

BigPanda and OpsRamp are both competitive products in the IT operations management space. OpsRamp appears to have the upper hand due to its comprehensive features that cater to complex IT environments.
Features: Users commend BigPanda for its incident automation, ease of data integration, and scalability. OpsRamp is praised for its advanced monitoring capabilities, multi-cloud management, and robust incident management.
Room for Improvement: BigPanda users highlight the need for enhanced reporting capabilities, better alert filtering, and improved AI algorithms. OpsRamp users suggest improvements in the user experience and documentation, along with better integration options.
Ease of Deployment and Customer Service: BigPanda is noted for its relatively straightforward deployment and responsive customer support, helping users get up to speed quickly. OpsRamp requires more effort and time for deployment due to its extensive functionality but also receives praise for its support team.
Pricing and ROI: BigPanda is perceived as cost-effective with a quick return on investment due to its affordable setup costs and efficient incident management. OpsRamp, while more expensive upfront, is seen as providing high value through its rich feature set, justifying its price over time.
BigPanda offers significant time-saving, cost-saving, and resource-saving benefits.
BigPanda saves time with its advanced features and manages large environments while requiring fewer resources compared to our previous tool, Netcool.
It is important to stick with available features and provide customers with clear, precise details about what can and cannot be done to avoid anomalies.
I find the licensing model convenient and clear enough, and I have seen a return on investment with OpsRamp.
If BigPanda can consistently provide such competent contacts, I would rate the support ten out of ten, otherwise, it is an eight out of ten.
Companies like CoreLogix, which is a log platform, achieve ten out of ten due to their responsiveness.
For technical support, we have only had to address password resets and alert mismatching.
Having a dedicated firefighter team for each MSP would be beneficial.
It handles large volumes of alerts without limitations.
We manage a large environment with over 50,000 servers and various monitoring tools like Dynatrace, New Relic, Splunk, Nagios, and Datadog.
I rate the scalability of BigPanda at eight.
BigPanda is now stable.
I would rate the availability of BigPanda at nine because it's almost 99.99% available.
However, when handling critical traffic, the BigPanda site can slow down, which we manage with a load balancer.
A 'deep dive' analysis feature would be appreciated to give detailed insights such as CPU usage and disk space analysis.
It would be beneficial if BigPanda leveraged AI to solve critical issues related to editing and sending alerts based on enrichment mapping files.
If BigPanda could integrate AI, it would enhance the platform significantly by offering chatbot functionality within the BigPanda UI.
Technical support should be improved.
The pricing for BigPanda is reasonable compared to other event management tools, given its advantages.
it does not strike me as expensive, and the licensing model is clear enough.
Its automation has significantly improved incident response times, reducing the process to within one minute.
It can correlate multiple issues within a single device, create a single incident, and thus reduce noise and provide faster resolution.
BigPanda improves service reliability with instant resolution, increased uptime, and reduced mean time to resolution, thus enhancing service quality.
I have utilized OpsRamp's capability for predictive analytics, and it has been important in fostering collaboration between my IT and development teams under DevOps methodologies, where applicable.
| Product | Mindshare (%) |
|---|---|
| BigPanda | 0.6% |
| OpsRamp | 1.2% |
| Other | 98.2% |

| Company Size | Count |
|---|---|
| Small Business | 6 |
| Large Enterprise | 11 |
| Company Size | Count |
|---|---|
| Small Business | 1 |
| Midsize Enterprise | 3 |
| Large Enterprise | 8 |
BigPanda enhances incident management through root cause analysis, alert deduplication, and event correlation. The AI-driven platform is designed for environments with high alert volumes, providing insights for data-driven decisions and seamless integration with tools like ServiceNow and Teams.
BigPanda addresses the complexities of incident management by offering an AI-focused approach to anomaly detection. Automation improves response times, while unified analytics supports informed decision-making. Despite AI integration and usability needing enhancement, the platform simplifies observability and ticketing through integrations with New Relic and Slack. Features like enrichment mapping and unified search improve functionality, though reporting and visualization aspects require development.
What are the key features of BigPanda?BigPanda is widely implemented in industries focusing on observability and predictive analysis, providing efficient alert processing and incident management. Users utilize its capabilities to seamlessly integrate with solutions like Dynatrace, particularly in environments that handle high volumes of alerts, ensuring effective notification delivery through various platforms.
OpsRamp offers a comprehensive IT management platform that enhances business operations through monitoring automation, AIOps, and integration capabilities.
OpsRamp provides a single pane of glass for hybrid infrastructure management, integrating with tools like Zendesk to streamline operations. With predictive analytics and AIOps features such as root cause analysis, it significantly improves IT efficiency. The platform's machine learning, event correlation, and personalized dashboards improve user experience. However, users have noted scalability issues, interface limitations, and patch management inconsistencies, with room for enhancement in network capabilities and ITSM maturity.
What features define OpsRamp?OpsRamp is widely implemented for managing and automating IT infrastructure across sectors. Enterprises apply it for Azure infrastructure management, resource threshold setting, and generating alerts. It supports digital transformation through incident management, tools consolidation, and leveraging AI for IT operations, facilitating network and storage device onboarding for customer environments.
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