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Netflix’s Distributed Counter Abstraction

The Netflix TechBlog

After selecting a mode, users can interact with APIs without needing to worry about the underlying storage mechanisms and counting methods. Let’s examine some of the drawbacks of this approach: Lack of Idempotency : There is no idempotency key baked into the storage data-model preventing users from safely retrying requests.

Latency 251
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What is Greenplum Database? Intro to the Big Data Database

Scalegrid

It can scale towards a multi-petabyte level data workload without a single issue, and it allows access to a cluster of powerful servers that will work together within a single SQL interface where you can view all of the data. The Greenplum Architecture. The Greenplum Architecture. Greenplum Architectural Design.

Big Data 321
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RabbitMQ vs. Kafka: Key Differences

Scalegrid

This article outlines the key differences in architecture, performance, and use cases to help determine the best fit for your workload. RabbitMQ follows a message broker model with advanced routing, while Kafkas event streaming architecture uses partitioned logs for distributed processing. What is RabbitMQ? What is Apache Kafka?

Latency 147
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AWS serverless services: Exploring your options

Dynatrace

To get a better understanding of AWS serverless, we’ll first explore the basics of serverless architectures, review AWS serverless offerings, and explore common use cases. Serverless architecture: A primer. Serverless architecture shifts application hosting functions away from local servers onto those managed by providers.

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Introducing Impressions at Netflix

The Netflix TechBlog

Architecture Overview The first pivotal step in managing impressions begins with the creation of a Source-of-Truth (SOT) dataset. These events are promptly relayed from the client side to our servers, entering a centralized event processing queue. This queue ensures we are consistently capturing raw events from our global userbase.

Tuning 166
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How to observe logs with Journald and Dynatrace

Dynatrace

The Grail architecture ensures scalability, making log data accessible for detailed analysis regardless of volume. Dynatrace Grail lets you focus on extracting insights rather than managing complex schemas or index and storage concepts. With real-time analysis, you gain faster data-driven decisions and simplified data ingestion.

Analytics 147
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Time Series Analysis: VAR-Model-As-A-Service Using Flask and MinIO

DZone

It is the second of a series of articles that is built on top of that project, representing experiments with various statistical and machine learning models, data pipelines implemented using existing DAG tools, and storage services, both cloud-based and alternative on-premises solutions.

Storage 264