How Edge Delta OnCall AI Leverages AWS Bedrock for Observability at Scale
Observability isn’t about reacting to issues after they happen; it’s about seeing the future as it unfolds. With Edge Delta OnCall AI, powered by Amazon Web Services (AWS) Bedrock, we’re turning petabytes of observability data into actionable insights for DevOps and SRE teams in real-time. The result? Lightning-fast detection and resolution of production issues. Let’s explore how this works with a real world scenario from this week:
How does OnCall AI allow us to correct potential production issues in literally seconds to a minute or two? This is how...
🚀 Real-Time AI at the Terabyte and Petabyte Scale
Dealing with telemetry at scale is no small feat. Logs, metrics, traces, it’s an high volume stream of data. At terabyte and petabyte scales, traditional monitoring systems simply can’t keep up, and that's even before the AI costs kick in. That’s where Edge Delta OnCall AI comes in, powered by Telemetry Pipelines to give you all the visibility without all the costs.
1️⃣ Federated Machine Learning in Action: Instead of shipping all your logs to a central database, our ML models run distributed, in real-time, within your architecture. This means even at billions or trillions of events, patterns in your logs are automatically identified without adding latency or excessive bandwidth usage.
The result? We start to process and analyze data where it’s generated, giving you insights faster than ever.
🔍 Sentiment Analysis: Reading Between the Lines
Not all logs are created equal. Some are innocuous, others are warning signs of impending disaster. Edge Delta uses real-time sentiment analysis on every log pattern to detect whether it’s negative in nature.
2️⃣ Why Sentiment Analysis Matters: By understanding the tone of your logs, we can elevate potentially critical issues for deeper processing instantly. A spike in redis failures? Negative patterns emerging in your app logs? These are flagged immediately, no human schema definition needed.
📊 Trend Analysis: Detecting Anomalies With Precision
Here’s where it gets even better. Once negative patterns are flagged, Edge Delta performs trend analysis across multiple timeframes: hour over hour, day over day, week over week. This multi-dimensional approach ensures that anomalies are detected with high accuracy and low noise.
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3️⃣ Case in Point: In one environment, we detected:
These cache and redis failures weren’t random issues, they were brand new patterns that didn’t exist before. The health alert and user errors were also significantly increased. That’s the power of trend analysis.
🤖 Expert Models + Real-Time Insights
Once anomalies are detected, it’s time to solve the problem. Significant patterns are fed into a mixture of expert models that analyze the data in real time. This isn’t generic AI, it’s purpose-built for observability and performance monitoring.
4️⃣ The Result: OnCall engineers are given a clear summary of the issue and a suggested resolution. No more starting at square one. Instead, they start at square six, armed with the context and insight they need to fix the problem fast.
💡 No Magic, No Stress—Just Full Automation
Here’s the kicker: everything I just described happens automatically. No data science expertise. No ML training. Setup takes just five minutes (but maybe don’t start in production... unless you like living dangerously. But seriously please don't).
This isn’t some magical black box. It’s real, practical AI that empowers your team, prevents outages, and keeps your customers happy.
🌟 Love the Power, Love the Price
With Edge Delta and AWS Bedrock, observability isn’t just effortless and scalable, it’s affordable and accessible. Whether you’re a small startup or managing a massive enterprise, you can harness the power of real-time AI to monitor, detect, and resolve issues before they become problems.
No stress. Full coverage. Real-time AI. This is the future of observability. And it’s here today.
💚 Edge Delta. No outages, no drama, just solutions. 💚