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#distributeddata — Public Fediverse posts

Live and recent posts from across the Fediverse tagged #distributeddata, aggregated by home.social.

  1. #CaseStudy - Discover how #Uber evolved their distributed storage platform from static rate limiting to a priority-aware load management system to safeguard their in-house databases.

    This shift tackled the limits of QPS-based rate limiting in large, multi-tenant systems - handling noisy neighbors, and protecting tail latency.

    Read more on #InfoQ 👉 bit.ly/4rjf8IW

    #DistributedData #LowLatency #Sharding #LoadBalancing

  2. #CaseStudy - Discover how #Uber evolved their distributed storage platform from static rate limiting to a priority-aware load management system to safeguard their in-house databases.

    This shift tackled the limits of QPS-based rate limiting in large, multi-tenant systems - handling noisy neighbors, and protecting tail latency.

    Read more on #InfoQ 👉 bit.ly/4rjf8IW

    #DistributedData #LowLatency #Sharding #LoadBalancing

  3. #CaseStudy - Discover how #Uber evolved their distributed storage platform from static rate limiting to a priority-aware load management system to safeguard their in-house databases.

    This shift tackled the limits of QPS-based rate limiting in large, multi-tenant systems - handling noisy neighbors, and protecting tail latency.

    Read more on #InfoQ 👉 bit.ly/4rjf8IW

    #DistributedData #LowLatency #Sharding #LoadBalancing

  4. #CaseStudy - Discover how #Uber evolved their distributed storage platform from static rate limiting to a priority-aware load management system to safeguard their in-house databases.

    This shift tackled the limits of QPS-based rate limiting in large, multi-tenant systems - handling noisy neighbors, and protecting tail latency.

    Read more on #InfoQ 👉 bit.ly/4rjf8IW

    #DistributedData #LowLatency #Sharding #LoadBalancing

  5. - Discover how evolved their distributed storage platform from static rate limiting to a priority-aware load management system to safeguard their in-house databases.

    This shift tackled the limits of QPS-based rate limiting in large, multi-tenant systems - handling noisy neighbors, and protecting tail latency.

    Read more on 👉 bit.ly/4rjf8IW

  6. Check out Google's tiered storage for #Spanner – its distributed SQL database on Google Cloud!

    With this tiered storage, you can store older data on HDDs - 80% cheaper than SSDs - without the hassle of traditional migrations.

    Learn more on #InfoQ 👉 bit.ly/43NM5ov

    #CloudComputing #GoogleCloud #CostOptimization #HDD #DistributedData

  7. Check out Google's tiered storage for #Spanner – its distributed SQL database on Google Cloud!

    With this tiered storage, you can store older data on HDDs - 80% cheaper than SSDs - without the hassle of traditional migrations.

    Learn more on #InfoQ 👉 bit.ly/43NM5ov

    #CloudComputing #GoogleCloud #CostOptimization #HDD #DistributedData

  8. Check out Google's tiered storage for #Spanner – its distributed SQL database on Google Cloud!

    With this tiered storage, you can store older data on HDDs - 80% cheaper than SSDs - without the hassle of traditional migrations.

    Learn more on #InfoQ 👉 bit.ly/43NM5ov

    #CloudComputing #GoogleCloud #CostOptimization #HDD #DistributedData

  9. Check out Google's tiered storage for #Spanner – its distributed SQL database on Google Cloud!

    With this tiered storage, you can store older data on HDDs - 80% cheaper than SSDs - without the hassle of traditional migrations.

    Learn more on #InfoQ 👉 bit.ly/43NM5ov

    #CloudComputing #GoogleCloud #CostOptimization #HDD #DistributedData

  10. Check out Google's tiered storage for – its distributed SQL database on Google Cloud!

    With this tiered storage, you can store older data on HDDs - 80% cheaper than SSDs - without the hassle of traditional migrations.

    Learn more on 👉 bit.ly/43NM5ov

  11. How do you create & operate planet-scale data storage solutions for derived data?

    How do you decide on the pieces that must be fitted to ensure a resilient operating system?

    🎧 Listen to the #InfoQ podcast with Felix GV, Principal Staff Engineer at LinkedIn, and discover the answers: bit.ly/41Fxw3A

    📄 #transcript included

    #database #DataStorage #DistributedData

  12. How do you create & operate planet-scale data storage solutions for derived data?

    How do you decide on the pieces that must be fitted to ensure a resilient operating system?

    🎧 Listen to the #InfoQ podcast with Felix GV, Principal Staff Engineer at LinkedIn, and discover the answers: bit.ly/41Fxw3A

    📄 #transcript included

    #database #DataStorage #DistributedData

  13. How do you create & operate planet-scale data storage solutions for derived data?

    How do you decide on the pieces that must be fitted to ensure a resilient operating system?

    🎧 Listen to the #InfoQ podcast with Felix GV, Principal Staff Engineer at LinkedIn, and discover the answers: bit.ly/41Fxw3A

    📄 #transcript included

    #database #DataStorage #DistributedData

  14. How do you create & operate planet-scale data storage solutions for derived data?

    How do you decide on the pieces that must be fitted to ensure a resilient operating system?

    🎧 Listen to the #InfoQ podcast with Felix GV, Principal Staff Engineer at LinkedIn, and discover the answers: bit.ly/41Fxw3A

    📄 #transcript included

    #database #DataStorage #DistributedData

  15. How do you create & operate planet-scale data storage solutions for derived data?

    How do you decide on the pieces that must be fitted to ensure a resilient operating system?

    🎧 Listen to the podcast with Felix GV, Principal Staff Engineer at LinkedIn, and discover the answers: bit.ly/41Fxw3A

    📄 included

  16. The #opensource distributed storage system #CubeFS has reached graduation status!

    CubeFS supports multiple access protocols, including POSIX, HDFS, S3 & its own REST API.

    Its key platform targets?
    ➡️Big data
    ➡️AI/LLM applications
    ➡️container platforms
    ➡️databases

    Learn more: bit.ly/3F7d2sQ

    #DistributedData #DevOps #InfoQ

  17. The #opensource distributed storage system #CubeFS has reached graduation status!

    CubeFS supports multiple access protocols, including POSIX, HDFS, S3 & its own REST API.

    Its key platform targets?
    ➡️Big data
    ➡️AI/LLM applications
    ➡️container platforms
    ➡️databases

    Learn more: bit.ly/3F7d2sQ

    #DistributedData #DevOps #InfoQ

  18. The #opensource distributed storage system #CubeFS has reached graduation status!

    CubeFS supports multiple access protocols, including POSIX, HDFS, S3 & its own REST API.

    Its key platform targets?
    ➡️Big data
    ➡️AI/LLM applications
    ➡️container platforms
    ➡️databases

    Learn more: bit.ly/3F7d2sQ

    #DistributedData #DevOps #InfoQ

  19. The #opensource distributed storage system #CubeFS has reached graduation status!

    CubeFS supports multiple access protocols, including POSIX, HDFS, S3 & its own REST API.

    Its key platform targets?
    ➡️Big data
    ➡️AI/LLM applications
    ➡️container platforms
    ➡️databases

    Learn more: bit.ly/3F7d2sQ

    #DistributedData #DevOps #InfoQ

  20. The distributed storage system has reached graduation status!

    CubeFS supports multiple access protocols, including POSIX, HDFS, S3 & its own REST API.

    Its key platform targets?
    ➡️Big data
    ➡️AI/LLM applications
    ➡️container platforms
    ➡️databases

    Learn more: bit.ly/3F7d2sQ

  21. In our new #InfoQ #podcast, Deepthi Sigireddi dives deep into the architecture of cloud-native distributed databases, sharding, replication, and failover.

    🎧 Listen now 👉 bit.ly/3QRUXSD

    #CloudNativeArchitecture #Database #DistributedData #Sharding

  22. In our new #InfoQ #podcast, Deepthi Sigireddi dives deep into the architecture of cloud-native distributed databases, sharding, replication, and failover.

    🎧 Listen now 👉 bit.ly/3QRUXSD

    #CloudNativeArchitecture #Database #DistributedData #Sharding

  23. In our new #InfoQ #podcast, Deepthi Sigireddi dives deep into the architecture of cloud-native distributed databases, sharding, replication, and failover.

    🎧 Listen now 👉 bit.ly/3QRUXSD

    #CloudNativeArchitecture #Database #DistributedData #Sharding

  24. In our new #InfoQ #podcast, Deepthi Sigireddi dives deep into the architecture of cloud-native distributed databases, sharding, replication, and failover.

    🎧 Listen now 👉 bit.ly/3QRUXSD

    #CloudNativeArchitecture #Database #DistributedData #Sharding

  25. In our new , Deepthi Sigireddi dives deep into the architecture of cloud-native distributed databases, sharding, replication, and failover.

    🎧 Listen now 👉 bit.ly/3QRUXSD

  26. #ModConFlex #MSCA researcher Ziqi Wang is a co-author of "FedADMM-InSa: An Inexact and Self-Adaptive ADMM for Federated Learning" Federated learning (FL) emerges as a promising framework for #Learning from #DistributedData while preserving privacy. It is useful in the #WindEnergy sector. For instance, it enables #CollaborativeTraining of #WindPower #ForecastingModels among multiple #WindFarms, overcoming challenges associated with #DataPrivacy and #CommercialCompetition.

    arxiv.org/pdf/2402.13989.pdf

  27. #ModConFlex #MSCA researcher Ziqi Wang is a co-author of "FedADMM-InSa: An Inexact and Self-Adaptive ADMM for Federated Learning" Federated learning (FL) emerges as a promising framework for #Learning from #DistributedData while preserving privacy. It is useful in the #WindEnergy sector. For instance, it enables #CollaborativeTraining of #WindPower #ForecastingModels among multiple #WindFarms, overcoming challenges associated with #DataPrivacy and #CommercialCompetition.

    arxiv.org/pdf/2402.13989.pdf

  28. #ModConFlex #MSCA researcher Ziqi Wang is a co-author of "FedADMM-InSa: An Inexact and Self-Adaptive ADMM for Federated Learning" Federated learning (FL) emerges as a promising framework for #Learning from #DistributedData while preserving privacy. It is useful in the #WindEnergy sector. For instance, it enables #CollaborativeTraining of #WindPower #ForecastingModels among multiple #WindFarms, overcoming challenges associated with #DataPrivacy and #CommercialCompetition.

    arxiv.org/pdf/2402.13989.pdf

  29. Uncover the secrets of CacheFront – Uber’s innovative #caching solution for its in-house distributed database, Docstore!

    Learn how it achieves over 40M reads per second & significant latency reductions: bit.ly/3T0l7mf

    #InfoQ #DistributedCache #Database #SQL #DistributedData #ChangeDataCapture

  30. Uncover the secrets of CacheFront – Uber’s innovative #caching solution for its in-house distributed database, Docstore!

    Learn how it achieves over 40M reads per second & significant latency reductions: bit.ly/3T0l7mf

    #InfoQ #DistributedCache #Database #SQL #DistributedData #ChangeDataCapture

  31. Uncover the secrets of CacheFront – Uber’s innovative #caching solution for its in-house distributed database, Docstore!

    Learn how it achieves over 40M reads per second & significant latency reductions: bit.ly/3T0l7mf

    #InfoQ #DistributedCache #Database #SQL #DistributedData #ChangeDataCapture

  32. Uncover the secrets of CacheFront – Uber’s innovative #caching solution for its in-house distributed database, Docstore!

    Learn how it achieves over 40M reads per second & significant latency reductions: bit.ly/3T0l7mf

    #InfoQ #DistributedCache #Database #SQL #DistributedData #ChangeDataCapture

  33. Uncover the secrets of CacheFront – Uber’s innovative solution for its in-house distributed database, Docstore!

    Learn how it achieves over 40M reads per second & significant latency reductions: bit.ly/3T0l7mf

  34. Curious about #DistributedFileSystems?

    #InfoQ brings you an insightful article by Changjian Gao, exploring the design principles, innovations & challenges behind 3 representative systems:
    1️⃣ #GoogleFileSystem
    2️⃣ #Tectonic
    3️⃣ #JuiceFS

    Gain valuable insights: bit.ly/3pvnNxt

    #DistributedData #BigData

  35. Curious about #DistributedFileSystems?

    #InfoQ brings you an insightful article by Changjian Gao, exploring the design principles, innovations & challenges behind 3 representative systems:
    1️⃣ #GoogleFileSystem
    2️⃣ #Tectonic
    3️⃣ #JuiceFS

    Gain valuable insights: bit.ly/3pvnNxt

    #DistributedData #BigData

  36. Curious about #DistributedFileSystems?

    #InfoQ brings you an insightful article by Changjian Gao, exploring the design principles, innovations & challenges behind 3 representative systems:
    1️⃣ #GoogleFileSystem
    2️⃣ #Tectonic
    3️⃣ #JuiceFS

    Gain valuable insights: bit.ly/3pvnNxt

    #DistributedData #BigData

  37. Curious about #DistributedFileSystems?

    #InfoQ brings you an insightful article by Changjian Gao, exploring the design principles, innovations & challenges behind 3 representative systems:
    1️⃣ #GoogleFileSystem
    2️⃣ #Tectonic
    3️⃣ #JuiceFS

    Gain valuable insights: bit.ly/3pvnNxt

    #DistributedData #BigData

  38. Curious about ?

    brings you an insightful article by Changjian Gao, exploring the design principles, innovations & challenges behind 3 representative systems:
    1️⃣
    2️⃣
    3️⃣

    Gain valuable insights: bit.ly/3pvnNxt