What is the business impact? – ITOA use case #4

In the first three parts of this series I’ve covered common ITOA use cases we’ve seen across our customer base:

Analyze the business impact

The fourth use case, analyzing business impact, is a way to quantify the value of all the work IT Operations professionals put in to making application environments run as smoothly as possible.  Most of the time, IT is viewed as a cost center because when a revenue generating application has an outage for example, IT Ops is an easy team to point a finger at.  However, by leveraging our new offering, Application Analytics, Operations teams now have a solution that enables them to have a more intelligent discussion about operational data and the associated business outcomes.  This enables Ops to have more positive conversations that revolve around the added value that the team provides to the business.

Consider the example below; the Ops team was able to build a dashboard showing the dollar amount associated with normal, slow, very slow, and error transactions.  The error transactions are the requests that did not complete as expected and resulted in no revenue.  This is the money the business is leaving on the table due to an application that isn’t performing well.  If the dollar value associated with these error transactions ($161K) is half of what it was during the same time period yesterday due to the work the Ops team completed by finding and fixing performance bottlenecks… they’ve added a very quantifiable number to the company’s top line.

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Suppose there was an unplanned outage that affected a large number of users – wouldn’t it be great if marketing could get a report showing all the users that were affected during the checkout process and the exact items that were in their cart at the time so they could kick off a ‘win back’ campaign?  With Application Analytics, Ops teams can make that wish a reality.

By filtering the set of transactions to only those with errors during a checkout process for a particular time range, and adding in the user IDs, product category, and product names, Ops teams can come out of a negative situation (like an outage) looking like a hero to their line of business peers.

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Not only can Ops teams analyze the business impact of the troubleshooting they do on a regular basis, they can also use Application Analytics to identify anomalies and use this information to start the triage and troubleshooting process instead of only analyzing the results of their work.  For example, Ops teams can leverage Application Analytics to discover the answers to these kinds of questions and proactively address issues:

  • Why is the number of TVs sold in the past 15 minutes far below normal?
  • Why are there a large number of slow transactions associated with trying to add a book to an online shopping cart?
  • Why did a particular customer’s package not get delivered?

Application Analytics provides a real-time view into how the business is correlated with the operational metrics they interact with on a daily basis, all with automatic propagation of business context in the form of business transactions and no application code changes required.

In the next post we’ll talk about the fifth common ITOA use case, creating an action plan.  In the meantime I encourage you to sign up for a free trial of AppDynamics to try these use cases out for yourself.

Prioritize with business context – ITOA use case #3

In the first two posts of this series we’ve taken a look at two common ITOA use cases:

I recommend spending some time familiarizing yourself with the first three use cases I’ve highlighted, they lay some important groundwork for the rest of this series. With that, let’s dive into use case #3 — prioritizing issues and opportunities.

Prioritizing issues and opportunities

Once operations teams isolate the root-cause of an application performance issue, the next step is to determine how to rank and prioritize these different issues. Oftentimes these fixes are simply prioritized in the order in which they came into the support team. However, what if the most recent root-cause that’s been discovered is one that is directly impacting revenue, not the support ticket that was filed first?

Let’s look at an example to illustrate this point. Put yourself in the shoes of an application support person and look at this short list of open issues that are in your queue:

  • November 1, 2014 – Issue #1075 – Open for 14 days
  • November 10, 2014 – Issue #1091 – Open for 4 days
  • November 12, 2014 – Issue #1087 – Open for 2 days

Which one do you tackle first? Most likely the one that has been open the longest, right? Prioritizing that ticket will help you, as an application support person, improve the KPIs you get measured on like average time taken to close out a ticket.

Now let’s take another look at that same list but this time we will add in one data point that indicates the business context of the particular issue.

  • November 1, 2014 – Issue #1075 – Open for 14 days – Related to ‘update profile’ function
  • November 10, 2014 – Issue #1091 – Open for 4 days – Related to ‘search products’ function
  • November 12, 2014 – Issue #1087 – Open for 2 days – Related to ‘checkout’ function

Now which one would you prioritize? A segment of users not being able to update their profiles or search for certain products is obviously not good for the end user experience, but if people are having issues checking out of your application, that means revenue is being directly impacted. Updating preferences in a profile is not nearly important to the business as making sure money is flowing in. That business context allows operations teams to focus their efforts on the issue with the largest potential business impact. In the Application Intelligence Platform, that business context is what we refer to as a business transaction.
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Simply put, a business transaction is a type of user request. AppDynamics automatically buckets these different types of user requests and baselines their normal behavior out of the box. Actions like ‘submit order’, ‘get quote’, ‘login’, ‘add to cart’ are all examples of business transactions.

Getting this business context, and automatically correlating it with the different performance issues that occur in the application, give operations teams that additional data point they need to stack rank remediation effort and tackle the large problems that are impacting the business first. And because AppDynamics dynamically baselines each business transaction separately, you’ll know when a certain business transaction breaches what we’ve defined as ‘normal’ performance. This allows Operations teams to create alerts and other automated actions when a business transaction has abnormal performance. For example, you could automatically create an incident in your ticketing system (ServiceNow, PagerDuty, VictorOps, Jira, etc.) anytime a really important business transaction deviates from the baseline, ensuring it gets proper prioritization within your team so they can proactively address the issue before it affects other end users.

By leveraging business transactions, Operations teams can easily understand how their technical perspective of the health of the environment relates to what really matters — the health of the business.

In the next post we’ll explore the fourth common IT Operations Analytics (ITOA) use case, analyzing business impact. In the meantime, discover how customers like Cisco, Edmunds, Fox News, OpenTable, and Salesforce.com have leveraged the power of business transactions by signing up for a free trial of AppDynamics and trying it out for yourself.

If you can’t see it, you can’t manage it – ITOA use case #1

“There was 5 exabytes of information created between the dawn of civilization through 2003, but that much information is now created every 2 days, and the pace is increasing…,” – Eric Schmidt, Former CEO, Google.

If IT leaders hadn’t already heard Schmidt’s famous quotation, today they are definitely facing the challenge he describes. Gone are the days when IT leaders were tasked with just keeping an organization running, now IT teams are charged with driving innovation. As businesses become defined by the software that runs them, IT leaders must not only collect and try to make sense of the increasing amount of information these systems generate, but leverage this data as a competitive advantage in the marketplace. This type of competitive advantage may come in many forms, but generally speaking, the more IT leaders know about their environments and the ways end users interact with them, the better off they (and the business) will be. Gleaning this type of insight from IT environments is what analysts refer to as IT Operations Analytics (ITOA). ITOA solutions collect the structured and unstructured data generated by IT environments, process that data, and display the information in an actionable way so operations teams can make better informed decisions in real-time. I’d like to discuss five common ITOA use cases we see across our customer base in this series, starting with visualizing your environment. In the rest of this series I’ll examine each of the other use cases and describe how a solution like the Application Intelligence Platform can address each and in turn provide value for operations teams.

The five common ITOA use cases I’ll delve into are:

  • Visualize the environment
  • Rapid troubleshooting
  • Prioritize issues and opportunities
  • Analyze business impact
  • Create action plans

Visualizing the environment

The first use case refers to the ability for an ITOA system to model infrastructure and / or the application stack being monitored. These models vary in nature but oftentimes are topological representations of the environment. Being able to visualize the application environment and see the dependencies is an important foundation for the rest of the use cases on this list.

In the Summer ‘14 release announcement blog, we highlighted the enhancements we’ve made in regard to our flow maps, which is the visual representation of the application environment, including application servers, databases, web services, and more.

What’s great about the AppDynamics approach is that this flow map is discovered automatically out of the box, unlike legacy monitoring solutions that require significant manual configuration to get the same kind of view. We also automatically adjust this flow map on the fly when your application changes (re-architected app, code release, etc.). Because we know all the common entry and exit points of each node, we simply tag and trace the paths the different user requests take to paint a picture of the flow of requests and all the interactions between different components inside the application. Most customers see something like the flow map below within minutes of installing AppDynamics in their environment.
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Now a flow map like this is obviously very valuable, but what happens when the application environment is very large and complex? How does this kind of view scale for the kinds of enterprise applications many AppDynamics customers have deployed? Environments with thousands of nodes and potentially hundreds of tiers? Luckily for our customers, the Application Intelligence Platform was built from the ground up to handle these kinds of environments with ease. There are two characteristics of our flow maps that enable operations teams to manage flow maps of large-scale application performance management deployments; self-aggregation and self-organizing layouts.

Self-aggregation refers to our powerful algorithms that make these complex environments more manageable by condensing and expanding the visualization to enable intelligent zooming in and zooming out of the topology of the application. This allows us to automatically deliver the right level of application health indicators to match the zoom level.

For example, this is what a complex application could look like when zoomed all the way out:
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As one zooms in, relevant metrics information becomes visible:
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Until you are zoomed all the way in on a particular tier and can see all of the associated metrics you’d care about:
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The ability to iterate back and forth between a macro-level view of the application and a close-up of a particular part of the environment gives operations teams the visibility they need to understand exactly how an application functions and how the different components interact with each other.

Self-organizing layouts relates to our ability to automatically format the service and tier dependencies by using auto-grouping heuristics to dynamically determine tier and node weightages. By leveraging static data (like application tier profiles) and dynamic KPIs (like transaction response times) we organize the business-critical tiers in a way that brings the most important parts of the application to the forefront depending on the type of layout you prefer.

One can automatically group the flow map into a circular view:
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You can let AppDynamics suggest a layout:
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You can create a custom layout just by dragging and dropping individual components:
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And you can auto-fit your layout to the screen for efficient zooming in / out:
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You’ve seen how AppDynamics can visualize individual applications, but what if, like many of our large enterprise customers, you have many different complex applications that have dependencies on one or more other applications? How does one obtain a data-center view to understand, at a high level, what application health looks like across all applications?

With the cross-app business flow feature, customers can do just that. AppDynamics even supports role-based access control (RBAC) so administers can limit user access to a particular application. We allow customers to group, define, and limit access to applications however makes the most sense for their individual environments and for their business.

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As you can see, AppDynamics provides a great way for IT Operations teams to discover and visualize their application environment. We automatically map the application out of the box, we provide flexible layout options so customers can customize the view to their liking, and offer a way for Ops teams to understand how different applications interact with each other.

In the next post in this series, we’ll discuss how the Application Intelligence platform can address the second common ITOA use case, rapid troubleshooting. In the meantime, I encourage you to sign up for free and try AppDynamics for yourself.