The cloud is growing more and more popular each day. We are in an era where there is a prominent trend of companies migrating from traditional on-premise systems to more reliable and fast cloud-based systems. However, the conversion is still not rampant on a large scale, primarily due to the lack of awareness in the up-and-coming businesses about the cloud’s fundamentals. However, the cloud has proven to be a sound and worthy option time and time again.
You’ve likely heard the term Observability lately. There’s a fundamental change taking place in the Monitoring space, and Observability is behind it. Observability itself is a broad topic, so in this post we’ll talk about what it means to move from Application Performance Monitoring to Application Performance Observability.
Before we dive into the Collector, let’s cover the components that make up the OpenTelemetry project. If you missed it, our post What is OpenTelemetry gives a high level introduction to OpenTelemetry and the key components of OpenTelemetry project: The OpenTelemetry collector is optional when using a SaaS service like Scout. Even so, knowing what the Collector can do and when to use it is helpful to understand.
Cloud and cloud-based technologies are at their peak today. More and more organizations are turning to intelligent architectures and systems to deploy their apps. And they are not wrong—the cloud has proven to be a great way of performance optimization and cost-cutting. However, there are issues to address with this growing trend. One of those is monitoring. Monitoring is a vital part of application maintenance.
As more and more organizations adopt cloud-native technologies, the need to align business objectives and end-user experience with IT infrastructure’s availability and performance is ever-growing. This trend requires infrastructure monitoring setups to ensure that all of your systems are active and working together across your cloud environments, host operating systems, storage systems, etc.
The world is moving towards a data-driven society, resulting in businesses gathering more data to leverage for profit. This data is either in structured forms like JSON/CSV/XML or unstructured forms like text written on a notepad or typed texts. Regardless of the data’s formatting, the important thing is the information it contains. Various tools in the market extract data from different agents and platforms that will improve your metric monitoring system.
Technology is taking over the world at a great pace. Everyone is getting in the loop of technology, whether it be a company, organization, startup, or even a 2-year-old kid. Most companies are using the latest technologies for updated features. They took their business online in order to remain in the current market. They make some applications for their base products and run their business through that website or application. But having an application is challenging.
Python’s USP as a programming language is that it’s flexible, easy to use, and quick to get started and iterate with. These virtues have led it to become the most popular programming language in 2022 and be used by millions of developers. As Python applications continue to multiply and scale to cater to millions of users worldwide, instrumentation and monitoring tools play a role more crucial than ever – in building robust, performant software.
Serverless Computing, or simply serverless, is a hot topic in the current software market. More and more companies are shifting their operations from traditional server-oriented architecture to faster, more modular serverless architecture. The “Big Three” cloud vendors (AWS, GCP, and Microsoft Azure) have shown immense interest in offering the best serverless experience possible. But what exactly is serverless? And how does it work if there is no server at all?
In our Configuring OpenTelemetry in Ruby blog post, we showed how to configure OpenTelemetry in a Ruby on Rails backend. In this post, we’ll cover how to configure OpenTelemetry in the front-end JavaScript in order to measure performance of browser and mobile devices and how to configure distributed tracing to work across the frontend and back end telemetry collection. Let’s dive in!
