Category: Tech Talk
Practice What You Preach: Capgemini’s Journey of IT Transformation
Practice What You Preach: Capgemini’s Journey of IT Transformation
A Q&A with Guest Speaker, Forrester Senior Analyst, Rich Lane We sat down with guest speaker Rich Lane from Forrester to discuss the core issues IT Operations leaders face as they evolve towards intelligent, automated operations (AIOps). Then, we kept him for a Q&A to dive deeper into the biggest challenges facing the adoption of… Continue reading Why AIOps? Why Now?
Why AIOps? Why Now?
Our CMO, Murali Nemani sat down with our CPO, Michael Nappi, to discuss the SolarWinds breach that occurred last December.
Enhancing Our Security Posture – Post SolarWinds Breach
As “good enough” legacy monitoring technology fails to keep up with the speed of the rapidly evolving AIOps market, improved analytics and automation dictate the leaders in operating and running IT.
A Leader of the Pack: ScienceLogic Recognized in Forrester 2020 AIOps Wave
As ScienceLogic refocused to a SaaS-based delivery model, we needed to find a relational database that supported our requirements.
Shifting From On-Premises to Cloud Architecture with Amazon Aurora
The promise of AIOps for Service Providers & Enterprises is to enable the collection of data, processes, and storage at scale as well as to derive actionable insights that help drive automation.
The Technical Building Blocks of a Modern AIOps Platform
What if you could ensure the right model is deployed for each device and metric you monitor—without hiring a data scientist or even writing one line of code?
Why You Don’t Need a Data Scientist: Automatically Selecting the Right Anomaly Detection Model
In my last blog, I highlighted incident response as a candidate for automation for ITOps. In this post, I’ll look at how the troubleshooting process can be automated to help reduce incident MTTR.
How to Reduce MTTR by Automating Incident Troubleshooting
Data scientists waste a lot of time preparing and cleaning data. But when you use ScienceLogic as your AIOps platform, cleaning data is already handled, so your data scientists can focus on analysis.
Setting Your Data Scientist Free With Clean Data
Most ITOps teams have data collection and alerting in place, but with organizations pushing for more automation, acting on that data is the next big step.