February 5th, 2020
Unit, Integration, and Snapshot Testing in React with Jest and Enzyme
In an article last fall I spoke about my change in mindset towards unit testing. In my early programming days I thought unit tests slowed down development to a fault. Nowadays they are mandatory in all my applications. Unit tests are assertions that a unit of code is working as expected in isolation of other components in the codebase. They promote code review, help catch recurring bugs, and ease the burden of upgrading and switching technologies.
For React applications, the de facto testing framework is Jest. Jest was written by Facebook with React unit testing in mind, making it a natural fit. Alongside Jest, Enzyme is used to test React components. Enzyme was created by AirBnB to render components for testing. It provides an API to traverse the rendered DOM nodes in a component and hook into stateful component instances.
January 31st, 2020
Exploring New Features in React 16.3
When I was interviewing for jobs in the fall, one interviewer asked me if I had React 16 experience. I said "yes", figuring I must have worked on React 16 features during my year and a half experience. I've worked with React since I created a React and Webpack seed application in March 2018. Since then I wrote jarombek.com (the website you are currently viewing) in React along with contributing to a client-facing React application for seven months at my job.
As the interview questions rolled on, it became obvious that I wasn't utilizing the latest React features. Luckily I aced the coding assignment and other technology questions, so the interview ended up going well.
December 28th, 2019
Basic Elasticsearch Queries
Elasticsearch is a search and analytics engine. It's also a NoSQL database that holds JSON documents. These documents are stored in an inverted index and are queried with JSON syntax. In my previous article I explored analyzers and the process of storing documents in an inverted index. This article focuses on querying documents with JSON.
November 10th, 2019
The Basics of Programming Language Garbage Collection
While reading a book on C#, I came across a section about garbage collection. I always knew that programming languages such as Java performed garbage collection, but I never researched how garbage collectors (GCs) worked. The book mentioned that C# uses a tracing GC with generations and marking. These were foreign concepts to me, so I decided to conduct additional research on the topic. This article gives a high-level overview of garbage collectors and the APIs available to interact with them in Java and C#.
October 28th, 2019
Unit Testing AWS Infrastructure with Python
From October 2018 to May 2019, I moved the infrastructure for both my websites to AWS. The process for building and tearing down this infrastructure is automated with IaC, specifically Terraform. I've had a lot of fun working with Terraform and learning the different design patterns for infrastructure in the cloud.
After my infrastructure was built, I realized I needed a way to test that my IaC was behaving as expected. The obvious solution to this requirement was a unit test suite. I implemented this unit test suite in Python with the help of the AWS SDK. This article explains why I took the time to write unit tests and walks through of the basics of testing AWS infrastructure in Python.
October 18th, 2019
Writing Elasticsearch Analyzers
One of the biggest strengths of Elasticsearch is text searching. Elasticsearch holds strings for text searching in
text data types. A document can contain one or more fields of type
When strings are placed into a field of type
text they are processed by an analyzer. Elasticsearch analyzers can be viewed as a pipeline that takes text as an input, breaks it into terms, and returns the terms as output1. These terms are placed in an inverted index which makes an index searchable.
September 30th, 2019
Integrated Queries with LINQ and SQL Server
My previous article explored LINQ, a module that brings query syntax to C#. All the examples in that article queried local data structures. While using LINQ on local data is valuable in itself, LINQ can do much more. LINQ really shines when used to query remote data sources. Queries on remote data sources such as relational databases are known as integrated queries. In this article, I explore integrated queries with a SQL Server database. First I create the SQL Server database instance with Docker and then query it using LINQ.
September 17th, 2019
Using LINQ in C#
During free time at work, I've been reading a book called C# 7.0 In a Nutshell. When I get home, I write C# programs based on what I learned. One of the really interesting topics I read about was LINQ (Language Integrated Query), which is the integration of query functions and keywords in the C# language1. LINQ can be used to query remote data sources such as an RDBMS or local data structures.
LINQ reminds me of writing PL/SQL, which is a procedural language provided for the Oracle database. PL/SQL is a superset of SQL, allowing for looping, variable declarations, conditional logic, error handling, and more. The best feature of PL/SQL is the integration of SQL queries directly into an imperative programming language. Unfortunately, PL/SQL is strictly tied to the Oracle database and has clunky syntax in my opinion. LINQ on the other hand can be used with multiple different databases along with local data structures. Also, in my opinion, C# has much nicer syntax.
September 15th, 2019
Introduction to Elasticsearch
Over the past few months I've read a book about the ELK stack. ELK stands for Elasticsearch, Logstash, and Kibana. Together these three technologies provide the ability to search, stream, and visualize data. In this article I discuss Elasticsearch, which is the core technology of ELK Stack. First I'll define Elasticsearch and provide details about what its used for. Second I'll create AWS infrastructure for Elasticsearch using Amazon Elasticsearch Service. Third and finally I'll populate Elasticsearch with data and show some basic queries.
September 5th, 2019
AWS Lambda Function for MySQL RDS Backups Part II: Building the Function
In my previous article I discussed my existing AWS infrastructure and the additional resources needed to automate backups for a RDS MySQL instance using a lambda function. In this article I'll create those additional resources and further explain my design decisions. Finally, I'll test the lambda function and show the backup file in my S3 bucket.
September 3rd, 2019
AWS Lambda Function for MySQL RDS Backups Part I: VPC Infrastructure
When working with Amazon RDS (Relational Database Service) or any other database, creating backups of your data is an important safety precaution. The data of an application is often its most important asset, and if its lost or damaged the app is rendered useless. With RDS, Amazon provides a backup mechanism called snapshots. Snapshots backup the database instance and allow users to restore their RDS instance from a snapshot1.
Internally snapshots are stored in an Amazon S3 (Simple Storage Service) bucket. However, these backups aren't accessible through S3, since the bucket is hidden from the users AWS account2. The only way to see snapshots is through the RDS service. Also, snapshots aren't downloadable and their contents can't be viewed. This poses some serious limitations when trying to test a database backup.
August 24th, 2019
Last summer, I wrote an article about CSS Grid. CSS Grid is a new web page layout module introduced in 2017. Today I'm writing about Flexbox, another new web page layout module released to new browsers in 20171. While CSS Grid is a two-dimensional system used to create rigid layouts, Flexbox is a one-dimensional system used to create flexible layouts with dynamic resizing of elements. Let's go over the basics!