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Leveraging Infrastructure as Code for Data Engineering Projects: A Comprehensive Guide

DZone

Data engineering projects often require the setup and management of complex infrastructures that support data processing, storage, and analysis. In this article, we will explore the benefits of leveraging IaC for data engineering projects and provide detailed implementation steps to get started.

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Building Resilience With Chaos Engineering and Litmus

DZone

The scalability, agility, and continuous delivery offered by microservices architecture make it a popular option for businesses today. Various factors, such as network communication, inter-service dependencies, external dependencies, and scalability issues, can contribute to outages.

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Building Netflix’s Distributed Tracing Infrastructure

The Netflix TechBlog

a Netflix member via Twitter This is an example of a question our on-call engineers need to answer to help resolve a member issue?—?which Now let’s look at how we designed the tracing infrastructure that powers Edgar. We needed to increase engineering productivity via distributed request tracing.

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How To Deploy the ELK Stack on Kubernetes

DZone

The ELK stack is an abbreviation for Elasticsearch, Logstash, and Kibana, which offers the following capabilities: Elasticsearch: a scalable search and analytics engine with a log analytics tool and application-formed database, perfect for data-driven applications.

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How Data Inspires Building a Scalable, Resilient and Secure Cloud Infrastructure At Netflix

The Netflix TechBlog

Netflix’s engineering culture is predicated on Freedom & Responsibility, the idea that everyone (and every team) at Netflix is entrusted with a core responsibility and they are free to operate with freedom to satisfy their mission. All these micro-services are currently operated in AWS cloud infrastructure.

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Unmatched scalability and security of Dynatrace extensions now available for all supported technologies: 7 reasons to migrate your JMX and Python plugins

Dynatrace

that offers security, scalability, and simplicity of use. already address SNMP, WMI, SQL databases, and Prometheus technologies, serving the monitoring needs of hundreds of Dynatrace customers. Python code also carries limited scalability and the burden of governing its security in production environments and lifecycle management.

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Observability engineering: Getting Prometheus metrics right for Kubernetes with Dynatrace and Kepler

Dynatrace

For busy site reliability engineers, ensuring system reliability, scalability, and overall health is an imperative that’s getting harder to achieve in ever-expanding, cloud-native, container-based environments. Because of its adaptability, Prometheus has become an essential tool for observability engineering.

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