Every millisecond, humans generate significant volumes of data, from various IoT devices such as our wearable devices to daily activities such as internet surfing and tracking our workouts. Data continues to accumulate. Statista estimates that by 2025, the amount of data will have increased to 180 zettabytes. That's far too much information.
A typical bit of feedback I have had during my time at Splunk is that the Splunk Machine Learning Toolkit (MLTK) looks nice and all, but how are we supposed to get started using it? Choosing the right technique, let alone the right algorithm can be a daunting task for those who are unfamiliar with machine learning (ML). We’ve been thinking long and hard about how we can help offer more prescriptive introductions into using ML at Splunk and I’m pleased to present our set of MLTK deep dives.
Synthetic monitoring can be one of the most powerful tools in your DevOps team’s toolkit, especially for the SRE, yet is one that is often overlooked by people building out a reliability mindset. Synthetic monitoring permits you to simulate any transaction or interaction users can have in your website or app, from places around the world, as often as you’d like.
The question isn't whether an incident will happen: it's when it will happen. Systems will crash. Software will fail. Vendors will suffer an outage of their own. It's your job to be prepared for these problems, and incident severity levels are one of the tools you need. Incidents have varying impacts on your business and customers. Incident severity levels are how you classify their impact and manage your response.
It's always interesting to hear what feature requests dashboard users share with our product team. Sometimes it's big things — such as being able to set tokens on drilldowns — and sometimes it's little things. In Splunk Cloud Platform 9.0.2208, we've included a handful of Dashboard Studio "little things" updates.
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.
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.
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.
Splunk embodies the top 5 principles of unified security and observability, and has been an expert in log management, security, and observability for years.
I'm excited to announce that Splunk Data Manager now supports onboarding of Google Cloud Platform (GCP) data sources, effective immediately. With this launch, you can now get the benefits of Splunk data analysis for the high-value events generated by Google Cloud when you onboard GCP data sources into Splunk using Data Manager.
