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Sumo Logic

What are the differences between artificial intelligence, machine learning, deep learning and generative AI?

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.

Setting Up the Latest AWS Observability Solution

The tutorial demonstrates how easy it is to deploy the AWS Observability Solution using the CloudFormation template using the quick and new method. The CloudFormation template being used in this method sets up an automated collection of logs and metrics from AWS to the Sumo Logic service.

Crossing the machine learning pilot to product chasm through MLOps

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.

Splunk second thoughts? It's time for the cloud-native alternative

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.

Reduce alert noise, automate incident response and keep coding with AI-driven alerting

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.

Four reasons to consider a new economic model for log management

Today's data and log analytics solutions are centered on the volume of data ingested. But as businesses continue to grow, the applications at the heart of that growth continue to increase in complexity. With modern applications, attempting to scale investments in observability and security by log volume isn’t possible, until now. Sumo Logic's VP of Product Marketing, Michael Cucchi, talks about some of the cost barriers associated with managing log analytics and the top four reasons to consider a modern unlimited ingest pricing model as part of your log management strategy.

What happens when you can afford to ingest all your log data?

Sit down with Joe Kim, Sumo Logic's CEO, and Michael Cucchi, VP of Product Marketing, for a fireside chat (minus the fire) about Sumo Logic's new flex licensing plan. They'll discuss how removing the cost of ingesting log data across an enterprise: Tune in for a 20-minute chat about what happens when you can finally log everything with $0 ingest.

Log it all and eliminate visibility gaps

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.