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What is IBM Cloud Pak for Watson AIOps?

Begin your AIOps adventure and transform your IT operations with IBM Cloud Pak for Watson AIOps. This cutting-edge platform seamlessly incorporates advanced, explainable AI into the ITOps toolchain, empowering you to thoroughly assess, diagnose, and resolve incidents impacting vital workloads. For those accustomed to IBM Netcool Operations Insight or previous IBM IT management solutions, transitioning to IBM Cloud Pak for Watson AIOps marks an evolution in your current capabilities. It consolidates data from various critical sources to identify hidden anomalies, forecast potential problems, and accelerate resolutions. By addressing risks proactively and automating runbooks, workflows see a remarkable enhancement in efficiency. AIOps tools enable real-time correlation of both structured and unstructured data, allowing teams to maintain focus while obtaining valuable insights and recommendations that seamlessly integrate into current operations. Furthermore, the ability to establish policies at the microservice level facilitates effortless automation across diverse application components, significantly boosting overall operational efficiency. This holistic strategy guarantees that your IT operations are not merely reactive but also strategically anticipatory, paving the way for future advancements in your technological landscape. Embracing this innovative approach positions your organization to respond adeptly to the ever-evolving demands of the digital environment.

What is Amazon SageMaker Clarify?

Amazon SageMaker Clarify provides machine learning practitioners with advanced tools aimed at deepening their insights into both training datasets and model functionality. This innovative solution detects and evaluates potential biases through diverse metrics, empowering developers to address bias challenges and elucidate the predictions generated by their models. SageMaker Clarify is adept at uncovering biases throughout different phases: during the data preparation process, after training, and within deployed models. For instance, it allows users to analyze age-related biases present in their data or models, producing detailed reports that outline various types of bias. Moreover, SageMaker Clarify offers feature importance scores to facilitate the understanding of model predictions, as well as the capability to generate explainability reports in both bulk and real-time through online explainability. These reports prove to be extremely useful for internal presentations or client discussions, while also helping to identify possible issues related to the model. In essence, SageMaker Clarify acts as an essential resource for developers aiming to promote fairness and transparency in their machine learning projects, ultimately fostering trust and accountability in their AI solutions. By ensuring that developers have access to these insights, SageMaker Clarify helps to pave the way for more responsible AI development.

Media

Media

Integrations Supported

Amazon SageMaker
Amazon SageMaker Unified Studio
Amazon Web Services (AWS)
Hazelcast
Humio
IBM Data Refinery
IBM Fusion
IBM ILOG CPLEX Optimization Studio
IBM Turbonomic
IBM Watson Studio
IBM WebSphere Commerce
Microsoft Teams
Red Hat OpenShift
Slack
Sysdig Secure

Integrations Supported

Amazon SageMaker
Amazon SageMaker Unified Studio
Amazon Web Services (AWS)
Hazelcast
Humio
IBM Data Refinery
IBM Fusion
IBM ILOG CPLEX Optimization Studio
IBM Turbonomic
IBM Watson Studio
IBM WebSphere Commerce
Microsoft Teams
Red Hat OpenShift
Slack
Sysdig Secure

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

IBM

Date Founded

1911

Company Location

United States

Company Website

www.ibm.com/cloud/cloud-pak-for-watson-aiops

Company Facts

Organization Name

Amazon

Date Founded

2006

Company Location

United States

Company Website

aws.amazon.com/sagemaker/clarify/

Categories and Features

Incident Management

Audit Trail
Corrective Actions (CAPA)
Disaster Recovery
IT Incident Management
Incident Reporting
OSHA Compliance
Root-Cause Diagnosis
Safety Management
Task Management
Ticket Management

IT Management

Capacity Monitoring
Compliance Management
Event Logs
Hardware Inventory
IT Budgeting
License Management
Patch Management
Remote Access
Scheduling
Software Inventory
User Activity Monitoring

Categories and Features

Machine Learning

Deep Learning
ML Algorithm Library
Model Training
Natural Language Processing (NLP)
Predictive Modeling
Statistical / Mathematical Tools
Templates
Visualization

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Popular Alternatives

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