In practice, large-scale applied Machine Learning (ML) requires substantial infrastructure and systems engineering investment. Learn about scaling machine learning in heterogeneous language environments across several domains and at all stages of a project’s lifecycle, including ad-hoc exploration, preparing training data, model development, and robust production deployment.

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5. I Heart Logs ebook

Why a book about logs? That’s easy: the humble log is an abstraction that lies at the heart of many systems, from NoSQL databases to cryptocurrencies. Even though most engineers don’t think much about them, this short book shows you why logs are worthy of your attention.

Based on his popular blog posts, LinkedIn principal engineer Jay Kreps shows you how logs work in distributed systems, and then delivers practical applications of these concepts in a variety of common uses—data integration, enterprise architecture, real-time stream processing, data system design, and abstract computing models.

Go ahead and take the plunge with logs: you’re going to love them.

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6. Five steps to Event Streaming
Plenty of businesses make an initial toe-dip into event streaming to solve for a particular task that requires moving large amounts of data around. This sort of bottom-up, or developer- led, entree is a typical start to the adoption journey of event streaming. But if the platform never reaches the sight line of company leadership, it may be blocked from reaching its full potential—and the organization may not truly capitalize on data, or event streaming, to transform.

There’s profound strategic potential in an event streaming platform for enterprise businesses of many kinds. The types of business challenges’ event streaming is capable of addressing include driving better customer experience, reducing costs, mitigating risk, and providing a single source of truth across the business. It can be a game changer.

Here are the five crucial steps to turning event streaming into a business driver and digital transformer.

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10 Principles for Streaming Services
As streaming data becomes an increasingly significant factor for modern, digital-age businesses, organizations need flexible tools for managing data streams efficiently and in real-time. Microservices architectures enable businesses to evolve their systems away from the slow and unresponsive shared-state architectures of the past. Businesses can deploy a microservice- based environment either with event-based or request-response approaches, or a hybrid of the two. The trend in business today is towards hybrid or predominantly event-driven architectures, in which the services themselves raise events.
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Five Event Streaming use cases that Transform Business
The recent revolution in data infrastructure and application architecture has transformed the way all kinds of organizations, from the traditional to the digital native, work with data. But to truly take advantage of event streaming as the most strategic platform within your company, it must move from the domain of one-off engineering initiatives into a central nervous system for the enterprise.

Transformation takes thoughtful strategy with specific business impact in mind. Knowing what business use cases other companies are putting into best practice is a great way to start envisioning—and enabling—your own shift to a centralized event streaming paradigm.

Read on to discover five of the top use cases Confluent has witnessed, with real-world customer examples and insights into how your organization can make the leap.

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Modernizing the Established Bank

Technology is transforming the business of banking. Goldman Sachs has 1.5 billion lines of code across 7,000+ applications. JPMorgan Chase employs over 50,000 people in technology and has $10B+ technology spend. Just as Amazon.com is famously a data company that happens to sell books — corporate, investment and retail banks are now software companies that happen to deal with money.

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