Logs have moved beyond a basic tool for debugging during development. A recent Logentries survey carried out across a sample of 25k users of log management software shows that the most common use case is using log data for production monitoring, which has traditionally been the stronghold of Application Performance Management (APM) and server monitoring tools.
Using logs for application monitoring comes with a major benefit. Logs not only allow you to look at trends in your data, but – unlike APM or server monitoring tools – they also maintain the evidence so that you can drill down to the log event level to understand exactly what led to a spike in response time or CPU for example.
Furthermore, you can also use logs to be proactive, such that you can create notifications or automated actions when particular events occur or thresholds are breached. That way you can get notified and react when symptoms of more serious issues begin to occur so you can react before a major incident happens.
So what are the most important steps to follow to investigate and resolve particular issues when they occur? When using your logs for performance monitoring, here are some useful steps you can follow to dig a little deeper into any issues that you identify:
1. Set up real-time alerts
The first step is to get notified in real time when something important happens. For example, if you get an OutOfMemoryException (one of the common Tomcat errors we identified from our analysis), this can be pretty critical. You want to know right away so you can react appropriately. If an OutOfMemoryException was caused by a slow memory leak, often a server restart will buy you some time so you might even want to have your notifications configured with your infrastructure API to automatically restart an instance upon a given issue. Make sure your logging supports alerts that can be configured with third-party APIs and are sent in real time - i.e. seconds not minutes.
2. Understand what user behavior caused the issue
Once you know there is a particular problem in the system, the next set of steps are usually related to figuring out what caused it. Understanding how your system was being used at the time of, or leading up to, an issue can be a big help. This can help you localize the problem to a set of system components or functions. If your hunch is that a single user action can lead to a problem (e.g. you released a new UI feature that crashed when users started to play with it), session- or transaction-tracing techniques can really help here. Session or transaction tracing allows you to follow a user’s steps through your system in the order in which they were carried out such as the order in which they navigated your app interface or the steps they took before they added something to a shopping cart, for example.
Tracing in this way can be achieved by following some logging best practices, which suggest you should add the following details to your log events:
- A timestamp
- A unique user identifier (e.g. user name, user ID, email address)
- A unique session or transaction ID
Combining these three parameters allows you to retrace the steps of a user before an incident occurred.
If, on the other hand, the system issue was caused by group user behavior rather than a single user action, which is often the case with an OutOfMemoryException that featured as a common issue that surfaced in our research analysis, tracing a given transaction or session may not be sufficient to identify the root cause. Instead you might want to understand what were the most common system functions that all users have been carrying out. A great way to do this is to group log events by user actions to get a break down of what the most common user behavior is and how this breaks down over the past hour, day or week for example.
This will give you an immediate view of how your system is being used by groups of users and can help you nail down actions that may be resulting in leaking memory. Correlating increases in a given user action over the past 24 hours with increases in your heap size over that same time period can be a good way to point you in the right direction of a leak.
3. Check resource usage
Resource usage data can also be streamed into your log data such that it can be correlated with application exceptions or system errors.
When a given issue occurs in your system it may or may not be related to exhausted system resources such as CPU or memory. Typically issues like slow response time, timeouts or memory leaks can be related to resource usage. A quick look at your system resource usage when there is an issue is almost always a good idea and can help save you time when troubleshooting.
4. Determine if performance was affected
One of the first things you will need to communicate across your team when there is a system issue is: which users were effected and how it affected them. Another logging best practice worth following is to log important performance parameters from your application code, web servers and database queries. Request response time, response size and slow queries can be particularly useful to track. Combining this information with unique user identifiers (see #2) allows you to track performance at the per-user level such that you can see if individual users have been affected by a given system issue.
Furthermore, real user monitoring (RUM) using client-side logging libraries will allow you to capture log data from a client device (smart phone/tablet) apps or web browser. With RUM, you will not only capture the time spent in the system backend, but can also capture the perceived performance from the client’s perspective capturing total time it took before the response was received by the client. This can also capture delays in the network or with page loading times for example.
5. Identify what part of the application code caused the issue
Once you have established the exception type, the user behavior that led to the issue, resource usage at the time as well as how users were affected, you will want to immediately dive into the low-level details to figure out the issue in your code or the system process that caused the problem. Examining exception stack traces in your logs can help identify the culprit. For example, in the case of a UI bug, tracing a user transaction (as outlined in #2 above) will often capture the exception caused by a particular action. Digging into the exception stack trace can show you the exact method/object/function and line number where a bug was introduced.
When choosing your logging solution, make sure it can handle multi-line events, as exception traces are essentially single events that can span 10s or 100s of lines. With some solutions, it can be very frustrating when you search for an exception and do not get the full trace. Solutions that support multi-line events and show surrounding events around a given search can make life a lot easier when dealing with exception traces.
ABOUT Trevor Parsons
Trevor Parsons, PhD, is Co-founder and Chief Scientist of Logentries. Parsons is responsible for product strategy and direction. He works closely with customers and partners to continuously understand what they need, and to validate product market fit. Parsons also leads the product management and UX teams and assures the best possible user experience. Parsons enjoys speaking at local devops meet-ups and events, and is always looking for how log data and analytics can be applied in more and more powerful use cases. Parsons was a post doctoral researcher and member of the Performance Engineering Lab at the School of Computer Science and Informatics in University College Dublin, Ireland. He received a PhD from University College Dublin for his thesis titled Automatic Detection of Performance Design and Deployment Antipatterns in Component Based Enterprise Systems.
A growing IT delivery gap is slowing down the majority of the businesses surveyed and directly putting revenue at risk, according to MuleSoft's 2017 Connectivity Benchmark Report on digital transformation initiatives and the business impact of APIs ...
Why containers are growing in popularity is no surprise — they’re extremely easy to spin up or down, but come with an unforeseen issue. Without the right foresight, DevOps and IT teams may lose a lot of visibility into these containers resulting in operational blind spots and even more haystacks to find the presumptive performance issue needle ...
Much emphasis is placed on servers and storage when discussing Application Performance, mainly because the application lives on a server and uses storage. However, the network has considerable importance, certainly in the case of WANs where there are ways of speeding up the transmission of data of a network ...
The majority of IT executives believe investment in IT Service Management (ITSM) is important to gain the agility needed to compete in an era of global, cross-industry disruption and digital transformation, according to Delivering Value to Today’s Digital Enterprise: The State of IT Service Management 2017, a report by BMC, conducted in association with Forbes ...
Let’s say your company has examined all the potential pros and cons, and moved your critical business applications to the cloud. The advertised benefits of the cloud seem like they’ll work out great. And in many ways, life is easier for you now. But as often happens when things seem too good to be true, reality has a way of kicking in to reveal just exactly how many things can go wrong with your cloud setup – things that can directly impact your business ...
IT leadership is more driven to be innovative than ever, but also more in need of justifying costs and showing value than ever. Combining the two is no mean feat, especially when individual technologies are put forward as the single tantalizing answer ...
The move to Citrix 7.X is in full swing. This has improved the centralizing of Management and reduction of costs, but End User Experience is becoming top of the business objectives list. However, delivering that is not something to be considered after the upgrade ...
As organizations understand the findings of the Cyber Monday Web Performance Index and look to improve their site performance for the next Cyber Monday shopping day, I wanted to offer a few recommendations to help any organization improve in 2017 ...
Online retailers stand to make a lot of money on Cyber Monday as long as their infrastructure can keep up with customers. If your company's site goes offline or substantially slows down, you're going to lose sales. And even top ecommerce sites experience performance or stability issues at peak loads, like Cyber Monday, according to Apica's Cyber Monday Web Performance Index ...
Applications and infrastructure are being deployed and commissioned at a faster rate than ever before, the number of tools it takes to effectively manage these services is multiplying, and the expectations placed on IT to ensure customer satisfaction is increasing, according to The State of Monitoring 2017 report from BigPanda ...