What is our primary use case?
Currently, my use case for OpsRamp is using it as an infrastructure monitoring tool for customers, where we can provide infrastructure monitoring as a platform. We can have AI appended to those monitoring capabilities where we can have correlations, alert prediction, some automations, deduplication, noise reduction, and these features predominantly.
What is most valuable?
What I appreciate most about OpsRamp is that while many tools in the market provide standard monitoring, OpsRamp stands out as a differentiator by providing AIOps features, including correlation, deduplication, and automation where we can run RBA scripts on top of created alerts. Additionally, it has multiple out-of-the-box integrations available where we can connect to various external tools and integrate them for orchestration between systems.
As a monitoring tool, compared to standard monitoring tools, the benefits include increased productivity and significant noise reduction through its correlation capabilities. The comprehensive monitoring capabilities cover infrastructure monitoring, synthetics, network monitoring, and integrations. It can act as a monitor of monitors, which we currently utilize when customers have multiple monitoring tools in their landscape. OpsRamp can integrate with these monitoring tools and create leverage by providing monitoring as a comprehensive solution.
What needs improvement?
If we treat OpsRamp as an infrastructure monitoring tool, there are many positive aspects. However, when viewed as an AIOps tool, there are numerous potential additions. Currently, it performs infrastructure monitoring but has limited capability in application monitoring, which needs improvement. They are introducing observability as a feature where metrics, logs, and traces can be implemented, but this is currently in a primitive state that can grow over time.
The platform is very stable, and the UI is excellent. However, regarding AIOps features, enhancements could be made to provide more value, such as dynamic thresholding and other capabilities that competitor tools have, such as LogicMonitor.
For how long have I used the solution?
I have been using OpsRamp for the past four years.
How are customer service and support?
We have discussions with both the customer success team and the support team. When we encounter platform challenges or issues, we raise a ticket. Previously, when it was smaller and not acquired by HP, support was more primitive. Now that it is HP's OpsRamp, things are improving, but there is definitely scope for better support.
The availability could be improved. With other tools, there is dedicated support for specific customers or implementation partners and MSPs. Having a dedicated firefighter team for each MSP would be beneficial, as we are handling around 30 to 35 customers where we are implementing OpsRamp. With the current generic support system, issue resolution takes considerable time. I would rate their support at seven out of ten.
How would you rate customer service and support?
Which solution did I use previously and why did I switch?
I have worked with ignio initially, a tool made by TCS that functions as an AIOps tool performing automation, RPA, and monitoring. I have also used Zabbix, SolarWinds, and OpsRamp. Currently, I am being trained with LogicMonitor.
How was the initial setup?
The initial setup is very straightforward. Compared to other monitoring tools, the initial configurations in OpsRamp are simpler. However, regarding AI capabilities, one definitely needs substantial hands-on knowledge of the tool to provide value to the customer.
What about the implementation team?
We have a partnership where we act as an MSP and implementation partner to HP's OpsRamp.
What was our ROI?
We are implementing OpsRamp successfully as it is an excellent tool for infrastructure monitoring for a standard customer base. However, overselling features can complicate implementation. 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.
What other advice do I have?
I use the capability for predictive analytics. The feature is effective in its current form. OpsRamp provides prediction features on the alerts themselves by analyzing data from created alerts and predicting future alert creation. However, it does not predict utilization or forecast utilization from the metric details collected for each monitored parameter.
The flexibility of being deployable both in cloud and on-premises is beneficial as it is a SaaS platform that doesn't require extensive infrastructure. You only need gateways in your customer landscape to operate. Compared to other tools with on-premises setups that require managing numerous servers, this makes it more cost-effective for implementation teams.
I rate OpsRamp 8 out of 10.
Which deployment model are you using for this solution?
On-premises
If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?
Other
Disclosure: My company has a business relationship with this vendor other than being a customer. partner/customer