Docker and Kubernetes have taken the software world by storm. DevOps, containers, and container management are at the center of most conversations about what’s relevant to technology. Tooling and services that ease running software in containers, therefore, occupy the minds of developers. Great tools and platforms create options and possibilities. They also create challenges in understanding available choices, though.
Imagine a man, a metaphorical man, slumped over, sitting silently across from you. Do you see him? Hastily smashing his fingers against the keyboard with a feverish sweat running down his neck. He, like many, only opens his APM solution after those universally feared “oh shit!” moments. Like a firefighter with a magnifying glass, he dives into his logs looking for a needle in a haystack. But you… Well, you know better than that. You wouldn’t just use your APM on bad days.
AWS Lambda is a service that confuses many people. For that reason, you may be wondering just how it works, and how you’d use it to build a highly scalable event-driven application. As someone who’s presumably no stranger to the internet, you must have seen the terms serverless, function-as-a-service, or AWS Lambda thrown across your screen a few times. Perhaps you’re looking to learn more. If so, you’re in luck.
So you want a faster application? If you’ve not heard of a flamegraph, it can be a great way to improve and gain insight into your application performance. Today, we’ll explain what a flamegraph is. We’ll cover the stack trace and its origin, the call stack. Finally, we’ll define the flame graph and show how to leverage it for improving the performance of your application. Sound good? Let’s get to it. Before we get to what a flamegraph is, we need to discuss stack traces.
A great thing about building applications for the internet is that people from all around the world can benefit from your effort. You can gather new users from Taiwan to Colorado and meet their needs just as effectively. In this global context, it can be good to provide your users with local flavor to help them feel connected to you and your applications. It can also be useful for you to know where your users are coming from to make sure that your infrastructure is configured in the best way.
The introduction of Google Maps in 2005 changed the way we think about the internet. It’s hard to remember now, but there was a time where the internet was disconnected from the physical world. You might find a business’s website, and if you were lucky, they’d have an address included. A national chain of restaurants or grocery stores probably wouldn’t be able to tell you their nearest location to your home. All of that has changed, today.
In this post, we’ll learn what Amazon Web Services (AWS) Lambda is, and why it might be a good idea to use for your next project. For a more in-depth introduction to serverless and Lambda, read AWS Lambda: Your Quick Start Guide to Going Serverless. In order to show how useful Lambda can be, we’ll walk through creating a simple Lambda function using the Python programming language. We’ll test it out, as well as take a look at what Lambda provides for metrics and logging.
Ruby, like most other modern, high-level programming languages, doesn’t force you to manage memory. This feature is called garbage collection, or GC, and you get it for free in Ruby. You can write tons of Ruby code and never give a second thought to the fact that under the covers, Ruby is doing a bang-up job of allocating and freeing memory for your code to use. But it certainly couldn’t hurt to learn something about how Ruby garbage collection works.
