Operations | Monitoring | ITSM | DevOps | Cloud

This is the 3rd article in our Orange Matter series on AI by Design IT professionals must trust their tools. When it comes to artificial intelligence (AI) solutions, trust is built on several factors, such as the adoption of privacy and security practices and safeguards against algorithmic bias. In this article, we explore the third principle of our AI by Design framework and discuss how SolarWinds navigates transparency challenges to cultivate user trust in our AI systems.

The IT service community is rightly buzzing about the wealth of possibilities AI offers to automate service management operations and better assist customers — especially in this age of expanding Everywhere Work. But without sound data, the path to leveraging AI for IT service management becomes quite daunting. With so many more people working outside a traditional office setting, more end users than ever are logging in more often to access employee services.

Artificial Intelligence (AI) tools have the potential to revolutionize IT infrastructure and operations (ITOps) by automating routine tasks, enhancing system reliability, and improving efficiency. However, the term “Artificial Intelligence” can sometimes be misleading in this context. A more accurate description might be “Automated Intelligence” because these tools often automate predefined tasks and processes rather than exhibit true cognitive intelligence.

Business consultants are leveraging software and workflow AI to radically elevate service delivery. ‍ According to a survey by Hinge Marketing, the top three reasons businesses hire consultants are to (70%) access specialized expertise, (52%) gain an outside perspective, and (44%) supplement internal resources.

As a key part of furthering its autonomous IT operations vision, OpsRamp, a Hewlett Packard Enterprise company, this week announced its new operations copilot feature, a natural-language interface that enables enterprises to identify, predict and solve IT problems more quickly by converting machine data into a human-friendly and actionable form.

Artificial intelligence is a game-changing technology across industries and business processes, designed to make workers more efficient, reduce the steps it takes to complete a task, and gain answers and insights faster. But those powerful capabilities also put new demands on compute infrastructure and this requires a new class of infrastructure observability metrics.

Datadog Actions help you respond to alerts and manage your infrastructure directly from within Datadog. This can be done by creating workflows that automate end-to-end processes or by using App Builder to build resource management tools and self-serve developer platforms. With more than 550 available actions, Datadog Actions offers capabilities such as creating Jira tickets, resizing autoscaling groups, and triggering GitHub pipelines.

So, your company uses LLMs? You’re not the only ones. A survey by Gartner in October 2023 revealed that 55% of organizations were piloting or releasing generative AI projects, and it’s safe to assume that this number has increased since that survey was published. From personalized recommendations in e-commerce, to automated grading in education and fraud detection in finance, LLMs have helped many organizations level up.