Many performance benchmarks measure peak throughput or requests per second (RPS), but those metrics can oversimplify the performance story at real‑world sites. Few organizations run their services at or near peak throughput, where a 10% change in performance either way can make a significant difference. The throughput or RPS a site requires is not infinite, but is fixed by external factors like the number of concurrent users they have to serve and the activity level of each user. In the end, what matters most is that your users receive the best level of service. End users don’t care how many other people are visiting your site. They just care about the service they receive and don’t excuse poor performance because the system is overloaded.
This leads us to the observation that what matters most is that an organization deliver consistent, low‑latency performance to all their users, even under high load. In comparing NGINX and HAProxy running on Amazon Elastic Compute Cloud (EC2) as reverse proxies, we set out to do two things:
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A multi-cloud approach is nothing but leveraging two or more cloud platforms for meeting the various business requirements of an enterprise. The multi-cloud IT environment incorporates different clouds from multiple vendors and negates the dependence on a single public cloud service provider. Thus enterprises can choose specific services from multiple public clouds and reap the benefits of each.
Given its affordability and agility, most enterprises opt for a multi-cloud approach in cloud computing now. A 2018 survey on the public cloud services market points out that 81% of the respondents use services from two or more providers. Subsequently, the cloud computing services market has reported incredible growth in recent times. The worldwide public cloud services market is all set to reach $500 billion in the next four years, according to IDC.
By choosing multi-cloud solutions strategically, enterprises can optimize the benefits of cloud computing and aim for some key competitive advantages. They can avoid the lengthy and cumbersome processes involved in buying, installing and testing high-priced systems. The IaaS and PaaS solutions have become a windfall for the enterprise’s budget as it does not incur huge up-front capital expenditure.
However, cost optimization is still a challenge while facilitating a multi-cloud environment and a large number of enterprises end up overpaying with or without realizing it. The below-mentioned tips would help you ensure the money is spent wisely on cloud computing services.
Most organizations tend to get wrong with simple things which turn out to be the root cause for needless spending and resource wastage. The first step to cost optimization in your cloud strategy is to identify underutilized resources that you have been paying for.
Enterprises often continue to pay for resources that have been purchased earlier but are no longer useful. Identifying such unused and unattached resources and deactivating it on a regular basis brings you one step closer to cost optimization. If needed, you can deploy automated cloud management tools that are largely helpful in providing the analytics needed to optimize the cloud spending and cut costs on an ongoing basis.
Another key cost optimization strategy is to identify the idle computing instances and consolidate them into fewer instances. An idle computing instance may require a CPU utilization level of 1-5%, but you may be billed by the service provider for 100% for the same instance.
Every enterprise will have such non-production instances that constitute unnecessary storage space and lead to overpaying. Re-evaluating your resource allocations regularly and removing unnecessary storage may help you save money significantly. Resource allocation is not only a matter of CPU and memory but also it is linked to the storage, network, and various other factors.
The key to efficient cost reduction in cloud computing technology lies in proactive monitoring. A comprehensive view of the cloud usage helps enterprises to monitor and minimize unnecessary spending. You can make use of various mechanisms for monitoring computing demand.
For instance, you can use a heatmap to understand the highs and lows in computing visually. This heat map indicates the start and stop times which in turn lead to reduced costs. You can also deploy automated tools that help organizations to schedule instances to start and stop. By following a heatmap, you can understand whether it is safe to shut down servers on holidays or weekends.
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The moving of applications, databases and other business elements from the local server to the cloud server called cloud migration. This article will deal with migration techniques, requirement and the benefits of cloud migration.
In simple terms, moving from local to the public cloud server is called cloud migration. Gartner says 17.5% revenue growth as promised in cloud migration and also has a forecast for 2022 as shown in the following image.
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Learn about the benefits of Cloud Performance Testing along with the correct approaches for an effective solution, while developing web and mobile apps.
In case the cloud performance testing is outsourced to an external cloud service provider, carefully ensure their security, reliability, quality, and bandwidth. There are certain aspects that shouldn’t be compromised while selecting a Cloud Computing Solution Provider. When it comes to performance testing, it varies with varying user demands and other factors. Thus, it should be tested according to defined test strategies and also on real-time to ensure continuous improvement over the period of time. Ensure you rely on a company that provides end-to-end performance testing solution to launch future-proof applications that are reliable, responsive, and scalable.
Read More:- Cloud Performance Testing: Benefits and Approach
#benefits of performance testing on cloud #top cloud computing solution providers #cloud performance testing #cloud computing #app testing #cloud infrastructure
Technology is hard. As technologists, I think we like it that way. It’s built‑in job security, right? Well, unfortunately, the modern application world has become unproductively hard. We need to make it easier.
That’s why I like describing the current developer paradox as the need to run safely with scissors.
Running with scissors is a simple metaphor for what is the admittedly difficult ask we make of software engineers. Developers need to run. Time to market and feature velocity are critical to the success of digital businesses. As a result, we don’t want to encumber developers with processes or technology choices that slow them down. Instead we empower them to pick tools and stacks that let them deliver code to customers as quickly as possible.
But there’s a catch. In the world of fast releases, multiple daily (or hourly or minutely!) changes, and fail‑fast development, we risk introducing application downtime into digital experiences – that risk is the metaphorical scissors that make it dangerous to run fast. On some level we know it’s wrong to make developers run with scissors. But the speed upside trumps the downtime downside.
That frames the dilemma of our era: we need our developers to run with scissors, but we don’t want anybody to get hurt. Is there a solution?
At NGINX, the answer is “yes”. I’m excited to announce eight new or significantly enhanced solutions built to unleash developer speed without sacrificing the governance, visibility, and control infrastructure teams require.
As my colleague, Gus Robertson, eloquently points out in his recent blog The Essence of Sprint Is Speed, self‑service is an important part of developer empowerment. He talks about developers as the engines of digital transformation. And if they’re not presented with easy-to-use, capable tools, they take matters into their own hands. The result is shadow IT and significant infrastructure risk.
Self‑service turns this on its head. It provides infrastructure teams with a way to release the application delivery and security technologies that developers need for A/B, canary, blue‑green, and circuit‑breaker patterns. But it does so within the guardrails that ensure the consistency, reliability, and security that ensure your apps remain running once in production.
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The shift towards microservices and modular applications makes testing more important and more challenging at the same time. You have to make sure that the microservices running in containers perform well and as intended, but you can no longer rely on conventional testing strategies to get the job done.
This is where new testing approaches are needed. Testing your microservices applications require the right approach, a suitable set of tools, and immense attention to details. This article will guide you through the process of testing your microservices and talk about the challenges you will have to overcome along the way. Let’s get started, shall we?
Traditionally, testing a monolith application meant configuring a test environment and setting up all of the application components in a way that matched the production environment. It took time to set up the testing environment, and there were a lot of complexities around the process.
Testing also requires the application to run in full. It is not possible to test monolith apps on a per-component basis, mainly because there is usually a base code that ties everything together, and the app is designed to run as a complete app to work properly.
Microservices running in containers offer one particular advantage: universal compatibility. You don’t have to match the testing environment with the deployment architecture exactly, and you can get away with testing individual components rather than the full app in some situations.
Of course, you will have to embrace the new cloud-native approach across the pipeline. Rather than creating critical dependencies between microservices, you need to treat each one as a semi-independent module.
The only monolith or centralized portion of the application is the database, but this too is an easy challenge to overcome. As long as you have a persistent database running on your test environment, you can perform tests at any time.
Keep in mind that there are additional things to focus on when testing microservices.
Test containers are the method of choice for many developers. Unlike monolith apps, which lets you use stubs and mocks for testing, microservices need to be tested in test containers. Many CI/CD pipelines actually integrate production microservices as part of the testing process.
As mentioned before, there are many ways to test microservices effectively, but the one approach that developers now use reliably is contract testing. Loosely coupled microservices can be tested in an effective and efficient way using contract testing, mainly because this testing approach focuses on contracts; in other words, it focuses on how components or microservices communicate with each other.
Syntax and semantics construct how components communicate with each other. By defining syntax and semantics in a standardized way and testing microservices based on their ability to generate the right message formats and meet behavioral expectations, you can rest assured knowing that the microservices will behave as intended when deployed.
It is easy to fall into the trap of making testing microservices complicated, but there are ways to avoid this problem. Testing microservices doesn’t have to be complicated at all when you have the right strategy in place.
There are several ways to test microservices too, including:
What’s important to note is the fact that these testing approaches allow for asynchronous testing. After all, asynchronous development is what makes developing microservices very appealing in the first place. By allowing for asynchronous testing, you can also make sure that components or microservices can be updated independently to one another.
#blog #microservices #testing #caylent #contract testing #end-to-end testing #hoverfly #integration testing #microservices #microservices architecture #pact #testing #unit testing #vagrant #vcr