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Sustainability Talks and Updates from AWS re:Invent 2023

Adrian Cockcroft

The Pantheon in Rome — Extremely sustainable architecture — photo by Adrian I wrote a medium post after AWS re:Invent 2022 summarizing the (lack of) news and all the talks related to Sustainability. Google Cloud and Microsoft Azure released Scope 3 data in 2021. You must bring your laptop to participate.

AWS 52
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What are microservices? An agile architecture for software development

Dynatrace

Microservices are run using container-based orchestration platforms like Kubernetes and Docker or cloud-native function-as-a-service (FaaS) offerings like AWS Lambda, Azure Functions, and Google Cloud Functions, all of which help automate the process of managing microservices. Focused on delivering business value. Complexity.

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What are microservices? An agile architecture for software development

Dynatrace

Microservices are run using container-based orchestration platforms like Kubernetes and Docker or cloud-native function-as-a-service (FaaS) offerings like AWS Lambda, Azure Functions, and Google Cloud Functions, all of which help automate the process of managing microservices. Focused on delivering business value. Complexity.

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The future of synthetic testing is in the cloud

Dynatrace

If you’re spending the majority of your time on data center and hardware logistics, it doesn’t leave a lot of time to build better features, keep browsers updated, or satisfy your customers. With Cloud, we are leveraging the largest cloud providers’ locations, including AWS, Azure, Alibaba and Google coming very soon.

Cloud 201
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Top 9 web development trends to expect in 2022

Enprowess

The most preferred single-page applications are Gmail, Google Drive, Facebook, Twitter, and Instagram. Low data usage and Offline accessibility: It works fine in low internet reception and is also possible to access offline like Google Maps. Serverless Computing – AWS Lambda – Amazon Web Services. Examples of SPAs.

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5 key areas for tech leaders to watch in 2020

O'Reilly

From pre-built libraries for linear or logistic regressions, decision trees, naïve Bayes, k-means, gradient-boosting, etc., This is the logic of cloud native design: specific deployment contexts will still matter, of course—which features or constraints do developers need to take into account when they’re developing for AWS?