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As with error logs, the advantage of centralized logging is that it lets you examine access logs from multiple Apache servers and S3 buckets simultaneously. Web application problems can also be recorded as 400- and 500-level status codes in your Apache or S3 access logs. Even so, this is usually a good jumping-off point for investigating problems with your web application.
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So, we have to continue our analysis elsewhere. In our example scenario, we only see minor warnings-nothing that indicates a serious issue related to user accounts. It uses fuzzy logic to group similar messages, making it much easier to inspect your log data. This is exactly what the summarize operator was designed to do. However, even smaller web applications will output millions of log messages a month, which means you need a way to cut through the noise. Running this in Sumo Logic will return all of the logs that contain the keyword error. With centralized logging, you can check error logs from Apache, EC2, S3, and CloudTrail with a single query: error | summarize Check the Error LogsĪs in traditional debugging, the first step when something goes wrong is to check your error logs. As we’ll see in this article, the ability to cross-reference logs from different sources makes it easy to find problems that are virtually impossible to see when examining individual components. This helps you find correlations between different components of your web stack. But, more importantly, it lets you examine all of your log data. It lets you perform sophisticated queries with SQL-like syntax and visualize trends with intuitive charts. If you want a scalable web application, you also need scalable troubleshooting techniques.Ĭentralized logging helps manage the complexity associated with large cloud-based applications. Imagine having a dozen EC2 instances that are all communicating with a handful of S3 buckets, and you can see how this kind of troubleshooting could quickly become a bottleneck.
This might work when you only have one or two machines, but the whole point of switching to AWS is to make your web application scalable. Traditional debugging would involve SSH’ing into individual machines and grep’ing their log files for common errors. But where do you start? The breakage could be in your custom application code, Apache, the EC2 instance, an S3 bucket, or even third-party libraries that you’re using. This is mission-critical functionality, and fixing it is a high priority.
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We’ll be walking through an example troubleshooting scenario to learn how AWS log data can help you identify problems faster than traditional debugging techniques.Īfter a recent code push, you start receiving complaints from existing users saying that they can’t upload new images. This article assumes that you’re running an Apache web server on an EC2 instance, storing user photos in S3 buckets, and using CloudTrail to monitor your AWS administration activity. A powerful query language makes it easy to perform complex lookups, visualizations help you quickly identify trends, and its centralized nature lets you cross-reference logs from different parts of your stack. Instead of logging into individual machines and grep’ing log files, you identify root causes by querying all of your log data from a single interface.
#Sumologic timeslice get oldest software
Instead of wasting developer time tracking down software bugs in all the wrong places, you can identify issues quickly and reliably by replaying every event that occurred in your system leading up to a breakage.Īs you read through this article, keep in mind that troubleshooting with a centralized log management tool like Sumo Logic is fundamentally different than traditional debugging. This visibility dramatically reduces the time and effort required to troubleshoot a complex cloud application.
#Sumologic timeslice get oldest full
We’ll learn how a centralized log manager gives you complete visibility into your full AWS stack. In this article, we’ll introduce the basics of AWS log analytics. This makes it an indispensable security tool-but only if you can correlate CloudTrail activity with changes in web traffic, spikes in error log messages, increased response times, or the number of active EC2 instances. For example, CloudTrail provides an audit trail of everything that’s happened in your AWS environment. Your web application’s log data contains a vast amount of actionable information, but it’s only useful if you can cross-reference it with other events in your system.