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The new battleground in Analytics Part 2: Transforming APM into Application Intelligence

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In Part 1 of this series, I talked about my transition from the world of Analytics into the APM space and my assertion that APM is simply another form of Analytics. It’s turning large amounts of data into information you can use to take quick action. Like other forms of Analytics it can help you drive revenue, reduce costs and mitigate risks. The impact to the business can be truly compelling — but that’s only the beginning of the story.

As powerful as traditional APM is, it’s very quickly evolving into what we call Application Intelligence. Our Application Intelligence Platform allows you to do three key things:  See, Act and Know.

  • See what’s happening in real-time:  We enable an integrated view of real-time user experience, application performance and infrastructure capacity.
  • Act fast to resolve issues:  We provide the ability to automate resolution of application or infrastructure bottlenecks – in production.
  • Know that you’re running at your best:  We enable deep, real-time analytics to help businesses make better decisions and create bigger impact – all with certainty and confidence.

It gives IT the operational visibility and control they need. It gives end users the great experience they demand. It gives the business real-time insight into business performance that most have never had.

In this post I’m going to focus on real-time analytics, but before I dive into how it works let me start with the context of traditional analytics. In the past people have tried to directly query the underlying databases of an application.  Unfortunately these databases are primarily designed for inserting small amounts of data. When complex queries run against it there can be a significant performance hit to the application, which is a very bad thing. The workaround was an Operational Data Store (ODS) that would replicate the data in its current structure so you could run queries without impacting the application’s performance. However, since the structure was designed to support transactional applications with short reads and writes, query performance and the ability to ask complicated questions easily weren’t good enough. This meant extracting the data from the ODS, transforming it and loading it into a data mart or data warehouse in a structure that was much easier to query. Given ever-growing data volumes query performance was still an issue, so the next step was adding indexes and aggregates. These workarounds put the end business user further and further away from real-time information. Often the delay in usable information means you’re looking at information that’s hours, days, or even weeks old. In the last few years there have been some disruptive technologies introduced that can simplify this. Though they’re actually quite effective, they come with an exorbitant price tag.

The Application Intelligence approach is considerably different. To get the benefits of Application Intelligence, the complete path the transaction takes through the end user device, the application server tiers, middleware, third party API calls, databases etc. is fully instrumented and the transaction context is propagated in real time. That’s how it sees everything and identifies performance problems and bottlenecks, often before end users are impacted. It also provides the opportunity to extract payload information such as the quantity of items in a shopping cart, revenue in executed transactions, dollar amount of funds transferred and so much more. AppDynamics introduced this concept with Real-Time Business Metrics. It’s allowed customers access to metrics like revenue, number of new accounts, support ticket volume, items shipped and campaign effectiveness in real-time. You can even correlate them with the performance of the application to see how changes in response times for end users impact business performance. It plucks all of this information out as it passes through the application and stores it in a data platform that’s easy to query. AppDynamics is taking this concept to the next level in the recently announced Transaction Analytics, which will extend the scale of the underlying data platform, enabling larger data volumes, more complex queries and impressive visualizations. In real time you can answer questions like:

  • What was the revenue impact by product category associated with the two marketing campaigns we ran on Black Friday?
  • Which Android users experienced failed checkout transactions in the last 24 hours, and what was in their cart at the time?
  • How many customers experienced a slow ‘submit reservation’ transaction in the last hour from a Chrome browser in New York and what was the total dollar amount of those reservations?
  • How many transactions originated from Tier 1 partners over the last 90 days and what was the resource utilization and revenue associated with those requests?

This is the transformation from APM to Application Intelligence. IT has leveraged APM to drive business success through application performance and efficiency. Application Intelligence extends beyond those benefits, allowing the business to use information to make better decisions and differentiate against the competition. In an era where IT and the CIO are expected to lead the business into the future, Application Intelligence is an incredible opportunity for leaders to drive success.

If you’d like to get started using AppDynamics to try business & operational analytics out for yourself, you can create a free account and start monitoring and analyzing your applications today.  If you are interested in being a part of our upcoming Transaction Analytics beta program, you can find more information here.

 

The post The new battleground in Analytics Part 2: Transforming APM into Application Intelligence written by appeared first on Application Performance Monitoring Blog from AppDynamics.

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