Knowing what business problem you want to address will help you know which data mining technique will produce the best results. Each of the data mining strategies listed below addresses a different business challenge and yields a different result. We are surrounded by big data in today’s digital world, which is expected to rise at a rate of 40% per year over the next decade. The irony is that we are awash in data yet deficient in knowledge. Why?
Speedscale is proud to announce its Centralized Log Collection capability. When diagnosing the source of problems in your API, more information is better. For most engineers, the diagnosis process usually starts with the application logs. Unfortunately, logs are usually either discarded or stored in Observability systems that engineers don’t have direct access to. Compounding this issue is that the log information is typically not correlated to what calls were made against the API.
System outages happen to the best of us. Communicating with your customers and other stakeholders effectively during downtimes is vital to maintaining a solid relationship with them. When a system outage occurs, technical teams are tasked with swiftly locating the cause and resolving the issue, while communications teams are tasked with notifying stakeholders and customers about the outage to maintain transparency.
2021 was another challenging year globally. Despite this, the N-able™ Take Control team continued to deliver top-notch releases to increase product functionalities and improve customer satisfaction. In this blog, we’ll take a brief look at the key client-facing features we’ve delivered in the past 12 months.
Modern workflows are primarily aimed at one thing—reducing operational complexities so that stakeholders can focus on initiatives that boost business and innovation. For IT teams, Artificial Intelligence and Machine Learning play key roles in bringing this goal to life. And even though AIOps is considered to be not yet in mature stages, there is no denying that IT teams that do not adopt AI processes will be left behind. By 2023, the market for AIOps tools is predicted to reach $11.02 B.
No one will be surprised to hear that ransomware is, once again, on the rise. The last two years have seen a stratospheric increase in both the frequency and sophistication of attacks. In a just-released report from Ivanti, Cyber Security Works and Cyware, 2021 closed out with alarming statistics including a 29% increase in CVEs associated with ransomware, and a 26% increase in ransomware families compared to the previous year.
We often hear from customers that they’re dealing with unmanageable levels of noise and complexity, which makes it harder to pinpoint root cause and get to resolution quickly. All this effort spent on sifting through noise, processing events, and gathering context results in a lot of wasted time. That’s why we’ve launched Event Orchestration, which became generally available to our Event Intelligence and Digital Operations customers on Monday.
As an idea conceived by Gartner four years ago, AIOps is already a mature practice. But it is also one that continues to evolve as businesses turn to AIOps to support new use cases, and as AIOps vendors build better and more efficient AIOps tools. That fact begs the questions: what’s next for AIOps? What are the relevant trends that will shape the future of AIOps over the next several years, and how will AIOps use cases evolve going forward?
