Log Management

5 Weird Use Cases for Log Management

Paul Stefanski
Paul Stefanski

We’re all familiar with the typical use cases for log management, such as monitoring cloud infrastructures, development environments, and local IT infrastructure. So we thought it would be fun to cover some of the less usual, more wild use cases for log management, just to show that log management tools are more versatile, and more interesting, than they may seem. If any of these use cases look too interesting to ignore, let us know and we can do a full article on them!

1. Monitoring Household Video Game Time (Or Netflix, HBO, etc.)

I think we all saw our gaming and streaming hours increasing during the COVID-19 lockdowns. For parents, the value of tracking game and stream time is an easy sell. Most parents want to limit their young children’s screen time. There’s nothing wrong with games and shows, but most agree that variety and moderation is the key to a fulfilling lifestyle. Any adult can make use of monitoring their own gaming and streaming. For the rare few of us with the power to self-moderate unassisted, there’s less value, but most of us are used to seeing hours, even days, disappear into screens. Maybe it won’t motivate us to change anything, but at least we will have some visibility into our screen time.

2. Collecting data on your IOT devices

I don’t have any kids, but the other day I had a pregnant friend over and some of our conversation was naturally about babies. Within twenty-four hours, Amazon was advertising me baby diapers. Which of my eleven networked devices recorded and sent that information? It’s no secret that many IOT devices, like Alexa, Google Home, and our TV’s are constantly collecting data on us. It’s about time we return the favor. With plug and play observability solutions like observIQ supporting a wider range of sources and log types every day, it’s becoming much easier to monitor the tech that’s monitoring you. You could check, for example, how frequently applications on your IOT devices are active, when they’re communicating with the cloud, and maybe even get some insight into what data they’re sending out.

3. Checking which apps on your PC are hogging resources

I can’t count how often my computer’s fans are running at full tilt while I’m doing something innocuous, like word processing. I’m always left wondering, what is my computer doing in the background that’s heating up its internal components so much? The big fear is always that someone has managed to sneak a crypto-mining or data-stealing program onto your machine, but usually it’s just bloatware that came with some free application, or a confused application eating resources to do a whole lot of nothing. On PC, you can see real time hardware usage with task manager, and there are a host of other hardware monitoring softwares for PC and Mac, but local hardware monitoring applications don’t provide the same depth of information as log management platforms, nor can they effectively track usage over time or present information on useful dashboards.

4. Generating insights from trading bot activity

It’s always fun when a human gets a rare chance to play the meta game against machines and win. When it comes to day trading, bots make up 80% of all trades. Mostly that’s actually due solely to the fact that bots can trade faster, and not that they’re actually smarter than us when it comes to financial predictions. The stock market is a complicated beast that responds to literally everything our species does, our planet does, and sometimes it even seems like it responds to the stars, as if connected to some otherworldly informant. Ultimately, a lot of it feels random, and whether that’s true or not, we’re a long way off from any AI understanding what’s really going on. (And manipulating prices by moving large amounts of wealth around is not the same as understanding how and why prices are what they are. AI has the same data to look at as everyone else, and it’s no less obscure just because they can do math faster.)

So where does log management come in? Well, if you have access to a network of machines running trading bots, each of those bots will behave differently, based on their programming and instructions. Collectively, they can generate trends that become apparent to an intuitive mind before they are clear to the bots themselves. Sure, you could hook a bot up to that information pipeline and instruct a bot to trade based on the other bots’ trades, but what’s the fun in that when you can watch for trends yourself and take advantage of a big swing? It doesn’t always work, so this is certainly not financial advice, but it’s quite satisfying when it pays off.

5. Learn about your AI as it learns about you

Personal assistants are taking hold. Siri, the original AI assistant that began as an iOS app that Apple purchased and folded into its OS, was quickly followed by Amazon’s Alexa and Google’s Personal Assistant. After that, Samsung released Bixby, and a handful of other small players emerged over time. The original version of Siri was worse than an average high school coding project would be today, but back in the early 2010’s, it was the first program that could reliably listen and understand what a human was saying to it. Now our AI understands almost everything we say, incorporating context and tones to derive deeper significance. They can make appointments for us and remind us of things we may have forgotten even without us asking for a reminder. How does it know all of that?

It’s all linked to your profile on whatever platform your AI assistant of choice lives on. Monitoring your AI assistant is similar to monitoring your IOT devices, but more focussed on one application and often on only one device – your phone. With the right log management set up, you can see when your AI is sifting through your phone’s data, other applications, and listening in on your daily life, to ship it off to the cloud for processing and incorporation into your digital clone. Different people regard our machines’ surveillance of us in different ways, but whether you think it’s good or bad, it’s happening, so why not get some insight into exactly who Siri thinks you are?

Why use observIQ

If any of these use cases look interesting to you, check out observIQ. observIQ is the easiest log management platform to use, especially for those who are new to observability. It has all the log management features expected in a robust observability solution, wrapped in an approachable package with an intuitive user interface. Let us know on twitter if you want to see a longer article about any of these use cases, or think of one of your own you want to share.

Paul Stefanski
Paul Stefanski

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