Cloud services are designed to be scalable, flexible and self-service, which makes them ideal for companies trying to transform their legacy systems. It gives them operational agility in a cost-effective way to help them to remain competitive. As they move to private and hybrid clouds, they have to ensure that they don’t experience a loss of data or a disruption of services.
Their network infrastructure layer is often the biggest challenge when businesses migrate to the cloud and network operation problems can have an adverse effect on productivity. Companies need scalable systems to store and process data for network monitoring synchronously with processing interactional data. This is where companies such as Mirantis can prove beneficial to the management of the infrastructure, helping the software function with this change.
The solution lies in memory. In-memory computing is easily deployed on site or across clouds. When it comes to speed, a combination of in-memory and cloud computing have a distinct advantage over in-house fixed disk servers.
What is in-memory computing?
In memory computing allows for data storage in random access memory (RAM) across a cluster of computers, enabling processing in parallel. Processing is about 5,000 times faster in RAM than when using the traditional spinning disk. A drop in memory prices has been a major factor in making this possible.
An in-memory data grid (IMDG) is a component of an in-memory computing system. It is a low-latency, high throughput data fabric that provides a cost-effective way to scale services and applications. IMDGs are becoming the solution of choice for many businesses that want an approach that’s easy to implement. It’s easy to insert an IMDG between an app and data layer without affecting either layer.
As IMDGs cache application data in RAM and apply parallel processing across a distributed cluster of server nodes, they can greatly improve application performance. The distributed architecture means that rapid scaling of applications is possible simply by adding new server nodes.
How does in-memory computing help?
In-memory computing helps business owners to analyze massive data volumes (be they produced by synthetic data companies or by organic generation) quickly and make informed decisions. An e-commerce infrastructure today has to be fast, highly available and scalable – in-memory computing makes this possible.
In-memory computing helps business owners to predict trends and customer needs. They can monitor and analyze any deviations in quality in the production process. They can quickly see changes in supply or demand across the supply chain. They can improve the online ordering process to help retain customers. Quickly running profit analysis can help them decide what discounts or special offers to give customers. There is virtually no area of business that can’t benefit from using in-memory computing.
What is cloud computing?
Cloud computing is an application-based software infrastructure that stores data on remote servers with access via the internet. Placing data stores and software services on the cloud means they aren’t stored on individual servers or computers and are made available through a web-based interface. Users can access services wherever they are via a web connection to the cloud platform using just about any device.
How does cloud computing help?
Cloud computing removes many of the physical and financial difficulties of aligning the needs of IT with ever-changing business goals. With its promise to deliver better platforms, infrastructure and applications cost-effectively and quickly, cloud computing is a major force in business innovation.
Some of the main reasons to use the cloud are mobility, scalability, automation, convenience and the fact that it makes collaboration easy and almost effortless. For example, using a web-based email service means being able to access emails from any computer with an internet connection and recover emails if something happens to a computer. Dropbox is a popular cloud-based storage service that allows for sharing of documents. There are also web apps that run in the cloud and don’t have to be installed on a computer.
Different cloud computing deployment models
Using the public cloud through a cloud provider means the provider maintains the hardware and computing infrastructure. A business typically pays a monthly fee for the use, which can lower capital expenditure for servers and hardware. A big disadvantage is that public clouds may be less secure than private clouds.
Where industries are heavily regulated and data breaches can ruin a reputation, businesses can create a private cloud, although the upfront costs will be high. For lower costs and greater security, hybrid clouds allow for locking down sensitive data on private cloud servers and using public cloud servers for running applications and analytics.
There are also three different service delivery options – software as a service (SaaS), platform as a service (PaaS) or infrastructure as a service (IaaS). SaaS means businesses only pay for what they need and they can scale software services and data storage as required. PaaS provides the ability to create and manage custom cloud applications which is ideal when plenty of developers are working on the same project. IaaS provides cloud infrastructure that is typically accessed by IT and operations.
In-memory cloud computing
When businesses use cloud computing, they can take advantage of cost-effective storage, distributed in-memory technologies and smart scaling. They can drastically improve data transfer speeds and analytics performance while reducing operating costs.
In cloud computing with its remote data centers, there may be a time lag between collecting and processing data. In-memory computing could change that and prevent any time delays when using time-sensitive apps.
Using hybrid cloud infrastructure and in-memory computing takes speed, scalability and flexibility to new heights. It can prepare businesses for the increases in data capacity from adopting the Internet of Things. It can also help with duplicating data in real-time when businesses are migrating to new cloud-based applications so there are few disruptions or a loss of service.
Conclusion
An in-memory computing platform offers businesses the use of real-time analytics, the ability to deliver high performance, real-time personalization, and high-speed transactions. They can avoid costly upgrades to legacy systems and run real-time analytics to make informed decisions. Cloud computing uses sequential processing and secondary storage, whereas in-memory computing uses parallel processing and RAM storage. By combining in-memory and cloud computing, it is possible to implement cloud technology in the best possible way.