Cloud Computing
What happened to edge computing?
Edge computing offers less latency and bandwidth savings, but the lack of standards and problems with interoperability and security still need to improve.
Best practices for operating cloud-based generative AI systems
From system design to daily performance tuning, here's a checklist of ways to make your systems run effectively.
Generative AI and migrations to the public cloud
GenAI can analyze application dependencies, network configurations, and security risks, but it will mostly help lazy companies that aren't doing this anyway.
When open source cloud development doesn't play nice
In addition to integration and intellectual property challenges, companies may not have the technical expertise to customize or secure open source software.
Cloud infrastructure spending is growing
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.
Why we need both cloud architects and cloud engineers
AI-based design and development is exciting but it doesn't replace sound, solid architecture and engineering in building and deploying cloud-based solutions.
A crisis of spending and cloud-based generative AI
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.
When your cloud finops system rats you out to your boss
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?
Even with repatriation cost savings, the value of cloud computing is still strong
2023 might be the year of repatriation, but more challenging architectural decisions need to be made besides what saves a few cloud dollars.
The risks of low-code and no-code development in cloud architecture
These prebuilt components simplify development and offer flexibility and speed, but watch out for scalability, security, and integration problems.
3 things to do right now to enhance your cloud computing career
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.
A comeback for private clouds
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.
Adding generative AI systems may change your cloud architecture
From data availability and security to model selection and monitoring, adding generative AI means re-examining your cloud architecture.
Generative AI may displace traditional cloud development
With the explosion of interest (and money) in generative AI, what will be left for traditional cloud service development and enhancement that companies need?
What happens when finops finds bad cloud architecture?
Finops practices and tools can spot inefficiencies and opportunities to optimize. Here's what to do when you find waste in cloud deployments.
The shortcomings of serverless computing
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.
3 meta career paths for cloud computing
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?
The digital divide, rural businesses, and cloud computing
Rural businesses lack easy access to high-speed internet and thus cloud-based resources, causing vast disadvantages that affect the overall economy.
Centralized cloud security is now a must-have
Cloud security is largely siloed by cloud provider. Enterprises are demanding strategic approaches for complex distributed multicloud deployments.
The looming battle over where generative AI systems will run
Putting AI on cloud versus on-premises systems may seem like a simple decision, but it's much more complex (and potentially expensive).
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