Remove Continuous Integration Remove Enterprise Remove Microservices Remove Scalability
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Latest DZone Kubernetes in the Enterprise Survey Highlights Key Trends

d2iq

Building on findings from previous years, DZone’s 2022 Kubernetes in the Enterprise Trend Report looks more deeply into the growing ecosystem and tooling, use cases, and advanced strategies for Kubernetes adoption in the enterprise. Figure 8 You can read the full “DZone Kubernetes in the Enterprise Report 2022” here.

Trends 125
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Custom Software Development Services & Modern Practices

Apiumhub

Custom software development benefits Scalability Custom software can grow as the business grows and changes. Scalability with Microservices The microservices architecture (MSA) infrastructure is the building block of many modern network apps and a crucial prospect of modern software design.

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Cloud-Native Applications: Principles, Benefits, and Best Practices

Altexsoft

Enterprises are embracing cloud-native applications to attain the speed, size, and flexibility necessary to operate in fast-paced and dynamic markets. The cloud-native approach offers the best features, such as service meshes, immutable infrastructure, declarative APIs , microservices and containers. Microservices.

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How to get started with your test automation strategy

Agile Engine

Better scalability The ability to handle an increased volume of test cases or adapt to changes in the application architecture is a distinct advantage of automated testing. Executed swiftly by a continuous integration server. Measures reliability, speed, scalability, and responsiveness.

Testing 52
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Software Architecture Youtube Channels to Follow

Apiumhub

These 10 minute YouTube videos contain various aspects of application, integration, and enterprise architecture. . Mark is an experienced, hands-on software architect involved in the architecture, design, and implementation of microservices architectures, service-oriented architectures, and distributed systems.

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Machine Learning with Python, Jupyter, KSQL and TensorFlow

Confluent

Building a scalable, reliable and performant machine learning (ML) infrastructure is not easy. It allows real-time data ingestion, processing, model deployment and monitoring in a reliable and scalable way. It allows real-time data ingestion, processing, model deployment and monitoring in a reliable and scalable way.

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You don’t need to migrate from Jenkins. Start building beside it.

CircleCI

Ten years ago, continuous integration (CI) was just getting off the ground, and tools like Jenkins were first-class automation platforms for your CI pipelines. Many large enterprises use Jenkins for CI. Instead, migrate to modern CI tools gradually as you add new apps and microservices. There is an alternative.