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What is serverless computing? Driving efficiency without sacrificing observability

Dynatrace

The phrase “serverless computing” appears contradictory at first, but for years now, successful companies have understood the benefit of using serverless technologies to streamline operations and reduce costs. In a serverless architecture, applications are distributed to meet demand and scale requirements efficiently.

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Enhancing Kubernetes cluster management key to platform engineering success

Dynatrace

As organizations continue to modernize their technology stacks, many turn to Kubernetes , an open source container orchestration system for automating software deployment, scaling, and management. You can ask for the best configuration to reduce latency or improve the user experience.” It’s not just a cost-reduction tool.

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Rebuilding Netflix Video Processing Pipeline with Microservices

The Netflix TechBlog

This architecture shift greatly reduced the processing latency and increased system resiliency. We expanded pipeline support to serve our studio/content-development use cases, which had different latency and resiliency requirements as compared to the traditional streaming use case. divide the input video into small chunks 2.

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Build and operate multicloud FaaS with enhanced, intelligent end-to-end observability

Dynatrace

As companies accelerate digital transformation, they implement modern cloud technologies like serverless functions. According to Flexera , serverless functions are the number one technology evaluated by enterprises and one of the top five cloud technologies in use at enterprises. And serverless support is a core capability.

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Netflix Cloud Packaging in the Terabyte Era

The Netflix TechBlog

By Xiaomei Liu , Rosanna Lee , Cyril Concolato Introduction Behind the scenes of the beloved Netflix streaming service and content, there are many technology innovations in media processing. Our previous tech blog Packaging award-winning shows with award-winning technology detailed our packaging technology deployed on the streaming side.

Cloud 237
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Bulldozer: Batch Data Moving from Data Warehouse to Online Key-Value Stores

The Netflix TechBlog

Usually Data scientists and engineers write Extract-Transform-Load (ETL) jobs and pipelines using big data compute technologies, like Spark or Presto , to process this data and periodically compute key information for a member or a video. The data warehouse is not designed to serve point requests from microservices with low latency.

Latency 243
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Automated observability, security, and reliability at scale

Dynatrace

However, scaling up software development requires more tools along the software product lifecycle, which must be configured promptly and efficiently. Efficient environment configuration at scale One of software engineers’ most significant challenges is managing the numerous tools and technologies required for the software product lifecycle.