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Integration Architecture Guiding Principles, A Reference

Dzone - DevOps

The Integration Architecture guiding principles are guidelines to increase the consistency and quality of technology decision-making for the integration solutions. In the context of Integration Architecture, the guiding principles drive the definition of the target state of the integration landscape.

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Sustainable change requires architecture of technology and organization

Xebia

Nicole Forsgren, the lead researcher of the State of DevOps reports, puts it in this way: “Investments in technology, are also investments in people, and these investments will make our technology process sustainable.”. The definition shows it is broader than just the software systems that we create. My definition is.

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An IT leader’s mission to retrofit the tech foundation at Eon

CIO

Weber definitely didn’t want the merger of two old IT infrastructures to create one big old IT infrastructure. This was followed by a phase in which the IT landscape was stabilized and the IT architecture was prepared for the future. That’s why his focus was on grassroots work that modernized IT.

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20 Software architecture podcasts to follow

Apiumhub

At Apiumhub we listen to hours of working software and software architecture podcasts each week covering architecture patterns, DevOps and architecture, iOS architecture, Android architecture, Backend architecture, Frontend architecture, etc. DevOps and Docker Talk. The Changelog.

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Scaling DevOps: key strategies and best practices

Agile Engine

Introduction Over the past decade, DevOps has had a transformative impact on how companies manage their software engineering efforts. Yet, eight out of 10 companies practicing DevOps are barely in the middle of this transformation. It seems that scaling DevOps is a challenge in itself, so let’s look at how companies can solve it.

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Coralogix streams $142M into its coffers to expand its production analytics into a full-stack observability platform

TechCrunch

We’ve long documented the challenges that DevOps and operations teams in specific areas like security face these days when it comes to data observability: a wide range of services across the landscape of an organization’s network translates into many streams of data that they need to track for performance, security and other reasons.

Analytics 246
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Data lake architecture

Apiumhub

The concept of Data lake architecture has recently become a hot topic. Data lakes really became the cornerstones of modern big data architecture. Rich Computing Engines Data lake architecture supports a diversity of computing engines, including batch processing, stream computing, interactive analytics, and machine learning engines.