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Crafting the Best Golang Developer Environments

Aug 26, 2024 By Nate Lee In Speedscale

Go is an open-source programming language and developer environment from Google that allows for incredibly efficient and powerful applications. Go’s expressive syntax enables developers to write clean, efficient, concise code, allowing faster development cycles and easier maintenance. Whether you’re developing complex distributed systems or lightweight microservices, Go and its powerful libraries provide the tools necessary to create robust and scalable solutions.

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Developer's Guide To Smoke Testing : Ensuring Basic Functionality

Aug 26, 2024 By tvisha In Keploy

Imagine running a Python project without a requirements.txt file. Just as you rely on these checks to ensure everything runs fine, smoke tests are performed to confirm that your code is ready for the next phase. Let’s dive into the world of smoke testing now!

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5 Strategies for Decreasing API Latency and Improving App Performance

Aug 23, 2024 By Shaun Duncan In Speedscale

Application performance can make the difference between retaining or losing customers, with delays beyond a few seconds leading to dropped conversions. Performance testing and monitoring are vital for improving the overall user experience, achieving a competitive advantage, enhancing resource efficiency, enabling scalability, and reducing costs.

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A Guide To Test Cases In Software Testing

Aug 23, 2024 By Animesh Pathak In Keploy

In software development, test cases are essential components that validate the functionality, quality, and reliability of an application. Writing effective test cases ensures that the code behaves as expected in all scenarios, including edge cases, and can be confidently deployed into production. In, this blog will dive deep into test cases, covering different types, test coverage, tools used, and how to handle edge cases.

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What is API Monetization? Exploring API Revenue Streams

Aug 23, 2024 By Kong In Kong

APIs enable our digital world. But they can also be a powerful source of revenue through the process of API monetization or API productization. A decade ago, many business workflows were conducted through manual tasks, logging into monolithic SaaS applications that were rolled out across entire business units or companies. Fast forward to 2024, and we find individual developers leveraging automation, AI, and APIs to tackle specific, targeted use cases.

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AI-based API Testing in WSO2 API Manager 4.3.0

Aug 23, 2024 By WSO2 In WSO2

WSO2 API Manager is stepping into the age of AI. We’re thrilled to announce one of the core features that we have released with WSO2 API Manager 4.3.0: AI-based API Testing. If you have any questions or need further information, feel free to reach out in the comments or contact us directly.

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Elevating Developer Productivity with Speedscale Ephemeral Environments

Aug 22, 2024 By Matthew LeRay In Speedscale

Speedscale leveraged Ephemeral / Preview Environments to help balance developer productivity and high-quality code by dynamically spinning mini-staging environments up and down on command for experimentation and deployment safety. The primary goals of the project were to reduce cloud infrastructure operating costs and increase deployment frequency. Benefits included speed, resource efficiency, and improved collaboration.

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How To Handle Node.Js Code Coverage With Nyc In Docker Containers

Aug 22, 2024 By Shivam In Keploy

There are particular difficulties in getting NYC coverage from Node.js operating in Docker containers. This blog discusses the procedures needed to operate Node.js clusters in Docker and produce reliable code coverage reports.

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The AI Gateway Pattern: Adopt AI and Multi-LLM Strategies in a Secure and Governable Way

Aug 22, 2024 By Kong In Kong

The AI Gateway Pattern enables organizations to adopt and securely govern AI technologies like large language models (LLMs) at scale. Acting as a centralized control plane, it streamlines data flow into AI models, ensures proper data handling and compliance, and simplifies the management of multiple LLMs. This architectural pattern empowers organizations to leverage AI’s strengths while mitigating risks, maintaining performance, and adapting to evolving technologies.

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