Remove Design Remove Example Remove Latency Remove Traffic
article thumbnail

How Dynatrace boosts production resilience with Site Reliability Guardian

Dynatrace

The Dynatrace Site Reliability Guardian is designed for this practice; it allows development teams to define quality objectives in their code, which is validated throughout the delivery process before the code reaches production. The functionality is implemented via an automated workflow.

DevOps 186
article thumbnail

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. Similarly, an increased throughput signifies an intensive workload on a server and a larger latency.

Metrics 130
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

Data Reprocessing Pipeline in Asset Management Platform @Netflix

The Netflix TechBlog

This feature support required a significant update in the data table design (which includes new tables and updating existing table columns). Existing data got updated to be backward compatible without impacting the existing running production traffic. Following is the example of tables primary and clustering keys defined: Figure 2.

Media 237
article thumbnail

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. In practice, however, SLOs’ value varies significantly based on how teams design, deploy, and manage them.

DevOps 214
article thumbnail

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. Example use case: Building model explainers Here’s a fascinating example of the usefulness of portable execution environments.

Systems 226
article thumbnail

Seamlessly Swapping the API backend of the Netflix Android app

The Netflix TechBlog

As an example, to render the screen shown here, the app sends a query that looks like this: paths: ["videos", 80154610, "detail"] A path starts from a root object , and is followed by a sequence of keys that we want to retrieve the data for. Replay Testing Enter replay testing.

Latency 233
article thumbnail

Migrating Critical Traffic At Scale with No Downtime?—?Part 2

The Netflix TechBlog

Migrating Critical Traffic At Scale with No Downtime — Part 2 Shyam Gala , Javier Fernandez-Ivern , Anup Rokkam Pratap , Devang Shah Picture yourself enthralled by the latest episode of your beloved Netflix series, delighting in an uninterrupted, high-definition streaming experience. This is where large-scale system migrations come into play.

Traffic 279