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How to overcome the cloud observability wall

Dynatrace

You may be using serverless functions like AWS Lambda , Azure Functions , or Google Cloud Functions, or a container management service, such as Kubernetes. In contrast to modern software architecture, which uses distributed microservices, organizations historically structured their applications in a pattern known as “monolithic.”

Cloud 225
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Trends and Topics for 2022

Adrian Cockcroft

The need for systems to be resilient is still increasing, and chaos engineering tools and techniques are developing as a key way to validate that resilience is working as designed. For example AWS launched an instance type with 800 Gbits/s of network bandwith in 2021.

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Design Patterns: Queue-Based Load Leveling Pattern

cdemi

Modern software usually involves running tasks that invoke services. If the service is subjected to intermittent heavy loads, it can cause performance or reliability issues. Control Costs : You don't have to design your service to meet peak load, but rather average load. Considerations.

Design 47
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5 key areas for tech leaders to watch in 2020

O'Reilly

Software architecture, infrastructure, and operations are each changing rapidly. The shift to cloud native design is transforming both software architecture and infrastructure and operations. R was designed for use in academic, scientific, and, more recently, commercial use cases.

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Open-Sourcing Metaflow, a Human-Centric Framework for Data Science

The Netflix TechBlog

The infrastructure should allow them to exercise their freedom as data scientists but it should provide enough guardrails and scaffolding, so they don’t have to worry about software architecture too much. It leverages elasticity of the cloud by design?—?both On the surface, this doesn’t seem like much.

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Open-Sourcing Metaflow, a Human-Centric Framework for Data Science

The Netflix TechBlog

The infrastructure should allow them to exercise their freedom as data scientists but it should provide enough guardrails and scaffolding, so they don’t have to worry about software architecture too much. It leverages elasticity of the cloud by design?—?both On the surface, this doesn’t seem like much.

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MLOps and DevOps: Why Data Makes It Different

O'Reilly

Let’s start by considering the job of a non-ML software engineer: writing traditional software deals with well-defined, narrowly-scoped inputs, which the engineer can exhaustively and cleanly model in the code. In effect, the engineer designs and builds the world wherein the software operates. Software Development Layers.

DevOps 138