Dynatrace

JULY 6, 2022

At its most basic, automating IT processes works by executing scripts or procedures either on a schedule or in response to particular events, such as checking a file into a code repository. Adding AIOps to automation processes makes the volume of data that applications and multicloud environments generate much less overwhelming.

Artificial Intelligence 198

Artificial Intelligence Tuning Strategy Big Data 198

The Netflix TechBlog

DECEMBER 3, 2022

Obviously not all tools are made with the same use case in mind, so we are planning to add more code samples for other (than classical batch ETL) data processing purposes, e.g. Machine Learning model building and scoring. This allows other processes, consuming our table, to be notified and start their processing.

Best Practices 358

Best Practices Code Testing Data Engineering 358

O'Reilly

FEBRUARY 18, 2020

This year’s growth in Python usage was buoyed by its increasing popularity among data scientists and machine learning (ML) and artificial intelligence (AI) engineers. Software architecture, infrastructure, and operations are each changing rapidly. Also: infrastructure and operations is trending up, while DevOps is trending down.

Software Architecture 132

Software Architecture DevOps Data Engineering Architecture 132

The Netflix TechBlog

SEPTEMBER 10, 2019

Our A/B tests range across UI, algorithms, messaging, marketing, operations, and infrastructure changes. Due to compression and high performance computing, scientists can analyze billions of rows of raw data on their laptops using languages and statistical libraries they are familiar with like Python and R.

Metrics 215

Metrics Architecture Infrastructure Innovation 215

The Netflix TechBlog

DECEMBER 21, 2020

There are several benefits of such optimizations like saving on storage, faster query time, cheaper downstream processing, and an increase in developer productivity by removing additional ETLs written only for query performance improvement. Some of the optimizations are prerequisites for a high-performance data warehouse.

Storage 203

Storage Latency Efficiency Data Engineering 203

The Netflix TechBlog

FEBRUARY 9, 2022

Let’s define some requirements that we are interested in delivering to the Netflix data engineers or anyone who would like to schedule a workflow with some external assets in it. By the end of the migration process our Jenkins configuration went from: Figure 4. The slightly improved approach is shown on the diagram below.

Storage 201

Storage Data Engineering Testing Code 201

High Scalability

MARCH 17, 2020

Etleap is analyst-friendly , enterprise-grade ETL-as-a-service , built for Redshift and Snowflake data warehouses and S3/Glue data lakes. Our intuitive software allows data engineers to maintain pipelines without writing code, and lets analysts gain access to data in minutes instead of months.

Education 105

Education Engineering Java Software Engineering 105

All Things Distributed

NOVEMBER 15, 2016

Previously, I wrote about Amazon QuickSight , a new service targeted at business users that aims to simplify the process of deriving insights from a wide variety of data sources quickly, easily, and at a low cost. Put simply, data is not always readily available and accessible to organizational end users.

Analytics 152

Analytics Availability Media Social Media 152

High Scalability

MARCH 3, 2020

Etleap is analyst-friendly , enterprise-grade ETL-as-a-service , built for Redshift and Snowflake data warehouses and S3/Glue data lakes. Our intuitive software allows data engineers to maintain pipelines without writing code, and lets analysts gain access to data in minutes instead of months.

Education 114

Education Engineering Games Java 114

The Netflix TechBlog

NOVEMBER 22, 2019

Netflix shares how Amazon EC2 Auto Scaling allows its infrastructure to automatically adapt to changing traffic patterns in order to keep its audience entertained and its costs on target. Instead, we provide them with delightfully usable ML infrastructure that they can use to manage a project’s lifecycle. Wednesday?—?December

AWS 100

AWS Entertainment Open Source Benchmarking 100

The Netflix TechBlog

NOVEMBER 22, 2019

Netflix shares how Amazon EC2 Auto Scaling allows its infrastructure to automatically adapt to changing traffic patterns in order to keep its audience entertained and its costs on target. Instead, we provide them with delightfully usable ML infrastructure that they can use to manage a project’s lifecycle. Wednesday?—?December

AWS 100

AWS Entertainment Open Source Benchmarking 100

High Scalability

FEBRUARY 18, 2020

Etleap is analyst-friendly , enterprise-grade ETL-as-a-service , built for Redshift and Snowflake data warehouses and S3/Glue data lakes. Our intuitive software allows data engineers to maintain pipelines without writing code, and lets analysts gain access to data in minutes instead of months.

Education 113

Education Engineering Games Java 113

High Scalability

APRIL 14, 2020

Etleap is analyst-friendly , enterprise-grade ETL-as-a-service , built for Redshift and Snowflake data warehouses and S3/Glue data lakes. Our intuitive software allows data engineers to maintain pipelines without writing code, and lets analysts gain access to data in minutes instead of months.

Education 105

Education Software Engineering Scalability Engineering 105

High Scalability

MAY 12, 2020

Etleap is analyst-friendly , enterprise-grade ETL-as-a-service , built for Redshift and Snowflake data warehouses and S3/Glue data lakes. Our intuitive software allows data engineers to maintain pipelines without writing code, and lets analysts gain access to data in minutes instead of months.

Education 102

Education Software Engineering Scalability Engineering 102

High Scalability

MARCH 24, 2020

Etleap is analyst-friendly , enterprise-grade ETL-as-a-service , built for Redshift and Snowflake data warehouses and S3/Glue data lakes. Our intuitive software allows data engineers to maintain pipelines without writing code, and lets analysts gain access to data in minutes instead of months.

Education 105

Education Software Engineering Engineering Big Data 105

High Scalability

FEBRUARY 9, 2020

Etleap is analyst-friendly , enterprise-grade ETL-as-a-service , built for Redshift and Snowflake data warehouses and S3/Glue data lakes. Our intuitive software allows data engineers to maintain pipelines without writing code, and lets analysts gain access to data in minutes instead of months.

Education 108

Education Engineering Games Java 108

High Scalability

APRIL 28, 2020

Etleap is analyst-friendly , enterprise-grade ETL-as-a-service , built for Redshift and Snowflake data warehouses and S3/Glue data lakes. Our intuitive software allows data engineers to maintain pipelines without writing code, and lets analysts gain access to data in minutes instead of months.

Education 102

Education Software Engineering Scalability Engineering 102

High Scalability

MARCH 30, 2020

Etleap is analyst-friendly , enterprise-grade ETL-as-a-service , built for Redshift and Snowflake data warehouses and S3/Glue data lakes. Our intuitive software allows data engineers to maintain pipelines without writing code, and lets analysts gain access to data in minutes instead of months.

Education 105

Education Software Engineering Engineering Big Data 105

High Scalability

MAY 26, 2020

Etleap is analyst-friendly , enterprise-grade ETL-as-a-service , built for Redshift and Snowflake data warehouses and S3/Glue data lakes. Our intuitive software allows data engineers to maintain pipelines without writing code, and lets analysts gain access to data in minutes instead of months.

Education 100

Education AWS Software Engineering Scalability 100

The Netflix TechBlog

MARCH 2, 2021

At Netflix, our data scientists span many areas of technical specialization, including experimentation, causal inference, machine learning, NLP, modeling, and optimization. Together with data analytics and data engineering, we comprise the larger, centralized Data Science and Engineering group.

Analytics 207

Analytics C++ Innovation Engineering 207

All Things Distributed

OCTOBER 7, 2015

In such a data intensive environment, making key business decisions such as running marketing and sales campaigns, logistic planning, financial analysis and ad targeting require deriving insights from these data. However, the data infrastructure to collect, store and process data is geared toward developers (e.g.,

Cloud 137

Cloud Big Data AWS Analytics 137

Adrian Cockcroft

FEBRUARY 13, 2023

This is the AWS Professional Services built tooling that customers can use to track the carbon footprint of their operations and processes, along with a customer example. STP213 Scaling global carbon footprint management — Blake Blackwell Persefoni Manager Data Engineering and Michael Floyd AWS Head of Sustainability Solutions.

AWS 64

AWS Energy Architecture Programming 64

Abhishek Tiwari

JULY 12, 2018

In recent times, in order to gain valuable insights or to develop the data-driven products companies such as Netflix, Spotify, Uber, AirBnB have built internal data pipelines. If built correctly, data pipelines can offer strategic advantages to the business. Depending on frameworks, data processing units (a.k.a

Latency 63

Latency Analytics Scalability Engineering 63

The Netflix TechBlog

NOVEMBER 22, 2019

Netflix shares how Amazon EC2 Auto Scaling allows its infrastructure to automatically adapt to changing traffic patterns in order to keep its audience entertained and its costs on target. Instead, we provide them with delightfully usable ML infrastructure that they can use to manage a project’s lifecycle. Wednesday?—?December

AWS 37

AWS Entertainment Open Source Benchmarking 37

The Symphonia

JUNE 19, 2018

Since then Donna’s been bringing her expertise to Pulumi , a startup promising to make infrastructure automation much more friendly and less, well, YAML’ey. From data engineering, to cost management, via conversations about team dynamics and architecture, we like to get involved with all-things-cloud-and-DevOps related at our clients.

Serverless 40

Serverless AWS DevOps Open Source 40

O'Reilly

MARCH 2, 2020

When a project is going off track because some requirement wasn’t understood properly, you need to fix that as soon as possible—not after a year-long development process. When processes change, who wins, who loses, and why? Software architecture, infrastructure, and operations are each changing rapidly. Coincidence?

Artificial Intelligence 20

Artificial Intelligence Software Architecture Programming Infrastructure 20