The sheer scale of connected devices across physical, virtual, and distributed networks has come to scale that it has become practically impossible for most network administrators to manually keep an eye on each node. Along with the scale, the connectivity between devices within each network has also become denser.

As the networks become more complex, administrators are left to cope with monitoring and analysing the IT Infrastructure’s functioning to ensure uptime and security. Machine Data has a ton of insights already embedded into it in the forms of trends and usage statistics. Most of these insights are just one exploration away with the right log management platform in place. Now you can proactively safeguard the confidential and proprietary data on your system and create simple workflows to prohibit unauthorized access to files or folders.

The log data will also help you understand security breaches at a more detailed level, with event correlation analytics engineered from different network sources. These sources generally include Network, Server, Application, and Custom Logs.

Still thinking about how you can deploy log monitoring systems to generate value for your business? Here are some industry-leading use-cases for you to consider:

1. Security and Audit Violations

Keeping user data and proprietary data secure has become one of the most challenging tasks for network administrators. Using an advanced log management system adds a deeper analysis layer across the various nodes in the system.
The general workflow to deal with security breaches revolves around investigating the matter and ensuring it is not repeated. The investigation part, although heavily dependent on data, is generally guided by arbitrary analysis. An advanced log management system can help the network administration and IT teams perform root-cause analysis with one click.

2. Pattern-Based Modelling

Even though root-cause analysis is an effective mechanism, it is looking backward. To create more time-sensitive tools that can detect system anomalies, the network administration team must create ground rules that can be easily followed for highlighting the breaches. Pattern-Based Modelling can be the answer to this problem.

Pattern-Based Modelling is executed by using a log management system that considers several key fields from different log formats and arranges them in the structured created based on their statistical significance and frequency. These pre-defined patterns are then stored in the system, and as soon as a breach of these patterns is detected, the system administrators are alerted in time.

3. Centralized Monitoring

A key issue with networking monitoring by using log files is that such data is often stored on systems locally. The ITSM team has to search across sources, locations, and devices to aggregate all the data. Even if the team is very efficient in doing so, this can be a very time-consuming process. And even after going through the arduous manual process, there is always a probability of missing some critical data.

Centralized Monitoring platforms target this problem. Using such features of an advanced log management system, ITSM teams can Aggregate all log data from multiple heterogeneous sources and log format at one single location.  Centralized log aggregation makes it easy to manage and analyze raw data.

4. Compliance Reporting

As more devices become geographically distributed, ITSM teams are now facing the challenge of ensuring that the network’s nodes are adhering to the already defined compliance requirements.

Not having a log management system would leave the team with a ton of work on its plate to ensure compliance principles and rules are satisfied. Log Data can be a structured solution to ensure that all the network systems are complying with the rules set by the management team or local authorities, round the clock. This data can also be used in compliance reporting using tangible evidence if a situation necessitating it arises.

5. More Effective System Troubleshooting

System Troubleshooting is often looked at as an ancillary service offered by the DevOps team. However, for the users in the network, this can affect the daily responsibilities to take care of at work. DevOps teams are designed to work on production and still somehow manage to offer troubleshooting. This can be achieved by having a log management tool that detects application crashes, configuration issues, and hardware failures in real-time.

This way, DevOps teams can execute troubleshooting in real-time, prioritize problems & issues, and be effective in reducing downtime. Eventually, the time saved by not having to go on a manual hunt for finding problems and then troubleshooting them, DevOps teams can efficiently take care of their production priorities.

In Conclusion

Log Management is much more than just an internally available service. It can be actively used as an asset to monitor, analyse, record, and optimize performance, compliance adherence, and security across the system. The Motadata Log Analyser allows administrators to track specific IT Infrastructure components using in-built or custom metrics. It also comes with easy rule-configuration features, which allow it to detect specific patterns and send alerts or take a specific action when such patterns are breached. This allows for proactive and real-time network security and gives the network administration team the reports necessary to manually detect activity on a daily, weekly, and monthly basis.