What Are Containers? A Simple Guide to Containerization and How Docker Works

Docker is awesome. It enables software developers to package, ship and run their applications anywhere without having to worry about setup or dependencies. Combined with Kubernetes, it becomes even more powerful for streamlining cluster deployments and management. I digress. Back to Docker. Docker is loved by software developers and its adoption rate has been remarkable.

So what exactly is Docker?

It’s a platform for building, testing, deploying and publishing containerized applications. I say platform because Docker is a set of tools for managing all-things related to containers. Containers are at the heart of Docker so that’s what we’re going to explore in depth next.

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YAGNI, Cargo Cult and Overengineering - the Planes Won't Land Just Because You Built a Runway in Your Backyard

It was April. Year was probably was 2010. The cold, snowy winter was finally coming to an end and the spring was almost in the air. I was preparing for my final exams. The review lectures were going on for the RDBMS course that I was enrolled in at my university.

uofc

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Caching Strategies and How to Choose the Right One

Caching is one of the easiest ways to increase system performance. Databases can be slow (yes even the NoSQL ones) and as you already know, speed is the name of the game.

speed-matters

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Basics of Java Garbage Collection

  • Knock, knock.
  • Who’s there?
  • …long GC pause…
  • Java.

wiseguy-eh

It’s an old joke from the time when Java was new and slow compared to other languages. Over time, Java became a lot faster. Today it powers many real-time applications with hundreds of thousands of concurrent users. These days, the biggest impact on Java’s performance comes from its garbage collection. Fortunately, in many cases, it can be tweaked and optimized to improve performance.

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Message Batching to Increase Throughput and Reduce Costs

A while ago, I was working on a backend system on the AWS cloud. Individual services in the system communicated by exchanging asynchronous messages with each other using Amazon SQS. During early stages of development, we ran small load tests and found that CPU use was high and we would need more servers to handle the load. (Estimated peak load was 50,000 requests per second.) Services were generating lots of small messages every second and the profiler showed that threads responsible for handling and sending messages to SQS, one message at a time, were using CPU more than they should. This was affecting performance and throughput.

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