When you run the uptime command, most of you might be familiar with the three numbers appearing on the top right corner of your Linux screen. But, do you know what those numbers indicate or why there are three such numbers? It is called the load average, a metric that assesses the load on your computer systems. While it can be considered a precise tool for measuring system and resource engagement, it would only be worthwhile if you understand it right.

In recent years, there has been a rapid expansion in the API market. Today, every piece of software is either an API or uses one. They are now a crucial component of the modern digital economy. As a result, it is becoming increasingly important to grasp how to examine them carefully. In this article, we'll discuss the definitions of API observability and API monitoring as well as how API observability is better than API monitoring.

The open-source data platform Redis, based on in-memory data, is complicated enough when hosted only on one server. Therefore, a critical aspect of Redis management is monitoring its performance. Despite serving a vast number of queries, Redis is known for its low latency response time. Keeping track of your Redis instance's performance can be done by monitoring certain vital metrics. As well as storing data in memory and on disk simultaneously, Redis stands apart from most other databases.

Cloud monitoring is the process of tracking, reviewing, and managing the health and security of cloud-based systems and applications. Cloud monitoring is essential for any organization that relies on cloud-based applications and services. It provides visibility into the performance of these systems and can help identify potential issues before they cause downtime or data loss.

In both the corporate and personal areas, a significant portion of daily life is spent glued to screens in an era where digital transformation is widespread. We engage with many digital services, apps, and websites daily. During these digital encounters, we occasionally encounter websites with slow-loading pages or 404/server error messages.

Distributed architectures are becoming an increasingly important source of application services for organizations. Advances in observability and monitoring are being driven by this trend. But exactly how do observability and monitoring differ from one another? It's essential to know when something goes wrong in the application delivery chain so you can identify the root cause and resolve it before it has an impact on your business. Monitoring and observability offer a two-pronged strategy.

Mission-critical apps that are deployed on the cloud drive today's modern enterprises, which in turn power their businesses. These applications' fundamental units are microservices, which tiny development teams created to enable speedy feature releases to the market. APIs serve as the ties that bring these microservices together so they can cooperate.

On 10th December 2021, Apache foundation admitted the Log4Shell vulnerability of its Log4j 2.16 version. Chen Zhao Jun was an Alibaba cloud services security analyst who first found out about this security threat and consequently reported it to the foundation. Upon further investigation, they identified that the vulnerability had existed since 2013. Unfortunately, by then all the corporations, big and small were affected by this malicious security breach.

Docker is a PaaS product, developed by Docker.Inc to containerize applications. It does so by combining app source code with OS libraries and dependencies required to run that code in any environment. Kubernetes is a similar tool developed by Google, which scales up this containerized application after deployment. While one works in building the containers the other essentially helps in scaling it up, then why so much buzz around these two?

JavaScript is one of the most widely used programming languages for creating dynamic, interactive websites. However, there may be instances where a function is not operating as intended because of a coding error while creating JavaScript projects. Therefore, the majority of developers hunt for JavaScript debugging tools to avoid problems and identify errors before execution.