Operations | Monitoring | ITSM | DevOps | Cloud

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Using Trend Analysis for Better Insights

Centralized log collection has become a necessity for many organizations. Much of the data we need to run our operations and secure our environments comes from the logs generated by our devices and applications. Centralizing these logs creates a large repository of data that we can query to enable various types of analysis. The most common types are conditional analysis and trend analysis. They both have their place, but trend analysis is perhaps the more often underutilized source of information.

Log Management Comparison: ELK vs Graylog

Production logs can help ensure application security, reveal business insights and find and understand errors, crashes, and exceptions. But as useful as logs are, they’re difficult to manage and hard to keep track of. Making matters worse is that as log data volume grows, so does the difficult task of maintaining and managing them. It’s for this reason that developers, DevOps engineers, and CTOs turn to log management tools.

Using AI analytics to detect real-time application issues

Anodot’s Solutions Engineer and AI specialist, Steven Kirkpatrick, presents how leading gaming companies are leveraging the powerful anomaly detection capabilities of Anodot’s AI Analytics to proactively address business incidents in real time, minimizing revenue loss and identifying opportunities.

5 Critical Reasons for Network Traffic Analysis

As communication and network infrastructure grows in size and complexity, having a complete view and understanding of your network environment (including the amount and type of network traffic going back and forth) becomes vital to your business’ health and operations. Having the right tools to do the job is just as important. If you can’t quickly determine the source, destination, rate and the type of traffic going across the network, you don’t have the right tool.