SkiStarRead the full case study
Using Splunk for automated log management
Every winter brings the definitive trial to SkiStar, the company which operates major ski resorts in Sweden and Norway. Alpine skiing continues to be the hub around which the enterprise revolves, but SkiStar also has an expanding set of peripheral businesses – from ski lessons to real estate projects.
SkiStar manages the majority of its IT inhouse. Much of the company’s data centre infrastructure was supplied by, and is supported by Proact. A large portion of business operations runs on systems which SkiStar have developed over the past 25 years. These applications cover a wide range of services, from hotel receptions and ski rentals to the online reservation website.
”There are obviously no turnkey systems for ski resorts available in the market, which is why we develop many of our business applications inhouse,” says Peter Larsson, IT manager at SkiStar.
Development is organised using agile methodology and integrated with applications maintenance and operations, in keeping with DevOps tenets. From this follows continuous application updates. SkiStar deploys new code releases practically on a daily basis.
Log data from IT operations is viewable in real time, for instant analysis.
Splunk enables resolution of more difficult issues compared with manual log analysis.
Troubleshooting is much quicker with automated log management, and this translates to more time to spend on development
Under a DevOps regime, following up and reviewing each new software release is an essential undertaking. The review procedure gives developers relevant feedback, e.g. regarding response times prior to and following the release, and if bugs targeted for correction in the new release are decidedly gone.
Application log files is the most important source for these insights, and these contain large volumes of often impenetrable data. To extract the desired feedback, SkiStar’s developers have been relegated to manually scanning the log files. But as the data centre operating environment grows increasingly complex, this task becomes more difficult and time consuming. For instance, SkiStar runs a cluster of web servers which are connected and load balanced to allow traffic to be redirected between servers. This presents developers not with a single but perhaps ten different devices which require individual troubleshooting.
The mere difficulty to overview and identify patterns in the vast volumes of log data could render it practically impossible to obtain the desired answers. SkiStar therefore went searching for tools to help them automate log management and make troubleshooting and software release reviews more efficient.
SkiStar decided to use Splunk, which has emerged as one of the premier tools for log data analysis – operational data generated by applications and systems. Splunk enables real-time decision support and automated analysis of sprawling, and many times arcane log files.
“We have designed custom dashboards with graphs displaying our key performance metrics in real time, allowing us to track instances of errors as well as application performance,” says Peter Larsson.
SkiStar’s struggles to compile and analyse log files from multiple systems is now history, as all relevant operational data associated with each application is compiled into a single interface.
The deployment of log analysis was made together with Proact, and their Splunk expert team. SkiStar has a long-lasting working relation with Proact, including delivery of servers, storage, tech support, and as advisors on data centre matters.
Generic tool with many use cases
Peter Larsson describes the many use cases for Splunk as a “both fascinating and terrifying” prospect. For despite that SkiStar has chosen a limited approach where Splunk is only used within IT, it is fundamentally a generic tool which can collect, index and analyse all kinds of machine data. This may involve business operations, security monitoring or customer activity.
“I can hardly see any limitations with Splunk as a platform. We can use any kind of data and make any type of queries on selected data, which is tremendously powerful.
“I can hardly see any limitations with Splunk as a platform. We can use any kind of data and make any type of queries on selected data, which is tremendously powerful.”
Read the full case study
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