ScienceLogic and BigPanda compete in the IT operations analytics market. BigPanda appears to have the upper hand due to its advanced machine learning capabilities and effective incident management.
Features: ScienceLogic provides comprehensive monitoring, integration with various IT tools, and a centralized IT view. BigPanda offers automation features, effective incident correlation, and advanced predictive analytics with automated remediation.
Room for Improvement: ScienceLogic could improve the complexity of its setup process, enhance navigation, and simplify its interface. BigPanda can work on reducing delays in incident correlation, expand integration options, and improve documentation.
Ease of Deployment and Customer Service: ScienceLogic is robust but challenging to deploy without experienced IT staff, with mixed reviews on customer support responsiveness. BigPanda has a smoother deployment process due to its SaaS nature and receives consistent praise for its responsive and helpful customer service.
Pricing and ROI: ScienceLogic offers good value for money and a notable return on investment, especially for extensive monitoring needs. BigPanda, though more expensive, is seen as worth the investment due to its exceptional incident management and automation capabilities, contributing to quicker issue resolution and reduced downtime.
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.
The return on investment is fair but often challenged by medium-sized businesses who may question its adequacy.
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.
For technical support, we have only had to address password resets and alert mismatching.
Their collaboration was good, and I would rate them nine out of ten.
Problems with Skylar may require longer wait times due to limited resource expertise.
I received excellent support from ScienceLogic.
We have a lab environment to test solutions before offering them to customers, ensuring everything works correctly.
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.
Stability should relate to whether the platform fails, stops working, or breaks.
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.
While some other companies have easier APIs, using this solution demands significant expertise.
If the knowledge for implementation could be spread through articles, it would reduce this dependency.
Integrating observability and APM monitoring into the overall portfolio would be beneficial.
The pricing for BigPanda is reasonable compared to other event management tools, given its advantages.
It could be cheaper.
ScienceLogic is not that expensive and is cost-effective overall.
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.
Notably, its automation features, such as Runbook action, enable domain experts like me to execute one-click automation solutions, which contributes significantly to reducing MTTR.
The solution excels in three areas: application monitoring, server monitoring, and network performance monitoring.
The CMDB update and the automatic CMDB update are valuable.
| Product | Market Share (%) |
|---|---|
| ScienceLogic | 1.7% |
| BigPanda | 0.9% |
| Other | 97.4% |
| Company Size | Count |
|---|---|
| Small Business | 6 |
| Large Enterprise | 11 |
| Company Size | Count |
|---|---|
| Small Business | 13 |
| Midsize Enterprise | 11 |
| Large Enterprise | 24 |
BigPanda Autonomous Operations platform is a cutting-edge solution that helps IT Ops, NOC and DevOps teams detect, investigate, and resolve IT incidents faster and more easily than ever before. Powered by Open Box Machine Learning, BigPanda correlates IT noise into insights, automates incident management, and unifies fragmented IT operations.
BigPanda’s Autonomous Operations platform increases the ease with which IT administrators are able to both manage their systems and respond to issues that arise. It combines machine learning and automation, which not only provide administrators with reliable suggestions concerning future issues that may arise, but also allows for certain tasks to be assigned to the system itself. These allow organizations to save both time and resources that can be dedicated to more critical tasks.
BigPanda’s Autonomous Operations platform possesses a simplified and unified user interface, enabling users to manage the solution from one place. The UI allows users to view and manage all of the information and controls that IT teams need to be able to easily access, providing a level of visibility that ensures users will be able to view all of their system’s most up-to-date and critical information at any time that they wish.
Benefits of BigPanda Autonomous Operations Platform
Some the benefits of using BigPanda’s Autonomous Operations platform include:
Reviews from Real Users
BigPanda’s Autonomous Operations platform stands out among its competitors for a number of reasons. Two major ones are its centralized user interface and its ability to easily integrate with other security solutions. The centralized UI gives users the ability to clearly see all their alert data in a single location without having to search for it. Its easy integration allows administrators to augment their IT security capabilities when they find it necessary to do so.
PeerSpot user Larry C., the principal engineer in charge of site operations for a tech vendor, notes this benefit when he writes, "Alert aggregation was the primary requirement. BigPanda pulls all this together into a single UI for us, allowing us to see related alerts grouped together into an incident, and enables us to easily create a JIRA ticket and Slack channel to manage an issue."
Another PeerSpot user, who is an independent entrepreneur in the IT environment at a tech services company, notes the flexibility of this platform when they write “BigPanda integrates well with other solutions, such as WatchGuard.”
ScienceLogic excels in customizable dashboards, seamless integrations, and real-time data analysis, supporting diverse IT environments with multi-tenant capabilities.
ScienceLogic provides robust infrastructure and network monitoring, catering to cloud, applications, and server environments. It supports hybrid setups, integrating with CMDB and ticketing systems while automating incident management. ScienceLogic's PowerPacks eliminate visibility gaps and its adaptable nature supports modern and legacy systems. Offering agentless monitoring, it ensures efficient operations with scalable infrastructure support and detailed reporting. However, the interface complexity and need for professional support can present usability challenges. Enhancements in reporting, application coverage, API support, and customization are desirable for improved user experience.
What are ScienceLogic's most important features?ScienceLogic is often implemented across industries requiring detailed attention to infrastructure and network monitoring. It finds utility in managing hybrid environments, integrating seamlessly with essential systems like CMDB and ticketing platforms. Its scalability and adaptability are valued in unifying complex, diverse environments under one monitoring platform.
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