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LinkedIn Migrates Espresso to HTTP2 and Reduces Connections by 88% and Latency by 75%

InfoQ

LinkedIn was able to dramatically improve the scalability and performance of its Espresso database by migrating it from HTTP1.1 to HTTP2, resulting in a reduction in the number of connections, latency, and garbage collection times. By Rafal Gancarz

Latency 99
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Scalable Annotation Service?—?Marken

The Netflix TechBlog

The service should be able to serve real-time, aka UI, applications so CRUD and search operations should be achieved with low latency. A data model in Marken can be described using schema — just like how we create schemas for database tables etc. The databases we pick should be able to scale horizontally.

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Dynatrace accelerates business transformation with new AI observability solution

Dynatrace

This blog post explores how AI observability enables organizations to predict and control costs, performance, and data reliability. Figure 1: Sample RAG architecture While this approach significantly improves the response quality of GenAI applications, it also introduces new challenges.

Cache 204
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Front-End: Cache Strategies You Should Know

DZone

It is a transversal component that applies to all the tech areas and architecture layers such as operating systems, data platforms, backend, frontend, and other components. It is a transparent layer for the data consumer in terms of user usability except to improve performance.

Cache 141
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Datadog Creates Scalable Data Ingestion Architecture

InfoQ

Datadog created a dedicated data ingestion architecture offering exactly-once semantics for their third-generation event store, Husky. The event-driven architecture (EDA) can accommodate bursts in traffic in the multi-tenant platform with reasonable ingestion latency and acceptable operational costs. By Rafal Gancarz

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Presentation: Azure Cosmos DB: Low Latency and High Availability at Planet Scale

InfoQ

Mei-Chin Tsai, Vinod discuss the internal architecture of Azure Cosmos DB and how it achieves high availability, low latency, and scalability. By Mei-Chin Tsai, Vinod Sridharan

Latency 52
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Improved Alerting with Atlas Streaming Eval

The Netflix TechBlog

Ruchir Jha , Brian Harrington , Yingwu Zhao TL;DR Streaming alert evaluation scales much better than the traditional approach of polling time-series databases. It allows us to overcome high dimensionality/cardinality limitations of the time-series database. It opens doors to support more exciting use-cases. OK, Results?

Storage 288