BigPanda Reviews

BigPanda's main use case is AI Ops, focusing on observability with AI detection and prevention as a filtering mechanism for alerts and related work. AIOps is the headline for the solution. The tool performs complex work that may seem simple on the surface but is actually quite sophisticated. BigPanda works entirely on the incident side, automating the aspects of IT operations and service management.

In my opinion, the best feature of BigPanda is its speed in terms of deployment. It has very strong integration with all of the major platforms and workflows that organizations need. The biggest customers are enterprises like HSBC and Barclays. Implementing something effective for them that dramatically reduces meantime to repair and the number of incidents is substantially difficult, as projects can often extend three years with very small results. BigPanda is different; it is a tool relied on by many enterprises, fitting over existing toolsets rather than trying to replace them, which makes it non-competitive to many existing alerts and monitoring tools. It enhances existing systems to provide actionable intelligence for business solutions.

There is room for improvement in BigPanda, and I believe they are fixing this. Agentic operations exist in these types of tools, and companies are catching up. Logic Monitor has a slightly different and better version of agentic AI. BigPanda has that on their roadmap, and I saw their kickoff where they explained what they are doing to enhance it. I believe that by the end of this year, improvements will be in place.

I have been working with BigPanda and selling clients on it for approximately seven years in total.

BigPanda is a stable solution. There is almost no downtime and availability issues with the platform.

BigPanda is a very scalable solution. It deals with some of the biggest customers in the world, and I have clients like UBS, Tesco, and Wells Fargo, which are huge companies with five to six million pound contracts.

I would rate technical support from BigPanda at a seven out of ten. They are a smaller company, and I am quite particular about support. I would say seven or eight out of ten is fair. Companies like CoreLogix, which is a log platform, achieve ten out of ten due to their responsiveness, whereas BigPanda's response time is more standard, typically taking about twenty-four hours.

Positive

The initial setup of BigPanda is a very straightforward process.

Regarding the pricing of BigPanda, I feel that their pricing is below market price. It could be significantly more expensive given the impact on OpEx savings and customer satisfaction scores. They sell it at a remarkable value, and in my opinion, it is underpriced. They have been fair and flexible with their pricing to ensure it still shows value for money.

The most common deployment model among my clients for BigPanda is typically cloud-based technology. This SaaS-based solution integrates with their cloud, allowing events and alert trees to push through their platform, providing a dashboard with intelligence. It features bidirectional integration, for example, pushing information into ServiceNow and updating tickets back into BigPanda, making it a straightforward SaaS deployment that is much easier than many other companies.

BigPanda operates on AWS, though I am not entirely certain as it is their company platform and may change.

I give this review an overall rating of nine out of ten.

The overall use cases involve a few of the applications and servers sending data to BigPanda from an incident perspective, along with a few other tools from an analytic perspective. In terms of incident management, I am focusing on correlation and AIOps capabilities, which reduce noise and provide crisp, clear information regarding incidents.

The features of BigPanda that have most improved my incident response times include AIOps, correlation pieces, and grouping, which is a big win for us. The timelines it groups on specific mentions are considerable advantages.

BigPanda's automation and correlation features impact my operations by reducing incident count due to its capability to project parent-child relationships across incidents. Grouping them together helps narrow down issues faster, and resolution also improves because I can focus on impact-specific issues rather than multiple issues, which made determining impact difficult in the past.

Something that comes to mind regarding improvements is communication, as I rely heavily on another tool. If BigPanda could provide communication capabilities beyond just sending notifications—such as creating a war room style of notification, creating channels, getting people on calls, and opening a bridge—I would prefer functionalities similar to PagerDuty within the tool.

I have been working with BigPanda for close to six years now.

In terms of product stability, I can rate it around nine. It is quite good, though I would not rate it a full ten because every time there is a new feature, I have to go through documents or contact support. As the world moves toward AI, there should be features that auto-enable or help direct users on how to navigate for what they are looking for.

BigPanda's technical support is good, and they are pretty effective, though sometimes I may not be in a position to explain situations well, or they may require more information. Setting that aside, they are responsive.

I am familiar with a couple of those solutions, and I have been using them.

Regarding deployment, I did not face challenges that I need to highlight, but it went smoothly considering any other software deployment. A few scenarios had some challenges, but solutions could be identified for those, and those challenges did not require extensive support.

The deployment required close to a week, considering the complexity and the architecture, as it depended on approvals and process cycles.

My implementation strategy during that week involved procuring a few servers ourselves and dedicating them. I found the resource, started setting up the environment, connected that to BigPanda's SaaS world, defined the configurations, ensured all configuration management data was coming into BigPanda, and created the groups and entities, all taken care of during that one week period. Testing included making sure data was accurate with no drops, and I tested the network bandwidths and any latency, with each having its own set of guidelines, which helped me achieve everything in a week's time.

There were three dedicated people involved in the deployment process, and depending on who wants to send data to BigPanda, there are many core services teams involved as well.

From an operational perspective, while I do not have much detail about costs, I can say that resource count has probably reduced by about ten to twenty percent due to the reduced incident count, which enables me to identify issues faster, meaning business recovery is quicker. Certain internal applications that users faced issues with are restored at faster time intervals, which I can vouch for.

Regarding extra expenses, I pay more for communication and do not incur costs for another dashboard perspective, but there are indirect costs related to managing open-source products, leading to resource investment in maintaining the dashboards for these capabilities.

I am using BigPanda.

The impact of BigPanda's AI on managing and prioritizing IT alerts is something I have not yet explored.

BigPanda supports my team during high-pressure, critical incidents quite well.

I would absolutely recommend BigPanda to other users and companies. My overall rating for this review is eight.

Positive

Positive

Positive

Positive

Positive

Neutral

We recently started using BigPanda for event and alert management. Our team, new to incident management, is still learning. 

One of the most valuable features of BigPanda is its user-friendly interface.

BigPanda could improve by syncing its threshold settings with Dynatrace to align with users' familiarity. This would reduce manual effort in analyzing alerts. Automation is needed to distinguish real incidents from false alarms. Additionally, better synchronization with configuration management for server status updates is necessary. Currently, the system is evolving, requiring time to stabilize, given the newness of the tools and technologies being adopted.

I have been using BigPanda for two months.

BigPanda is stable overall without significant breakdowns or bugs. However, there is a challenge in fully trusting its alerts and incidents, requiring manual validation. This could be due to the tool being new and users not fully realizing its intended potential yet.

We have approximately 150 users of the solution at our company.

For new users, I would advise using BigPanda for its comprehensive alert monitoring and integration with ServiceNow. Its mapping capabilities and user-friendly interface make it valuable for incident analysis and prioritization. As users become more familiar with the tool, its full potential will become apparent, enhancing efficiency and effectiveness over time.

It is easy for someone to learn to use BigPanda for the first time. We start with basic examples that everyone can understand, then provide verbal introductions followed by hands-on training over two weeks. We encourage making mistakes and asking questions to ensure understanding. It depends on the trainer's approach, but with proper guidance, anyone can learn effectively.

Overall, I would rate BigPanda as a five out of ten. For it to be a perfect ten, it would need to consistently provide accurate alerts without requiring manual validation. This means it should effectively suppress similar incidents, eliminating the need for constant monitoring. Once it reaches this level of reliability, BigPanda would be exceptional.

BigPanda is used for event correlations, deduplication, suppression, and auto incident creation. Those are the basic functionalities that we were looking for.

The most valuable features of BigPanda are the API integration was good. It enables us to do faster onboarding.

BigPanda can improve the correlations. We didn't see any big value. It is still good at the same event deduplication, event processing, and ticket creation, but I was more looking at event analysis and event correlation. In that area, it is still no big difference between the other solutions on the market. All of them, are in the same immature stage.

I have been using BigPanda for approximately six years.

I have not used the technical support from BigPanda.

The initial setup of BigPanda's difficulty level depends on the environment. For example, it depends on the level of security we go through, and how many design approvals need to do. However, it is technically straightforward, but the process to navigate receiving the architecture approval, and security clearance, varies from customer to customer.

The deployment time depends on the complexity, but typically it is at least two months to complete.

We bring our resources and we help customers deploy BigPanda. We have two people that do the deployment. We use one for management and the other for the availability of the backup.

If you are dealing with more than 10,000 events per week, then there is a return on investment using BigPanda.

The price of BigPanda is in the middle compared to other solutions.

My advice to others is if you use this solution or not it depends on the requirement. For example, if a customer has only a couple of monitoring tools, purchasing BigPanda is useless. If the customer has more than 10 monitoring tools in place and generates a large number of alerts and tickets, such as events generated, then it's worth considering BigPanda as a solution. However, at the same time, if the customer already is invested in a solution, such as ServiceNow then going to the BigPanda is another overhead. 

I would recommend they put it in ITAM itself so that everything goes into one platform. It's easy to control, and manage. You are reducing many hops because that makes the job easier than sending dollars to BigPanda, then BigPanda converting them into tickets into the ServiceNow. It's an unnecessary overhead. It doesn't mean I'm a fan of ServiceNow, but I'm looking from an architectural point of view.

I rate BigPanda a six out of ten.