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Log Management: Why it Matters

With technology constantly changing, IT infrastructure isn’t the same as it used to be. Cloud solutions have far surpassed traditional data centers in scalability and efficiency. They’ve levelled all companies, and everyone has access to the same technology now.


That means monitoring methods have changed as well. “DevOps” is a movement that links operations and development teams. It makes it easier to deliver results constantly while keeping track of the consequences of these changes.





Monitoring has to adapt to change

Monitoring is the best advantage when implementing DevOps approaches. It enables companies to solve performance issues with fewer complications. Proper log management lets everyone discover what went wrong exactly.


A good monitoring system these days must be able to tag metrics; this enables them to analyze specific data. Furthermore, it makes it easier to keep track of every infrastructure layer.


These aspects result in better scalability for the system. Monitoring methods adapt to host changes. It builds over the collaboration features with these solutions; they let multiple people collaborate to solve issues faster.

Having the right data is equally important

Data collection varies. Some systems work by constantly collecting logs, yet others export logs only with specific events. The simplest example is automatic log exports when a program crash.


Logs can be useful for either identifying the specific problem, yet others can be better for analyzing them in-depth. What matters is to minimize false alarms and having a system that lets you act quickly.

Data collection is done right

Logs can split into two categories. Metrics show system values during certain times; they’re collected continuously. Events are relatively infrequent, and they’re better for assessing changes, like code releases, alerts, adding hosts, and more.


Properly-collected data should meet a few requirements. The most important one is being easy to understand. The team must be able to spot the most important information and implement it quickly.


Collection frequency should find a balance: it has to be frequent enough to collect as much information as possible without being too taxing on the system. Tagging logs is also important, for it allows you to focus on specific scopes and data. Finally, raw data has to last for a long time; this reduces the effort needed to keep track of the “normal” conditions.

What should the right solution do?

Increasing development speed is paramount, yet this should never impact system performance. Proper planning and unifying infrastructure view let companies boost their deployment while maintaining performance.


Collaboration between different teams and people must be seamless and done from a single platform in real-time. This factor builds into efficient transitions into modern cloud solutions, keeping up with more efficient-yet-complex changes.


Another important consequence of meeting these requirements is faster resolution times.

Conclusion

Proper log management can make a huge difference for any company’s operations. That’s because implementing operational or system changes requires a holistic view of the current system’s metrics and conditions.


Condensing all logs into a from different environments to a single platform can be a game-changer for anyone. With proper tagging and viewing options, anyone can track their system’s performance and spot any error’s cause in minutes.


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