InfoQ Homepage Infrastructure Content on InfoQ
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Writing a Kubernetes Autoscaler with Groovy and Spring Boot
Ray Tsang shares his experience in writing a custom metrics collector plus an autoscaler using Groovy and Spring Boot, deployed as containerized microservices in Kubernetes.
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The Lego Model for Machine Learning Pipelines
Leah McGuire describes the machine learning platform Salesforce wrote on top of Spark to modularize data cleaning and feature engineering.
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Enterprise Architecture in a Heterogeneous Environment
Dustin Hudson discusses enterprise architecture using case studies and life examples to illustrate how to put together legacy systems and third-party apps while considering user-driven decisions.
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LinkedIn's Active/Active Evolution
Erran Berger discusses how they scaled architecture at LinkedIn across multiple data centers.
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How Netflix Directs 1/3rd of Internet Traffic
Haley Tucker and Mohit Vora discuss the architecture at Netflix that makes streaming happen, while highlighting interesting lessons and design patterns that can be widely applied.
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The future of Agile in the Enterprise
The panelists, Alisa Bowen, Pete Steel, Cameron Gough, Lachlan Heasman (moderator), discuss the current status and the future of Agile in the enterprise.
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Building and Tuning High Performance Java Platforms
Emad Benjamin covers various GC tuning techniques and how to best build platform engineered systems; in particular the focus is on tuning large scale JVM deployments.
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Orchestrating Containers with Terraform and Consul
Mitchell Hashimoto shows how Terraform and Consul can be used together to easily deploy and scale large-scale containerized workloads using container runtimes like Docker.
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Bringing javax.cache'ing to your Application
Chris Dennis and Alex Snaps discuss introducing caching into a Spring application to solve real world problems.
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Workers, Queues, and Cache
Jason McCreary takes a look at using background job processes, messaging queues, and cache to help an application scale.
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Tuning Java for Big Data
Scott Seighman discusses causes of common performance issues in Big Data environments, heap size, garbage collection, JVM reuse tuning guidelines and Big Data performance analysis tools.
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20 Minutes from Ticket to Production. Zero Downtime.
Paul Payne explains the benefits of containerization of a Go web service, discussing testing, integration, canary deploys and how they achieve 20 minute development cycles with zero downtime.
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