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How The Cloud Made ‘Data-Driven Culture’ Possible | Part 2: Cloud Adoption

BizAcuity

We had a look at the way in which cloud computing transformed itself through some astonishing innovations in the past decade. We also differentiated cloud adoption from cloud washing. Cloud resources are plenty and they keep multiplying over time. Cloud is now the backbone of digital transformation.

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The future of application delivery starts with modernization

IBM Big Data Hub

IDC estimates that 750 million cloud native will be built by 2025. The reality is that application landscapes are complex, and they challenge enterprises to maintain and modernize existing infrastructure, while delivering new cloud-native features. How can you keep innovating consistently while delivering value?

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Mainframe and the cloud? It’s easy with open source

IBM Big Data Hub

This is part four in a five-part series on mainframe modernization. The secret to mainstreaming the mainframe into today’s modern, cloud-centric IT environments is to make the experience of working with the mainframe like the experience of working off the mainframe—especially the developer experience (DX).

Software 128
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Accelerate release lifecycle with pathway to deploy: Part 2

IBM Big Data Hub

As enterprises embrace cloud native and everything as code, the journey from code to production has become a critical aspect of delivering value to customers. Pathway to deploy roadmap To realize an accelerated pathway to deploy, there are several moving parts and stakeholders that must come together.

Testing 82
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Cloud Analytics Powered by FinOps

Cloudera

Cloud transformation is ranked as the cornerstone of innovation and digitalization. The legacy IT infrastructure to run the business operations — mainly data centers — has a deadline to shift to cloud-based services. However, the reality is that the “move to cloud” is a turbulent flight for many of them. Why FinOps?

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Debunking observability myths – Part 6: Observability is about one part of your stack

IBM Big Data Hub

In modern software and system management, observability goes beyond focusing on just one part of the stack. However, this approach can overlook intricate interactions and dependencies between different parts of the stack. This misconception arises from a fundamental misunderstanding of observability’s core concept.

Metrics 78
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Debunking observability myths – Part 3: Why observability works in every environment, not just large-scale systems

IBM Big Data Hub

In our blog series, we’ve debunked the following observability myths so far: Part 1: You can skip monitoring and rely solely on logs Part 2: Observability is built exclusively for SREs Observability refers to the ability to gain insights into a system’s internal behaviour based on external outputs or signals.

Metrics 67