Remove Data Remove Data Engineering Remove Engineering Remove Monitoring
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SIEM Volume Spike Alerts Using ML

DZone

SIEM platforms offer centralized management of security operations, making it easier for organizations to monitor, manage, and secure their IT infrastructure. SIEM systems enable early detection of security threats and suspicious activities by analyzing vast amounts of log data in real time.

Storage 145
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3. Psyberg: Automated end to end catch up

The Netflix TechBlog

In the previous installments of this series, we introduced Psyberg and delved into its core operational modes: Stateless and Stateful Data Processing. Pipelines After Psyberg Let’s explore how different modes of Psyberg could help with a multistep data pipeline. Audit Run various quality checks on the staged data.

Tuning 244
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Supporting Diverse ML Systems at Netflix

The Netflix TechBlog

Berg , Romain Cledat , Kayla Seeley , Shashank Srikanth , Chaoying Wang , Darin Yu Netflix uses data science and machine learning across all facets of the company, powering a wide range of business applications from our internal infrastructure and content demand modeling to media understanding.

Systems 226
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Data Pipelines: The Hammer for Every Nail

Abhishek Tiwari

In the era of big data and complex data processing, data pipelines have emerged as a popular solution for managing and manipulating data. They provide a systematic approach to extract, transform, and load (ETL) data from various sources, enabling organizations to derive valuable insights.

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Your technology architecture and engineering organization should coevolve as your startup grows

Abhishek Tiwari

The evolution of your technology architecture should depend on the size, culture, and skill set of your engineering organization. There are no hard-and-fast rules to figure out interdependency between technology architecture and engineering organization but below is what I think can really work well for product startup. Caveats ?:

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What is IT automation?

Dynatrace

Scripts and procedures usually focus on a particular task, such as deploying a new microservice to a Kubernetes cluster, implementing data retention policies on archived files in the cloud, or running a vulnerability scanner over code before it’s deployed. Monitoring and logging are fundamental building blocks of observability.

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Friends don't let friends build data pipelines

Abhishek Tiwari

Building data pipelines can offer strategic advantages to the business. Often companies underestimate the necessary effort and cost involved to build and maintain data pipelines. Data pipeline initiatives are generally unfinished projects. In this post, we will discuss why you should avoid building data pipelines in first place.

Latency 63