Splunk Mobile puts the power of Splunk in your hands. But with great power, comes great responsibility. That’s why this year with the release of Splunk Enterprise 9.0, we’ve shipped Splunk Secure Gateway (the backend service that powers Splunk Mobile) with even more features and tools to help you responsibly manage your mobile fleet.
In Cribl Stream and Cribl Edge, you can operate on your observability event data in flight, all the way down to the field level. Instead of writing complex regex to wrangle JSON and other structured formats, use Cribl’s built-in functions and extensibility to get the results you want. You’ll see formerly complex situations become easier to address and manage over the long term. In this blog, we’ll cover two troublesome use cases.
After months–or potentially, years–of hard work by teams across a gaming enterprise, when the day arrives for a game launch, the last thing your enterprise needs is slowdowns, glitches, outages or poor performance. It’s the death knell for any game, because for your avid gaming customers, there’s always something else (read: a game that isn’t yours) to check out.
We're excited to announce that starting with the new Splunk Cloud Product 9.0.2205 release, it's easier to create, manage and use private apps. Although Splunk is great by itself, we can all agree that the real value of Splunk comes from all the applications that Developers, SplunkTrust folks and Splunkers build.
Syslog is a very common method for transmitting data from network devices and open systems servers data to analytics platforms like Elastic and Splunk. As adaptable as syslog is, it still has significant constraints, which is a pain for most companies that lack the resources to scale their capability needed for syslog.
Stoking fears about the threat landscape is a popular approach, and one that I don’t particularly care for. Many will tell you that the threat landscape is constantly changing, that threats are getting more complex, and that actors are getting more sophisticated. “The whole world is getting more difficult and scarier, so buy our stuff!” There’s a ton of media sensationalism too, with the popular image of the hacker sitting at a computer, wearing a dark hoodie.
Most classical, batch-oriented machine learning systems follow the paradigm of “fit and apply”. In an earlier blog post, I discussed a few patterns on how to better organize data pipelines and machine learning workflows in Splunk. In this blog, we’ll review how you can organize your machine learning model in a new way: online learning.
At this point, you already know how powerful syslog is (and if you don’t, check out “Introduction to Syslog”). But here’s the thing: Scaling your systems to consume high volume syslog is like fighting zombies. Weird unexpected behavior and no easy solutions. Before you fight zombies, though, you have to understand them. So, here are the challenges for scaling syslog one by one.
