Auto-scaling, the ability to automatically adjust resources to match load requirements, is a major benefit of cloud technology. In this video, we will show approaches to automatic scaling in the cloud using ECP and data sharding. Examples will include using the auto-scale features of AWS, GCP, and Azure.
💡 Takeaway: InterSystems IRIS provides several ways to take advantage of auto-scaling.
🗣 Presenter: Ken Takemura, Performance Specialist, InterSystems
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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We started a new series of interviews with our everyday users – our developers, which we are calling **Developers Say. **In the first interview, we talked about cloud automation with Marko, a full-stack developer from Vertt. This time, we have @Dzanna_Molly, a DevOps engineer working on We are Laika. She talked to us about how she likes Microtica as a cloud infrastructure automation platform.
You can read more about how Laika created a secure and scalable platform with Microtica here.
We are Laika is a recruitment platform where Tech professionals can find the job they love, and companies can acquire top professionals from the Balkans. Tech professionals know everything about the company and the job they apply for, and they stay anonymous before a job offer has been made final. We perform matching talents and companies based on skills, preferences, and competencies through a smart platform.
The product is a web application, responsive, using React JS for the frontend. The backend is a collection of microservices in NodeJS, with AWS as a cloud provider and Microtica for deployment.
I am a junior backend developer with one year of experience with NodeJS. I’ve also worked with the cloud as an AWS DevOps engineer on previous projects. We are Laika was an exceptional experience as a back-end developer. Here, I learned the architecture of microservices and how to develop backend solutions for the application. Through the use of Microtica on this project, I enhanced my knowledge as I learned a lot about the deployment process, CI/CD, and automation.
#product #cloud automation #cloud infrastructure #cloud infrastructure automation #developer teams #devops #devops automation #software development
In this Lab, we will configure Cloud Content Delivery Network (Cloud CDN) for a Cloud Storage bucket and verify caching of an image. Cloud CDN uses Google’s globally distributed edge points of presence to cache HTTP(S) load-balanced content close to our users. Caching content at the edges of Google’s network provides faster delivery of content to our users while reducing serving costs.
For an up-to-date list of Google’s Cloud CDN cache sites, see https://cloud.google.com/cdn/docs/locations.
Cloud CDN content can originate from different types of backends:
In this lab, we will configure a Cloud Storage bucket as the backend.
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