There are many pros and cons for both GraphQL and REST APIs, but one of the areas where GraphQL really shines is API composition. Taking data from multiple APIs and combining them to make something new is a key part of delivering a useful service.

Recovering revenue is an important part of running a successful venture in the modern API economy. With an API product it can be easy to undervalue your services and, ultimately, your business. This is why many API providers turn to billing customers for their usage, but which API monetization method is best for your product stack? Moesif enables you to make smart, informed decisions around your customers and maximize the monetization of your business model.

We previously wrote how the data mesh architecture rose as an answer to the problems of the monolithic centralized data model. To recap, in the centralized data models, ETL or ELT data pipelines collect data from various enterprise data sources and ingest it into a single central data lake or data warehouse. Data consumers and business intelligence tools access the data from the central storage to drive insights and inform decision-making.

As organizations invest ever more heavily in modernizing their data stacks, data teams—the people who actually deliver the value of data to the business—are finding it increasingly difficult to manage the performance, cost, and quality of these complex systems. Data teams today find themselves in much the same boat as software teams were 10+ years ago. Software teams have dug themselves out the hole with DevOps best practices and tools—chief among them full-stack observability.

Some time ago, we covered the key metrics that a Product Manager in a fintech organization should make a top priority when determining their KPIs, breaking them down into five groups: Session-based data, Customer Feedback, Technical Metrics, Action Stats, and Revenue. With that in mind, we conducted a series of surveys on LinkedIn, asking PMs in the fintech industry which of those groups were the most important for them while running digital product analytics.

A JSON Web Token (JWT) is an open standard (RFC 7519) that securely sends and receives data between parties (in the form of a JSON object). In this article, we’ll implement JWT authentication to secure a Node.js application. We’ll also find out what JWT is all about and build a demo app. Let's get going!

Hi there, Here at k6, we’re constantly shipping new features to help our users get the most out of k6. In case you missed it, here’s a roundup of all the k6 and k6 Cloud news, updates, and improvements you should know about.

A decade ago, getting data was a critical task in every industry. Today, we see data flowing into the organization’s database from everywhere. Organizations can access massive amounts of data from sales, marketing, customer experience, finance, operations, human resources, and other departments. The requirement of today is how to use this data efficiently and effectively.

July brings summer vacations, holiday gatherings, and for the first time in two years, the return of the Massachusetts Institute of Technology (MIT) Chief Data Officer symposium as an in-person event. The gathering in 2022 marked the sixteenth year for top data and analytics professionals to come to the MIT campus to explore current and future trends. A key area of focus for the symposium this year was the design and deployment of modern data platforms.

In this article, you’ll be introduced to two tools: Speedscale and NeoLoad. Both of these tools offer you a way to load test your applications. This post will compare their ease of setup, development experience, fit within a modern infrastructure, and integration into CI/CD. Load testing is not a new concept in any way: the term was common even before Google Trends started recording data in 2004.