Remove designing-event-driven-systems
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Enhancing Distributed System Load Shedding with TCP Congestion Control Algorithm

Zalando Engineering

But our system is event driven, all requests we process are delivered as events via Nakadi. We know if our system runs within its normal limits that we meet our SLOs. If we would control the ingestion of message requests into our system we would be able to process the task in a timely manner.

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How Systems Thinking Can Be Applied To Agile Transformations

Knowledge Hut

Applying systems thinking views a system as a set of interconnected and interdependent components defined by its limits and more than the sum of their parts (subsystems). When one component of a system is altered, the effects frequently spread across the entire system. are the main objectives of systems thinking.

Systems 98
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The Stream Processing Model Behind Google Cloud Dataflow

Towards Data Science

Implementation and designs of the model. The processing system must also be simple and flexible to adapt to the business’s complexity. They also require a system that can handle global-scale data since the Internet allows companies to reach more customers than ever. Where in event time they are being computed.

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How to trigger a spark job from AWS Lambda

Start Data Engineering

Event driven pipelines Lambda function to trigger spark jobs Setup and run Monitoring and logging Teardown Conclusion Further reading References Event driven pipelines Event driven systems represent a software design pattern where a logic is executed in response to an event.

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Automating Dynamic Table Creation with Event Logging

Cloudyard

This blog post showcases a novel approach combining Snowflake’s Event Logging and Dynamic Tables to automate the creation and population of dynamic tables based on Copy operations. Event-Driven Logging The journey begins with an innovative approach to log and monitor data copy operations.

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Data Engineering Weekly #165

Data Engineering Weekly

The challenge multiplies when designing a singular AI/ML system amid rapid application and model advancements, from XGboost to deep learning recommendation and large language models. The Netflix blog emphasizes the importance of finding the zombie data and the system design around deleting unused data.

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Leveraging Flink to Detect User Sessions and Engage DoorDash Consumers with Real-Time Notifications

DoorDash Engineering

To do this, we built a large stateful Flink job to track user sessions using mobile/web client events. We delve here into the different options we considered, why we believe our new design is most efficient, and what we have learned as we implemented this solution. This new solution has yielded significant conversion improvements.