Anyone who has been assigned the task of gleaning usable information from log data understands the complexity of the process. Simply put, log data analysis means collecting, organizing, and arranging log data into a presentation easily understood by all. The information gathered from log analysis is crucial in decision-making, especially those related to network security, monitoring, and development.
How massive is the log data collected by enterprises?
It is hard to imagine the amount of log data collected by enterprises every day. 1 Gigabyte of data alone equates to approximately 700,000 pages in print form. If an IT admin had to pore through these pages to spot errors and anomalies, it would be an ineffective method of correcting issues. It is, therefore, safe to conclude that to make sense of log data, every organization needs an advanced log analysis tool. There are log analysis tools for Windows, log analysis tools for Linux or any other operating system for that matter. The platform will automate some if not all of the interrelated functions associated with log management and analysis.
Solution: Build or buy a log management platform?
There are many different tools out there, offering different value propositions. Adopting a platform that does not fit the needs of the organization will not lead to favorable results, therefore it is best to do the research in advance. The purpose of deploying a log management system is to break down massive volumes of log data and aggregate, parse, and group them into useful reports. Whether the organizations prefer to build or buy an out-of-the-box solution, keep the following functions in mind:
- Search function. A search function should go above and beyond returning log data that matches the search string. A more intuitive search feature gives context to the search results, such as providing visibility to preceding and prior events.
- Broad collection capability. The platform needs to support all types of logs, especially those that come from various devices, operating systems, and use different languages.
- Real-time alerts. An essential feature of a log management platform is its capability to send real-time alerts at it automatically scans log data for errors and threats.
- Degree of automation. In earlier versions of log analysis, most of the functions required user programming and manual operation. But the complexity of log data, as well as the growing needs of organizations gave rise to the development of platforms with AI capability. Through machine learning, log analysis platforms can detect trends and patterns and use them to discover potential risks and errors. With a higher degree of automation, DevOps and IT managers can increase their productivity and spend less time on manual tasks.
- Ease of use. As we are talking about massive amount of data, advanced tools offer an automated log collection and parsing which saves weeks and even months of work. There are log management tools that also offer automated log analysis and visualization of the log data (Such as log analysis apps).
From the perspective of IT and DevOps teams, innovative features of log management platforms lead to successful implementation and operation. In addition to IT teams, log analysis also benefits security engineers in their performance of security-related tasks. Lastly, log analysis and management is often required as part of a company’s compliance with laws and regulations.
Going back to the vital question of whether it is better to build or buy a log management solution, the choice depends on resource availability. Building a platform requires human and monetary capital, but the resulting solution is tailor-fitted to the company’s needs. On the other hand, there are several excellent out-of-the-box solutions available with varying versatility and quality. Choosing the right service is tricky, but finding one that works to the organization’s best advantage is not impossible.
