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By Shaun Duncan
Testing AWS services is an essential step in creating robust cloud applications. However, directly interacting with AWS during testing can be complicated, time-consuming, and expensive. The AWS SDK Mock is a JavaScript library designed to simplify this process by allowing developers to mock AWS SDK methods, making it easier to simulate AWS service interactions in a controlled environment. Primarily used with AWS SDK v2, AWS SDK Mock integrates with Sinon.js to mock AWS services like S3, SNS, and DynamoDB.
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By Kush Mansingh
Mocking APIs is a popular practice in software development. An increasing number of developers are reaping the benefits and no longer using their valuable time to spin up duplicate resources. Many mock services do not require account creation, making them easy to use and privacy-friendly. In the rest of this article, we explain what mock APIs are, when you should think about using them, and what solutions are available within the open-source and proprietary markets.
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By Kasper Siig
Measuring throughput and latency is a critical step in load testing software to ensure application performance and stability. In this article, we’ll discuss essential considerations before beginning performance testing and provide a detailed, step-by-step guide on leveraging production traffic replication in Kubernetes. This approach helps you accurately determine your software’s maximum throughput during performance testing.
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By Shaun Duncan
As developers, one of the most important things we can consider when designing and building applications is the ability to know if our application is running in an ideal operating condition, or said another way: the ability to know whether or not your application is healthy. This is particularly important when deploying your application to Kubernetes. Kubernetes has the concept of container probes that, when used, can help ensure the health and availability of your application.
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By Kush Mansingh
At some point, your development team may be considering implementing load testing (also known as stress testing) as part of your software testing process. Load testing validates that your web app is able to withstand a large number of simultaneous users, decreasing the chance that any traffic spikes will bring down your services once deployed. These stress tests can be highly granular, giving you the opportunity to test run virtually unlimited strategies before they are set into the wild.
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By Kasper Siig
Transactions-per-Second (TPS) is a valuable metric for evaluating system performance and is particularly relevant for engineers overseeing Kubernetes environments.TPS, alongside average response time, provides critical insights into system performance during load testing. This post covers two approaches to calculating TPS; a manual approach applicable in all environments, and an automatic Kubernetes-specific solution using production traffic replication.
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By Nate Lee
What do good tests look like, and do you even need a Golang testing framework? It’s a loaded question with an open answer. Not only do tests help ensure that your code will work as intended, but good tests can also serve as documentation for your codebase, making it easier to update and maintain in the future, while accelerating and streamlining your software development process. In this article, we outline 6 Golang testing frameworks for every type of test.
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By Ken Ahrens
Developing highly resilient Kubernetes deployments is crucial for ensuring that your hosted applications in Kubernetes can effectively manage and recover from disruptions. This capability is vital in order to maintain continuous availability for your customers. The importance of resilience in your distributed system also escalates depending on your customer base and the critical nature of your application. Even brief periods of downtime can have a significant negative impact on your business.
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By Josh Thornton
All but the simplest applications borrow code. You could write everything yourself from just core language features but who has time for that? Instead you take on dependencies, pieces of code written by others that usually give us 80% or more of what we need with 20% of the effort. Sometimes these dependencies are made to interact with a specific technology like a database, or perhaps it’s just a library providing some feature that would be onerous to write yourself.
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By Nate Lee
Go, often referred to as Golang, is a popular programming language built by Google. Its design and structure help you write efficient, reliable, and high-performing programs. Often used for web servers and rest APIs, Go offers the same performance as other low-level languages like C++ while also making sure the language itself is easy to understand with a good development experience.
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By Speedscale
Building and debugging Kubernetes microservices can be tough, especially when you don't have realistic data or environments. See how Speedscale can quickly mock DBs and APIs based on observed production behavior, so you can debug and develop features quickly. People familiar with GoReplay will notice a more modern and automated approach to turning user behavior into reproducible developer environments.
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By Speedscale
Check out Matt LeRay's talk on How to Test in Kubernetes at Star WEST 2024. Distributed architectures like Kubernetes present unique performance challenges. Autoscaling, Load Balancing and other mechanisms help with resiliency but can also serve to cover up fundamental problems. In this video, learn best practices and high level concepts around Kubernetes and achieving high throughput.
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By Speedscale
Mocks can be useful, but hard to build. You can use them as backends for development, or even tests (like load and performance testing). Speedscale takes the legwork out of building mocks, by modeling them after real observed traffic. This video covers a real-world example of how to use mocks to backend a JMeter load test.
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By Speedscale
Speedscale's Traffic Viewer is the perfect complement to your production monitoring or observability system because it provides detailed information (like request and response payloads, headers, cookies, and more) that actually helps developers debug any issues and requires zero developer intervention--all of the data is provided from traffic.
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By Speedscale
In a conversation with Sephora's Senior Performance Engineer, Diana Manulik discusses why their current load testing tool, JMeter, wasn't meeting their needs for reporting, and why they chose Speedscale.
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By Speedscale
In this conversation with Sephora's Senior Performance Engineer, Diana Manulik discusses how she uses Speedscale and WireMock to generate mocks much faster.
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By Speedscale
When working with #AI in cloud environments, traditional data provisioning and software testing methods don't work because of the behavior of AI and LLM APIs. In this Cloud Native Computing Foundation (CNCF) webinar recording, we discuss the top 4 challenges of scaling cloud-native AI workloads, and the solutions developers are turning to instead.
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By Speedscale
In this brief demo, we show how engineers can build and test quickly by autogenerating traffic simulations, load and mocks from actual traffic using Speedscale.
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By Speedscale
How does Speedscale compare to Observability tools? CTO Matt LeRay quickly explains the differences in this one-minute video.
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By Speedscale
Speedscale is a Y-Combinator backed startup that helps Kubernetes engineering teams build resilient and performant containerized apps. Our production traffic replication platform is a more reliable, cost-effective, and scalable way to test and deliver cloud-native software applications. Unlike other tools, we use agents/sidecars to record and playback sanitized traffic that you see in prod. With Speedscale, engineers can generate load, simulate production conditions, and mock third party backends modeled after real traffic patterns.
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Continuous Resiliency from Speedscale gives you the power of a virtual SRE-bot working inside your automated software release pipeline. Forecast the real-world conditions of every build, and know you’ll hit your SLO’s before you go to production.
Feed Speedscale traffic (or let us listen) and we’ll turn it into traffic snapshots and corresponding mock containers. Insert your own service container in between for a robust sanity check every time you commit. Understand latency, throughput, headroom, and errors -- before you release! The best part? You didn’t have to write any scripts or talk to anyone!
Automated Traffic Replay for Every Stakeholder:
- DevOps / SRE Pros: Understand if your app will break or burn up your error budget before you release.
- Engineering Leads: Let Speedscale use traffic to autogenerate tests and mocks. Introduce Chaos testing and fuzzing.
- Application Executives: Understand regression/performance, increase uptime and velocity with automation.
Before you go to production, run the projection.