five steps to better application performance

A Sumo Logic White Paper

Five Steps to Better Application Performance

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Introduction

Modern enterprises increasingly rely on custom-built applications to provide differentiated services to their customers and to improve employee productivity. These business critical applications are distributed, large-scale, and rely on in-house developed software as well as open-source and 3rd-party components, making them difficult to manage, monitor and troubleshoot. Managing these applications is further complicated by the combination of physical, virtual and cloud computing infrastructures in which these applications are deployed. In short, the job of managing and supporting today’s applications has never been more important—or more difficult.

The solution to many of the above issues can be found in one of the most overlooked and undervalued IT assets: log data. Managing logs requires a solution that, unlike today’s home-grown and on-premise solutions, is built from the ground up to handle the volume, type and location of today’s rapidly proliferating logs.

The following paper outlines the different ways that the next generation in log management and analytics can dramatically improve your applications—and thus your business performance. The five steps to better application performance fall into three broad categories:

+ Reducing application downtime

+ Improving application performance

+ Improving your end users’ experience

Reducing application downtime

Step 1: Troubleshoot and get quickly to root cause analysis

When something goes wrong in a distributed production application, troubleshooting and root cause analysis can take hours. The ability to quickly isolate the problematic application server, module, or even a single line of code dramatically reduces mean-time to identification (MTTI) and mean-time to resolution (MTTR). But to do so requires a powerful and fast log analysis system that enables you to look across your entire application and underlying infrastructure in one fell swoop. With application downtime translating directly to business performance and profitability, proper collection and retention, coupled with a powerful analytics tool for your logs, is key to immediate and accurate diagnosis and resolution.

The ability to quickly isolate the problematic application server, module, or even a single line of code dramatically reduces mean-time to identification (MTTI) and mean-time to resolution (MTTR).



Today’s next-generation solutions collect, process and analyze all your application logs--regardless of volume, type or location--and do it in real time. So you can query up-to-the-minute relevant information that your application generates, then quickly narrow down the root causes and get your application running again.

Step 2: Uncover unknown issues lurking within your application

Certain types of issues causing application failure are difficult to identify by asking questions via traditional query language. Often the issue has not been observed in the past and isn’t easy to express in a query, so the root cause remains hidden, eventually causing a major, long-lasting failure.

Identifying new patterns in log data, such as new types of Exception, require new learning-based analytics technology. IT needs to be able to remove the noise and find a new type of log message within millions of others without having to identify it using traditional query language. As a result, application operation teams can quickly address the issue rather than spend hours on writing queries and chasing ghosts in their log data.

Step 3: Use your logs proactively

Keeping your applications running should not involve fighting one fire after another. To keep applications running smoothly it is important to set up proactive monitoring based on precise rules that help detect issues before they turn into critical events. The right solution should be able to deliver proactive notifications based on specific conditions or new patterns seen in log data with near-zero latency.

Identifying new patterns in log data, such as new types of Exception, require new learning-based analytics technology.



Conditions can be extremely precise and can describe, for example, a number of occurrences of a specific type of exception. More importantly, they should be able to be configured to notify when patterns in logs deviate from baseline seen within data during normal application operations. These types of notifications improve response time and help uncover new important conditions within applications before outages occur.

Improving overall application performance

Step 4: Dig deep into how your application is performing at every level

Once problem diagnosis and resolution is under control and your applications are running with minimal downtime, you can focus on improving overall application performance. Understanding underlying application performance does not stop with profilers and visibility into how long particular method calls take.

In order to get a deep and actionable understanding of application performance in the world of distributed applications, IT teams must dig deep and understand the performance of:

+ Individual application components, modules and methods

+ Transactions that span many modules and systems

+ Underlying infrastructure such as servers and networks

...with this new technology you can extract long-running or distributed end-to-end performance metrics.



Next-generation log management technology enables your organization to access and understand all of these metrics without new instrumentation. You can capture fine-grained individual API call metrics from your logs to gain a deep understanding of where your application spends its cycles. And extract those metrics, analyze them further, and share them with engineering as evidence.

Furthermore, with this new technology you can extract long-running or distributed end-to-end performance metrics that represent far more meaningful metrics, such as end-to-end customer transactions that span multiple systems and even multiple applications. With end-to-end transaction performance information you get a holistic view of where the biggest time sinks are and exactly how they impact your end users. You can then set meaningful end user-relevant targets that your teams can work towards achieving.

Finally, you can capture and correlate how network, server, and third party software performance impacts your application performance. For example, you might find that the performance issue is not related to your application but rather is a result of lack of network bandwidth capacity in a particular location.

Make your applications better for your end users

Step 5: Analyze and improve your end users’ experience

Once the application is stable and performs well, the final step is improving the overall application from the end-user perspective. This is especially valuable for customer-facing and revenue-generating applications, where end-user satisfaction is critical to business operations. The teams who develop, operate, market and sell these applications need to be able to glean insights into which features are driving customer engagement, where usage drop-offs are, and what the overall user experience is.

Next-generation solutions help enterprises quickly gain a deep understanding of what works and what doesn’t for their end users. Without any new instrumentation you can collect and analyze how customers interact with your application (e.g. which features are being used, which features are hard to discover) or figure out which workflows lead to confusion and understand where customers drop off (e.g. which steps in the purchasing process take too long). Log-ins by user, page load times, URL requests, form posts, session IDs, engagement duration, and much more is already in your logs - you just need to get the right log analysis tool to tap into it.



The Sumo Logic Solution

Logs are the most underutilized and overlooked asset in application management. Sumo Logic’s log management and analytics service enables IT, DevOps and Engineering teams to put their logs to work to:

+ develop, manage, and operate their applications and underlying infrastructure by accelerating troubleshooting and root cause analysis;

+ improve application performance monitoring;

+ dramatically improve visibility into application and user behavior.

Sumo Logic’s next-generation log management and analytics service delivers actionable insights into application and infrastructure operations while dramatically reducing complexity and cost. As a massively scalable, multi-tenant service, Sumo Logic performs log data collection, processing, storage and analysis within a centralized and highly secure cloud-based platform. It effortlessly handles all log data, regardless of volume, type or location, enabling IT teams to uncover operational insights buried under terabytes of logs in seconds. The result: logs are transformed from an IT afterthought into a strategic business asset.

© Copyright 2013 Sumo Logic, Inc. All rights reserved. Sumo Logic, Elastic Log Processing, LogReduce, Push Analytics and Big Data for Real-Time IT are trademarks of Sumo Logic, Inc. All other company and product names mentioned herein may be trademarks of their respective owners.

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five steps to better application performance

Technology

application failure

problematic application

new patternsin log data

normal application operations

new type of log message

inlog data

business performance

new types of exception