Five worthy reads is a regular column on five noteworthy items we’ve discovered while researching trending and timeless topics. This week, we discuss the growing concern about ransomware-as-a-service among organisations across the globe.
Spark is known as a fast general-purpose cluster-computing framework for processing big data. In this post, we’re going to cover how Spark works under the hood and the things you need to know to be able to effectively perform distributing machine learning using PySpark. The post assumes basic familiarity with Python and the concepts of machine learning like regression, gradient descent, etc.
MITRE ATT&CK is a comprehensive knowledge base and complex framework of over 200 techniques that adversaries may use over the course of an attack. While MITRE’s full ATT&CK framework is publicly available, it can be characterized into 3 key elements.
At LogicMonitor, we talk to customers and prospects constantly. This enables us to observe trends in requests for new features and functionality. There are two major topics that prospects and customers have been raising recently.
Cloud computing, containerization, and container orchestration are the most important trends in DevOps. Whether you’re a data scientist, software developer, or product manager, it’s good to know Docker and Kubernetes basics. Both technologies help you collaborate with others, deploy your projects, and increase your value to employers. In this article, we’ll cover essential Kubernetes concepts. There are a lot of Kubernetes terms, which can make it intimidating.
If you’re thinking about using containers to manage an application, there are a lot of options for technologies to use. It can be difficult to even know where to begin to make a decision. One common question is whether someone should use Docker vs Kubernetes for managing their application containers. This is a misleading question. In truth, Docker and Kubernetes aren’t competing technologies. There’s no need for them to face off.
In the last post, Samuell (from the og-aws Slack group) figured out his negative TTL problems in Cloudfront. During that session, we actually solved two different problems. This post is to finish off that conversation and address the other problem, which was how to use the default error page in Cloudfront.
So you want to A/B test your web app. The idea is simple, but the details can get messy, and you don’t want to re-invent the wheel. Services like Optimizely are pretty good, but they can be expensive and full of features you don’t need immediately. In this post, we’ll share how Sentry wrote an experimentation system with minimal work.
Welcome to the second edition of Serverless from the Trenches, our series of bite-sized blog posts aimed at developers and DevOps working in serverless. Each article will focus on a different technique or tool to solve a real-world problem and – hopefully – help make your work in serverless more productive. This week we look at how to add Cognito to your integration tests flow, making for true black box testing.
One of the most common questions we get at Honeycomb is about how to control costs while still achieving the level of observability needed to debug, troubleshoot, and understand what is happening in production. Historically, the answer from most vendors has been to aggregate your data–to offer you calculated medians, means, and averages rather than the deep context you gain from having access to the actual events coming from your production environment.
