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Data Reprocessing Pipeline in Asset Management Platform @Netflix

The Netflix TechBlog

Hence we built the data pipeline that can be used to extract the existing assets metadata and process it specifically to each new use case. This feature support required a significant update in the data table design (which includes new tables and updating existing table columns). N, first N rows are fetched from the table.

Media 237
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How Dynatrace boosts production resilience with Site Reliability Guardian

Dynatrace

To ensure high standards, it’s essential that your organization establish automated validations in an early phase of the software development process—ideally when code is written. While the first guardian validates the traffic, the second guardian checks the business transactions generated during the observation period.

DevOps 183
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Crucial Redis Monitoring Metrics You Must Watch

Scalegrid

Key Takeaways Critical performance indicators such as latency, CPU usage, memory utilization, hit rate, and number of connected clients/slaves/evictions must be monitored to maintain Redis’s high throughput and low latency capabilities. It can achieve impressive performance, handling up to 50 million operations per second.

Metrics 130
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SLOs done right: how DevOps teams can build better service-level objectives

Dynatrace

Monitors signals The first attribute of a good SLO is the ability to monitor the four “golden signals”: latency, traffic, error rates, and resource saturation. Includes the end user While SLOs for back-end silos and processes help eliminate internal issues, back-end-based objectives tell only half the story.

DevOps 210
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Dynatrace Managed turnkey Premium High Availability for globally distributed data centers (Early Adopter)

Dynatrace

The network latency between cluster nodes should be around 10 ms or less. Minimized cross-data center network traffic. For Premium HA, this has been extended from 10 ms latency (in the same network region) to around 100 ms network latency due to asynchronous data replication between regions.

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Towards a Reliable Device Management Platform

The Netflix TechBlog

The challenge, then, is to be able to ingest and process these events in a scalable manner, i.e., scaling with the number of devices, which will be the focus of this blog post. As such, we can see that the traffic load on the Device Management Platform’s control plane is very dynamic over time.

Latency 213
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Supporting Diverse ML Systems at Netflix

The Netflix TechBlog

Since its inception , Metaflow has been designed to provide a human-friendly API for building data and ML (and today AI) applications and deploying them in our production infrastructure frictionlessly. In other cases, it is more convenient to share the results via a low-latency API.

Systems 226