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Modernize Test Data Management with Traffic Replay

In software testing or platform engineering, having realistic data is crucial. For years, teams have relied on Test Data Management (TDM) to copy entire production databases, scrub any sensitive information, and then spin up test environments from these sanitized data sets. While TDM gets the job done, it can be costly, time-consuming, and can quickly become outdated. The issue of outdated data becomes more pronounced as deployment velocity increases and back end dependencies become more diverse (think: microservices).

Using Proxymock with AWS Services

Amazon Web Services, or AWS, offers a variety of cloud services ranging from AWS resources such as CDNs and data lakes to cloud computing and transformation services such as compute resources, virtual servers, and dynamic availability zones. For this reason, AWS cloud is one of the most broadly adopted cloud solutions, offering a global network of solutions at generally lower costs compared to on-premises solutions.

Benefits of Developers Using Service Mocks #speedscale #shorts #mocks #servicemocks #programming

Nate Lee discusses the benefits of developers using service mocks, highlighting how they allow teams to simulate APIs and external services during development and testing. This approach enables developers to work independently of backend systems, reduce dependencies, and catch issues early, ultimately improving productivity and software quality.

Using Proxymock with GCP Services

Google Cloud Platform, or GCP, is a cloud resources collection offered by Google for enterprise and standard users. GCP offers a wide range of cloud services, including compute, storage, networking, security, analytics, and even machine learning models. Google Cloud products are the backbone of many cloud applications. Google Cloud allows flexibility with the scalable and predictable cost management.
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Six Lessons from Production gRPC

In the half-decade since gRPC became part of our production ecosystem, we've encountered a range of challenges and discovered a few hidden pitfalls that can trip up even the most experienced teams. Below, we'll walk through some of the core lessons learned, with tips, best practices, and examples drawn straight from the trenches.

Automating API Mocks in Your CI Pipeline with proxymock

When running tests in a CI/CD pipeline, relying on external APIs can introduce instability, slow down execution, and even lead to failed builds due to rate limits or API downtime. Fortunately proxymock provides a solution by capturing API interactions and running a local mock server, enabling fully isolated and repeatable tests. In this blog, we’ll demonstrate how to integrate proxymock into a GitHub Actions CI pipeline using a demo app called outerspace-go.

Service Mocks #speedscale #service #mocks #software

Ken Ahrens from Speedscale break down the challenges with service mocks — from the complexity of building them to common misunderstandings about their purpose. Many think of mocks like unit test stubs, but service mocks are much more powerful. They can simulate production conditions right on your laptop, making testing more realistic and reliable.