On January 1, 2024, a price increase for a number of services in the IBM Cloud will take effect. Depending on the region and service, this value can be up to 29 percent.

IBM Cloud users can expect a price increase next year. This has already been announced but will not come into effect until the new year 2024. The new prices are not global, but vary by region and service used. There are 29 percent more unlucky people.

Small and large percentages

For PaaS services, the price increase is global, with a further three percent as of January 1 next year. The only prices increasing globally for IaaS are Accelerated Archive (up 25 percent) and Deep Archive Storage (up 26 percent).

The further price increase for IaaS varies by region. These are the following services:

• Use of bare metal servers
• Virtual Server Instance
• File and block storage
• network infrastructure

However, there is an important caveat to this price hike. When comparing the percentages to US IBM Cloud fees, the effective increase is much smaller. In São Paolo, for example, they pay 29 percent more than in the US from January 1, but the effective price increase is 7.5 percent.

In the rest of the world these increases apply:

• Amsterdam, Montreal and Toronto

six percent more than the US / effective increase – 2.9 percent

• London

thirteen percent more than the US / effective increase – 5.6 percent

• Frankfurt, Madrid, Milan and Paris

sixteen percent more than the US / effective increase – 5.5 percent

• Osaka, Singapore, Tokyo

twenty percent more than the US / effective increase – 6.3 percent

Chennai (India) and Sydney are lucky and there will be no increase in IaaS prices for the time being. IBM Cloud also confirms that there will be no price increases for Power Systems Virtual Servers, third party software and network bandwidth.

Earlier last month, IBM made headlines with its new tool for measuring emissions from cloud services. August seemed to be all about the climate at IBM. The company also announced its collaboration with NASA on an AI model for interpreting satellite imagery, with a focus on climate issues.