IBM Cloud Pak for Integration

It manages APIs and integrates microservices at the enterprise level. It offers a range of capabilities for handling APIs, microservices, and various integration needs. The platform supports thousands of APIs, providing tools for building, managing, and securing them effectively.

Redirection is a key feature. It helps in managing multiple microservices by centralizing control and access. With Monalytics, microservices are separated, and redirection ensures they are efficiently managed, including load balancing and recovery.

Enterprise bots are needed to balance products like Kafka and Confluent.

I have been using IBM Cloud Pak for Integration for two years.

Spring Framework is known for its simplicity and ease of use. For instance, IBM Cloud Pak for Integration leverages Spring Boot and Spring Cloud technologies. It also features its own API tools, which are straightforward to use. IBM also works extensively with various services and traditional architectures, continuously evolving to manage complexity over time.

The initial setup is straightforward. Two people are required for it.

IBM is already priced.

I rate the product’s pricing an eight out of ten, where one is cheap, and ten is expensive.

IBM Cloud Pak for Integration includes monitoring capabilities to track the performance and health of your integrations. You can quickly roll back to a previous version if an issue arises. Additionally, it supports incremental deployments, allowing you to shift traffic to a new version of an API gradually. For example, you can start by directing 10% of traffic to the new version while the rest continue using the legacy version. If everything works as expected, you can gradually increase the traffic to the new version over time.

IBM Cloud Pak for Integration has a client base that includes numerous organizations using AI and machine learning technologies. We leverage an open-source machine learning framework and integrate it with Kafka to help create and manage various products and data retrieval processes.

For companies with private data, the framework first retrieves relevant data from a GitHub database, which is then combined with the final request before being sent to a language model like GPT. This ensures that the language model uses your specific data to generate responses.

Kafka plays a key role by streaming real-time data from file systems and databases like Oracle and Microsoft SQL. This data is published to Kafka topics, then vectorized and used with artificial intelligence to enhance the overall process. It's like an old-fashioned approach. The best way is to redesign it with products such as Kafka.

Overall, I rate the solution an eight out of ten.

What do you like best about the product?

I like the most about their API management. They are best in class used and known for their integrations. Another best thing is the ease of UI and its operation

What do you dislike about the product?

I think they need to provide a good examples and steps to setup with the help of video tour and I think documentation should be a little easy

What problems is the product solving and how is that benefiting you?

Me and my team are depended on APIs alot and their management is my neccesity. I believe IBMs API management is a lot of help with their great tool

What do you like best about the product?

Simplify hybrid data chaos,Complete fabric solution, instant on-prem & cloud agility.
easy for begineers also

What do you dislike about the product?

When using third-party services, users often cede some degree of control over their data, privacy, and security.

What problems is the product solving and how is that benefiting you?

main use is deploymentto minimize deployment time and secure and optimize.

What do you like best about the product?

IBM PAK tool helps in the complex use cases for data analysis across IBM cloud.

What do you dislike about the product?

It should include multi cloud strategies and provide quite easy integrations with third party tools

What problems is the product solving and how is that benefiting you?

IBM Cloud Pak helped with the data integration, Data observanility with complete help on Modern Data architecture. The data governance helped to skip the extra additional cost of colibra integration and everything was managed with a single tool

What do you like best about the product?

Integration Options : Initially what made me stood out was it's ability to handle multiple integration styles. Weather it's about APIs or any event srteaming, it's versatility is impressive even this became a game-changer for my team when delaing with some complex integration cases.

User-Friendly : Although it look's complex in starting, but after a time interface feels quite intutive and navigating through platform is quite straightforward and anticipated.

API : Last but not the least it's API management tools are top-notch. Creating and managing APIs for me has really become hassel free now.

What do you dislike about the product?

Learning : For begineers, initial setup and understanding might look bit challanging but after a fair bit of time and some head scratching moments you will a pro.

Resources : It requires a decent amount of resources. Small business or business not equiped with a decent infrastructure, might find it bit sluggish.

Documentation : A lot of documentation, which is a good part but in daily work life sometimes it feels like finding a needle in haystack.

What problems is the product solving and how is that benefiting you?

API Management : With the help of it's tool's, I really enjoyed my work from API creating till retirement.
ETL : It's ETL capibilities are again top-notch with real time data integration and also handling a huge amount of data is now so easy.