The release of Confluent for Kubernetes puts Confluent APIs into Kubernetes API for data-streaming with Apache Kafka, enabling customers to manage all Confluent Platform components across multicloud and on-premise environments. By doing so, the platform bridges a much-needed gap for data access between on-premises and cloud infrastructure for data streaming in Kubernetes environments.
Confluent Platform 6.0 was created to solve several issues operations teams face when managing clusters with Kafka, including having to manually link clusters together. Remediating single cluster failures, as well as linking them together, has been one of the more time-consuming and resource-draining tasks for operations teams with Kafka. The new cluster link feature accomplishes this by both automating the pooling together of the different clusters into a “global mesh of Kafka,” Confluent said.
The wide-scale adoption of the Apache Kafka data-streaming platform can be reflected in the skyrocketing need for a data-management platform that can underpin data operations and address needs across a number of sources, often at a global scale. According to a recent Gartner report “Understanding Cloud Data Management Architectures: Hybrid Cloud, Multicloud and Intercloud,” for example, almost half of all organizations with data-management operations manage data on on-premises and cloud environments (typically multicloud). While Gartner says more than 80% of these organizations rely on multicloud environments.
If you are undertaking a mobile app development for your start-up or enterprise, you are likely wondering whether to use React Native. As a popular development framework, React Native helps you to develop near-native mobile apps. However, you are probably also wondering how close you can get to a native app by using React Native. How native is React Native?
In the article, we discuss the similarities between native mobile development and development using React Native. We also touch upon where they differ and how to bridge the gaps. Read on.
Let’s briefly set the context first. We will briefly touch upon what React Native is and how it differs from earlier hybrid frameworks.
Although relatively new, React Native has acquired a high degree of popularity. The “Stack Overflow Developer Survey 2019” report identifies it as the 8th most loved framework. Facebook, Walmart, and Bloomberg are some of the top companies that use React Native.
The popularity of React Native comes from its advantages. Some of its advantages are as follows:
Are you wondering whether React Native is just another of those hybrid frameworks like Ionic or Cordova? It’s not! React Native is fundamentally different from these earlier hybrid frameworks.
React Native is very close to native. Consider the following aspects as described on the React Native website:
Due to these factors, React Native offers many more advantages compared to those earlier hybrid frameworks. We now review them.
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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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If you accumulate data on which you base your decision-making as an organization, you should probably think about your data architecture and possible best practices.
If you accumulate data on which you base your decision-making as an organization, you most probably need to think about your data architecture and consider possible best practices. Gaining a competitive edge, remaining customer-centric to the greatest extent possible, and streamlining processes to get on-the-button outcomes can all be traced back to an organization’s capacity to build a future-ready data architecture.
In what follows, we offer a short overview of the overarching capabilities of data architecture. These include user-centricity, elasticity, robustness, and the capacity to ensure the seamless flow of data at all times. Added to these are automation enablement, plus security and data governance considerations. These points from our checklist for what we perceive to be an anticipatory analytics ecosystem.
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In today’s market reliable data is worth its weight in gold, and having a single source of truth for business-related queries is a must-have for organizations of all sizes. For decades companies have turned to data warehouses to consolidate operational and transactional information, but many existing data warehouses are no longer able to keep up with the data demands of the current business climate. They are hard to scale, inflexible, and simply incapable of handling the large volumes of data and increasingly complex queries.
These days organizations need a faster, more efficient, and modern data warehouse that is robust enough to handle large amounts of data and multiple users while simultaneously delivering real-time query results. And that is where hybrid cloud comes in. As increasing volumes of data are being generated and stored in the cloud, enterprises are rethinking their strategies for data warehousing and analytics. Hybrid cloud data warehouses allow you to utilize existing resources and architectures while streamlining your data and cloud goals.
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There are few companies operating in today’s markets affected most recently as we are with the events of 2020 that have not undergone a digital transformation of some sort. Research shows that 80% of executives are accelerating plans to digitize work processes and deploy new technologies in response to the impact of COVID on the business world. The traditional model of business is undergoing radical change in an endeavour to employ digital technologies better to suit multiple purposes across a variety of sectors, and cloud native is one of the key drivers that re-architects cloud environments with the intent of adapting the means for how to deliver services. cloud native is a modern and advanced software development approach; which is why it is becoming of high importance to many companies.
But moving to a new software development approach is not easy, and organizations can be slow to adopt radical change in the interests of safeguarding their market, output and business. So, to mitigate risk, organizations can take a step-by-step approach to becoming cloud native in several phases, where they can first replicate the new approach on a smaller scale inside a department/team/project architecture to test the results. If positive, it is then possible to scale the approach organization-wide continuously till the whole enterprise cloud architecture becomes cloud native. If implemented correctly, the cloud native approach supports organizations to improve speed, agility, and resilience in the app development and management process.
#cloud native #cloud #cloud computing #cloud native development #cloud-native applications