[Kappa architecture]
Kappa Architecture is a software architecture pattern. Rather than using a relational DB like SQL or a key-value store like Cassandra, the canonical data store in a Kappa Architecture system is an append-only immutable log. From the log, data is streamed through a computational system and fed into auxiliary stores for serving.
Kappa Architecture is a simplification of Lambda Architecture. A Kappa Architecture system is like a Lambda Architecture system with the batch processing system removed. To replace batch processing, data is simply fed through the streaming system quickly.
Repository dedicated to Kappa Architecture.
http://milinda.pathirage.org/kappa-architecture.com/
Kappa Architecture is a software architecture pattern. Rather than using a relational DB like SQL or a key-value store like Cassandra, the canonical data store in a Kappa Architecture system is an append-only immutable log. From the log, data is streamed through a computational system and fed into auxiliary stores for serving.
Kappa Architecture is a simplification of Lambda Architecture. A Kappa Architecture system is like a Lambda Architecture system with the batch processing system removed. To replace batch processing, data is simply fed through the streaming system quickly.
Repository dedicated to Kappa Architecture.
http://milinda.pathirage.org/kappa-architecture.com/
[Paper][Data lake]
Delta Lake: High-Performance ACID Table Storage over Cloud Object Stores
Delta Lake is an open source ACID table storage layer over cloud object stores initially developed at Databricks. Delta Lake uses a transaction log that is compacted into Apache Parquet format to provide ACID properties, time travel, and significantly faster metadata operations for large tabular datasets (e.g., the ability to quickly search billions of table partitions for those relevant to a query).
https://databricks.com/wp-content/uploads/2020/08/p975-armbrust.pdf
Delta Lake: High-Performance ACID Table Storage over Cloud Object Stores
Delta Lake is an open source ACID table storage layer over cloud object stores initially developed at Databricks. Delta Lake uses a transaction log that is compacted into Apache Parquet format to provide ACID properties, time travel, and significantly faster metadata operations for large tabular datasets (e.g., the ability to quickly search billions of table partitions for those relevant to a query).
https://databricks.com/wp-content/uploads/2020/08/p975-armbrust.pdf
[Article]
READING GROUP. PROTEAN: VM ALLOCATION SERVICE AT SCALE
This paper from Microsoft is full of technical insights into how they operate their datacenters/regions at scale. In particular, the paper discusses one of the fundamental components of any cloud provider — the VM service. The system, called Protean, is an allocation service that handles VM allocation requests
http://charap.co/reading-group-protean-vm-allocation-service-at-scale/
READING GROUP. PROTEAN: VM ALLOCATION SERVICE AT SCALE
This paper from Microsoft is full of technical insights into how they operate their datacenters/regions at scale. In particular, the paper discusses one of the fundamental components of any cloud provider — the VM service. The system, called Protean, is an allocation service that handles VM allocation requests
http://charap.co/reading-group-protean-vm-allocation-service-at-scale/
[Article]
Federated Quantum Machine Learning
Distributed training across several quantum computers could significantly improve the training
time and if we could share the learned model, not the data, it could potentially improve the
data privacy as the training would happen where the data is located. However, to the best of
our knowledge, no work has been done in quantum machine learning (QML) in federation setting
yet. In this work, we present the federated training on hybrid quantum-classical machine learning
models although our framework could be generalized to pure quantum machine learning model…
https://arxiv.org/pdf/2103.12010v1.pdf
Federated Quantum Machine Learning
Distributed training across several quantum computers could significantly improve the training
time and if we could share the learned model, not the data, it could potentially improve the
data privacy as the training would happen where the data is located. However, to the best of
our knowledge, no work has been done in quantum machine learning (QML) in federation setting
yet. In this work, we present the federated training on hybrid quantum-classical machine learning
models although our framework could be generalized to pure quantum machine learning model…
https://arxiv.org/pdf/2103.12010v1.pdf
[Article]
Introduction to modern network load balancing and proxying
https://blog.envoyproxy.io/introduction-to-modern-network-load-balancing-and-proxying-a57f6ff80236
Introduction to modern network load balancing and proxying
https://blog.envoyproxy.io/introduction-to-modern-network-load-balancing-and-proxying-a57f6ff80236
Medium
Introduction to modern network load balancing and proxying
It was brought to my attention recently that there is a dearth of introductory educational material available about modern network load…
[Article]
Internal consistency in streaming systems
https://scattered-thoughts.net/writing/internal-consistency-in-streaming-systems/
Internal consistency in streaming systems
https://scattered-thoughts.net/writing/internal-consistency-in-streaming-systems/
[Article]
Evolving reinforcement learning
http://ai.googleblog.com/2021/04/evolving-reinforcement-learning.html
Evolving reinforcement learning
http://ai.googleblog.com/2021/04/evolving-reinforcement-learning.html
research.google
Evolving Reinforcement Learning Algorithms
Posted by John D. Co-Reyes, Research Intern and Yingjie Miao, Senior Software Engineer, Google Research A long-term, overarching goal of research i...
[Article]
This article looks at a few approaches Amazon has taken to manage API requests to its systems to avoid overload by implementing API rate limiting (also referred to as “throttling” or "admission control”).
https://aws.amazon.com/builders-library/fairness-in-multi-tenant-systems/
This article looks at a few approaches Amazon has taken to manage API requests to its systems to avoid overload by implementing API rate limiting (also referred to as “throttling” or "admission control”).
https://aws.amazon.com/builders-library/fairness-in-multi-tenant-systems/
Amazon
Fairness in multi-tenant systems
Building fairness into multitenant systems to provide predictable performance and availability
Forwarded from GitHub repos
GoodManWEN/GoodManWEN.github.io
A website simulating linux system's GUI, using theme of Deepin distro.
Language: Vue
#blog #deepin #tailwindcss #vue
Stars: 202 Issues: 0 Forks: 12
https://github.com/GoodManWEN/GoodManWEN.github.io
A website simulating linux system's GUI, using theme of Deepin distro.
Language: Vue
#blog #deepin #tailwindcss #vue
Stars: 202 Issues: 0 Forks: 12
https://github.com/GoodManWEN/GoodManWEN.github.io
GitHub
GitHub - GoodManWEN/GoodManWEN.github.io: 📕 A website simulating linux system's GUI, using theme of Deepin distro. 网页模拟桌面
📕 A website simulating linux system's GUI, using theme of Deepin distro. 网页模拟桌面 - GoodManWEN/GoodManWEN.github.io
[Article]
Reliability Testing for Natural Language Processing Systems
https://arxiv.org/abs/2105.02590
Reliability Testing for Natural Language Processing Systems
https://arxiv.org/abs/2105.02590