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IBM Cloud Kubernetes Service vs. ScienceLogic AI Platform

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    Overview
    ProductRatingMost Used ByProduct SummaryStarting Price

    IBM Cloud Kubernetes Service

    Score8 out of 10
    Mid-Size Companies (51-1,000 employees)
    IBM Cloud Kubernetes Service is a managed Kubernetes offering, delivering user tools and built-in security for rapid delivery of applications that users can bind to cloud services related to IBM Watson®, IoT, DevOps and data analytics. As a certified K8s provider, IBM Cloud Kubernetes Service provides intelligent scheduling, self-healing, horizontal scaling, service discovery and load balancing, automated rollouts and rollbacks, and secret and configuration management. The Kubernetes…N/A

    ScienceLogic AI Platform

    Score8.2 out of 10
    Enterprise companies (1,001+ employees)
    ScienceLogic provides a unified IT Operations platform designed to manage operational workflows using high-fidelity Telemetry Data and explainable automation. The ScienceLogic AI Platform is deployable across On-Premises, Cloud, and Hybrid Environments. The platform consolidates monitoring tools to provide Observability and enables engineers to automate manual processes using Machine Learning capabilities. The platform utilizes automation for Closed-Loop Remediation and provides insights…N/A
    Pricing
    IBM Cloud Kubernetes ServiceScienceLogic AI Platform
    Editions & Modules
    No answers on this topic
    No answers on this topic
    Offerings
    Pricing Offerings
    IBM Cloud Kubernetes ServiceScienceLogic AI Platform
    Free Trial
    NoNo
    Free/Freemium Version
    YesNo
    Premium Consulting/Integration Services
    YesYes
    Entry-level Setup FeeOptionalRequired
    Additional Details—ScienceLogic SL1 offers four tiers: SL1 Advanced – Application Health, Automated Troubleshooting and Remediation Workflows SL1 Base – Infrastructure Monitoring, Topology & Event Correlation SL1 Premium – AI/ML-driven Analytics, Low-Code Automated Workflow Authoring SL1 Standard – Infrastructure Monitoring – with Agents, Business Services, Incident Automation, CMDB Synchronization, Behavioral Correlation
    More Pricing Information
    Community Pulse
    IBM Cloud Kubernetes ServiceScienceLogic AI Platform
    Considered Both Products
    IBM
    No answer on this topic
    ScienceLogic
    No answer on this topic
    Key User Insights
    Would buy again
    96%
    Would buy again
    27 Answers
    87%
    Would buy again
    81 Answers
    Delivers good value for the price
    100%
    Delivers good value for the price
    25 Answers
    91%
    Delivers good value for the price
    71 Answers
    Happy with the feature set
    100%
    Happy with the feature set
    28 Answers
    92%
    Happy with the feature set
    86 Answers
    Lived up to sales and marketing promises
    100%
    Lived up to sales and marketing promises
    19 Answers
    85%
    Lived up to sales and marketing promises
    44 Answers
    Implementation went as expected
    100%
    Implementation went as expected
    26 Answers
    81%
    Implementation went as expected
    58 Answers
    Features
    IBM Cloud Kubernetes ServiceScienceLogic AI Platform
    Container Management
    Comparison of Container Management features of IBM Cloud Kubernetes Service and ScienceLogic AI Platform
    Feature
    IBM Cloud Kubernetes Service
    8.1
    20 Ratings
    1% below category average
    ScienceLogic AI Platform
    -
    Ratings
    Security and Isolation8.120 Ratings00 Ratings
    Container Orchestration8.520 Ratings00 Ratings
    Cluster Management7.820 Ratings00 Ratings
    Storage Management8.020 Ratings00 Ratings
    Resource Allocation and Optimization8.020 Ratings00 Ratings
    Discovery Tools7.819 Ratings00 Ratings
    Update Rollouts and Rollbacks7.720 Ratings00 Ratings
    Self-Healing and Recovery8.418 Ratings00 Ratings
    Analytics, Monitoring, and Logging8.220 Ratings00 Ratings
    AIOps Features
    Comparison of AIOps Features features of IBM Cloud Kubernetes Service and ScienceLogic AI Platform
    Feature
    IBM Cloud Kubernetes Service
    -
    Ratings
    ScienceLogic AI Platform
    7.6
    26 Ratings
    0% below category average
    Monitoring and Alerting00 Ratings8.225 Ratings
    Performance Analytics00 Ratings7.826 Ratings
    Incident Management00 Ratings6.626 Ratings
    Service Desk Integration00 Ratings7.525 Ratings
    Root Cause Analysis00 Ratings7.721 Ratings
    Capacity Planning Tool00 Ratings7.222 Ratings
    Configuration and Change Management00 Ratings7.723 Ratings
    Automated Remediation00 Ratings7.620 Ratings
    Collaboration and Communication00 Ratings8.020 Ratings
    Threat Intelligence00 Ratings7.319 Ratings
    Best Alternatives
    IBM Cloud Kubernetes ServiceScienceLogic AI Platform
    Small Businesses
    Mirantis Kubernetes Engine
    Score8 out of 10
    No answers on this topic
    Medium-sized Companies
    Amazon Elastic Container Service (Amazon ECS)
    Score8.6 out of 10
    No answers on this topic
    Enterprises
    SUSE Rancher
    Score9.4 out of 10
    ignio AIOps
    Score8.1 out of 10
    All AlternativesView all alternativesView all alternatives
    User Ratings
    IBM Cloud Kubernetes ServiceScienceLogic AI Platform
    Likelihood to Recommend
    8.0
    (86 ratings)
    8.0
    (228 ratings)
    Likelihood to Renew
    8.9
    (16 ratings)
    8.5
    (24 ratings)
    Usability
    8.7
    (16 ratings)
    9.6
    (15 ratings)
    Availability
    9.1
    (1 ratings)
    9.2
    (14 ratings)
    Performance
    9.1
    (1 ratings)
    8.2
    (14 ratings)
    Support Rating
    7.7
    (4 ratings)
    6.6
    (20 ratings)
    In-Person Training
    -
    (0 ratings)
    8.8
    (6 ratings)
    Online Training
    8.7
    (15 ratings)
    7.7
    (8 ratings)
    Implementation Rating
    7.6
    (3 ratings)
    6.4
    (99 ratings)
    Configurability
    -
    (0 ratings)
    10.0
    (7 ratings)
    Ease of integration
    -
    (0 ratings)
    8.0
    (15 ratings)
    Product Scalability
    1.0
    (1 ratings)
    8.0
    (1 ratings)
    Vendor post-sale
    -
    (0 ratings)
    9.1
    (7 ratings)
    Vendor pre-sale
    -
    (0 ratings)
    8.3
    (7 ratings)
    User Testimonials
    IBM Cloud Kubernetes ServiceScienceLogic AI Platform
    Likelihood to Recommend
    IBM
    IBM Cloud Kubernetes Service also stands out in environments where the workloads vary continuously and require befitting scale. The product excels particularly in microservices structures, wherein the companies would harness the capacity for container orchestration and automated scaling. Still, it may face the challenges due to monolith applications that have not been originally developed for using container technology.
    Read full review
    ScienceLogic
    For Windows, the issue is in higher resource consumption related to WinRM monitoring, which provides better options then the SNMP monitoring, which on the other hand is less resource intensive. The problem is also with support for OS with other than English language.
    Incentivized
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    Pros
    IBM
    • IBM has a strong focus on serverless and Kubernetes. This shows in the platform. Deploying containers to Kubernetes was very easy.
    • Deploying a Kubernetes cluster through the GUI is very easy and quick. On top of that, IBM Cloud offers a single node cluster for Free.
    • Container Registry is a very good product for managing container images. Integration with Kubernetes was seemless.
    • Portability. To transition from Google Cloud Kubernetes to IBM Cloud Kubernetes took almost no effort. We mostly use the CLI and the standard tools such as kubectl were present.
    Incentivized
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    ScienceLogic
    • Best overall coverage of montioring different technologies.
    • Easy to use in any environment
    • Customizable being able to generate your own reports, dashboards, DA's, RBA's, etc.
    • Have very good out of the box integrations with other monitoring solutions such as ServiceNow
    • Always improving and regularly releasing new versions and upgrades to the system/DA's.
    • Interactive community
    Incentivized
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    Cons
    IBM
    • I constantly get this error even when everything is well configured prefect.exceptions.AuthorizationError: [{'path': ['auth_info'], 'message': 'AuthenticationError: Forbidden', 'extensions': {'code': 'UNAUTHENTICATED'}}]
    • Then sometimes the error disapear without changine anything, happened twice to me. Should there be an issue with the authentication service? Please let's improve or let users know why this may be happening.
    • Improve the UX in the browse console when removing many images at once
    • UX on the process of installing KeyCloack operator
    Incentivized
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    ScienceLogic
    • Dashboards are quite old and are of Iron age. Need to have AP2 dashboards only instead of AP1 and consistent new design across all functionalities.
    • Reporting is not improved since Y2020 and need to revamp completely. Need to integrate Dashboards and Reporting. PowerBI Like functionality to be given OOTB. Reports should be extracted in Excel, PDF, HTML and should be heavily automated.
    • Create and Open APIs for basic and advanced monitoring data extraction.
    • Topology based Event Correlation and Suppression should be improved drastically. Need to identify critical network interfaces based on Topology and monitor them. Basic customization of Dynamic App and/or Powerpack to exclude/include certain metrics/events to be permitted OOTB instead of customizations.
    • Integration with ServiceNow to be improved and to be taken to next level. Automation Powerpack should be made available OOTB as part of base product and to be priced attractively.
    • Take product to next level where we can monitor actual impacted IT or Business Service instead of metrics and events BSM and Topology map to be auto discovered and identify the network dependencies and alternate paths automatically instead of manual creation of BSM.
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    Likelihood to Renew
    IBM
    We have our application running on a CentOS compartment on IBM Cloud Kubernetes Service. We have been utilizing the help since IBM Cloud initially dispatched. We liked the adaptability and versatility that IBM Cloud Kubernetes Service give us. Since we are tiny, the Kubernetes administration is just utilized at present inside my venture bunch.
    Incentivized
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    ScienceLogic
    It is simply because of all the best possible autonomy solutions it is providing and getting better day by day. Using AI and Devops along with handy automation, The monitoring and Management of devices becomes much easier and the way it is growing in all the aspects is one the best reasons too. Evolution of the SL1 platform in the autonomy monitoring and management is quite appreciable.
    Incentivized
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    Usability
    IBM
    We actually haven't had any real problems in our clusters recently and the results we have gotten from adopting IBM Cloud Kubernetes Service have been beyond even our greatest expectations. The community has helped optimize the use of the system and make it relatively simpler to use.
    Incentivized
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    ScienceLogic
    The core functions are there.
    The complexity is due to the complexity of the space.
    The score is based on comfort (I no longer notice the legacy UI) and the promise that I see in the 8.12 Unified UI (a vast improvement).
    It is also based on the fact that with 8.12, you can now do everything in the new UI but you still have the legacy UI as a fallback (which should now be unnecessary for new installations)
    Incentivized
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    Reliability and Availability
    IBM
    IBM's cloud is almost infallible.
    Incentivized
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    ScienceLogic
    SL is always there and online when you need to get info from it. The only times when SL was not available in our own data center, was when network links from out side of the data center was down and those links were not in our controll. Having a central database and people accessing it all over the world, may put a bit of constarin on the performance of the dashboards when reports gets generated, but that is far and few n between.
    Incentivized
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    Performance
    IBM
    IBM's cloud has a site in my conuntry (MEXICO) so the network latency was almost 0
    Incentivized
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    ScienceLogic
    SceinceLogic SL1 architecture helps the platform to give a top-notch performance in every respect, Data collection to reporting happens very smoothly. With the new user interface pages load much faster. Individual appliances carrying the individual task ensure things are working without lag. Integration with ticketing tool(SNOW) is well managed by the ScienceLogic, no issue or much delay has been observed while interacting with an external tool.
    Incentivized
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    Support Rating
    IBM
    The self-guided support was solid, and there are plenty of online videos to guide first time users, but I think one area of improvement is a faster way to transfer a large quantity of files from our local machine to the cloud for storage (Aspera)
    Incentivized
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    ScienceLogic
    So far, it's good as part of my overall experience, except for a couple of use cases. The support team is well knowledgeable, has technical sound, and is efficient. When support escalates to engineering, the issue gets stuck and takes months to resolve.
    Incentivized
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    In-Person Training
    IBM
    No answers on this topic
    ScienceLogic
    It was good, Do the online training first and understand it and you will get the most out of the in-person training that way. This also takes you to an advanced level which is very good and the training as been overhauled once again along with new product coming in such as Zebruim / Skylar, worth going through again if it a while back that you first did this.
    Incentivized
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    Online Training
    IBM
    Online training is really an important resource for using these tools. IBM's help center is rich in useful information and tips. Also, external guides and tutorials are available (e.g. on youtube), but I followed only IBM ones and I had no difficulties.
    Incentivized
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    ScienceLogic
    There are a lot of educational materials and courses on the SL1 training site (Litmos university). However the recording quality is sometimes not very good - screen resolution is low. There is a lack of professional rather than user-oriented documents and there are mistakes in documentation and education is not well structured.
    Incentivized
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    Implementation Rating
    IBM
    Ease of use. Very intuitive. We have been looking for a product that allows us to orchestrate our docker containers in a way where it allows us to effectively scale our applications to production. It also provides us a way of monitoring all our infrastructure in a very clear concise way.
    Incentivized
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    ScienceLogic
    Implementation is smooth if we are to just support the out-of-the-box features available in ScienceLogic. For any custom requirement, having to go to SL1 Professional Services is the worst part of procuring this suite. And more often than not, SL1 Professional Services also ask to raise feature request. So, you subscribe to Professional Services to only hear back from them that "This feature is not supported and needs to have a separate feature request". At times frustrating.
    Incentivized
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    Alternatives Considered
    IBM
    We mainly selected [IBM Cloud Kubernetes Service] because IBM fabric blockchain service is mostly compatible with it. To have all the infrastructure in a single cloud to get the best output we selected the [IBM Cloud Kubernetes Service].
    Incentivized
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    ScienceLogic
    Science logic SL1 is so user friendly and it's really easy to navigate between function. I would recommend Sciene logic SL1 to all of them who are looking for really useful monitoring tool and expecting easy way of managing it.
    Incentivized
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    Scalability
    IBM
    IBM's CKS does not offers automatic autoscaling nor vertical scaling (automatic). Other services like Google Kubernetes Engine scales up and down very well
    Incentivized
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    ScienceLogic
    Our deployment model is vastly different from product expectations. Our global / internal monitoring foot print is 8 production stacks in dual data centers with 50% collection capacity allocated to each data center with minimal numbers of collection groups. General Collection is our default collection group. Special Collection is for monitoring our ASA and other hardware that cannot be polled by a large number of IP addresses, so this collection group is usually 2 collectors). Because most of our stacks are in different physical data centers, we cannot use the provided HA solution. We have to use the DR solution (DRBD + CNAMEs). We routinely test power in our data centers (yearly). Because we have to use DR, we have a hand-touch to flip nodes and change the DNS CNAME half of the times when there is an outage (by design). When the outage is planned, we do this ahead of the outage so that we don't care that the Secondary has dropped away from the Primary. Hopefully, we'll be able to find a way to meet our constraints and improve our resiliency and reduce our hand-touch in future releases. For now, this works for us and our complexity. (I hear that the HA option is sweet. I just can't consume that.)
    Incentivized
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    Return on Investment
    IBM
    • Increased development speed and agility allows to build features faster and more economically.
    • Improved resource utilization helps keep applications running very efficiently, which saves on cloud service expenses.
    • Scalability and resilience allows for scaling up or down based on demand, which keeps applications running efficiently and more economically.
    Incentivized
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    ScienceLogic
    • Once a powerpack is developed and configured for a device for one customer, it is easy to deploy the same powerpack on a second customer estate and configure specifically for that customer without having to reinvent the powerpack. This saves time and therefore money.
    • Once the customer estate tuning is complete, the Operations team have come trust the alerts. This is especially true when transient or self-correcting alerts are automatically cleared without ops team involvement, but a record is still available for audit and debugging purposes. This saves time and therefore money.
    • When setup correctly, it provides good visibility into applications, devices and whole customer estates. This saves time and therefore money when issues arise.
    Incentivized
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    ScreenShots

    ScienceLogic AI Platform Screenshots

    Screenshot of Unified Observability and Contextual IntelligenceScreenshot of Relationship Mapping & Service VisibilityScreenshot of ITSM and Collaboration IntegrationsScreenshot of Low-Code Workflow BuilderScreenshot of Dynamic Application DevelopmentScreenshot of Executive Overview Dashboard