Why this combination you ask? Load testing is my passion, and I am partial to Kubernetes. I challenged myself to share a use case that many could relate to, focused on a business critical application. Websites came to mind and WordPress is the world’s most popular website management system. Of course, nginx is the most popular web server so let’s throw that into the mix. And Kubernetes? With more than 50% of corporations adopting Kubernetes in 2021, what better system to run in.

Python code optimization may seem easy or hard depending on the performance target. If the target is “best effort”, carefully choosing the algorithm and applying well-known common practices is usually enough. If the target is dictated by the UX, you have to go down a few abstraction layers and hack the system sometimes. Or rewrite the underlying libraries. Or change the language, really. This post is about our experience in Python code optimizations when whatever you do is not fast enough.

To provide a fast, seamless, and highly available experience for the end-user, modern applications increasingly rely on third-party services. Due to this rising complexity, it's become important for IT employees to ensure that these services are up and running and communicating as they should. API monitoring has thus become a must-have for DevOps teams.

While Go provides a testing package and a go test command, the former only offers basic testing capabilities. The package also has some drawbacks, such as missing assertions and increasing repetition with large-scale tests. As a result, several Go testing frameworks have been created to augment it. Go testing frameworks consist of tools and resources for creating and designing tests. Some of these frameworks incorporate the testing package and go test command, while others take a different approach.

One of Checkly's strengths is the capability to monitor key transactions on your site. It'd be missed opportunity if we didn't reuse it to monitor our own product! But for some important flows that comes with a couple of pitfalls. In this post, we'll take a closer look at how we monitor one of our top key flows: signup.

The focus of the 2.5 version was on expanding support for HAProxy configuration keywords, and that’s where most of the effort during this release cycle was spent. We will continue doing that during the next couple of versions to gain complete feature parity with both the HAProxy configuration and Runtime API so that you can use the Data Plane API as a full-featured way to configure HAProxy.

Microservice is now the architecture of choice for many developers when crafting cloud-native applications. A microservices application is a collection of loosely coupled services that communicate with each other, enhancing collaboration, maintainability, scalability, and deployment. There are several options for enabling this communication between microservices. REST is the most popular among developers, sometimes used synonymously with APIs. However, gRPC can be a better alternative to REST.

Kubernetes has experienced rapid growth over the years, with a recent post from the Cloud Native Computing Foundation reporting a userbase increase of about 67% in just the past year. Kubernetes is a container orchestration platform that automates how containers are deployed, how they communicate, and how traffic is routed between them; it also scales configurations for both the containerized workloads and the underlying infrastructure that comprises the cluster.

Postman is a great tool for API testing during development. It’s GUI is simple to learn and ubiquitous. However, manually writing test cases for local development gets tedious fast if you have a lot of endpoints. Meticulously entering every detail for every use case takes forever. Also, if you get one HTTP Header or parameter wrong, it can take hours to diagnose. And even when it’s done, the API tests are almost immediately out of date because the API contract changes.

On Nov 13, 2019 Github made it’s CI/CD solution GitHub Actions generally available to the world. Since then tens of thousands of shared workflows have been published. It is now the default for most Github projects given how easy it is to integrate with an existing repo. Projects of all sizes have adopted it from our homegrown Terraform module to the Docker Cli. This is why at Speedscale we’ve published a template for how to use Speedscale in conjunction with GitHub Actions.

Has your team worked on an API and wanted (somehow) to implement more powerful security features? If you are dissatisfied with the level of security in an API, there are solutions for improving it! In this tutorial, I will lead you through the process of creating API endpoints that are secured with authentication tokens. Using these endpoints, we will be able to make requests to the Flask API only for authenticated users.

This article was written by Nicolas Bohorquez. Scroll below for the author’s picture and bio. Time series databases, like InfluxDB, index data by time. They are very efficient at recording constant streams of data, like server metrics, application monitoring data, sensor reports, and any data containing a timestamp. Data in a time series database is always written with the most recent data values but with the previous values not updated.

Speedscale is excited to join the AWS Partner Network (APN), the global community of partners who leverage Amazon Web Services (AWS) to build solutions and services for customers. AWS Partners are uniquely positioned to help businesses take full advantage of all that AWS has to offer and accelerate the journey to the cloud. As part of this achievement, Speedscale has completed the AWS Foundational Technical Review (FTR).

Modern product management philosophy encourages teams to use user-centered design, lean startup techniques, and agile development practices to build successful products that meet customer needs and respond to changes in technology and the marketplace.