Where Does OverOps Fit Into My Ecosystem of Tools?

 ● 02nd May 2016

7 min read

OverOps can seamlessly coexist and integrate with your existing ecosystem, providing unique data and insight to figure out when and why your application code breaks in production.

There are three common ways to monitor your application:

  • Application Performance Monitoring (APM)
  • Log analyzers
  • Error tracking tools

Most companies will use several tools to get the full picture of their production environment.
Whether you’re already using a certain tool (or 3 different ones), OverOps can seamlessly coexist and integrate with your existing ecosystem, providing unique data and insight to figure out when and why your application code breaks in production. We can even inject links to this insight into your existing log files.
In this post, we’ll see how OverOps fits in with APMs, server monitoring and and log analyzers.

What is APM and what is it good for?

APM tools provide us with analytics around our application’s performance. At the core this means timing how long it takes to execute different areas in the code, and how long it takes for certain transactions to complete – this is typically done using bytecode instrumentation (BCI) to tag and trace transactions and instrument call stacks so that you know which method or service request is slow.
AppDynamics Dashboard
APM enables you to see what the end users are experiencing inside your application. You’ll be able to monitor production environments, application loads (transactions, requests and pages per second), calculate response time and pinpoint what might cause a delayed response.
The top names in the APM space are New Relic, AppDynamics and Dynatrace (Ruxit). New Relic focuses on SMBs and Startups, while AppDynamic and Dynatrace are more enterprise driven, with higher pricing rates. They all give pretty much similar monitoring options, each with its own benefits depending on your specific use case. You can read our comparison posts about AppDynamics vs New Relic or AppDynamics vs Dynatrace.
There are other names in this category, such as AppNeta, Stackify, Scout, DripStat, InfluxData, perfino and Correlsense, and the list goes on and on. Smaller companies might prefer them due to pricing or basic expectations from a monitoring tool.

OverOps + APM = See Everything (Stack, Source Code & State)

Wait a minute, my APM solution already shows me stack traces, source code and variables? I’m afraid it doesn’t, and if it does, you’re looking at incomplete data.
APM will show you a stack trace for every error and exception that your application throws. At the top of every exception it’s also going to tell you the class and method where it originated. This is identical information to what log analyzers also collect from the application run-time. With APM you know when and where the problem is.
OverOps will also show you a stack trace for every error and exception. However, it will also show you the complete source code, objects, variables and values which caused that error or exception to be thrown. At OverOps we call this identifying the root cause of when your code breaks.
You can also integrate OverOps alongside your APM and keep your current workflow, inside your existing dashboard. For example, you can use our New Relic plug-in that puts a OverOps link next to every error and exception shown in New Relic (see below screenshot).
OverOps injects a hyperlink into the exception’s link, and you’ll be able to jump directly into the source code and actual variable state which cause it. Pretty cool huh?
OverOps Code Snippet
OverOps can co-exist in production alongside all major APM agents and profilers, allowing you to enjoy maximum visibility and productivity, as each tool provides its own unique capabilities. Using OverOps with your APM allows monitoring server slowdowns and errors, along with the ability to drill down into the real root cause of each issue.

Log Management to The Rescue

Your log files contain a large amount of data you have to sift through if you want to find out what happened inside your application. This includes machine data, business metrics such as sale transactions and user behavior, and information about product related issues.
Splunk and ELK (Elasticsearch-Logstash-Kibana) are dominating the log management space with the most comprehensive and customizable solutions. You’ll find other names such as Sumo Logic, Papertrail, Graylog, Loggly, Logentries, XpoLog and Logscape, who offer competitive pricing but don’t compare to the 2 bigger tools.
The strongest use case for logs is troubleshooting, when your log files include logged errors, warnings, caught exceptions and, if you’re lucky, notorious uncaught exceptions. In most cases, you’ll have to dissect the information in order to understand what went wrong in the execution of your code in production.

How OverOps Enhances Log Management

OverOps in Logs
The main challenge when using logs is that they often contain an unmanageable number of entries and require to manually find the needle in the haystack. Usually you’re left with the error message you’ve attached, and the stack trace at the moment of error. That’s just not enough to understand what’s the real root cause of the error, and you’re sent off to an iterative process of trying to replicate the same error, add more info to the log, and so on.
OverOps helps in the debugging process, by inserting hyperlinks into your existing log files, so ops and developers can instantly see the stack, source and state behind each event.
OverOps also de-duplicates the contents of log files to reduce the operational noise and time associated with analyzing them. Detecting exceptions and logging errors happens in real-time, at the JVM level without relying on parsing logs.

Error Tracking for Better Insights

Error Tracking Companies
Following and analyzing your errors can give you better insights about your application. Using it, you’re able to see which exceptions were thrown, get real-time crash reporting and find important issues even if you have a huge code base.
Among the names relevant to this category, you’ll find airbrake.io, bugsnag, Raygun, Sentry and Rollbar. The tools capture and track your application’s exceptions, giving you a friendly dashboard instead of the long and messy log. Most tools allow you to filter the relevant exceptions and errors, giving you a clean look on the state of your application.

Making Error Tracking Better

OverOps is the best choice when it comes to error tracking. While all tools can tell you when your code breaks in production, OverOps can tell you why it happened. OverOps’s dashboard shows you the code and the variable state of errors right when they occur, and automatically detects code deployments and alerts you when they introduce new errors.
If you want to be able to get the full path and cause of your errors, along with the actionable information you need to fix them – you should use OverOps.

OverOps can supercharge your monitoring ecosystem

It doesn’t matter if you’re using an APM, log management tool, an error tracker or all 3 tools – OverOps will complement and not replace what you already have.
OverOps runs as a native Java agent and does not require code changes, binary dependencies, or build configurations. The installation process takes less than five minutes and you’ll be able to see the root cause of every application error within a few minutes.
You can sign up for your free trial right here.

Henn is a marketing manager at OverOps covering topics related to Java, Scala and everything in between. She is a lover of gadgets, apps, technology and tea.

Troubleshooting Apache Spark Applications with OverOps OverOps’ ability to detect precisely why something broke and to see variable state is invaluable in a distributed compute environment.
Troubleshooting Apache Spark Applications with OverOps

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