Intro

Organizations are increasingly looking to containers and distributed applications to provide the agility and scalability needed to satisfy their clients. While doing so, modern enterprises also need the ability to benchmark their application and be aware of certain metrics in relation to their infrastructure.

In this post, I am introducing you to a cloud-native bench-marking tool known as Kubestone. This tool is meant to assist your development teams with getting performance metrics from your Kubernetes clusters.

How Does Kubestone Work?

At it’s core, Kubestone is implemented as a Kubernetes Operator in Go language with the help of Kubebuilder. You can find more info on the Operator Framework via this blog post.
Kubestone leverages Open Source benchmarks to measure Core Kubernetes and Application performance. As benchmarks are executed in Kubernetes, they must be containerized to work on the cluster. A certified set of benchmark containers is provided via xridge’s DockerHub space. Here is a list of currently supported benchmarks:

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The purpose of computing is insight, not numbers.  — Richard Hamming

The spiral of running the business, analyzing what to change & what to change to, and then changing the business is an eternal one. Do the right analysis, your spiral will get larger.  Else, you’ll spiral down.

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On Twitter, Michael Dyrynda writes:

Never ever ever ever ever ever ever ever ever ever ever ever ever ever ever ever ever ever ever ever ever ever ever ever ever ever ever ever ever ever ever ever ever ever ever ever ever ever ever ever ever ever ever ever ever ever store currency as a float in your database.

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The most effective method of testing an API program involves creating multi-step integration tests that validate common API consumer flows. API endpoints are meant to work together, so it follows that test data coming from one API that feeds another API should not be fixed or pre-built. This is very important because the less you rely on fixed data, the more unpredictable and therefore thorough the testing path will be.

Moreover, API mutation operations may have side effects that cannot be evaluated by simply validating the same endpoint. Side effects propagate throughout the system, and their efficacy can only be validated by querying other endpoints and comparing the results.

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As B2C companies look to offer an elevated user experience across all touchpoints, app developers are increasingly turning to customer identity and access management (CIAM) solutions that can help protect customer data and enhance the customer experience.

Customers have become increasingly receptive to new technologies and are using a wide array of digital solutions such as smartphones, wearable devices, virtual reality (VR), and Internet of Things-enabled systems in their daily lives. These digital solutions have made the execution of tasks easier and faster, bringing about a major change in customers’ behavior – i.e. the need for instant gratification of their demands. 

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In a post published on our blog earlier this year, we described some of the decision-making that went into the design and architecture of Snuba, the primary storage and query service for Sentry’s event data. This project started out of necessity; months earlier, we discovered that the time and effort required to continuously scale our existing PostgreSQL-based solution for indexing event data was becoming an unsustainable burden.

Sentry’s growth led to increased write and read load on our databases, and, even after countless rounds of query and index optimizations, we felt that our databases were always a hair’s breadth from the next performance tipping point or query planner meltdown. Increased write load also led to increased storage requirements (if you’re doing more writes, you’re going to need more places to put them), and we were running what felt like an inordinate number of servers with a lot of disks for the data they were responsible for storing. We knew that something had to change.

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Getting promoted to dev team lead

I was 24 years old. A baby.

Three years into my software engineering career and loving it.

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Today I am going to provide you an example of a small microservices based application, where I am going to implement a Eureka discovery server to register all the microservices application in it, so that each of these services can be accessible from all the microservices applications registered with Discovery Server. 

For this example, we are going to create total four microservices applications/services. 

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Users typically prefer to visit websites that load fast and fortunately, there are a lot of online tools that you can use to evaluate your website’s speed-related performance. Do you know that WordPress web hosting has a major role to play in boosting your website’s load speed?

In this article, we have shared some really easy-to-implement website speed boosting tips that would allow you to ensure optimal website performance, steady web traffic, and high sales conversion rates.

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