Remove Database Remove Definition Remove Efficiency Remove Tuning
article thumbnail

Conducting log analysis with an observability platform and full data context

Dynatrace

With more automated approaches to log monitoring and log analysis, however, organizations can gain visibility into their applications and infrastructure efficiently and with greater precision—even as cloud environments grow. ” A data warehouse, on the other hand, is an efficient and fast option for querying data.

Analytics 183
article thumbnail

Data Mesh?—?A Data Movement and Processing Platform @ Netflix

The Netflix TechBlog

Data Mesh Overview A New Definition Of Data Mesh Previously, we defined Data Mesh as a fully managed, streaming data pipeline product used for enabling Change Data Capture (CDC) use cases. They use different mechanisms to stream events out of the source databases. This article gives an overview of the system.

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

Best Practices for a Seamless MongoDB Upgrade

Percona

MongoDB is a dynamic database system continually evolving to deliver optimized performance, robust security, and limitless scalability. Our new eBook, “ From Planning to Performance: MongoDB Upgrade Best Practices ,” guides you through the entire process to ensure your database’s long-term success. In MongoDB 6.x:

article thumbnail

Orchestrating Data/ML Workflows at Scale With Netflix Maestro

The Netflix TechBlog

We want users to rely on shared templates and reuse their workflow definitions across their team, saving time and effort on creating the same functionality. Maestro high level architecture In Maestro, a workflow is a DAG (Directed acyclic graph) of individual units of job definition called Steps. But sometimes, it is not efficient.

Java 202
article thumbnail

Data Movement in Netflix Studio via Data Mesh

The Netflix TechBlog

With dependable near real-time data, Studio teams are able to track and react better to the ever-changing pace of productions and improve efficiency of global business operations using the most up-to-date information. In the initial stage, data consumers set up ETL pipelines directly pulling data from databases.

Big Data 253
article thumbnail

Rebuilding Netflix Video Processing Pipeline with Microservices

The Netflix TechBlog

Since then, the video pipeline has undergone substantial improvements and broad expansions: Starting with Standard Dynamic Range (SDR) at Standard-Definitions , we expanded the encoding pipeline to 4K and High Dynamic Range (HDR) which enabled support for our premium offering. The results are saved to a database so they can be reused.

article thumbnail

Observability engineering: Getting Prometheus metrics right for Kubernetes with Dynatrace and Kepler

Dynatrace

This challenge has given rise to the discipline of observability engineering, which concentrates on the details of telemetry data to fine-tune observability use cases. Kubernetes-based efficient power level exporter (Kepler) is a Prometheus exporter that uses ML models to estimate the energy consumption of Kubernetes pods.

Metrics 174