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DevOps automation: From event-driven automation to answer-driven automation [with causal AI]

Dynatrace

In the world of DevOps and SRE, DevOps automation answers the undeniable need for efficiency and scalability. This evolution in automation, referred to as answer-driven automation, empowers teams to address complex issues in real time, optimize workflows, and enhance overall operational efficiency.

DevOps 225
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So many bad takes?—?What is there to learn from the Prime Video microservices to monolith story

Adrian Cockcroft

I don’t advocate “Serverless Only”, and I recommended that if you need sustained high traffic, low latency and higher efficiency, then you should re-implement your rapid prototype as a continuously running autoscaled container, as part of a larger serverless event driven architecture, which is what they did.

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Should You Use ClickHouse as a Main Operational Database?

Percona

What if we use ClickHouse (which is a columnar analytical database) as our main datastore? Well, typically, an analytical database is not a replacement for a transactional or key/value datastore. However, ClickHouse is super efficient for timeseries and provides “sharding” out of the box (scalability beyond one node).

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Egnyte Architecture: Lessons learned in building and scaling a multi petabyte content platform

High Scalability

Egnyte is a secure Content Collaboration and Data Governance platform, founded in 2007 when Google drive wasn't born and AWS S3 was cost-prohibitive. In 2007, businesses had started to become more distributed; customers were using multiple devices to access their files and there was a need to make this experience as smooth as possible.

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Data Mining Problems in Retail

Highly Scalable

most of them are structured as data scientist manuals focusing on algorithms and methodologies and assume that human decisions play a central role in transforming analytical findings into business actions. This framework will later be used to describe analytical problems in a more uniform way.

Retail 152
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Rebuilding Netflix Video Processing Pipeline with Microservices

The Netflix TechBlog

The Netflix video processing pipeline went live with the launch of our streaming service in 2007. Future blogs will provide deeper dives into each service, sharing insights and lessons learned from this process.