Solution: Automated Root Cause Analysis

When a new/unknown software problem occurs, chances are an SRE or developer will start by analyzing and searching through logs for root cause – a slow and painful process. So it’s no wonder using machine learning (ML) for log analysis is getting a lot of attention. But machine learning (ML) with logs is hard. Here’s… Continue reading Log Analysis with Machine Learning: An Automated Approach to Analyzing Logs Using ML/AI

If you are a New Relic user, you’re likely using New Relic to monitor your environment, detect problems, and troubleshoot them when they occur. But let’s consider exactly what that entails and describe a way to make this entire process much quicker. Imagine that the dashboards used to monitor your application suddenly show a “blip”.… Continue reading Using New Relic For Observability? Speed up Troubleshooting with Zebrium

The Elastic Stack (often called ELK) is one of the most popular observability platforms in use today. It lets you collect metrics, traces, and logs and visualize them in one Kibana dashboard. You can set alerts for outliers, drill down into your dashboards and search through your logs. But there are limitations. What happens when… Continue reading Using the Elastic Stack (ELK) For Observability? Here’s How to Speed Up Troubleshooting

A few weeks ago, Larry Lancaster, wrote about a new beta feature leveraging the GPT-3 language model – Using GPT-3 for plain language incident root cause from logs. To recap – Zebrium’s unsupervised ML identifies the root cause of incidents and generates concise reports (typically between 5-20 log events) identifying the first event in the… Continue reading Real World Examples of GPT-3 Plain Language Root Cause Summaries

We believe the future of monitoring, especially for platforms like Kubernetes, is truly autonomous. Cloud-native applications are increasingly distributed, evolving faster, and failing in new ways, making it harder to monitor, troubleshoot and resolve incidents. Traditional approaches such as dashboards, carefully tuned alert rules, and searches through logs are reactive and time intensive, hurting productivity,… Continue reading Anomaly Detection as a Foundation of Autonomous Monitoring

This project is a favorite of mine and so I wanted to share a glimpse of what we’ve been up to with OpenAI’s amazing GPT-3 language model. Today I’ll be sharing a couple of straightforward results. There are more advanced avenues we’re exploring for our use of GPT-3, such as fine-tuning (custom pre-training for specific… Continue reading Using GPT-3 for plain language incident root cause from logs

The past three months has seen Zebrium reach several major milestones! We moved from beta to production and our platform is now in use by industry leading customers who rely on Zebrium to keep their production applications running. We were named in the Forbes AI50 list as one of “America’s Most Promising Artificial Intelligence Companies”.… Continue reading Zebrium Named a 2020 Gartner Cool Vendor