Today’s enterprises aspire to achieve IT process automation to help manage their infrastructure more efficiently and effectively. An AIOps platform like SL1 from ScienceLogic makes IT automation possible by discovering all devices, configuration, ingesting data from all resources, and creating an operational data lake populated with accurate and timely data. That data ensures the best possible result when automating simple, repetitive tasks.

Maintaining trust in the business services your customers rely on is everything. With ever-increasing customer expectations and the promise of ‘always-on’ services, poor digital experiences and outages can cause significant harm to your business. The Interlink Software AIOps and Observability platform strengthens IT teams’ capability to deliver more reliable, available digital services and reduce the risk of customer impacting disruption.

Digital business services are spread across on-premises, cloud, and SaaS environments. But assuring great service performance is increasingly difficult. Organizations are shifting from device-based monitoring to business service-based monitoring in order to meet the increasing expectations of end users and the business. And now you can see SL1 Business Services in action—without scheduling a live demo or free trial.

It may be counterintuitive to tackle a problem without knowing exactly what the problem is, but an incident commander often does just that. In fact Rob Schnepp—founding partner at Blackrock 3, an Alameda, California-based incident management consulting group—says identifying the root cause of an incident is typically secondary to addressing the symptoms.

ITOps professionals know that their AI and automation goals can only be achieved with high-quality data. How can you get good-quality data? Incident Intelligence. In this on-demand session from Pandapalooza, our Group Product Manager, Orr Ganani, joined our Regional VP of Professional Services Sales, Jordan Gamble, to discuss Incident Intelligence and its benefits. Read on to learn more about Incident Intelligence from this webinar.

This is the final blog of a three-part blog series on Observability—the challenges and the solutions.

In our research for the inaugural State of Availability Report, we asked 1,900 engineers about mean time to detect (MTTD) and mean time to recovery (MTTR) as two leading incident management Key Performance Indicators (KPIs) strongly associated with availability. We learned that less than 15% of respondents are tracking their MTTD. It takes twice as long to discover an issue than it does to resolve it.

Today, many digital technologies in IT can operate with minimal human intervention. However, while they boost productivity and drive growth, any failure or unpredictable behavior can pose a significant challenge for the ITOps and DevOps teams. So, effective IT incident management helps minimize the impact of incidents on business operations and ensures that systems are restored as quickly as possible.

It’s no secret that every ITOps leader can face an ever-increasing amount of alerts. Since the dawn of digital, alerts have served an important purpose. Sometimes all those alerts can become overwhelming noise, and sorting out what is and is not a priority can become challenging. The good news is that artificial intelligence (AI) and machine learning (ML) are adept at processing large data sets in real time, looking for patterns and being able to aid in decision making.