

PagerDuty Operations Cloud and DataRobot are two competitive products in their respective domains. While PagerDuty Operations Cloud excels in real-time incident management, DataRobot stands out in automated machine learning. Users tend to favor DataRobot's features despite its higher price.
Features: PagerDuty Operations Cloud offers an efficient alerting system, extensive integration capabilities, and straightforward setup. DataRobot provides automated machine learning, advanced data visualization tools, and comprehensive model deployment features.
Room for Improvement: PagerDuty Operations Cloud users suggest enhancing reporting capabilities, incident analytics, and automated workflows. DataRobot users recommend improvements in model deployment speeds, user training resources, and better usability in the model interface.
Ease of Deployment and Customer Service: PagerDuty Operations Cloud is praised for its straightforward setup and responsive customer support. DataRobot users appreciate its deployment process but desire more comprehensive guidance during implementation.
Pricing and ROI: PagerDuty Operations Cloud offers competitive pricing with quicker ROI. DataRobot, though more expensive upfront, delivers long-term value due to its extensive features and capabilities.
Previously we had five employees doing the entire workflow, and now we can do it with two employees because agents are being used to do the same which was previously being done by the employees.
On average, we're saving about 10 to 15 hours per project.
The escalation was not possible at all before, which led to the L1 team being under too much stress.
The alert reduction feature has greatly impacted our ability to prevent costly incidents, as we can accurately respond to alerts with the help of autonomous AI agents, which reduces erroneous notifications.
We definitely save time with PagerDuty Operations Cloud. It saves more than half an hour—30 minutes—for each incident.
They answer all my questions and share guidance on using DataRobot scripts if certain functionalities are not available in the UI.
Being cloud-hosted enables automatic resource scaling, which supports collaboration across teams.
The DataRobot team was very helpful in answering the questions which the customer had.
PagerDuty Operations Cloud is a good product for the organization and the support team is highly effective and responsive.
we have never had an issue when reaching out to someone in customer service
They understand our concerns and are willing to implement solutions that integrate into PagerDuty Operations Cloud effectively.
DataRobot is very scalable because the customer initially started with two licenses, and now they have around 20 licenses.
Scalability for PagerDuty Operations Cloud is excellent, and I rate it at 9.9.
Whatever top-notch tools we are using as an enterprise solution, PagerDuty Operations Cloud has kept itself current and integrates nicely with all the tools we use these days.
We are able to extend our PagerDuty Operations Cloud configuration without major challenges or changes to our overall operational model.
We have never experienced any downtime or latency issues from PagerDuty Operations Cloud.
It never breaks down for us, and considering I have devoted 20 years of my career to IT infrastructure operations, where everything typically breaks down, including Jira and ServiceNow, it is impressive to say that PagerDuty Operations Cloud has not caused disruptions.
Over three years, we have experienced zero outages on PagerDuty that prevented alerting or on-call notifications.
If DataRobot also adds those data transformation capabilities, then it will be an end-to-end tool and the customer will not have to procure many tools for doing the ingestion and transformation process.
DataRobot is a UI-based tool, which means it cannot provide all the features I might manually implement through notebooks or Python.
There is a lack of transparency in the models; sometimes it feels like a black box.
It would be useful to have a way to define all configurations in code that is similar to how Terraform operates.
With many new members, they need training to set up runbook workflows, event orchestration, and manage complex on-call schedules across 23 services, making it a challenge for new users.
Additionally, I think a sandbox mode would be helpful for new team members, allowing us to guide them in simulating alerts, performing escalation policies, and creating PagerDuty Operations Cloud channels.
The setup cost was minimal because it's cloud-hosted, eliminating the need for heavy on-premises infrastructure, allowing us to start using it immediately after purchase.
I had around seven users part of it for a base pricing of around $450 per user, primarily for custom workflows and the ITSM part.
The pricing for PagerDuty Operations Cloud is a bit expensive, especially for startups like us, compared to the other platform which I mentioned, which is Rootly.
We have been using PagerDuty Operations Cloud for several years, so our pricing and cost have definitely increased over time, especially as we have hired additional engineers.
By automating highly technical aspects like model comparison, DataRobot enhances productivity and reduces project timelines from three months to less than one month.
DataRobot has positively impacted our organization in many ways. First, it has improved efficiency; tasks such as model testing, feature engineering, and predictions that used to take us days or weeks can now be accomplished in hours.
DataRobot's one of the major features is model evaluation and model performance.
It integrates with multiple applications and is highly customizable, with policies, escalation procedures, and an event routing tool that ensures contacting the right person.
In addition to those features, I also find the integration and reporting aspects of PagerDuty Operations Cloud valuable, as it records all triggered calls and incidents, enabling us to analyze patterns and identify the times when systems go down, thus assisting us in understanding and addressing the underlying causes.
Before, setting up everything was very difficult. Now, we don't have to think about it. We can simply set it up in PagerDuty and it works.
| Product | Mindshare (%) |
|---|---|
| PagerDuty Operations Cloud | 2.5% |
| DataRobot | 1.6% |
| Other | 95.9% |


| Company Size | Count |
|---|---|
| Small Business | 2 |
| Midsize Enterprise | 1 |
| Large Enterprise | 6 |
| Company Size | Count |
|---|---|
| Small Business | 27 |
| Midsize Enterprise | 19 |
| Large Enterprise | 63 |
DataRobot automates model building and deployment, simplifying MLOps with user-friendly interfaces. Its AutoML and feature engineering streamline model comparison, selection, and testing, enhancing efficiency and scalability.
DataRobot facilitates efficient integration with cloud systems and data sources, reducing manual workload, enhancing productivity, and empowering data-driven decision-making. Its strengths lie in automating complex modeling tasks and supporting multiple predictive models effectively. Users emphasize the need for better handling of large datasets, integration with orchestration tools, and more flexibility for custom code integration and advanced model tuning. They also seek improved support response times, transparent model processing, real-world documentation, and enhanced capabilities in generative AI and accuracy metrics.
What are the key features of DataRobot?DataRobot is adopted across industries like healthcare and education for creating and monitoring machine learning models. It accelerates development with GUI capabilities, aids data cleaning, and optimizes feature engineering and deployment. Organizations can predict behaviors, automate tasks, manage production models, and integrate into data science processes to improve data processing and maximize efficiency.
PagerDuty Operations Cloud specializes in incident management and alert automation, with integration to 700+ platforms, reducing resolution time and manual workloads through AI-driven features and automated alerts.
PagerDuty Operations Cloud is a robust tool for automated incident management, integrating seamlessly with platforms like ServiceNow, Datadog, New Relic, and AWS. It provides AI-driven alert grouping, customizable escalation policies, and multiple notification methods, including SMS and mobile apps. Despite its intricate interface and cost concerns, it significantly enhances reliability and response times. Users utilize it for shift scheduling and automated responses via webhooks, optimizing operational management and improving reaction to high-severity alerts.
What are the key features of PagerDuty Operations Cloud?Organizations, especially in IT and DevOps, find PagerDuty Operations Cloud beneficial for automated incident management. Integrating with platforms such as Slack and cloud providers, it aids in efficient incident handling. Teams use it for monitoring and resolving critical issues effectively, leveraging webhooks and notifications to maintain operational efficiency.
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