Remove Efficiency Remove Presentation Remove Traffic
article thumbnail

Better dashboarding with Dynatrace Davis AI: Instant meaningful insights

Dynatrace

The market is saturated with tools for building eye-catching dashboards, but ultimately, it comes down to interpreting the presented information. For example, if you’re monitoring network traffic and the average over the past 7 days is 500 Mbps, the threshold will adapt to this baseline.

Traffic 262
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 282
Insiders

Sign Up for our Newsletter

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

article thumbnail

Black Friday traffic exposes gaps in observability strategies

Dynatrace

What’s the problem with Black Friday traffic? But that’s difficult when Black Friday traffic brings overwhelming and unpredictable peak loads to retailer websites and exposes the weakest points in a company’s infrastructure, threatening application performance and user experience. Why Black Friday traffic threatens customer experience.

Traffic 246
article thumbnail

Efficient SLO event integration powers successful AIOps

Dynatrace

When the SLO status converges to an optimal value of 100%, and there’s substantial traffic (calls/min), BurnRate becomes more relevant for anomaly detection. SLOs must be evaluated at 100%, even when there is currently no traffic. What characterizes a weak SLO? Use the default transformation.

article thumbnail

Title Launch Observability at Netflix Scale

The Netflix TechBlog

Accurately Reflecting Production Behavior A key part of our solution is insights into production behavior, which necessitates our requests to the endpoint result in traffic to the real service functions that mimics the same pathways the traffic would take if it came from the usualcallers. We call this capability TimeTravel.

Traffic 160
article thumbnail

Title Launch Observability at Netflix Scale

The Netflix TechBlog

This led to a suite of fragmented scripts, runbooks, and ad hoc solutions scattered across teamsan approach that was neither sustainable nor efficient. They allow us to verify whether titles are presented as intended and investigate any discrepancies. The stakes are even higher when ensuring every title launches flawlessly.

Traffic 168
article thumbnail

Introducing Impressions at Netflix

The Netflix TechBlog

This dual-path approach leverages Kafkas capability for low-latency streaming and Icebergs efficient management of large-scale, immutable datasets, ensuring both real-time responsiveness and comprehensive historical data availability. This integration will not only optimize performance but also ensure more efficient resource utilization.

Tuning 165