In this day in age, businesses rely heavily upon their website as a means of driving sales and reaching customers. It is usually the first point of contact between a potential customer and the business, and thus, it commands a level of investment. Because of this, it can be frustrating and upsetting to have one’s web page hacked and rendered useless.
You’re in the process of creating and launching new softwareand you want it to be as stable as possible. Or, maybe your software has been running for a while, but you’re frustrated with the bug-reporting workflow in place. Either way it’s time to look for a crash reporting process that fits your application. This leads to a natural question: Should we build it? Or should we buy it? To expand on this question, which will be better for my business?
Most of us here at BugSplat spend the majority of our day at our computer. If you are reading this post, there's a good chance that you probably do too. And, like us, you probably expect that computers are just supposed to work for you. However, in my experience, this close relationship we share with our machines just expands the realm of possible annoyances we encounter day-in and day-out.
ServiceNow® is facing one of the biggest opportunities to date: developing a self-healing IT environment that makes proactive IT support a reality. Although the concept of self-healing has been around for at least a decade, the ability to achieve it has fallen short. A lack of system intelligence stopped us from predicting and preventing many issues without human intervention somewhere in the process. AI technology is changing that paradigm.
If you are using InfluxDB to monitor your data and systems, then alerts may be an essential part of your workflow. We currently have a system for monitoring your data whether it enters a critical or non-critical state. Here I’m going to give a detailed guide on setting up alerts using our InfluxDB Cloud product as well as some best practices for having a good experience using alerts.
In sync with the upcoming release of Splunk’s Machine Learning Toolkit 5.2, we have launched a new release of the Deep Learning Toolkit for Splunk (DLTK) along with a brand new “golden” container image. This includes a few new and exciting algorithm examples which I will cover in part 2 of this blog post series.
In part 1 of this release blog series we introduced the latest version of the Deep Learning Toolkit 3.1 which enables you to connect to Kubernetes and OpenShift. On top of that a brand new “golden image” is available on docker hub to support even more interesting algorithms from the world of machine learning and deep learning! Over the past few months, our customers’ data scientists have asked for various new algorithms and use cases they wanted to tackle with DLTK.
You may already be using Splunk to ingest data and generate alerts and dashboards so you can take quick action on problems, but did you know you can quickly start a VictorOps trial and in three easy steps, have great Splunk alerts escalated to the right teams and people with a mobile app notification, SMS message or a live phone call?
Contact or Call... Center or Centre... Call them what you will, but, wow, we’re calling them and we’re counting on them now more than ever! The dramatic shift to remote everything has flooded Contact Centers with more calls, while also requiring providers to adopt remote, distributed architectures.
For those of you with some gray hair working in the manufacturing business, remember when order intake plunged suddenly by more than 40%? Remember when CFO and Controllers ruled the company, driving painful cost-cutting programs to counter double-digit business losses? It was the time of the Economic and Financial Crisis 2007/08, which forced manufacturing organizations to stare in the abyss.
