How to cut your company’s DevOps costs, according to the experts
As governments around the world struggle to keep inflation under control and recession rumors grow louder, many companies are facing a period of significant economic pressure.
To weather the turmoil, companies are looking for ways to cut costs. And of course the technology budget is one of the items under consideration as a large expenditure factor.
With this attitude Tech Radar Pro spoke to CTOs from a variety of industries who highlighted the best areas of the technology stack to drive savings. In this issue, we focus on containing development and data infrastructure costs.
Go low-code
Highly skilled developers are a priority these days as thousands of companies rush to digitize their operations and widespread skills shortages are driving prices up.
According to Richard Farrell, CTO at customer experience company Netcall, savvy companies can therefore realize significant savings in development costs by leaning on no-code and low-code.
“To overcome the developer shortage, companies need to think beyond traditional developer roles and recruitment. Development with low-code application platforms requires a lower skill level than traditional programming and is suitable for a wider range of lower-cost employees,” he explained.
“Organizations should consider ways to make more effective use of the workforce they already have by empowering talent with new digital skills. They should also expand the IT workforce by arming business technologists with low-code, automation, analytics, data science, and machine learning platforms and tools. This encourages cross-team collaboration, increases impact and reduces time to value.”
“Those who start now to extend such capabilities through low-code adoption will gain a head start and position themselves for long-term success despite the ongoing shortage of developers.”
Look for platforms with broad support
Another way companies can find a healthy balance between cost and performance is by making sensible decisions about the new technologies they deploy and factoring any indirect costs they may incur into the calculation.
Andrey Korchak, CTO and co-founder of payments company Monite, notes the need to ensure deployments are built on widely used languages and to exercise caution when adopting new technologies.
“For all СTOs, especially when you’re working in a startup, there’s always the dilemma of how to provide the best tools for making the IT infrastructure work while still justifying that cost,” he said Tech Radar Probefore offering a set of tips:
- use popular technology: Elixir may be a good programming language, but not many engineers use it – you’ll spend a fortune to hire it
- Be conservative with new features: EdgeDB could be great Databasebut it is new and may have unknown issues that may destroy your data
- Automate everything: Instead of hiring release engineers, it pays to build deployment automation pipelines. In this case, instead of hiring dozens of manual QA engineers, you can bring in two QA automation engineers and have them cover your code with reproducible automated tests.
Think long term
Although some transformations can have high upfront costs, the long-term cost savings potential of these projects should not be overlooked.
Dael Williamson, EMEA CTO (Field Advisory & Engineering) at data lakehouse company Databricks, says it’s a common mistake when choosing data architectures. Although cheaper in the short run, less advanced technologies can add costs over time.
“For CIOs who are under pressure to reduce spending, data architectures are a key area to look at. Legacy architectures – like data lakes and data warehouses – are cumbersome to operate, resulting in information silos and inaccurate, duplicated data sets. Ultimately, this can impact the bottom line of companies,” he noted.
“Yes, migrating to a modern data architecture like a data lakehouse has obvious upfront costs. But it is an investment in the future. Lakehouses, for example, offer a tailwind from increased spending pressures – they are easier to use, save crucial time and are also open platforms that free companies from vendor lock-in. Lakehouses also greatly simplifies the skills needed by data teams as they streamline their data architecture. The cost of migration quickly outweighs the cost of working with inaccurate data or the time spent navigating a clunky and legacy system.”
“For some, this jump may feel like a jump in the midst of the recession. They may feel inclined to build on top of the architectures they already have. But that would be like building a skyscraper on top of a cabin. You might get a couple of floors in, but the higher it gets, the more problems you have, and the costs go up as well.”