You’ve already used PHP streams in your PHP development. However, they’re transparent, so you may not have noticed them. Streams are powerful tools. In this article, you’ll learn to harness the power of streams in your PHP development and take your applications to the next level. Streams provide on-demand access to data. This means you don’t need to load the entire contents of your dataset into memory before processing can start.
Python is a powerful and versatile higher-order programming language. Whether you’re developing a web application or working with machine learning, this language has you covered. Python does well at optimizing developer productivity. You can quickly create a program that solves a business problem or fills a practical need. However, the solutions you reach when developing quickly aren’t always optimized for python performance.
The last decade has ushered in a golden era of software engineering. The rise of cloud computing freed companies from managing their own data centers and provided on-demand scaling. These services allow for provisioning servers on the fly using configuration and code. Treating that task as just another type of software development led to the advent of DevOps.
The shift to cloud computing and the DevOps revolution have fueled some important changes in the way we think about software development and monitoring. It has delivered huge benefits to the companies that have fully embraced the approach. In fact, the DevOps Research and Assessment (DORA) 2018 industry survey found a new small group of “elite” performers that are deploying code far more often and having a far better mean time to resolution (MTTR) than the next closest group.
Mean time to resolution (MTTR) is defined as the sum of the total amount of time that service was interrupted divided by the number of individual incidents. The unit of measurement is some quantity of time. Ideally, you can use minutes as the unit. That is, unless you blacked out the eastern seaboard for weeks!
Docker has changed the way we build, package, and deploy applications. But this concept of packaging apps in containers isn’t new—it was in existence long before Docker. Docker just made container technology easy for people to use. This is why Docker is a must-have in most development workflows today. Most likely, your dream company is using Docker right now. Docker’s official documentation has a lot of moving parts. Honestly, it can be overwhelming at first.
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.
