Over the last decade, the increasing complexity of technology systems including the growing adoption of cloud computing has created new challenges in the management and analysis of log data. The scalability that distributed and cloud systems provide is accompanied by the creation of enormous volumes of logging information.
Capturing, storing and analyzing these logs is vital to ensure optimal system performance. Yet, not just any approach to log management will work. While many system administrators focus on the cost of log management solution, how the solution works are even more important. Some techniques have been shown to be more effective than others. Here’s a look at the best practices of log management.
1. Start with a Strategy
You can log virtually any activity that takes place on a server or application. But how much of this information would actually be useful to you? The problem with capturing too much log data is that it becomes overwhelming and prevents you from focusing on system events that really matter.
That’s why the first thing you must do is develop a logging strategy. Look at what system events are most important and configure the logging process accordingly.
2. Structure the Logs
The strategy will help you identify the type of logging data you need to capture. However, you can capture the right logging information but in a format that’s unreadable and therefore unhelpful. You must structure system logs in formats that make it easier for you to extract insights.
Logs must be clear and understandable from both a human and a machine perspective (by machine here we mean the automated systems that can read and act on logging events). A readable log speeds up and simplifies log processing, facilitates coherent interpretation and speeds up troubleshooting.
3. Centralized Logging
System logs should be automatically captured, transmitted and stored in a central location that’s distinct from the production environment. Consolidation makes log management and analysis easier, enhances efficiency and enriches data correlation.
An event in one application can trigger a problematic event in another system. Data consolidation gives you a wider view of enterprise systems so you can get to the root of the problem. Centralization also means your system logs are secure in the event of an incident that affects your production environment.
4. Unique Identifiers
Logs should have unique identifiers for users, event types and applications. This is useful when debugging, investigating and monitoring since you can quickly identify the origin of a system problem.
Unique identifiers also make it easier to follow a sequence of actions by a specific user. If, for example, you suspect a certain user of fraudulent or otherwise unauthorized activity, you can simply filter your search with the user ID.
5. Provide Context
The more information you can provide with each logged event, the better. Of course, it may not be practical to have an entire paragraph describing each event logged as that will make log files bulky very fast. However, you want to make sure that each logged event can be understood on its own.
So as opposed to logging an action as ‘clicked button’, it would be better to be more specific (e.g. clicked purchase button). If the actions led to a system error, the log detail will facilitate quicker resolution.
6. Real-Time Logging
Service disruption can lead to disgruntled customers, lost sales, missing data and damage to reputation. For this reason, it’s important that any disruptions are resolved as quickly as possible. Real-time logging gives system administrators the ability to see events live as they happen thus allowing them to tackle problems before they spiral out of control.
It also ensures that in the event of major disruption that completely paralyzes the production environment, all events up to the very last incident are logged.
Implementing these best practices in log management will deliver tangible business value for your organization by leveraging the benefits that such real-time, aggregated data can provide.
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