Free online consultation available. Please feel free to contact us.

Scalable (scale up/down)

  • Glossary

"Scalable (scale up/scale down)"

This glossary explains various keywords that will help you understand the mindset necessary for data utilization and successful DX.
This time, we will explain the concept of "scalability," which is important for understanding the benefits of adopting cloud computing, and through that, we will consider the essence of future IT utilization.

What is scalability (scaling up/down)?

Scalable means that the scale of usage of an IT system can be increased or decreased (scaled). Increasing the scale of usage is called scaling up, and decreasing it is called scaling down.
Before the spread of cloud computing, IT systems often required that the scale of use be determined in advance before the system was built. However, cloud services often have mechanisms that allow the scale of use to be changed after the service has been used, and this advantage is referred to as "scalable use" or "scalability."

It is difficult to "decide the specifications in advance"

Scalable has many meanings. It is often thought of as a characteristic of cloud services, but it also refers to various characteristics and design considerations that allow the scale of system usage to be changed. For now, let's use the example of a situation where you're wondering what kind of smartphone to buy to explain the "big changes that have occurred in the cloud era."

When buying a new smartphone, do you ever worry about the specs?

When buying a new smartphone, you may be wondering what specs to get. For example, should you get 32GB of RAM or 64GB? Or should you just go for 128GB and not have to worry about the details? Naturally, the more memory you buy, the more expensive it will be.

The model I'm currently using has 16GB of built-in memory, which is a bit tight, but I've managed to get by with some ingenuity. When I think about what I usually use it for, I feel like I could eliminate all of the inconveniences I've had up until now by upgrading to 32GB. However, when I think about it more carefully, I remember that I've always wanted to do photo editing and video editing, although I've given up on doing them now. If I were to try those things, 32GB would probably not be enough.

So what should I do? I've come to realize that this decision will determine how I'll use my smartphone for several years until I upgrade. On the other hand, I'm also worried about my monthly data limit. I'm starting to feel like it would be better to get a cheaper phone and use that money to save on the gigabytes (data limit) that I tend to skimp on. It's become quite a difficult decision.

"Determining specifications in advance" is generally difficult.

When introducing an IT system, the same problem of what specifications to use for the hardware can arise. A high-spec server will prepare you for various future needs, but it will naturally be more expensive. Even if you choose a high-spec system, there are various factors to consider, such as the number of CPU cores, installed memory, and storage capacity, and you must decide how much to increase each of these.

Furthermore, unlike buying a smartphone for personal use, when using IT for business purposes, you need to explain "why you need to purchase a server with such specifications" to secure the budget. Now, how do you explain this, based on what basis and why? It can be quite difficult. If you introduce something with too high specs, you will be scolded, with "you end up not using it after all." However, you will also be scolded if the specs are insufficient and usage is hindered.

"Scalable services" solve these problems

The emergence of scalable cloud services has eliminated these worries that used to arise every time. Taking the smartphone example, if you could change the memory capacity of the device even after you bought it, the worries I've written about above would disappear. You can sign up for a 32MB contract without any worries, and if you need more, you can just increase it later, or if it's too much, you can just reduce it.

Of course, there are no smartphones like that, but it is possible to do so if you rent IT resources such as virtual machines from cloud services such as AWS. You can start with a system with sufficient resources for the time being, and if you find that you need more, you can increase or decrease the specifications later. For example, you can sign up for a virtual machine with an 8-core CPU, and then change it to a 64-core CPU when you know that processing will be concentrated at the end of the year.

Scalable services streamline decision-making by eliminating the need for difficult decisions upfront, and they also eliminate costs associated with "building in a buffer" for the uncertain future (such as a 64MB smartphone just in case).

This means that even if unplanned needs or uses arise, they can be easily incorporated into usage after the fact, without having to be excluded. This is a positive change for IT operations staff, payment processors, and users alike.

"Scale up/scale down" and "scale out/scale in"

There are several ways to scale your usage, let's take a virtual machine as an example.

Increasing the specifications of the virtual machines you are using is called "scaling up." There is also a method of increasing the scale of use by increasing the number of virtual machines you are using, which is sometimes called "scaling out." The former method is sometimes called "vertical scaling," and the latter "horizontal scaling."

Also, just as important as the ability to increase the scale of usage is the ability to reduce the scale of usage, such as by "scaling down" or "scaling in." Being able to return to the original scale when it is no longer needed (or if it turns out that it is not needed as expected) not only reduces costs but also the risk of deciding to scale up or scale out, making it easier to increase resources without hesitation.

It's not that this kind of response was impossible in conventional operations before the cloud. With a smartphone, you could do something similar by switching to a device with more memory and transferring the data, or you could buy a high-spec server and have the server administrator work hard at night to transfer the data, or you could increase the number of servers. However, these things were "possible, but quite difficult."

How exactly will changes to the scale of use be implemented?

Cloud services often have the ability to change the scale of usage in this way, but what you can change, how you can change it, and to what extent varies from service to service. What you need to do when changing the scale of usage may also differ.

Even though new virtual machines with various specifications can be accessed simply by clicking, scaling is still quite smooth compared to the old system, but in the end it is still often necessary to start up new virtual machines, perform the migration process, and shut down the old ones. This still requires time-consuming work by infrastructure engineers.

There are systems in place to automate such operational tasks. Although it is necessary to create an automated system for the work of infrastructure engineers, the system can be made to require less effort after that.

Alternatively, the cloud service itself may have a feature called auto-scaling that automatically adjusts the scale of use to match the load. In this case, ideally, you can even eliminate the need for infrastructure engineers altogether.

Also, if you don't mind the time and effort it takes, you can still adapt to changes in the scale of your usage by operating your own hardware in the traditional way. It's not necessary to use a scalable cloud service.

Do the services and apps you use take this into consideration?

So far, we have been talking about hardware as an example. However, we also need to consider software. Even if you can scale up your virtual servers, it's meaningless if the software doesn't have the ability to take advantage of that.

For example, there are cases where software or cloud services have a modern UI and are easy to use, but when you try to process a slightly heavy load, they suddenly become unable to process. In such cases, the software itself is not designed with sufficient consideration for processing large amounts of data or high performance, and increasing hardware resources may not be very effective.

Although it is said that cloud services can be scaled, there are cases where you have to wait until next month to request a change and have the change reflected, or where a large amount of work is required to reset data to the new scaled-up environment. When changes are needed, they cannot always be accommodated immediately. The functions and operational structure of cloud services may not be able to scale quickly and smoothly.

Furthermore, when selecting a cloud service, whether it can scale or not is not the only criterion for deciding whether to use it. For example, whether a cheap service that is not good at scaling or an expensive service that auto-scales is more appropriate will depend on the situation. Furthermore, needs may differ between the early stages of IT adoption and when use has become full-scale.

DataSpider: data integration software that is fully compatible with the multi-core era

Data utilization has become increasingly important, and the need to data integration in business, there is a need to be able to transfer and process large amounts of data at high speed.

When the language used to develop an application is a scripting language (for example, a cloud service created with Ruby on Rails), performance may be poor to begin with. The problem of insufficient performance may only become apparent after the use of IT has progressed and the amount of data has increased, in which case the impact can be severe.

Furthermore, CPU performance these days is primarily determined by an increase in the number of cores, rather than by an increase in clock speed. Therefore, if multi-core CPU processing is not taken into consideration (which can be difficult), even if you switch to a high-performance CPU with many cores, only a few of the cores will be used for the processing in question, leaving the majority of the cores idle and resulting in a slow system.

For example, with DataSpider,

  • The processing created on the GUI is internally converted into Java source code itself, which is then compiled and executed, resulting in high processing performance on the same level as full-scale development using Java.
  • It is equipped with a smart compiler function that automatically distributes processing according to the number of CPU cores in the environment. Unlike products that do not make use of the number of cores, it can utilize a large number of cores without the trouble of explicitly creating parallel processing.

"HULFT Square" allows users to change the scale of their usage themselves

Even if it is a scalable cloud service, you may only be able to request a change and have it take effect from the next month, or you may only be able to select the scale of use when you start using it, and any changes made after that may be the same as signing a new contract and moving.

HULFT Square, a Japanese iPaaS that can be used on the cloud with the same ease of use as DataSpider,

  • Cloud service users can make changes themselves on the user interface, and can scale up or down, or increase or decrease the processing environment, when necessary.

"Connecting" technology that allows a wide variety of cloud services and on-premise services to be combined and used

There are many cloud services out there, and each one is different. It depends on whether they are scalable or not, and what kind of convenience they offer. Having read this far, you might be thinking that it's difficult to decide, with so many things to consider. Furthermore, you won't adopt a service solely on whether it's scalable; you'll also need to consider whether it's cheap or expensive, its security, and what features the service offers. So what should you do?

Using smartphones as an example, we explained that predicting this in advance is difficult. Similarly, being able to smoothly change things later on can greatly reduce the difficulty of making decisions. If you can switch or combine the cloud services you use after you start using them, you can simply change them if they don't meet your needs after trying them out. And it's precisely these "connecting" products, such as the aforementioned "DataSpider" and "HULFT Square," that can help you meet these needs.

  • It can connect a wide variety of systems and data as needed, including cloud, on-premise systems, mainframes, etc.
  • Because you can create integration processes using only the GUI, you don't have to go through the trouble of asking a highly skilled engineer every time something happens.
  • Although it is possible to develop "connecting" processes using only a GUI, it is a professional product that has high processing performance that can be used for full-scale system development, and can be used firmly in full-scale operation in situations where various types of failures inevitably occur.

For more details, please also see the articles on "EAI" and "iPaaS" below. Systems that allow for the flexible use of a wide variety of IT and the ability to link them in all directions as needed are becoming increasingly important in today's IT utilization. Furthermore, "scalability" is also a very important factor in determining what type of IT to use.

Related keywords (for further understanding)

  • EAI
    • It is a concept of "connecting" systems by data integration, and is a means of freely connecting various data and systems. It is a concept that has been used since long before the cloud era as a way to effectively utilize IT.
  • iPaaS
    • A cloud service that "connects" various clouds with external systems and data simply by operating on a GUI.
  • ETL
    • In the recent trend of actively working on data utilization, the majority of the work is not the data analysis itself, but rather the collection and preprocessing of data scattered around, from on-premise to cloud. This is a means to carry out such processing efficiently.
  • SaaS
    • When people generally think of the "cloud," they are referring to an initiative to provide software usage as a service.

Are you interested in "iPaaS" and "connecting" technologies?

Try out our products that allow you to freely connect various data and systems, from on-premise IT systems to cloud services, and make successful use of IT.

The ultimate "connecting" tool: data integration software "DataSpider" and data integration platform "HULFT Square"

"DataSpider," data integration tool developed and sold by our company, is a "connecting" tool with a long history of success. "HULFT Square," a data integration platform, is a "connecting" cloud service developed using DataSpider technology.

Another feature is that development can be done using only the GUI (no code) without writing code like in regular programming, so business staff who have a good understanding of their company's business can take the initiative to use it.

Try outDataSpider/ HULFT Square 's "connecting" technology:

There are many simple collaboration tools on the market, but this tool can be used with just a GUI, is easy enough for even non-programmers to use, and has "high development productivity" and "full-fledged performance that can serve as the foundation for business (professional use)."

It can smoothly solve the problem of "connecting disparate systems and data" that is hindering successful IT utilization. We offer a free trial version and online seminars where you can try it out for free, so we hope you will give it a try.


Why not try a PoC to see if HULFT Squarecan transform your business?

Why not try verifying how "connecting" can be utilized in your business, the feasibility of solving problems using data integration, and the benefits that can be obtained?

  • I want to automate data integration with SaaS, but I want to confirm the feasibility of doing so.
  • We want to move forward with data utilization, but we have issues with system integration
  • I want to consider data integration platform to achieve DX.

Glossary Column List

Alphanumeric characters and symbols

A row

Ka row

Sa row

Ta row

Na row

Ha row

Ma row

Ya row

Ra row

Wa row

»Data Utilization Column List

Recommended Content

Related Content

Return to column list