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gdcohen

I'm a generalist

Location Santa Clara, CA Joined Joined on  github website

Work

Product at Zebrium

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3 ways ML is a Game Changer for your Incident Management Lifecycle

3 ways ML is a Game Changer for your Incident Management Lifecycle

3
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5 min read

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Real World Examples of GPT-3 Plain Language Root Cause Summaries

Real World Examples of GPT-3 Plain Language Root Cause Summaries

3
Comments
5 min read
Lessons from Slack, GCP and Snowflake outages

Lessons from Slack, GCP and Snowflake outages

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3 min read
Testing ML incident detection using a cloud native microservices app

Testing ML incident detection using a cloud native microservices app

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10 min read
Virtual tracing: A simpler alternative to distributed tracing for troubleshooting

Virtual tracing: A simpler alternative to distributed tracing for troubleshooting

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5 min read
Augment a PagerDuty Incident with Root Cause

Augment a PagerDuty Incident with Root Cause

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7 min read
This Slack App Speeds-up Incident Resolution Using ML

This Slack App Speeds-up Incident Resolution Using ML

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3 min read
Zebrium + Grafana = Awesome

Zebrium + Grafana = Awesome

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3 min read
You've Nailed Incident detection, what about Incident Resolution?

You've Nailed Incident detection, what about Incident Resolution?

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6 min read
Is Log Management Still the Best Approach?

Is Log Management Still the Best Approach?

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5 min read
Beyond Anomaly Detection: How Incident Recognition Drives down MTTR

Beyond Anomaly Detection: How Incident Recognition Drives down MTTR

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4 min read
Busting the Browser's Cache

Busting the Browser's Cache

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6 min read
Anomaly Detection as a foundation of Autonomous Monitoring

Anomaly Detection as a foundation of Autonomous Monitoring

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5 min read
Autonomous monitoring: is this the anomaly detection you actually wanted?

Autonomous monitoring: is this the anomaly detection you actually wanted?

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7 min read
Designing a RESTful API Framework

Designing a RESTful API Framework

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4 min read
How Fluentd collects Kubernetes metadata

How Fluentd collects Kubernetes metadata

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5 min read
Machine learning for logs (part 1 of 5)

Machine learning for logs (part 1 of 5)

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6 min read
The Future of Monitoring is Autonomous

The Future of Monitoring is Autonomous

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6 min read
The hidden complexity of hiding complexity

The hidden complexity of hiding complexity

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3 min read
Using machine learning to shine a light inside the monitoring black box

Using machine learning to shine a light inside the monitoring black box

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4 min read
Who is testing in production?

Who is testing in production?

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1 min read
Practical log anomaly detection using machine learning

Practical log anomaly detection using machine learning

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3 min read
Deploying into Production: The need for a Red Light

Deploying into Production: The need for a Red Light

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3 min read
Developers shouldn’t waste time structuring logs

Developers shouldn’t waste time structuring logs

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5 min read
Getting anomaly detection right by structuring logs automatically

Getting anomaly detection right by structuring logs automatically

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4 min read
Help come up with a term to describe a product targeted at developers and testers?

Help come up with a term to describe a product targeted at developers and testers?

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1 min read
Reliable signatures to detect known software faults

Reliable signatures to detect known software faults

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3 min read
Using machine learning to reliably detect anomalies in logs

Using machine learning to reliably detect anomalies in logs

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4 min read
Perfectly structuring logs without parsing

Perfectly structuring logs without parsing

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4 min read
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