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1. Introduction 2. Python environment setup 3. VSCode Primer 4. Extensions overview 1. Gitlens 2. Python test & debug 3. Ruff 4. SQL Tools 5. Jupyter 6. Data Wrangler 7. autoDocstring 8. Rainbow csv 9. DBT power user 5. Privacy, Performance, and Cognitive Overload 6. Conclusion 7. Recommended reading 1. Introduction Whether you are setting up visual studio code for your colleagues or want to improve your workflow, tons of extensions are available.
You work with data to gain insights, improve decisions, and develop new ideas. With more and more data coming from all sorts of places, it’s super important to have a good data plan. That’s where big data integration comes in! It’s all about combining data from different sources to get a complete picture.
Introduction At Zalando, we faced a critical challenge: our ingress controller was threatening to overload our Kubernetes cluster. We needed a solution that could handle the increasing traffic and scale efficiently. This is the story of how we implemented a Route Server to manage control plane traffic more effectively and ensure a stable cluster. Skipper: Our Ingress Controller We use Skipper , our HTTP reverse proxy for service composition, to implement the control plane and data plane of Kuber
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The current data-centric environment changes how organizations handle business information by implementing cloud data integration methods. By seamlessly connecting different data sources, companies gain real-time insights that drive smarter decisions and improve daily operations. Like for example Netflix, its advanced cloud strategies help process a staggering 550 billion events every day, generating 1.
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