All the worry over technical debt and the risks of cloud vendor lock-in has spread to AI, only the stakes are now much higher.
The mantra for computing is to use other people’s technology, so it's surprising that generative AI doesn’t seem to follow that pattern for many enterprises.
A new study shows that AI won’t work without a lot more talent in the employment market. Enterprises will need to be innovative to win this one.
I’m having ‘Sixth Sense’ moments when I see dead databases walking. With GenAI poised to eat your data for lunch, it’s time to fix performance problems.
With the rising costs of the cloud and the availability of connected computing and storage resources, we could see colossal cloud brands that don’t own data centers.
We used to be a lot more interested in the mechanics of multitenancy. What are the exciting evolutions in the technologies that support it?
The mega cloud conferences hosted by cloud providers never fail to mesmerize us with shiny new technology. We should focus on our business needs instead.
A recent study shows a narrowing gap between enterprises' application development skills and the likelihood of a vast data breach.
Most training covers cloud brand-related skills. However, if we’re looking for talent to scale, we must go broad rather than deep.
Predictions are the ability to see the continuation of existing patterns. Yes, genAI is on the list, as well as the talent crunch and the partnership between business and IT.
KubeCon + CloudNativeCon just concluded with another land grab for generative AI. What does this mean for the enterprise?
Forty years ago, AI was largely shelved because of its high price tag. By finding the real business benefits, you can do better than the developers of yesterday.
The higher the cloud bills, the more questions get asked. Here’s how to evaluate if you should divorce your cloud provider.
There’s a lot of talk but not many actual implementations of generative AI in the cloud. Better to have all the pieces in place before launching expensive projects.
It’s time to look at top priorities for cloud deployments. It's a great opportunity to tackle access controls, cost optimization, and complexity.
Cloud computing and IT are starting to prefer experience to an expensive college education. What’s the best hiring strategy in this new normal?
What do you do now? How do you keep your job? There are a few things that could save the project and your career.
Edge computing offers less latency and bandwidth savings, but the lack of standards and problems with interoperability and security still need to improve.
From system design to daily performance tuning, here's a checklist of ways to make your systems run effectively.
GenAI can analyze application dependencies, network configurations, and security risks, but it will mostly help lazy companies that aren't doing this anyway.
In addition to integration and intellectual property challenges, companies may not have the technical expertise to customize or secure open source software.
The cloud is integral to most business operations and spending remains unaffected by lower corporate revenue. Still, let's make the most of your cloud dollars.
AI-based design and development is exciting but it doesn't replace sound, solid architecture and engineering in building and deploying cloud-based solutions.
Enterprises want generative AI, but CIOs need a way to pay for it. Diverting spending from traditional cloud computing may not be the best strategy.
The time is coming when poor IT design and decisions will be outed by finops automation and artificial intelligence. Are you ready to defend yourself?
2023 might be the year of repatriation, but more challenging architectural decisions need to be made besides what saves a few cloud dollars.
These prebuilt components simplify development and offer flexibility and speed, but watch out for scalability, security, and integration problems.
You might think that running back to get a master's degree or joining a country club to make business contacts is the best strategy. It’s simpler than that.
Enterprises facing high cloud costs are taking a more balanced look at where workloads should reside and considering repatriation to a cloud in their own data center.
From data availability and security to model selection and monitoring, adding generative AI means re-examining your cloud architecture.
With the explosion of interest (and money) in generative AI, what will be left for traditional cloud service development and enhancement that companies need?
Finops practices and tools can spot inefficiencies and opportunities to optimize. Here's what to do when you find waste in cloud deployments.
Serverless computing is a popular approach for cloud-based applications, but it's not the best fit in every case. Too often serverless fails to deliver business value.
There are three main career options for most cloud pros: consulting, working in industry, or with a cloud vendor. Are you on the right road for you?
Rural businesses lack easy access to high-speed internet and thus cloud-based resources, causing vast disadvantages that affect the overall economy.
Cloud security is largely siloed by cloud provider. Enterprises are demanding strategic approaches for complex distributed multicloud deployments.
Putting AI on cloud versus on-premises systems may seem like a simple decision, but it's much more complex (and potentially expensive).
A solid finops process can keep the CFO's team happy and everyone out of jail. Too many enterprises lack a formal program, and it's time to get on board.
Like student loans and credit card balances, technical debt is holding you back or even killing your business. Unfortunately, the cloud can't always save you.
Cloud was the go-to choice for the past five years, but we could see traditional systems become more viable. Savvy architects consider all the options.
Should budget go to innovations or fixing existing systems so they don’t bankrupt you? The future of your business may ride on the answer.
AI-driven coding is now in wide use, but we may not know all the risks of using it until the damage has been done. Think security problems and code that wastes resources.
Microservices came in with a great deal of momentum a few years ago, but now we’re seeing their drawbacks for applications on cloud platforms.
Powered by edge computing, IoT, and 5G, today's systems are decentralized, context-aware, and real-time interactive.
As the costs for cloud services continue to rise, companies need to determine if the business value of those services is worth the price tag.
The push to adopt generative AI in the cloud will lead to new roles and needed skills, and enterprises will likely pay top dollar.
Too many IT shops just accept that autoscaling systems are right for them, at least until the massive cloud bill arrives.
Without proper data governance, interoperability, and access control, enterprises have no hope of maximizing the business value of their data.
Many cloud leaders prefer one technology selection over another, to the detriment of the business. It’s time we learn to be much more objective.
Many enterprises are finding that the applications they migrated to public cloud providers could be more cost-effective… to put it mildly.
Sponsored Links
