Strategic Tech

FEBRUARY 15, 2023

This article was co-authored by Eduardo da Silva and Nick Tune based on our individual and collective experiences. FThis article describes a pattern we have observed and applied in multi-team-scope architecture modernization initiatives, the Architecture Modernization Enabling Team (AMET).

Architecture 97

Architecture Innovation Airlines Technology 97

Adrian Cockcroft

MARCH 21, 2020

If you think about the scale that Netflix operates at, and the number of new customers they get every day, they can run far more and bigger tests than their smaller competitors, so they have a scale advantage that they can use to tune their product, and maintain a higher rate of innovation.

Testing 52

Testing Tuning Database Cache 52

Dynatrace

AUGUST 12, 2020

As companies strive to innovate and deliver faster, modern software architecture is evolving at near the speed of light. Following the innovation of microservices, serverless computing is the next step in the evolution of how applications are built in the cloud. So stay tuned! Dynatrace news. What’s next.

Serverless 236

Serverless Azure Monitoring Lambda 236

Dynatrace

AUGUST 12, 2020

As companies strive to innovate and deliver faster, modern software architecture is evolving at near the speed of light. Following the innovation of microservices, serverless computing is the next step in the evolution of how applications are built in the cloud. So stay tuned! Dynatrace news. What’s next.

Serverless 141

Serverless Azure Monitoring Lambda 141

Abhishek Tiwari

JULY 20, 2019

In this model, software architecture and code ownership is a reflection of the organisational model. I also have a strong feeling that long-lived teams are not good for innovation and disruption. Secondly, fine-tune team composition based on work. You want to move fast.

Engineering 61

Engineering Retail Airlines Healthcare 61

O'Reilly Software

APRIL 4, 2018

Here are five considerations every software architect and developer needs to take into account when setting the architectural foundations for a fast data platform. The data shape will dictate capacity planning, tuning of the backbone, and scalability analysis for individual components. Determine requirements first. At most once?

Architecture 80

Architecture Scalability Google Operating System 80