The main use cases for PagerDuty Operations Cloud are incident management and handling high severity incidents in an automated way. For example, at midnight, if we get a high severity incident, PagerDuty throws alarms or notifications to our Slack or team channel so other people get notified and start working on it. Another use case is that we are also monitoring our cloud VMs using PagerDuty automation, which we have done using service integration with our cloud provider. It identifies situations such as our cloud VM going to high CPU usage or requests getting dropped, which can significantly damage the application. At that time, PagerDuty sends alerts to the respective persons, the person who is on-call.

Another use case is that we also use PagerDuty to execute some of the installation scripts using PagerDuty webhooks integration in a totally automated way. Suppose any cloud resource goes faulty and we need to ensure that the respective installation or script gets executed automatically by the use of PagerDuty webhook, so that the issue gets fixed automatically. Nobody is going to be informed or bothered, as it is a self-healing process. We also use another notification to our mobile phone for any P1, which is a high severity incident that will definitely have a business impact. At that moment, we have also leveraged this tool to get a phone call.

The best features of PagerDuty Operations Cloud that I find most valuable are incident management and webhooks. The reason is that if you go for any P1 incident, somebody would usually need to do all the manual efforts, such as creating the Slack channel, informing the team leads and other team members, gathering information related to any service outage or component outage, and providing it in a text format to the Slack channel. All these manual efforts take much time, but PagerDuty does that for you. It gathers the related services and people who are already in that Slack channel and sends the alerts. It automates the whole process, so no human intervention is required.

Another very good functionality is webhooks. They work exceptionally well. If my cloud infrastructure has an issue, a person needs to investigate, and if it requires a server reboot or installation of a script, that person needs to intervene manually. However, using this webhook, we can send one alert or notification to our automated job indicating that this issue requires execution of a particular script or file on that server, which fixes the ongoing issue without requiring human intervention. If this happens at midnight, people can sleep easily without any headache, and PagerDuty will take care of the task.

PagerDuty Operations Cloud has a very good impact on our company, especially regarding business and service level agreements, as well as reducing incident resolution time. It also helps automate manual work.

An additional feature I think would improve PagerDuty Operations Cloud is integration with development scenarios or the code building side. For example, if there is a service outage, I believe PagerDuty could have functionality to check that out and verify if there was any faulty code pushed to our GitHub repository. If there was an error in our repository structure, then having a functionality to find these errors would provide much clarity. This would help developers quickly identify and fix issues, making sure they can change code wherever necessary. That would work exceptionally well.

I have been using PagerDuty Operations Cloud for more than three years.

PagerDuty Operations Cloud is stable, with very little chance of missed alerts. It catches almost all alerts, sending notifications in a timely manner. We have not seen PagerDuty Operations Cloud instance go down or fail; it works smoothly, so I would say PagerDuty Operations Cloud operates perfectly fine.

The scalability of PagerDuty Operations Cloud is totally doable. For example, I have created a group where I defined incident priorities, and if my team grows from five members to nine, I can easily onboard these new users to PagerDuty Operations Cloud and configure the alerting system to scale up or down based on requirements. The scalability is quite easy. PagerDuty Operations Cloud also offers many integrations, allowing us to scale to other cloud providers if necessary.

Customer service from PagerDuty is great. Sometimes we need help with setups, which are usually minor, but whenever we need support, we receive it promptly. I would say their support is quite good.

Before choosing PagerDuty Operations Cloud, we evaluated other solutions including Grafana, which is for monitoring cloud infrastructure. While we used Grafana for automated monitoring, it lacks the incident management and webhook features that PagerDuty Operations Cloud provides. Therefore, we can manage tasks effectively with PagerDuty Operations Cloud. We also used Nagios, which is another application monitoring tool that only allows monitoring application logs and lacks a solid alerting system, unlike PagerDuty Operations Cloud.

The initial setup of PagerDuty Operations Cloud was very straightforward. It was not complex at all. The documentation provided by PagerDuty is very handy and easy to understand, making the process comfortable and non-confusing.

We did not use an integrator, reseller, or consultant for the deployment. Since we were able to set it up ourselves, we never felt the need for any consultants or assistance from PagerDuty while setting up our environment or workspace.

I have seen a return on investment with PagerDuty Operations Cloud, particularly in incident management. Using this mechanism reduces the number of incidents I need to raise manually, decreasing the effort required. For example, I could say that in a month, we need to raise 150 incidents manually, but with PagerDuty Operations Cloud, I can cut that down to 100 incidents. This results in a reduction of about 40 or 50 incidents.

The setup cost and pricing for PagerDuty Operations Cloud are very cost-effective, but I have a suggestion: if PagerDuty could provide a trial version for individual users, rather than just corporate users, it would help others learn more about PagerDuty Operations Cloud. They could conduct proofs of concept, do hands-on testing, and recommend PagerDuty Operations Cloud in their respective companies or projects.

We did evaluate other tools and even assessed the trial version of those tools by checking all functionalities and use cases. Given that our use cases were larger, we ultimately chose to proceed with PagerDuty Operations Cloud.

We have started using PagerDuty's autonomous AI agents, but we have not leveraged it in detail yet. We have started using it, and hopefully very soon we will implement the AI agent to create solutions in our architectures, which will definitely help us a lot.

For decision-making, when we leverage the AI agent, we need to deploy it in our workspace and feed data to the agent in more use cases, including data in a spreadsheet or JSON or XML format. Cases and scenarios will be added so that the agent will analyze all the data we feed. In the future, if any such scenarios occur in our workspace or infrastructure, PagerDuty Operations Cloud agent will react and make decisions based on the previous trained data.

The influence of PagerDuty's embedded AI on revenue protection is significant. PagerDuty Operations Cloud helps us resolve incidents much faster, which means we consistently meet our SLAs, thereby avoiding penalties for service outages. This helps us save revenue by ensuring that clients or stakeholders do not impose penalties due to outages.

PagerDuty Operations Cloud's AI functionality helps improve my team's ability to focus on core tasks rather than routine issues, particularly with cloud service monitoring and incident response time. These aspects significantly increase our productivity. The solution's alert reduction feature has a significant impact on preventing costly incidents in our company. Creating multiple incidents manually takes a lot of time, but PagerDuty Operations Cloud does that in seconds. This reduction in incident creation time greatly influences our project delivery. Overall, I would rate this product a perfect ten.

The major part of PagerDuty Operations Cloud is for communication and pinging people and engaging them and pulling them into the call.

The most valuable thing I appreciate about PagerDuty Operations Cloud is the escalation process, where it automatically escalates incidents. It features a level one, level two, level three escalation process. When I engage or page someone at level one and start working on priority one or priority zero calls, and I am busy with those tasks, it automatically escalates to the next person in the chain of command, the second higher authority. There are many automation features in PagerDuty Operations Cloud.

If I complete one form, it automatically communicates with people and automatically scribes the incident in my ServiceNow incident. It automatically performs many tasks simultaneously, including sending Outlook emails. These automations are very important and well-known features in PagerDuty Operations Cloud, and they are the main reasons I value this product.

Infrastructure autonomous agents are installed in important servers and important devices in the infrastructure, and these are required components.

I do not have anything that I dislike about PagerDuty Operations Cloud. Sometimes it hangs and occasionally I am unable to open PagerDuty Operations Cloud, which occurs due to an outage or similar issues. Other than that, I do not have any other issues with PagerDuty Operations Cloud.

PagerDuty Operations Cloud developer team is working on enhancements. From my understanding, it is learning quickly and helping me when I require suggestions. PagerDuty Operations Cloud AI provides a combined benefit for my work.

I have been using PagerDuty Operations Cloud for six years.

PagerDuty Operations Cloud automatically learns based on the infrastructure. If I am in a commodity scenario, it learns in that specific way for that company. If I am in e-commerce, it learns in a different way for that industry. If I am in a hospital infrastructure scenario, it learns hospital-specific things and performs accordingly. This is an additional level of comfort for a PagerDuty Operations Cloud user, giving me extra convenience and suggesting many things immediately during priority calls.

For the stability of PagerDuty Operations Cloud, I rate it at 9.8.

Scalability for PagerDuty Operations Cloud is excellent, and I rate it at 9.9. I can scale it as and when required, however much I need. Because we do not place much load on PagerDuty Operations Cloud, I can scale as much as needed.

I have created tickets with PagerDuty Operations Cloud support. In those scenarios, I received good responses from PagerDuty Operations Cloud, and they provide informative assistance when required. I update that information into my ServiceNow ticket. I have received good technical support from PagerDuty Operations Cloud, and I do not have any negative comments regarding their support quality.

Initial deployment of PagerDuty Operations Cloud is easy and not difficult. It guides me through next steps and what to do and what not to do and where it should install and where it should not. It gathers the necessary information during the setup process.

I used Slack as an alternative to PagerDuty Operations Cloud. I have used Slack, Microsoft Teams, Outlook, and sometimes Zoom instead of paging PagerDuty Operations Cloud. I call people directly using Zoom in those situations. These are the alternative communication tools I have used instead of PagerDuty Operations Cloud when I face problems opening it, as sometimes it does not open and some links do not function properly.

Maintenance is not a concern because I am installing PagerDuty Operations Cloud into the supportive infrastructure and then connecting that to the production infrastructure, so it does not require any maintenance. I rate this product a 9 overall.

PagerDuty Operations Cloud is used for production incident management to automate incidents when alerts come from our tools. When we have a critical issue and receive that alert and notification, we configure it accordingly. On-call scheduling, escalation policies, and tracking MTTR improvement are areas where we interact and interrogate with the tools. This approach reduces downtime, enables faster incident response, provides clear accountability, and improves reliability.

We support different clients including JPMorgan, Wells Fargo, PL, LPL, and Bank of America, though we are not a customer, partner, or reseller. More than 300 clients use the solution. In my company, we have 21 specialists working with PagerDuty Operations Cloud.

The best features of PagerDuty Operations Cloud are intelligent alerting, the code fixture, on-call scheduling, escalation capabilities, automation, runbooks, and integration. PagerDuty Operations Cloud has improved downtime mostly by 30 to 50%.

We are not using the autonomous AI agent in PagerDuty Operations Cloud, and we have not integrated with AI Ops, which uses machine learning to group similar alerts automatically and suggest root cause analysis from past incidents. However, we are planning to implement this functionality.

Improvement in PagerDuty Operations Cloud should focus on areas where we need to reduce alert noise by filtering unnecessary alerts. PagerDuty should send actionable alerts, and grouping and suppression should be managed from PagerDuty's side.

Alert noise and grouping do not work together seamlessly in PagerDuty Operations Cloud, but they should be consolidated. Alerts should be directed to the right person with real-time notification to ensure no critical issue is missed. Currently, when we receive alerts through call, SMS, or email, some users do not receive them, and the end client providing support to their clients may miss something important. This is the most critical feature that PagerDuty should improve.

Defining on-call scheduling and escalation by groups is also necessary. The duty roster should clearly indicate which alerts go to L1, L2, or L3 level support. Automatic escalation is not happening if nobody has responded to an alert, which I have observed.

While I did not deploy PagerDuty Operations Cloud, I performed the migration and reconfigured PagerDuty from scratch, then migrated to ServiceNow where I handled redeployment. I have observed that MTTR is very slow, and wrong escalation sometimes routes alerts to the wrong team rather than the proper team. On-call schedules should map the different teams we have, such as the application team, infrastructure team, or database team, who will take ownership. They need to align to the same team only for that incident. Proper service configuration for each application is required.

I have almost three or more years of experience with PagerDuty Operations Cloud.

The stability of PagerDuty Operations Cloud is good. I have worked with Opsgenie, and PagerDuty is better than Opsgenie and ServiceNow as well. I can give a rating of a minimum of eight.

The scalability of PagerDuty Operations Cloud is also good.

I can give PagerDuty Operations Cloud a rating of a minimum of 7.5 to eight for technical support.

Previously, we were using PagerDuty Operations Cloud on-premises, and now we are planning to implement a hybrid approach with both cloud and on-premises solutions. I have worked with Opsgenie, and PagerDuty is better than Opsgenie and ServiceNow as well.

Alert reduction in PagerDuty Operations Cloud does not help prevent costly incidents.

PagerDuty Operations Cloud is the best tool available. I have never worked with other solutions, but whenever I have had the chance to work with PagerDuty Operations Cloud, there is nothing on my mind to say negatively. I can confidently say it is the best tool for all aspects, not just incident management or escalation, but for all analytical functions as well. This is the best tool in the market.

Regarding maintenance, I have not observed that part of PagerDuty Operations Cloud directly. The on-site USA team is located in Jacksonville, and some team members might be handling maintenance from their end, but I am not certain about their specific involvement.

I would recommend PagerDuty Operations Cloud to other users because it provides the best tool for instant alerting, ensuring the right person responds, automatic escalation, and reducing downtime and alert noise. It integrates with different monitoring tools including DataDog, New Relic, Prometheus, and Grafana. The main strengths are real-time alerting, proper escalation, and faster incident response, which help reduce downtime and improve MTTR.

I have experience with MTTR in PagerDuty Operations Cloud. Faster detection and alerting reduce MTTR significantly. When PagerDuty is integrated with other monitoring systems, alerts are real-time and actionable.

The end-to-end flow of PagerDuty Operations Cloud, including on-call schedules, escalation policies, and services, is excellent. It is highly reliable, offers easy escalation setup, and has strong interaction capabilities that reduce manual effort. However, the cost might be high.