Operations | Monitoring | ITSM | DevOps | Cloud

Logs are useful for troubleshooting and identifying issues in applications, as they provide a record of events and activities. However, managing log data can be challenging due to the large volume of log events generated by modern applications, as well as the need to balance the level of detail in the logs and the impact on the application's performance.

Elasticsearch and Splunk can both be used as log analysis tools for software applications. Elasticsearch, as part of the Elastic Stack, offers a highly scalable, open-source solution for real-time search and analytics across diverse data types, excelling in customization but with a steeper learning curve.

Log analysis is a very powerful feature for an application when it comes to debugging and finding out which flow is working properly in the application and which is not. In a world of containerization and cloud computing, it is essential to understand logs generated by a Docker environment to maintain healthy performing applications. In this article, we will discuss log analysis in Docker and how logging in Docker containers is different than in other applications.

OpenTelemetry is a Cloud Native Computing Foundation(CNCF) incubating project aimed at standardizing the way we instrument applications for generating telemetry data(logs, metrics, and traces). However, OpenTelemetry does not provide storage and visualization for the collected telemetry data. And that’s where an OpenTelemetry backend is needed. Cloud computing and containerization made deploying and scaling applications easier.

Almost everyone acknowledges that log monitoring is essential for maintaining the reliability, security, and performance of modern applications. However, the complexities increase as organizations adopt diverse architectures to effectively manage the various log data challenges they encounter. In our previous blog post, we discussed the significance of log monitoring alongside a few popular log monitoring tools available in the market today.

Software is in a crisis. This is nothing new. Complex distributed systems are perpetually in a state far from equilibrium, operating in what Richard Cook has called a “degraded mode.” It’s through a combination of technical artifacts, organizational practices and policies, and pure gumption that they manage to maintain themselves through time. However, there are some organizations that seem to have an easier time of it than others.

After a year in business consistently meeting revenue benchmarks and audience cultivation goals, it’s time to reap the fruits of your labor by launching the store’s first new product line. You’ve spent the last couple of months preparing for this day: stocking your inventory, cooking up ad creative for your social feeds, and perfecting marketing email subject lines. Now it’s time to sit back and watch those sales pour in—except they don’t.

The Internet of Things (IoT) is all the rage these days, and for good reason. It lets us connect all sorts of devices to the internet, opening up a world of possibilities. However, managing all those devices and the data they generate can be a challenge. That's where AWS and MetricFire come in. AWS offers a robust suite of cloud services called AWS IoT that makes it easy to develop and manage IoT applications. MetricFire is a platform that helps you monitor your AWS services, including your IoT devices.