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How Log Data Could Help Win Your Fantasy Football League

This time of year, the waiver wire is open more than outlook, and in those offices, fantasy football is the great unifier

Log data is a powerful resource being overlooked by businesses. The value that may be hidden in the data is so large, it is borderline reckless not to manage your log data. The main reason this is occurring, is because the beneficiaries of this information are often the end business users, who couldn't tell you the difference between a log and a blog. So there is no urgency to invest in a solution.

This is where I step in, if you are in DevOps, software engineering, system administration, etc and want your company to invest in a log management solution; this is the article to show them. If you are a business user trying to understand the value of log data, then you are in the right place.

This is the time of year when the waiver wire is open on monitors across the country more than outlook, and in those offices, fantasy football can be the great unifier.

logentries-fantasy-football

DevOps and sysadmins battling it out with accounting and upper management over who to start on Sunday. Let us imagine, every player in the NFL as a server, application or website, who creates logs on every single action they do during a week of practice.

Every handoff, every throw, every fumble. If a player even moves it generates a log.

Log management software would revolutionize the way you would look at your team. Let me explain:

Aggregate Live Tail:

The first (and most important) characteristic, is a way to organize every piece of log data for all of your players, and be able to view these logs in real time. You would have one centralized location to view every movement as it happens, live.

You could search for data in the logs such as "fumble" or "injury" and logs could tell you that 2 of your starting running backs fumbled 3 times in practice, or your quarterback strained his hamstring on Thursday. If you were viewing this in real time, you could pick up a QB for the week, or make a trade before anyone else read the report online in the morning.

Tags and Alerts:

The live tail is fine at home on your couch, being able to watch the screen for logs. But, what if your star player is having a bad practice at 2PM on a Monday? With tags and alerts, you could set alerts to be sent no matter what time of day, if the word "injury" showed up in your logs.

Receiving an email the second it happens, could be the difference between picking up that backup, or waiting until your opponent finds out and snags him. This way you are aware of the status of your important assets at all times and can be alerted to problems or bugs.

Inactivity Alerting:

Did your star wide receiver get in trouble with the team and hasn't caught a ball all week? Did he say something negative about the quarterback's mom and not getting targeted? You could set an alert if something isn't happening.

You could set the "my wide receiver hasn't caught a ball in two days" alert. What this does, is alerts you to an interruption before it becomes too big of a problem. If you are tracking logins on your app and you don't see any for a 6-hour period, wouldn't you wonder why?

Team Annotations:

There is always that one person in the office, who just seems to know exactly who to play, and can provide insight that not everyone else has. With team annotations you could allow your own personal insider to write notes on certain players in your dashboard so you could see them in your view.

This allows you to get that insider information, even when he takes that vacation to Arkansas in the middle of the season. He would be able to log on, and insert notes on players and logs that would populate in your screen, eliminating the need for him to physically be near you.

Anomaly Detection AKA The Sleeper watcher:

Hunting the waiver wire can make or break your season. Just ask that guy who always seems to snag the backup when your starting player goes down for the season. With this feature, you will be that guy. On Sunday (the most important day of the week), you are busy checking your lineup, getting the snacks ready, and hopefully (after this article) grabbing a calculator to add up all your fantasy points.

With all these distractions, anomaly detection could be set to alert you when a certain threshold is broken. Set an alert for when that 2nd string running back's carries increase 10%, or your slot wide receivers yards-per-reception average starts to rise above 7 to determine he is now the deep threat on the team.

Unfortunately, we don't live in a world where we can extract log data from NFL athletes (well, not to my knowledge at least). We do however, live in a world where all of these features can be used in a way that might even be more constructive than fantasy football. Log data contains some mission critical information that can lead to better customer service, performance, and answers to problems that haven't even come up yet.

As much as I wish for a world where I use log data to win my fantasy leagues, I am going to have to settle for this one. To bring back the fantasy football analogy, there are a multitude of types of players in the league and there are multiple log analysis players.

You have your proven, reliable, players who aren't going to have much upside, but you know what you are getting. Then, you have the players that are extremely volatile; one week they might outscore your opponent's entire team, while the next 3 weeks they only put up 3 points. Lastly, there is the player who you take in the 2nd round who has incredible upside, will consistently get you points and provide the most value at the drafted position.

With whatever draft you are in, and whatever position, everyone should be targeting Logentries at the top of their log management draft board.

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More Stories By Trevor Parsons

Trevor Parsons is Chief Scientist and Co-founder of Logentries. Trevor has over 10 years experience in enterprise software and, in particular, has specialized in developing enterprise monitoring and performance tools for distributed systems. He is also a research fellow at the Performance Engineering Lab Research Group and was formerly a Scientist at the IBM Center for Advanced Studies. Trevor holds a PhD from University College Dublin, Ireland.

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