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| Cloud computing and AI are two technologies that have driven change among American companies in 2023. |
In order determine your top technological problems for 2023, I looked back over the previous year and combined customer input with activity on my site.
Here are some excerpts from my top-ranked blogs, arranged in descending order so you'll read to the end: the highest-ranked topic is covered last.
5. Cloud Partnerships and Contracts
It's no secret that cloud service providers fetch high fees. At any costs, they want you to go to the cloud. Once the consumption starts, you are locked in for years—even with massive early discounts, a strategic alliance where they promise to use your services as part of the contract, or by allowing you to migrate faster. The annual recurring revenue that cloud providers receive later on adds up to make them incredibly successful.
Challenges for Technology Teams
The basic puzzle is that a business decides to invest millions of dollars in the cloud. Still, if they move too soon to meet their minimum spend need, they might not be aware of the possible costs and effects on the health and performance of their application.
The problem of choosing the best cloud provider for their technological expenditures is another. Different suppliers may be highly skilled in some areas but immature in others. One common problem is that businesses usually move all of their application workloads to one cloud provider, which may not necessarily match their goals or business SLAs.
However, throughout the coming years, we are unable to predict the growth rate of our business, data, or transactions. These factors have a big influence on cloud computing expenses. Month-by-month estimates are all we have for high-level growth, not years.
We are unable to forecast our expenses, the technology we will require, or the cost of our utilisation as a consequence. Round, reliable figures are not the way the cloud operates. Because of this, there is a great deal of danger, complexity, and uncertainty in these interactions.
We observe businesses failing to achieve the minimum spend requirement as a result of inaccurate projections. Money was wasted on this. Why is the estimate so inaccurate?
Cloud migrations typically take longer than anticipated since the organisations involved don't fully understand what they are moving.
In order to get a better bargain on cloud services, some businesses form partnerships with cloud providers, whereby the provider consents to use the company's services as a customer. These contracts may last for several years, tying you into a scenario that might not be ideal for your business in the long run.
How to Do Better in 2024
I advise you to think things through carefully before committing to anything, even if it's just a three-year contract or a strategic relationship where the cloud provider uses your services in exchange for an annual spend agreement.
Businesses are embracing cloud computing without fully realising the associated technical expenses and other ramifications. Let's relocate there now and figure it out later, they might think, but frequently it's too late because the financial harm has already been done. Moving to the cloud is acceptable as long as it is done so for the correct reasons and with consideration for
- Business technology requirements
- The expenses incurred by a consumption-based paradigm to support application workloads.
- How to maximise 1% of your resources, which can result in significant cloud cost reductions.
You are wasting money by locking yourself into more than you need if you don't have these protections.
Pay particular attention to application workloads that might benefit from native cloud services and migrate at a reasonable cost. After that, gradually concentrate on the workloads that weren't designed for the cloud and rework or rewrite them to make them compatible with the new expenses they will entail.
4. Redefining Technology in the Age of AI
The study of 2023 would not be complete if AI was not included. The launch of Chat GPT in November 2022 has led to an increase in the growth of AI, which is further worsened by other applications that use AI's capabilities to accomplish more, quicker, and better.
An estimated 180.5 million people use ChatGPT worldwide; of these, 100 million users utilise the generative software on a weekly basis, with 92% of Fortune 500 organisations among them.
The Challenges for Technology Teams
Without the assistance of the IT professionals from Day 1, organisations may now develop and implement technology faster than ever thanks to AI and other services. However, this does not negate the necessity for us to continue working on finding ways to facilitate, support, and integrate these advances into enterprise technology ecosystems.
Additionally, data production and growth rates will only rise due to the rapid use of AI, IoT, and business applications; already, they are at a rate that is becoming unsustainable for current technology teams. Talent acquisition will be a challenge for businesses looking to develop their own AI services. Preparing the data to train and support the AI models, however, will provide an even greater challenge.
If the data is not clear, accessible, categorised, or well-known, it is impossible to develop a successful AI solution. To validate the AI models we are developing and implementing, we need appropriate data governance, security, and other controls to avoid bias, guarantee accurate results, and make sure the system is safe to use as a whole.
How to Do Better in 2024
In reaction to the AI revolution, a new way of thinking is required. Things will need to adjust and rebalance when millions of new technological services and apps are brought online over the course of the next few years.
This rate of change will result in the creation of new employment rather than their replacement. It will be necessary for us to make greater investments in cutting-edge technologies and develop brand-new management strategies for them.
Accept the challenge. If it's not, there's usually something else you can do to help make sense of it. If it is, your work is probably more required than ever. Instead of worrying about what lies ahead in the era of artificial intelligence, let's consider how businesses and engineers might collaborate more effectively to capitalise on one of the biggest technological breakthroughs of the century.
3. Estimating Budgets for the Cloud
CFOs will have to make additional decisions as cloud expenditure increases about which budget requests to approve or reject without slowing down innovation or raising the possibility of taking important technological services offline at crucial moments. It follows that it is not surprising that CFOs find it difficult to estimate cloud spending.
The Challenge for CFOs
CFOs are in charge of making sure that investments in technology yield a profitable return on investment (ROI). However, in the cloud spending era, CFOs are using different methods to assess ROI and, consequently, adjust their budgets.
Spending on the cloud is unpredictable, and projections for several years out are not very accurate. As a result, when it comes to cloud technology, the conventional financial models are inadequate.
How to Do Better in 2024
I offer CFOs a few pieces of advice:
- Take up your proper position at the IT table. (Initiating collaboration is crucial.)
- Recognise your technological system's total cost of ownership. (These expenses accumulate over time and go unnoticed.)
- Boost application efficiency and technological capabilities. Refer to the following section.
2. Improving Technology Efficiency
For the sake of our cloud bills and our environmental duties, IT companies need to adopt a culture shift where efficiency is considered a standard benchmark. The bottom and top lines, as well as the way you develop and apply all code, processes, and data moving forward, can be greatly impacted by adopting an efficient attitude within the technology industry.
The Challenge for Technology Teams
In the past, technology teams have not prioritised process or code efficiency while creating our application development workflows. Businesses frequently deploy ineffective code and procedures into production without considering the long-term financial effects. What if an application that costs $1,000 to run actually only costs $100 to obtain the same outcomes?
Over the course of the 10 or 20 years that the application is in production, the expenses will accumulate if efficiency and resource consumption are not taken into consideration during design. Your carbon footprint is another item that won't decrease unless you start focusing on efficiency.
How to Do Better in 2024
This needs to be changed, and part of the business's acceptance criterion needs to include efficiency. Reducing the resources that each application process or code uses will boost efficiency and lighten the load on the server that hosts everything.
Considering the negatively compounded nature of inefficient operations and the millions of times that process runs daily, even a seemingly tiny boost in efficiency can result in large returns.
You don't need the capacity if you're not using it, at least not right now. To effect efficiency, we must, however, refocus attention to the larger, longer-term capacity plays at hand. Over time and throughout the sector, we must establish a measurement standard for efficiency (FinOps for Data and Code are showing promise for doing just that.)
When processing an identical workload as an inefficient system, more efficient systems use less CPU, memory, storage, and bandwidth. Since most apps are used for ten to twenty years, the decisions we make about how to build the data model, coding, and processes all have long-term effects on the bottom line, both in terms of resources and, more significantly, in terms of the financials. How much will it ultimately cost to own that code, and how might that be affected during the design process?
1. Green Data Centers
Since this topic also has to do with efficiency, I was delighted to see that in 2023 it had the most views on my blog. As a matter of fact, my book and everything I write and discuss revolve around efficiency.
It's fantastic that businesses like Microsoft, AWS, and Google are concentrating on the structures that contain our data in an effort to reduce emissions, and that they are creating green data centres with 100% renewable energy. The majority of the systems and apps that operate in these data centres were not created with efficiency in mind, which is another issue that is rarely discussed.
The Challenge for Technology Teams
Environmental effect is not frequently linked to software development. However, the direct impact on the environment and carbon footprint increase with the number of CPU programmes in use. Furthermore, by concentrating on efficiency, you get the most for your money and contribute to sustainability, as most businesses base their licencing fees on the quantity of CPUs needed.
Saying that data centres are energy-efficient and green gives a false sense of security if the applications running in them are wasteful and inefficient. It would be likened to constructing a brand-new, energy-efficient home, only to fill it with appliances from the 1980s, thus nullifying any efficiency advantages.
How to Do Better in 2024
By concentrating on creating optimised, effective code, we can lower the energy and resource footprint of our applications. Here are several methods to help you do this:
- Create and advocate for effective data structures and algorithms.
- Minimise redundant code and repetitive tasks; maintain simplicity.
- Make use of code optimisation and code profiling for the top 1% of processes.
- Create and use green coding techniques.
Maintaining the status quo for another year will only lead to more levels of inefficiency. The health of our systems is being severely harmed by outdated legacy systems.
I will keep bringing up these concerns, point out red flags, and solicit your input in order to collaboratively move towards a paradigm change that ushers in the age of efficiency rather than the end of abundance in technology.
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