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The Latest Data Engineering Topics

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Firebase vs. MongoDB: Which Database to Use for Your App Development
MongoDB vs. Firebase. A comparison between the best NoSQL databases to find the best one for your app development project.
Updated June 26, 2019
by Paresh Sagar
· 89,249 Views · 7 Likes
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An Angular PWA From Front-End to Backend: Kubernetes Deployment
This tutorial shows how to deploy a Angular PWA on a Kubernetes cluster with a Helm Chart.
June 26, 2019
by Sven Loesekann
· 14,388 Views · 2 Likes
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15 WPF Performance Tips for 2019
Even over a decade later, there is still plenty to say for Windows Presentation Foundation developers to make their apps more performant.
June 26, 2019
by Brian Lagunas
· 39,372 Views · 3 Likes
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Mitigate Slow HTTP GET/POST Vulnerabilities in the Apache HTTP Server
Learn how you can mitigate slow HTTP GET/POST vulnerabilities in the Apache HTTP Server.
June 26, 2019
by Ian Muscat
· 17,365 Views · 1 Like
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Microservice Best Practices: Build an Archetype
In this article, we focus on learning why creating proper archetypes is important for a successful microservices architecture.
June 26, 2019
by Ranga Karanam
· 18,743 Views · 6 Likes
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AWS Workflow With PyCharm
Avoid some of the snafus of creating a workflow using AWS Toolkits with this tutorial.
June 26, 2019
by Marco Christiani
· 11,210 Views · 3 Likes
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7 Strategies for Assigning Ids to Microservices
In this article, we'll discuss seven strategies for assigning Ids and their trade-offs.
June 25, 2019
by Victor Chircu
· 24,485 Views · 14 Likes
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Oracle vs. Snowflake
Take a look at Oracle vs. Snowflake from someone who has worked for both.
Updated June 25, 2019
by John Ryan
· 20,680 Views · 5 Likes
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The 4 AWS Pricing Principles with a Critical Eye
Amazon Web Services advertises four principles that guide their pricing strategy - pay as you go, pay less by using more, save when you reserve, and their free tier. These principles provide immense benefits and efficiencies for thousands of organizations, which has driven AWS’s stellar growth. But there are downsides as well. In this article we'll review the five principles and provide a grain of salt you should consider before hooking into the Amazon machine. Principle #1: Pay as You Go The Principle: This is the main idea behind AWS - instead of buying or building costly infrastructure, rent it. AWS is dedicated to turning your CapEx expenses into OpEx. It also provides extreme flexibility - you can order 1,000 machines for an hour and then stop them and pay only for those 1,000 machine hours. The Good: It’s why organizations started moving to the cloud. Pay per use is great because it eliminates overcapacity and wasted computing resources. The Bad: Flexibility comes at a cost. If you want to really “pay as you go”, you’ll have to settle for Amazon’s On-Demand Pricing, which becomes quite expensive even for small workloads, when used for ongoing server deployments. Truth be told, most servers don’t have huge peaks or troughs in their usage - and running them on dedicated hosting or on-prem will be a lot cheaper than on Amazon. Principle #2: Pay Less by Using More The Principle: AWS provides volume discounts. Amazon S3 and many other services offer tiered pricing, and Amazon EC2 offers volume discounts for users who spend more than $500,000 in upfront costs. Amazon also provides a plethora of services and options for most use cases, allowing you to switch to a service that meets your need at a lower cost. For example, there are several AWS backup options including the AWS Backup service and storage services like S3, Glacier, EBS, EFS, etc. Organizations can move data between these storage services to gain efficiencies. The Good: Sophisticated users of AWS can save a lot by dynamically moving workloads between services and creating economies of scale. The Bad: This principle is also one of the hidden reasons for Amazon’s enormous complexity. True - you can create a tiered storage strategy and save 90% or more in many cases. But do your engineers or IT staff know the intricacies of each data service, and have the know-how to detect the relevant events and store data selectively into different data stores? Amazon provides the tools to do all this. But it requires time and expertise which by itself costs organizations serious money. Principle #3: Save When You Reserve The Principle: At the core of AWS is its compute service, Amazon EC2. EC2 machine instances are substantially discounted (on the order of 30-50%) if you reserve an instance for 1-3 years in advance. Another option is to use “spot instances” - machine instances that happen to be available at a given time, and will be taken away from you when another user demands them. Switching loads dynamically between spot instances, and helping Amazon manage their demand, can give you even bigger discounts. The Good: Amazon provides a lot of price flexibility. You can significantly cut costs by committing to 1 years or more - it’s possible to do this selectively for some workloads, while using others on demand. The spot instances option is a creative one, which lets anyone with expertise, and the time to architect a spot instances solution, shave 60% off costs. The Bad: Committing to a machine instance for 1 to 3 years on the cloud might sound like an oxymoron. Organizations are moving to the cloud to get computing resources on demand. A long-term financial commitment flies in the face of this flexibility. Many AWS users take on-demand prices as a given, and pay the price of flexibility. Principle #4: Free Usage Tier The Principle: Amazon grants 1 year of free usage with generous quotas for many of its services, to reduce risk and encourage cloud adoption. This was a primary way AWS gained its initial market share in the early years. The Free Tier Grants (as of the time of this writing) 1 year of usage with 750 hours of EC2 instances, 750 hours of RDS usage (can run managed databases like MySQL), 5 GB on S3, 1 million requests on the cool serverless delivery platform Lambda, 50 GB storage on CloudFront (delivery network), 5GB on EFS (file storage), 30GB on EBS (block storage), 750 hours of ElasticSearch, and more. The Bad: The free tier has helped many organizations and technologists get “hooked” on Amazon’s offerings - it is a showcase of the astounding depth, breadth and technical excellence of their service profile. Amazon provides - and encourages - an enormous amount of sophistication within its ecosystem. It provides power, but power brings with it responsibility, overhead and a high cost of skills. Very often, organizations select AWS by default because it is a market leader and the option most well known by their teams. I can’t say the free tier is bad, but it has creatd an unfair advantage vs. other cloud offerings, which have their own strengths. Wrap Up AWS is great, but it is also a business and has established pricing that safeguards its interests. Carefully consider the benefits and tradeoffs of the Amazon pricing philosophy before entering a large-scale engagement. If you're already heavily engaged, plan your cloud consumption 1-2 years ahead and see if other cloud platforms - such as Azure or Google Cloud Platform - can give Amazon a run for its money.
Updated June 25, 2019
by Gilad David Maayan
· 23,170 Views · 2 Likes
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Develop a REST API in PHP
Feeling tired? Read on to get some REST.
June 25, 2019
by Aaron Parecki
· 34,691 Views · 3 Likes
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Inserting BLOB Values With SQL INSERT Statements
This article describes how to insert BLOB values as normal strings using INSERT statements.
June 25, 2019
by Mark Rules
· 56,280 Views · 4 Likes
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Microservice Architecture Best Practices: Messaging Queues
In this article, we discuss why queues are needed, and how they form the cornerstone of asynchronous communication in microservices architectures.
June 25, 2019
by Ranga Karanam
· 64,069 Views · 14 Likes
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Spring Boot: Metrics With Micrometer and AWS CloudWatch
Learn more about how to make Spring Boot work with Micrometer and AWS CloudWatch.
June 25, 2019
by Dawid Kublik
· 47,592 Views · 4 Likes
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Hibernate Bytecode Enhancement: Dirty Tracking
Take a look at how you can boost the performance of your Java bytecode in Hibernate using dirty tracking.
Updated June 24, 2019
by Nicolae Sirbu
· 15,849 Views · 6 Likes
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Monitoring Couchbase Sync Gateway With Prometheus and Grafana
Learn how to successfully setup monitoring with Prometheus and Grafana and drive replications with Couchbase Lite clients and monitor it.
June 24, 2019
by Priya Rajagopal
· 5,016 Views · 2 Likes
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Organizing My APIs Using OpenAPI Tags
It's time to get organized.
June 24, 2019
by Kin Lane
· 14,340 Views · 4 Likes
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NGINX Ingress Controller Configuration In AKS
Take a look at some of the different configurations NGINX's controller configuration.
June 24, 2019
by Ashwin Sebastian
· 35,946 Views · 5 Likes
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Spring Batch to Read From MongoDB and Generate XML Files
We take a look at how to use these two popular and open source database projects together to generate XML file versions of our data.
June 24, 2019
by Chaandan Banerjee
· 23,744 Views · 3 Likes
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Learn How to Secure Service-to-Service Microservices
You've built a microservices architecture, but have you secured your service-to-service communication? If not, read on to learn how!
June 24, 2019
by Matt Raible
· 56,908 Views · 23 Likes
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Microservices Best Practices: Why Build a Vertical Slice?
In this article, we look at what a vertical slice is, why we build it, some best practices involved in building vertical slices.
June 21, 2019
by Ranga Karanam
· 22,401 Views · 6 Likes
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