IBM K8 made our batch processing great, again!
Updated May 24, 2019

IBM K8 made our batch processing great, again!

jonathan gough | TrustRadius Reviewer
Score 3 out of 10
Vetted Review
Verified User

Overall Satisfaction with IBM Cloud Kubernetes Service

We are migrating our current application from IBM Cloud Foundry to Kubernetes. We grew out of CF and needed more compute power, therefore we turned to Kubernetes. Currently, we are using it as the primary architecture for our UI and a few of our complex processing processes (pseudo batch processing). We are implementing it for this one client, but we have other clients on Kubernetes on other cloud platforms. The application that it is running supports 300 million dollars in business for this company. The solution is only for a single subset of a larger department. Many pieces of the application are still in Cloud Foundry; we are still in the process of migrating.

Pros

  • It scales really well
  • Depending on how you measure, it is cheaper and more powerful than Cloud Foundry
  • Deployments are fast, comparably.

Cons

  • It is very unreliable. We have seen nodes and machines randomly go down without warning or helpful error messages.
  • Documentation is not great.
  • The autoscale and documentation on autoscale are not good. We had to write/re-write our own and as a result; we found a lot of issues that caused problems.
  • Batch processes that used to take hours, we brought down to minutes or an hour.
  • We have found it to be more buggy or less stable than other cloud offerings.
  • Lack of documentation has been challenging.
  • Lack of positive experience might lead us to recommend a different cloud provider.
Internally, we have evaluated and used Google Kubernetes Engine, Azure Kubernetes, and AWS Kubernetes. Overall, our team would rank IBM's offering as 2nd or 3rd amongst those we have used and deployed thus far. We selected IBM Kubernetes here because the client has almost all of their assets with IBM. K8 is better than Cloud Foundry for many things. The scaling is much better than running things on lots of EC2 instances.
IBM Cloud Foundry, IBM Cloud Functions, IBM Sametime, IBM Notes, IBM Watson Studio (formerly IBM Data Science Experience), IBM Watson Analytics, Amazon SageMaker, Amazon Elastic Compute Cloud (EC2), IBM Cloud Object Storage, Amazon S3 (Simple Storage Service), Amazon Simple Queue Service (SQS)
If you have a big budget to spend on IBM services and have a lot of services with IBM, yes. For the most part, it does handle heavy batch processes well. However, we have had issues with intermittent outages that have been very challenging. If you need to have redundancies built in and seamless cross-region support, it is a bit more challenging.

Comments

  • Shannon Cardwell | TrustRadius Reviewer
    Hello Jonathan, This is Shannon from IBM Cloud, thanking you for your feedback and sharing your experience with IBM Cloud Kubernetes Service. We are glad to see you are pleased with the scalability and deployment speed, as we see many of our customers making huge strides in their industry with these features. On the other hand, we are sorry to hear about your reliability and documentation issues.  As we continue to improve our product roadmap, these comments are extremely valuable.  While we work to resolve your issues, please visit https://cloud.ibm.com/docs/containers?topic=containers-ca#ca_about for autoscaling documentation, and reach out to our technical team on slack https://cloud.ibm.com/kubernetes/slack.

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