With all the buzz around ChatGPT and the rapid mainstreaming of generative AI, 2024 was predicted to be the year of AI. While the market certainly talks a lot about AI this year, we’ve yet to see much of it in production environments. Events are a great chance for tech companies to showcase or announce new innovations to the market.

Tool consolidation outcomes have driven some customers to drop Splunk and consolidate their log analytics use cases on Sumo Logic. Long-term Splunk customers with many dashboards, saved searches and monitors understandably want to retain a consistent experience for end users. As a result, a replacement strategy requires migration.

Not so long ago in my career, I remember when it was relatively acceptable for infrastructure or development teams to solve a problem by rebooting a server or just “turning things off and on again.” It didn’t matter what caused the problem or how long the reboot would fix things, provided they were fixed for now. Security teams were always held to a different standard.

Even now, plenty of businesses are still making the shift to the cloud. Chief decision-makers are plagued by fears about availability, potential downtime and security. Organizations adopting Microsoft Azure need to be able to confidently make the transition without interruptions, which requires building out a strategy for monitoring your Azure environment.

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.

Classified as a "Management and Governance” tool in the AWS console, AWS CloudTrail is an auditing, compliance monitoring and governance tool from Amazon Web Services (AWS). With CloudTrail, AWS account owners can ensure every API call made to every resource in their AWS account is recorded and written to a log. An API call request can be made when: These actions can be coming from: CloudTrail saves the API events in a secured, immutable format, which can be used for later analysis.

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.