Rails is a classic on Ruby for a reason. The framework is powerful, intuitive and the language has a low entry bar. However, being designed when systems existed on a single server, standard Rails logging is excessively fractionalized. Even on a single server, a straightforward call can quickly turn into seven unique, unconnected logs.
Security is a top-of-mind topic for software companies, especially those that have experienced security breaches. Companies must secure data to avoid nefarious attacks and meet standards such as HIPAA and GDPR. Audit logs record the actions of all agents against your Elasticsearch resources. Companies can use audit logs to track activity throughout their platform to ensure usage is valid and log when events are blocked.
Have you ever glanced at your logs and wondered why they don't make sense? Perhaps you've misused your log levels, and now every log is labelled "Error." Alternatively, your logs may fail to provide clear information about what went wrong, or they may divulge valuable data that hackers may exploit. It is possible to resolve these issues!!!
Cloud monitoring and observability can involve all kinds of stakeholders. From DevOps engineers, to site reliability engineers, to Software Engineers, there are many reasons today’s technical roles would want to see exactly what is happening in production, and why specific events are happening. However, does that mean you’d want everyone in the company to access all of the data?
Log management has been around for a long time, but how we manage our logs has changed profoundly over the years. For effective log management, there are times when you may have to trade off the new for the old, and vice versa. A clear understanding of log agents and log libraries will help assess what works best for different applications and infrastructures.
As developers, we would like our users to interact with applications that run smoothly and without issues. We want the libraries that we create to be widely adopted and successful. All of that will not happen without the code that handles errors. Java exception handling is often a significant part of the application code. You might use conditionals to handle cases where you expect a certain state and want to avoid erroneous execution – for example, division by zero.
Good logging practices are crucial for monitoring and troubleshooting your Node.js servers. They help you track errors in the application, discover performance optimization opportunities, and carry out different kinds of analysis on the system (such as in the case of outages or security issues) to make critical product decisions. Even though logging is an essential aspect of building robust web applications, it’s often ignored or glossed over in discussions about development best practices.
The ultimate success of any security monitoring platform depends largely on two fundamental requirements – its ability to accurately and efficiently surface threats and its level of integration with adjacent systems. In the world of SIEM, this is perhaps more relevant than any other element of contemporary IT security infrastructure.
MEAN is evolving as a popular web stack for developing cloud native applications because of its scalability, ease of extension, and high reliability. Each component in MEAN is built on JavaScript, contributing to a cohesive development platform. In this post, we take you through the log management options that are available for each component of the MEAN stack framework and their respective limitations – limitations that are addressable with a refined log management solution like observIQ.
