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Dynatrace supports SnapStart for Lambda as an AWS launch partner

Dynatrace

Lambda serverless functions help developers innovate faster, scale easier, and reduce operational overhead, removing the burden of managing underlying infrastructure when updating and deploying code. Most enterprises use serverless functions as part of a broader hybrid environment, covering both cloud and traditional technologies.

Lambda 246
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Seamlessly Swapping the API backend of the Netflix Android app

The Netflix TechBlog

We went from an essentially serverless model in a monolithic service, to deploying and maintaining a new microservice that hosted our app backend endpoints. This allows the app to query a list of “paths” in each HTTP request, and get specially formatted JSON (jsonGraph) that we use to cache the data and hydrate the UI.

Latency 241
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Implementing AWS well-architected pillars with automated workflows

Dynatrace

For example, optimizing resource utilization for greater scale and lower cost and driving insights to increase adoption of cloud-native serverless services. Storing frequently accessed data in faster storage, usually in-memory caching, improves data retrieval speed and overall system performance. Beyond

AWS 305
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Azure Well-Architected Framework: What it is and how to tame it with AI and automation

Dynatrace

Using a data-driven approach to size Azure resources, Dynatrace OneAgent captures host metrics out-of-the-box to assess CPU, memory, and network utilization on a VM host. Too many fine-grained services leading to network and communication overhead. Missing caching layers. Too much data requested from a database.

Azure 246
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Cloudburst: stateful functions-as-a-service

The Morning Paper

Today’s paper choice is a fresh-from-the-arXivs take on serverless computing from the RISELab at Berkeley, addressing some of the limitations outlined in last year’s ‘ Berkeley view on serverless computing.’ A low-latency autoscaling KVS can serve as both global storage and a DHT-like overlay network.

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Building an elastic query engine on disaggregated storage

The Morning Paper

If all data was read from S3 every time, performance would suffer, so of course Snowflake has a caching layer – a distributed ephemeral storage service shared by all the nodes in a warehouse. The caching use case may be the most familiar, but in fact it’s not the primary purpose of the ephemeral storage service.

Storage 112
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A one size fits all database doesn't fit anyone

All Things Distributed

Typical use cases for a graph database include social networking, recommendation engines, fraud detection, and knowledge graphs. Zynga also uses ElastiCache (Memcached and Redis) in place of their self-managed equivalents for in-memory caching. Amazon Neptune is a fully-managed graph database service.

Database 167