In modern software development, distributed systems have become increasingly common. As systems grow more complex and distributed, it can be challenging to understand how requests or messages move through the system and where bottlenecks may occur. This is where distributed tracing comes in. Distributed tracing is a technique that allows developers and operators to monitor and understand the behavior of complex systems.
Do you know what your website users are really experiencing? Are they satisfied with your website's performance? Are they able to easily navigate and find what they're looking for? Real User Monitoring (RUM) is a powerful technique that can answer these questions and more. By collecting and analysing data on real user interactions, RUM provides valuable insights into user behaviour, website or application performance, and overall user experience.
SIEM is an overarching mechanism combining Security Event Management (SEM) and Security Information Management (SIM). It is a combination of different tools such as Event Logs, Security Event Logs, Event Correlation, SIM etc. These work in tandem to provide you an up-to-date threat intelligence infrastructure and enhanced security for your applications and hardware.
The modern business heavily depends on an active online presence for customer engagement and revenue generation. But have you ever stopped to think about what makes these online services accessible to users around the world? Enter the Domain Name System (DNS), a crucial component of the internet infrastructure that translates domain names into IP addresses and directs traffic to the appropriate server.
RabbitMQ is a widely-used open-source messaging broker that facilitates message-oriented middleware for modern applications. It serves as a reliable and scalable mechanism for managing communication channels and messages between distributed applications. However, as modern distributed systems become increasingly complex, monitoring RabbitMQ's performance, availability, and other critical metrics becomes crucial for seamless operations. This is where RabbitMQ monitoring metrics come into play.
Logs are a vital source of information for any system, providing valuable insights into its performance and behaviour. However, with the increasing complexity of modern systems and the massive amount of data generated by them, managing logs can be a daunting task. This is where log shippers come into play. Log shippers are tools designed to simplify the process of collecting and forwarding log data to a centralized location, allowing for easy analysis and troubleshooting.
The core functionality of the Java Instrumentation API lies in its ability to modify the bytecode of classes being executed by the virtual machine. This capability allows for a range of monitoring tasks to be carried out, such as event recording and data gathering, which can provide valuable insights into an application's performance and behavior.
Have you ever visited a website that took forever to load, leaving you staring at a blank screen and clicking your mouse in frustration? If so, then you have experienced the slow Time to Interactive (TTI). TTI is the ultimate test of a website's speed and responsiveness, measuring the time it take s for a page to fully load and become interactive. A slow TTI can leave your users feeling bored, frustrated, and downright furious.
Prometheus and Nagios are both open-source infrastructure monitoring solutions created by SoundCloud Engineers and Ethan Galstad respectively. They both find popular usage in monitoring the availability and performance of computer systems, networks, and applications. While Prometheus uses a pull-based model to collect metrics and its dynamic service discovery support, Nagios uses a push-based model modeled on plugins.
Data generation today is at an unprecedented level, and we are generating an inexhaustible amount of data. As a matter of fact, more data has been created over the past two years than ever before in the history of mankind. This throws a big complexity in front of us. How do we even manage such a huge amount of data? Where do we store them? Can they be segregated to fit into our needs, who would do that for us, and so on! The questions are endless, and so is the rate of generation of new data.
