
Compute Engine (IaaS), a platform from Google that allows organizations to create and manage cloud-based virtual machines, is an infrastructure as a services (IaaS).
Computing infrastructure in predefined sizes or custom machine shapes to accelerate cloud transformation. General purpose machines (E2, N1,N2,N2D) offer a good compromise between price and performance. Compute optimized machines (C2) offer high-end performance vCPUs for compute-intensive workloads. Memory optimized (M2) systems offer the highest amount of memory and are ideal for in-memory database applications. Accelerator optimized machines (A2) are based on A100 GPUs, and are designed for high-demanding applications. Integrate Compute services with other Google Cloud Services, such as AI/ML or data analytics. Reservations can help you ensure that your applications will have the capacity needed as they scale. You can save money by running Compute using the sustained-use discount, and you can even save more when you use the committed-use discount.
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Dragonfly serves as a seamless substitute for Redis, offering enhanced performance while reducing costs. It is specifically engineered to harness the capabilities of contemporary cloud infrastructure, catering to the data requirements of today’s applications, thereby liberating developers from the constraints posed by conventional in-memory data solutions. Legacy software cannot fully exploit the advantages of modern cloud technology. With its optimization for cloud environments, Dragonfly achieves an impressive 25 times more throughput and reduces snapshotting latency by 12 times compared to older in-memory data solutions like Redis, making it easier to provide the immediate responses that users demand. The traditional single-threaded architecture of Redis leads to high expenses when scaling workloads. In contrast, Dragonfly is significantly more efficient in both computation and memory usage, potentially reducing infrastructure expenses by up to 80%. Initially, Dragonfly scales vertically, only transitioning to clustering when absolutely necessary at a very high scale, which simplifies the operational framework and enhances system reliability. Consequently, developers can focus more on innovation rather than infrastructure management.
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Rider
JetBrains Rider is a robust and efficient cross-platform IDE for .NET development, allowing users to create applications for .NET, ASP.NET, .NET Core, Xamarin, and Unity across Windows, Mac, and Linux operating systems. Built on the IntelliJ platform and enhanced by ReSharper, Rider offers compatibility with .NET Framework, cross-platform .NET Core, and Mono projects. This versatility enables developers to build a diverse array of applications, from desktop software and web services to Unity games and mobile apps. Rider boasts over 2200 live code inspections along with numerous context actions and refactorings, seamlessly integrating ReSharper's capabilities with the comprehensive features of the IntelliJ platform. With its extensive functionality, Rider maintains a focus on speed and responsiveness, ensuring a smooth development experience. Additionally, it supports running and debugging across various runtimes while being fully operational on multiple operating systems. Moreover, Rider incorporates more than 60 refactorings from ReSharper and offers a wide selection of over 450 context actions, enhancing productivity further.
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dotTrace
dotTrace serves as a robust performance profiler specifically designed for .NET applications, seamlessly integrating within Visual Studio and JetBrains Rider to effectively identify and analyze performance bottlenecks. This tool is versatile, supporting a range of .NET applications such as desktop software, .NET Core, ASP.NET hosted on both IIS and IIS Express, as well as Mono, Unity applications, WCF services, Windows services, Universal Windows Platform applications, and unit tests. In contrast to traditional performance profiling, which primarily focuses on measuring the execution time of method calls, timeline profiling offers insights into the temporal distribution of calls. This feature is particularly valuable for diagnosing performance challenges where the sequence of events is critical, including issues like UI lags, excessive garbage collection, uneven workload distribution, and inefficient file input/output operations. With dotTrace, users can manipulate and analyze profiling data through various tools such as filters, call trees, and visual diagrams, enhancing their ability to pinpoint and resolve performance issues effectively. Moreover, the intuitive interface allows developers to quickly adapt their strategies based on real-time insights, ensuring that applications run smoothly and efficiently.
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