Log Management for IT Ops: 5 Best Practices
February 23, 2015

Jim Frey
Kentik

Share this

Log data may be many things, but one thing is for sure – it isn't sexy. In fact, in most cases, it's downright ugly, because there are really no standards out there for how log data should be structured. For decades, this fact has kept log data from being a practical source of information for anything beyond a few specific use cases, such as watching for important events (like system reboots or config changes), security monitoring (like firewall blockages), or deep troubleshooting.

Times have changed, and the most recent crop of log management vendors have taken advantage of the steady growth in processor capacity to overcome the complexity and scale challenges of harvesting and analyzing all of the log data that an IT infrastructure continuously throws off. Now there are practical ways for taking advantage of the unique perspective and insights that log data can provide on a much broader basis.

In my last post, I shared some key findings from an EMA research report published last fall that dove into the ways in which log analytics is being used to support network operations. Building on that, following are a couple of the recommendations that EMA is making on how best to think about log data as part of an integrated management architecture and strategy:

1. Think twice before planning to store all log data

While most organizations are gathering log data for analysis on a continuous, ongoing basis, only a third are storing all log entries all the time. Interesting, those organizations considering log data to be "strategic" are actually much less likely to be storing all log entries all the time than those who consider log data to be "tactical". Strategic log users prefer instead to be more surgical, looking for specific types of logs or storing all log data only when certain trigger situations occur.

2. Consolidate your log analysis tools

We find that an overwhelming majority of organizations are either currently using one centralized log analysis system or are planning to consolidate the multiple tools that they have into a single system. This makes tremendous sense if you are trying to get the most out of your log data either in support of integrated operations or simply for better collaboration and cross-team sharing.

3. Focus on fast and intuitive search capabilities

The number one challenge voiced with respect to analyzing log data is knowing what to look for. It's not surprising then that the most popular feature that IT pros look for in a log data analysis solution is fast search. The latest generation of tools have made quick and effective search a high priority, and if you don't have such capabilities in your current system, you should consider an upgrade or alternative.

4. Don't implement log data analysis as an island

Consistently, we find that organizations are getting the most value when log data collection and analysis is integrated with other data sets and analysis systems. This can be done either via log data collection/analysis tools incorporating non-log data themselves or by openly sharing log data with other management aggregation systems. Some of the strongest values are being achieved by connecting the insights available from streaming log data with other performance monitoring measures, to proactively recognize performance degradations and related root causes.

5. Log data is relevant for BSM/ITSM

EMA has found a very high usage rate of network log data for higher level BSM and ITSM type initiatives, such as service quality monitoring, unified IT operations, and CMDB. Such usages were particularly high among those who consider log data to be strategic rather than tactical. So even though log data may be ugly, don't overlook its importance in supporting your highest level management objectives.

There were a couple of surprising dichotomies uncovered in the research study as well. For instance, the top reason people value log data is that they consider it to be cost-effective, however the second greatest challenge was identified as cost of tools. Another example involves just how effective log data is. The second highest perceived value was faster time to resolution than other data sources, however the number one challenge was knowing what to look for.

Clearly there is great and growing value in collecting and analyzing log data for IT planning, operations, and security. And while there are still challenges to be faced, best practices are emerging to help everyone understand what to expect and how to get the most returns on investments into log data collection and analysis tools.

Jim Frey is VP of Strategic Alliances at Kentik
Share this

The Latest

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 ...

July 12, 2017

Achieving broad competence in event-driven IT will be a top three priority for the majority of global enterprise CIOs by 2020, according to Gartner, Inc. Defining an event-centric digital business strategy will be key to delivering on the growth agenda that many CEOs see as their highest business priority ...

July 11, 2017

It's not especially surprising that a new IT survey shows that cloud use for business and government poses challenges. In significant numbers across the board, respondents cited cloud complexity, compliance and security, cost control, speed of delivery, and domain expertise as the cloud problems their organizations were working to overcome this year ...

July 10, 2017
Your organization's Application Management and IT Help Desk teams are your "first line of defense," and they also wear many hats. One of the biggest challenges they face is the management of application portfolios. To help ensure your application and help desk operations are effective and manageable, there are a few simple things that IT leaders can do ...