While deep learning, machine learning and artificial intelligence (AI) may seem to be used synonymously, there are clear differences. One school of thought is that artificial intelligence is a larger umbrella category under which machine learning falls and deep learning falls under machine learning. Therefore, while everything that is categorized as deep learning or machine learning is part of the artificial intelligence field, not everything that is machine learning will be deep learning.

Numerous companies keep launching AI/ML features, specifically “ChatGPT for XYZ” type productization. Given the buzz around Large Language Models (LLMs), consumers and executives alike are growing to assume that building AI/ML-based products and features is easy. LLMs can appear to be magical as users experiment with them.

Back in September when Cisco announced they were acquiring Splunk, we explained how the market was consolidating with Sumo Logic ahead of the pack, challenging traditional vendors with our cloud-native platform. Now that the deal is complete and Splunk is officially a Cisco company, we’re hearing from more Splunk customers who are considering their options.

Noisy monitors can lead to alert fatigue, which frustrates engineers and hinders innovation. With our patent-pending anomaly detection capabilities built on the power of AI, you can eliminate 60-90% of alerts. A unique differentiator, Sumo Logic’s alerts can also trigger one or more playbooks to drive auto-diagnosis or remediation and accelerate time to recovery for application incidents. Faster issue remediation means engineers can focus more time on development and releasing software.

Doing security and observability by budget sucks. Choosing where to limit your visibility and deciding which logs and data you may need before you actually need them is backward logic in today’s AI-driven world. The plain reality is that log management and analytics shouldn’t be based only on what you can afford to ingest.

It’s safe to say that Generative AI and the launch of GPT4 caused the most excitement – and fear – in technology in 2023. It’s not surprising with its possible areas of application and ease of use. Even schoolchildren are using it!

In a perfect world, there would be no issues with the operating system and no problems with the applications. Unfortunately, this isn’t a perfect world. System failures can and will occur, and when they do, it is the responsibility of system administrators to diagnose and resolve the issues. But where can system administrators begin the search for solutions when problems arise? The answer is Windows event logs.

Modern systems look very different than they did years ago. For the most part, development organizations have moved away from building traditional monoliths towards developing containerized applications running across a highly distributed infrastructure. While this change has made systems inherently more resilient, the increase in overall complexity has made it more important and more challenging to effectively identify and address problems at their root cause when issues occur.

You should read this if you are an executive (CIO/CISO/CxO) or IT professional seeking to understand various Kubernetes business use cases. You’ll address topics like: Many enterprises adopting a multi-cloud strategy and breaking up their monolithic code realize that container management platforms like Kubernetes are the first step to building scalable modern applications.

The clock is ticking for financial services companies that operate in the European Union (EU). Starting in January 2025, financial services providers and their third-party technology service providers must meet the new regulatory requirements of the Digital Operational Resilience Act (DORA).