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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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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.

Metrics 180
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Storage Autoscaling With Percona Operator for MongoDB

Percona

Previously, deploying and maintaining a database usually meant many burdensome chores and repetitive tasks to ensure proper functioning. In the cloud era, however, developers and operation engineers started fully embracing automation tools making their job significantly easier. kubectl annotate pvc --all resize.topolvm.io/storage_limit="100Gi"

Storage 112
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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.

Analytics 255
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Making it Easier to Manage a Production PostgreSQL Database

Scalegrid

PostgreSQL is an amazing relational database. However, beyond just the features, there are other important aspects of a database that need to be considered. However, beyond just the features, there are other important aspects of a database that need to be considered. Feature-wise, it is up there with the best, if not the best.

Database 184
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Improved Alerting with Atlas Streaming Eval

The Netflix TechBlog

Ruchir Jha , Brian Harrington , Yingwu Zhao TL;DR Streaming alert evaluation scales much better than the traditional approach of polling time-series databases. It allows us to overcome high dimensionality/cardinality limitations of the time-series database. Engineers want their alerting system to be realtime, reliable, and actionable.

Storage 288
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Designing Instagram

High Scalability

Machine Learning Engineer at Amazon and has led several machine-learning initiatives across the Amazon ecosystem. FUN FACT : In this talk , Rodrigo Schmidt, director of engineering at Instagram talks about the different challenges they have faced in scaling the data infrastructure at Instagram. This is a guest post by Ankit Sirmorya.

Design 334