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Efficient SLO event integration powers successful AIOps

Dynatrace

For instance, consider how fine-tuned failure rate detection can provide insights for comprehensive understanding. Please refer to How to fine-tune failure detection (dynatrace.com) for further information. Let’s assume we created a service-availability SLO, monitoring the request failure count against the overall request counts.

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Machine Learning for Fraud Detection in Streaming Services

The Netflix TechBlog

We present a systematic overview of the unexpected streaming behaviors together with a set of model-based and data-driven anomaly detection strategies to identify them. Manifest is requested by the client and gets delivered to the player before the license request, and it itemizes the available streams.

C++ 312
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Best Practices in Cloud Security Monitoring

Scalegrid

Continuous cloud monitoring enables real-time detection and response to incidents, with best practices highlighting the importance of assessing cloud service providers, adopting layered security, and leveraging automation for efficient scanning and monitoring.

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Dynatrace SaaS release notes version 1.241

Dynatrace

To stay tuned, keep an eye on our release notes. General Availability (Build 1.241.153). General Availability (Build 1.241.153). Reintroduced a limit of 100,000 process group instances (last 72h) running on hosts presented on the “Deployment status” page for OneAgents. (APM-370529). Application Security.

Tuning 194
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Mastering MongoDB® Timeout Settings

Scalegrid

For example, if there’s some trouble connecting due to networking problems or excessive load requests from customers present on the server’s side, that might result in a resolution-related delay causing a subsequent timeout problem. Fine-tuning these settings would lead to improved performance and provide an enhanced user experience. <p>The

Java 130
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Crucial Redis Monitoring Metrics You Must Watch

Scalegrid

Understanding Redis Performance Indicators Redis is designed to handle high traffic and low latency with its in-memory data store and efficient data structures. Evaluating factors like hit rate, which assesses cache efficiency level, or tracking key evictions from the cache are also essential elements during the Redis monitoring process.

Metrics 130
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AWS re:Invent 2017: How Netflix Tunes EC2

Brendan Gregg

My last talk for 2017 was at AWS re:Invent, on "How Netflix Tunes EC2 Instances for Performance," an updated version of my [2014] talk. Our team looks after the BaseAMI, kernel tuning, OS performance tools and profilers, and self-service tools like Vector. Casey Rosenthal (traffic and chaos) Models of Availability.

Tuning 61