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5 key areas for tech leaders to watch in 2020

O'Reilly

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. Python libraries are no less useful for manipulating or engineering data, too.).

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Building and Scaling Data Lineage at Netflix to Improve Data Infrastructure Reliability, and…

The Netflix TechBlog

We adopted the following mission statement to guide our investments: “Provide a complete and accurate data lineage system enabling decision-makers to win moments of truth.” Nonetheless, Netflix data landscape (see below) is complex and many teams collaborate effectively for sharing the responsibility of our data system management.

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Orchestrating Data/ML Workflows at Scale With Netflix Maestro

The Netflix TechBlog

Meson was based on a single leader architecture with high availability. increasing at > 100% a year, the need for a scalable data workflow orchestrator has become paramount for Netflix’s business needs. Figure 1 shows the high-level architecture. We developed our own secured expression language (SEL) to ensure security.

Java 202
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How Data Inspires Building a Scalable, Resilient and Secure Cloud Infrastructure At Netflix

The Netflix TechBlog

As a micro-service owner, a Netflix engineer is responsible for its innovation as well as its operation, which includes making sure the service is reliable, secure, efficient and performant. How can we develop templated detection modules (rules- and ML-based) and data streams to increases speed of development?

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Microservices Adoption in 2020

O'Reilly

Software engineers comprise the survey audience’s single largest cluster, over one quarter (27%) of respondents (Figure 1). If you combine the different architectural roles—i.e., Adding architects and engineers, we see that roughly 55% of the respondents are directly involved in software development.

Database 134
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Optimizing data warehouse storage

The Netflix TechBlog

At this scale, we can gain a significant amount of performance and cost benefits by optimizing the storage layout (records, objects, partitions) as the data lands into our warehouse. Some of the optimizations are prerequisites for a high-performance data warehouse. Both automatic (event-driven) as well as manual (ad-hoc) optimization.

Storage 203
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Zendesk Moves from DynamoDB to MySQL and S3 to Save over 80% in Costs

InfoQ

Zendesk reduced its data storage costs by over 80% by migrating from DynamoDB to a tiered storage solution using MySQL and S3. The company considered different storage technologies and decided to combine the relational database and the object store to strike a balance between querybility and scalability while keeping the costs down.

Storage 134