Forum Release: Accelerating & Securing Your Digital Transformation with AIOps
Introducing ScienceLogic Forum. Designed to expand your ability to see, contextualize, and act to reinforce the framework of AIOps.
Operations | Monitoring | ITSM | DevOps | Cloud
The Place Where Modern Operations & Technology Come Together
The latest News and Information on AIOps, alerting in complex systems and related technologies.
Hey! Let's talk AIOps-Part 2
Welcome back! In the previous blog, we discussed what AIOps is and the significant role it plays in ITOps with our panelists: Carlos Casanova, Principal Analyst at Forrester, and Gowrisankar Chinnayan, head of product management at ManageEngine. In this blog, I am going to walk you through the rest of our discussion. Our talk revolved around the reasons why organizations should adopt AIOps.
Sponsored Post
How Is AIOps Transforming the Future of IT Operations?
Did you know that Artificial Intelligence began as an experimental program? However, as the global spending on Artificial Intelligence stood at over $118 billion in 2022 and continues to grow, it's become apparent that this is one experiment that's here to stay and will completely transform the way business operations are undertaken.
AIOps for Managed Service Providers
AIOps for Managed Service Providers: modernize and monetize your monitoring offering. For Managed Service Providers, a highly competitive market and the rapidly changing digital landscape can present a threat or an opportunity.
ITIL and CI/CD
In the world of IT, there are two main approaches to managing changes—the information technology infrastructure library (ITIL) and continuous integration and continuous delivery/deployment (CI/CD). Both have their own benefits and drawbacks, so it’s important to understand the difference between them before deciding which one is right for your organization. In this article, learn about the difference between CI/CD and ITIL, and find out which approach is best for your needs.
Sponsored Post
Transcending Observability for a Cloud-Native Future
With digital transformations continuing apace and the popularity of cloud-native and microservice-based applications and architectures growing, Gartner sees investments in such technologies and services increasing, predicting that "cloud-native platforms will serve as the foundation for more than 95% of new digital initiatives by 2025 - up from less than 40% in 2021."
What is AIOps (artificial intelligence for IT operations)?
Deploying software to support the work of an enterprise is an increasingly complex job that’s often referred to as ‘devops.’ When enterprise teams started using artificial intelligence (AI) algorithms to more efficiently and collaboratively run these operations, end users coined the term AIOps for these tasks.
How to Help Teams Create Optimal Infrastructure for Availability
Teams are locked into a cycle of suffering characterized by the feeling that they are sprinting just to stay still. This morale and productivity-destroying state is caused by an inability to find time to save time. Our new research, The State of Availability Report 2022, discovered that teams know what they want to do—harness cloud and DevOps practices and tools to advance digital transformation—but something’s getting in the way.
Just Maintaining Availability? Try Building Stability
Today’s customers see availability as a given. What do they really want? Bigger, better technology with new features and faster platforms. But, according to our recently released Moogsoft State of Availability Report, teams burn their time, money and energy on incident management. In fact, engineers overwhelmingly report that incident management takes up most of their time.
Sponsored Post
Is AIOps Bad for Your Business?
With advances in the field of IT, the amount of data needed to manage IT Operations has grown. In particular with more complex environments, such as the SaaS world, the amounts of data and raw data needed to manage operations have grown exponentially. Managing data manually has become a waste of professionals' skill sets, which could be better used in analyzing and applying the conclusions drawn from the raw data, and not dealing with basic issues that may arise.