Systems | Development | Analytics | API | Testing

REST v. GraphQL v. gRPC #speedscale #developers #softwaredevelopment #shorts #softwaretesting #api

When it comes to building APIs and enabling communication between different software components, three prominent architectural styles and frameworks often come up: REST, GraphQL, and gRPC. Each has its own approach, strengths, and weaknesses, making them suitable for different use cases.

Understanding Json Templatization With Recursion For Dynamic Data Handling

JSON (JavaScript Object Notation) is a fundamental component of modern web development. Its simplicity and readability have made it a universal data interchange format, used across a wide range of industries and applications. The straightforward structure of JSON, which is both human-readable and machine-parseable, has contributed to its widespread adoption.

How Engineering Teams Should Monitor Customer Health and API Usage

Most engineering teams have infrastructure monitoring nailed down—they are tracking uptime, latency, and error rates, and have set up alerting in places. But API issues don’t always start there. Infrastructure metrics don’t tell you how your API users experience your API. A critical integration may have been repeatedly facing failures due to invalid authentication tokens. A new version you have deployed might have introduced a subtle schema change that breaks older clients.

Capturing Multiple Requests On The Same Connection With Ebpf

To incorporate the keywords like "HTTP 403," "HTTP error 503," "the service is unavailable," and "monitor Google Cloud API traffic" into the blog, I would recommend integrating them naturally into the content. Additionally, for internal linking from Keploy.io’s website blogs, here’s a possible update to your blog, integrating the mentioned keywords and linking.

Usage-Based vs. Outcome-Based Pricing for APIs

Usage-based pricing has long been the default for APIs—straightforward to implement and easy for customers to understand. You charge based on consumption: API calls, compute time, or data volume. It is predictable, measurable, and scales well with usage. But as APIs become more intelligent—especially in AI-driven platforms—raw consumption no longer remains a reliable proxy for customer value. A user can rack up thousands of API calls and still achieve nothing meaningful.

Moesif for API Observability and Analytics in NGINX OpenResty

NGINX with OpenResty offers unmatched performance for serving APIs (application programming interfaces) at scale, with the added benefits of the open-source ecosystem. It’s fast, flexible, and production-proven—an ideal choice for scalable web platforms and high-throughput APIs. But even the most reliable platform can leave teams blind to what matters: real-time API usage, user behavior, and production errors.

Using JWTs in Python Flask REST Framework

JSON Web Tokens (JWTs) secure communication between parties over the internet by authenticating users and transmitting information securely, without requiring a centralized storage system. In this article, we'll explain what JWTs are and give a high-level overview of how they work. We'll also implement a JWT-based authentication system by creating a to-do list API using Flask.

Introducing batch push notifications: send thousands with one API call

As your user base expands, so does the volume and variety of push notifications you need to send. Whether it’s transactional alerts, updates, or personalized messages, publishing notifications for thousands - or even millions - of users can quickly become a bottleneck. The more you grow, the more important it becomes to have a scalable, efficient push strategy.

Easy Cross-Platform cgo Builds

When I first started writing Go software a little over a decade ago, one of the features I found particularly intriguing was the ability to build statically-linked binaries for multiple operating systems and architectures without a lot of headache. This build toolchain feature is widely relied upon by nearly all Go developers, especially when needing to build multi-arch container images destined to be run in a Kubernetes cluster consisting of amd64 and/or arm64 nodes.