Currently, I do not have any negative points in mind about Amazon Bedrock because I think Amazon Bedrock and other services are good. We have to use OpenSearch as well. We have not implemented RAG in our data pipeline, but I have studied OpenSearch and I think it is good. I do not see any negative points so far. The end-to-end application setup integration was very difficult. An end user needs a URL where a page should appear and they should be able to use it. We created one ECR inside one VPC and created one EC2 instance inside that VPC, and we copied our data into the EC2 instance. From there, we launched Agent Core and ran it. In that case, we had to give the public URL to the user, which was not secure. The integration part was very difficult.
I may not be the right person to provide this insight or recommendation. I am not really following the progress in it. Some new features may have been implemented and I am not aware of it. I would have to go back to Amazon Bedrock for that information. Working on agentic tools and providing more capability on agentic AI is what was missing at the last time I explored Amazon Bedrock. As I recall now, I found some limitations or some models are not present in Amazon Bedrock sometimes while they are present in other platforms. There are new models that are coming, and sometimes I cannot find them in Amazon Bedrock. The limitation of region sometimes also caused some problems. Some models are found in regions and not in others, and the customers or the clients do not want the model to be hosted in a region different than their own. These are some limitations that we encounter sometimes while working on a product for a specific customer.
The only aspect that could be improved about Amazon Bedrock is the pricing. There are no additional features or improvements needed for the product itself.
I have to gain more maturity to provide some improvements to Amazon Bedrock. I have a lot to do with the environment they already provided. For example, they are able to connect to any LLM solution such as Llama, Meta, Gemini, or ChatGPT. It is open; you just choose your favorite LLM solution, and you can integrate it into Amazon Bedrock. We have a lot of possibilities to do this integration at this moment; we just need to work on it, create more maturity, and then we can provide some enhancements that we can see on the solution as a whole. 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. They wonder if they are providing some company information that can run away, and I think that is the challenge we have now. We need to find ways to work on it and make our clients' data secure. They are looking for that to guarantee that this is a great solution for companies that is also secure.
AWS ( /products/amazon-aws-reviews ) could add prompt engineering methods to its services. Currently, there are no prompt methods, so we have to experiment on our own. If AWS provided methods, like five or six prompts that yield specific results, it would ease development.
I am not going to speak to their roadmap. Amazon operates Bedrock as an ecosystem supporting third-party models. I am speculating here, but I am sure those third-party models will always be present. However, one must consider that Amazon native models could proliferate Bedrock in the future. We would welcome Amazon native models to Bedrock, since, if they are natively built by Amazon, they are tuned to SageMaker and other Amazon service layers. They have done this somewhat for generative AI, however, 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.
AWS cloud AI & data scientist at a tech services company with 51-200 employees
Real User
Top 20
Nov 25, 2024
It would be beneficial if Amazon Bedrock could provide multiple responses to a query, allowing users to choose the best option. This feature would be especially useful for tasks requiring creativity.
While working with Bedrock, I incurred charges that were not explicitly mentioned in the pricing documentation. Amazon could provide a more detailed explanation of the costs, including upfront pricing information and examples of common cost scenarios, which would help people starting out with these services to make informed decisions and avoid unexpected expenses.
There is a need for improved documentation, smoother integration, and possibly reduced prices given the competition. I would also like to see more automated integration systems and features.
Amazon Bedrock offers comprehensive model customization and integration with AWS services, making AI development more flexible for users. It streamlines content generation and model fine-tuning with a focus on security and cost efficiency.Amazon Bedrock is engineered to provide a seamless AI integration experience with a strong emphasis on security and user-friendliness. It simplifies AI development by offering foundational models and managed scaling, enhancing both trust and operational...
Currently, I do not have any negative points in mind about Amazon Bedrock because I think Amazon Bedrock and other services are good. We have to use OpenSearch as well. We have not implemented RAG in our data pipeline, but I have studied OpenSearch and I think it is good. I do not see any negative points so far. The end-to-end application setup integration was very difficult. An end user needs a URL where a page should appear and they should be able to use it. We created one ECR inside one VPC and created one EC2 instance inside that VPC, and we copied our data into the EC2 instance. From there, we launched Agent Core and ran it. In that case, we had to give the public URL to the user, which was not secure. The integration part was very difficult.
I may not be the right person to provide this insight or recommendation. I am not really following the progress in it. Some new features may have been implemented and I am not aware of it. I would have to go back to Amazon Bedrock for that information. Working on agentic tools and providing more capability on agentic AI is what was missing at the last time I explored Amazon Bedrock. As I recall now, I found some limitations or some models are not present in Amazon Bedrock sometimes while they are present in other platforms. There are new models that are coming, and sometimes I cannot find them in Amazon Bedrock. The limitation of region sometimes also caused some problems. Some models are found in regions and not in others, and the customers or the clients do not want the model to be hosted in a region different than their own. These are some limitations that we encounter sometimes while working on a product for a specific customer.
The only aspect that could be improved about Amazon Bedrock is the pricing. There are no additional features or improvements needed for the product itself.
I have to gain more maturity to provide some improvements to Amazon Bedrock. I have a lot to do with the environment they already provided. For example, they are able to connect to any LLM solution such as Llama, Meta, Gemini, or ChatGPT. It is open; you just choose your favorite LLM solution, and you can integrate it into Amazon Bedrock. We have a lot of possibilities to do this integration at this moment; we just need to work on it, create more maturity, and then we can provide some enhancements that we can see on the solution as a whole. 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. They wonder if they are providing some company information that can run away, and I think that is the challenge we have now. We need to find ways to work on it and make our clients' data secure. They are looking for that to guarantee that this is a great solution for companies that is also secure.
AWS ( /products/amazon-aws-reviews ) could add prompt engineering methods to its services. Currently, there are no prompt methods, so we have to experiment on our own. If AWS provided methods, like five or six prompts that yield specific results, it would ease development.
Currently, I do not have any thoughts about what areas of Amazon Bedrock need improvement.
I am not going to speak to their roadmap. Amazon operates Bedrock as an ecosystem supporting third-party models. I am speculating here, but I am sure those third-party models will always be present. However, one must consider that Amazon native models could proliferate Bedrock in the future. We would welcome Amazon native models to Bedrock, since, if they are natively built by Amazon, they are tuned to SageMaker and other Amazon service layers. They have done this somewhat for generative AI, however, 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.
The user interface of Amazon Bedrock on the management console needs improvements. It's very bland at the moment.
It would be beneficial if Amazon Bedrock could provide multiple responses to a query, allowing users to choose the best option. This feature would be especially useful for tasks requiring creativity.
While working with Bedrock, I incurred charges that were not explicitly mentioned in the pricing documentation. Amazon could provide a more detailed explanation of the costs, including upfront pricing information and examples of common cost scenarios, which would help people starting out with these services to make informed decisions and avoid unexpected expenses.
There is a need for improved documentation, smoother integration, and possibly reduced prices given the competition. I would also like to see more automated integration systems and features.