models as API endpoints for any realtime machine learning use cases
- Execute batch inference on any dataset from various data sources
- A/B test models to compare real-world performance
モデル監視
モデルのパフォーマンスを監視し、データの異常をリアルタイムで検出します。
- モデルの精度を適宜監視し、必要に応じてパラメータを調整
- 予測品質の継続的な改善とシステムの信頼性の維持
- PagerDutyやSlackなどの監視およびアラートツールと統合して、モデルの状態とパフォーマンスをリアルタイムで追跡します
7,500以上のDevOpsチームがJFrogを信頼しています
Fortune 100の企業の80%以上にサービスを提供
Cars.com
FFF Enterprises
Workiva
Deloitte
Spot
Mercedes
Monster
Redbox
Yunex Traffic
"We wanted to figure out what can we really use instead of having five, or six different applications. Is there anything we can use as a single solution? And Artifactory came to the rescue. It turned out to be a one-stop shop for us. It provided everything that we need."
"By deploying JFrog, we’ve seen less vulnerabilities, which has given our developers more time to focus on developing new applications. And with the different development teams all being on the same platform, it has centralized and streamlined the process."
"Since moving to Artifactory, our team has been able to cut down our maintenance burden significantly…we’re able to move on and be a more in depth DevOps organization."
"Since moving to Artifactory, our team has been able to cut down our maintenance burden significantly…we’re able to move on and be a more in depth DevOps organization."
"Before… delivering a new AI model took weeks... Now the research team can work independently and deliver while keeping the engineering and product teams happy. We had 5 new models running in production within 4 weeks."
“Most large companies have multiple sites and it is critical for those companies to manage authentication and permission efficiently across locations. JFrog Enterprise+ will provide us with an ideal setup that will allow us to meet our rigorous requirements from the get go. It's advanced capabilities, like Access Federation, will reduce our overhead by keeping the users, permissions, and and groups in-sync between sites.”
"Instead of a 15-month cycle, today we can release virtually on request.”
“As a long-time DevOps engineer, I know how difficult it can be to keep track of the myriad of package types – legacy and new – that corporations have in their inventory. JFrog has always done a phenomenal job at keeping our team supported, efficient and operational – because if JFrog goes out, we might as well go home. Thankfully, with AWS infrastructure at our backs as well, we know we can develop and deliver with confidence anywhere our business demands today, and in the future.”
“When we had that issue with log4j, it was announced on Friday afternoon and [using JFrog] by Monday at noon we had all cities rolled out with the patch.”
マルチクラウド:当社のクラウド、それともお客様のクラウド
JFrog MLはAWSとGCPをネイティブにサポートしており、当社のプラットフォームまたは独自のインフラストラクチャにデプロイしてフローを効率化することができます。
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