Akamai Connected Cloud and Amazon Bedrock compete in the cloud computing and AI services category. Amazon Bedrock appears to have the upper hand due to its advanced AI capabilities and flexibility.
Features: Akamai Connected Cloud offers simple cloud services focused on Linux users with worldwide data center coverage, favored for its fast setup and stability. Amazon Bedrock provides a broad range of foundational models for AI applications, offers fine-tuning, and supports serverless operation for cost efficiency.
Room for Improvement: Akamai Connected Cloud could enhance its security features, expand European data centers, and improve support for newcomers. Amazon Bedrock might focus on reducing pricing, improving cost transparency, and expanding its AI offerings to include voice and image support.
Ease of Deployment and Customer Service: Akamai Connected Cloud is noted for 24/7 support with a personal touch, making issue resolution user-friendly. Amazon Bedrock's customer service is reliable, with its stable services reducing the necessity for frequent support.
Pricing and ROI: Akamai Connected Cloud offers clear pricing, allowing easy scalability and predictable budgeting, appreciated for its cost-effectiveness. Amazon Bedrock's pricing is reasonable within the AI feature space but could benefit from improved price transparency and reductions.
They respond with relevant and easy-to-follow solutions.
They were very responsive to my issue.
We are experiencing the fastest time ever to get things done with AI integrating into our work, regardless of where we are.
So, you always have to bridge the gap by presenting scenarios, getting recommendations, and testing or validating those assumptions.
For my usage, which is a small business, I rate the scalability of Akamai Connected Cloud (Linode) around nine or ten.
It is scalable on a truly global basis.
Amazon Bedrock is quite highly scalable, but there are some limitations they impose on the accounts, which could be an area for improvement.
It scales well with AWS Lambda, AWS Transcribe, and Polly.
The main area for improvement is the lack of a backup feature to the local hard disk or storage.
The main improvement I would like to see from Akamai Connected Cloud (Linode) is the ability to duplicate the server as it is and initialize a new one with the same features.
It would be useful to have the option to sort or group by tags on the domains page.
In AgenTek AI business, the only foundation models we can rely on for scaling now are the Cloud 3.5 models like Haiku and SONNET, designed for low latency and complex AI business use cases.
For companies in general, the main pain point or main issue related to Amazon Bedrock is security because they are not confident that all information is hidden by this kind of architecture.
If AWS provided methods, like five or six prompts that yield specific results, it would ease development.
I find Akamai Connected Cloud (Linode)'s pricing very competitive.
Our cost is incredibly low, operating for a few hundred dollars a month in production.
One customer paid around $100 to $200 per month, which was significant given their overall infrastructure costs.
The pricing and licensing of Amazon Bedrock are quite flexible.
Akamai Connected Cloud (Linode) is easy to use and has a fair price, making it accessible and straightforward, which is crucial when compared to other complex solutions.
Their support is really good. I can ask anything at any time, and they are able to resolve issues like reinstating deleted Linodes.
I use the backup features as my main benefit from Akamai Connected Cloud (Linode), and since my business is small, I don't need more than this.
It has improved operational costs and efficiency significantly, saving money and enhancing the quality of operations.
The ability to make changes in the foundational model is valuable since different customers have specific needs, allowing customization.
Our encryption keys are managed through Bedrock ecosystem by our clients.
Linode Pricing Page
CPU, transfer, storage, and RAM bundled into one simple price.
Amazon Bedrock enhances AI integration by providing a suite of foundational models with customization options. It simplifies data integration and offers security, traceability, and cost-efficiency through its serverless architecture.
Amazon Bedrock empowers users by offering models from multiple providers, ensuring model flexibility and ease of use. It supports quick development for applications such as vector search and SQL query generation. While the system is beneficial for AI integration and analytics enhancement, there is a desire for improved documentation, smoother integration, and more competitive pricing. Additional integration points, markdown features, and support for voice and images could enhance its use. Users also seek to optimize for hyperscale use and receive multiple responses for creative tasks.
What are the key features of Amazon Bedrock?
What benefits should be considered?
In industries like data analytics and software development, Amazon Bedrock is implemented for tasks such as deploying large language models, performing sentiment analysis, and creating chatbots. It's used for generating AI-driven text and images, and enhancing data retrieval via SQL query generation.
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