Chasing a Moving Target: APM in the Cloud - Part 2
Detection, Analysis and Action
February 21, 2013

Albert Mavashev
Nastel Technologies

Share this

In my last blog, I discussed strategies for dealing with the complexities of monitoring performance in the various stacks that make up a cloud implementation. Here, we will look at ways to detect trends, analyze your data, and act on it.

The first requirement for detecting trends in application performance in the cloud is to have good information delivered in a timely manner about each stack as well as the application.
We acquire this information via data collectors that harvest all relevant indicators within the same clock tick. For example: response time, GC activity, memory usage, CPU Usage. Doing this within the same clock tick is called serialization. It is of little use to know I have a failed transaction at time X, but only have CPU and memory data from X minus 10 minutes.

Next, we require a history for each metric. This can be maintained in memory for near real-time analysis, but we also need to use slower storage for longer-term views.

Finally, we apply pattern matching to the data. We might scan and match metrics such as “find all applications whose GC is above High Bollinger Band for 2+ samples.” Doing this in memory can enable very fast detection across a large number of indicators.

Here are three steps you can use to detect performance trends

1. Measure the relevant application performance indicators on the business side such as orders filled, failed or missed. And then, measure the ones on the IT side such as  JVM GC activity, memory, I/O rates.

2. Create a base line for each relevant indicator. This could a 1- to60-second sampling for near real-time monitoring. In addition set up a 1-, 10- and 15-minute sample or even daily, weekly or monthly for those longer in duration. You need both.

3. Apply analytics to determine trends and behavior

Keeping it Simple

Applying analytics can be easier than you expect. In fact, the more simple you keep it, the better.

The following three simple analytical techniques can be used in order to detect anomalies:

1. Bollinger Bands – 2 standard deviations off the mean – low and high. The normal is 2 standard deviations from the mean.

2. Percent of Change – This means comparing sample to sample, day to day or week to week, and calculating the percentage of change.

3. Velocity – Essentially this measures how fast indicators are changing. For example, you might be measuring response time and it drops from 10 to 20 seconds over a five-second interval or (20-10)/5 = 2 units/sec. With this technique, we are expecting a certain amount of change; however, when the amount of change is changing at an abnormal rate, we have most likely detected an anomaly.

Now That You Know ... Act On It

After the analysis, the next activity is to take action. This could be alerts, notification or system actions such as restarting processes or even resubmitting orders. Here, we are connecting the dots between IT and the business and alerting the appropriate owners. 

And In Conclusion

Elastic cloud-based applications can’t be monitored effectively using static models, as these models assume constancy. And the one thing constant about these applications is their volatility. In these environments, what was abnormal yesterday might likely be normal today. As a result, what static models indicate may be wrong. 

However, using a methodology comprised of gathering both business and IT metrics, creating automated base lines and applying analytics to them in real time can produce effective results and predict behavior. 

Albert Mavashev is Chief Technology Officer at Nastel Technologies.

Share this

The Latest

July 26, 2017

The retail industry is highly competitive, and as retailers move online and into apps, tech factors play a deciding role in brand differentiation. According to a recent QualiTest survey, a lack of proper software testing — meaning glitches and bugs during the shopping experience — is one of the most critical factors in affecting consumer behavior and long-term business ...

July 25, 2017

Consumers aren't patient, and they are only one back-button click from Google search results and competitors' websites. A one-second delay can bump the bounce rate by almost 50 percent on mobile, and a two-second delay more than doubles it ...

July 24, 2017

Optimizing online web performance is critical to keep and convert customers and achieve success for the holidays and the entire retail year. Recent research from Akamai indicates that website slowdowns as small as 100 milliseconds can significantly impact revenues ...

July 21, 2017

Public sector organizations undergoing digital transformation are losing confidence in IT Operations' ability to manage the influx of new technologies and evolving expectations, according to the 2017 Splunk Public Sector IT Operations Survey ...

July 20, 2017

It's no surprise that web application quality is incredibly important for businesses; 99 percent of those surveyed by Sencha are in agreement. But despite technological advances in testing, including automation, problems with web application quality remain an issue for most businesses ...

July 19, 2017

Market hype and growing interest in artificial intelligence (AI) are pushing established software vendors to introduce AI into their product strategy, creating considerable confusion in the process, according to Gartner. Analysts predict that by 2020, AI technologies will be virtually pervasive in almost every new software product and service ...

July 18, 2017

Organizations are encountering user, revenue or customer-impacting digital performance problems once every five days, according a new study by Dynatrace. Furthermore, the study reveals that individuals are losing a quarter of their working lives battling to address these problems ...

July 17, 2017
Mobile devices account for more than 60 percent of all digital minutes in all 9 markets profiled in comScore's report: Mobile’s Hierarchy of Needs ...
July 14, 2017

Cloud adoption is still the most vexing factor in increased network complexity, ahead of the internet of things (IoT), software-defined networking (SDN), and network functions virtualization (NFV), according to a new survey conducted by Kentik ...

July 13, 2017

Gigabit speeds and new technologies are driving new capabilities and even more opportunities to innovate and differentiate. Faster compute, new applications and more storage are all working together to enable greater efficiency and greater power. Yet with opportunity comes complexity ...