Operations | Monitoring | ITSM | DevOps | Cloud

In the past decade, we've seen explosive growth in the adoption of the cloud-based infrastructure model. IT organizations are increasingly choosing to reduce their up-front investments in IT infrastructure by deploying their applications into cloud environments. These environments offer on-demand availability of data storage and computing power that organizations need to handle high volumes of data and growing demand for application access and services.

FluentD is a free and open-source data collector. With its decentralized ecosystem, it’s known for its built-in reliability and cross-platform compatibility. One of the biggest challenges in big data collection is the lack of standardization between collection sources. They just aren’t able to talk to each other. With FluentD, you can address one of the biggest challenges to big data log collection.

Everyday when you come into work, you’re bombarded with a constant stream of problems. From service desk calls to network performance monitoring, you’re busy from the moment you login until the moment you click the “shut down” option on your device. Even more frustrating, your IT environment consists of an ever-expanding set of network segments, applications, devices, users, and databases across on-premises and cloud locations.

You’ve made the decision to implement a centralized log management solution because you know that it’s going to save you time and money in the long term. However, to get the most bang for your log management buck, you need to understand how the different parts of your log management deployment work. Once you understand each resource, you can implement a more efficient log management architecture.