PagerDuty Operations Cloud

I have integrated other monitoring tools like LogicMonitor, and alerts come to PagerDuty Operations Cloud where we acknowledge them and work upon the issues. I have created multiple services that send alerts to out-of-hours groups for the on-call engineers. We detect issues faster and this helps in root cause analysis. Alert noise reduction is a major use case for us, as it groups duplicate alerts, which is very useful. The mobile application is also excellent.

I appreciate the event de-duplication feature in PagerDuty Operations Cloud because my company has many alerts for similar devices or servers, and it groups them together. This helps us see when a particular server's CPU and memory are both spiking, which aids significantly in root cause analysis.

Another feature I value is push notifications. We receive calls, SMS messages, and emails for the same alert, so we do not miss any notifications.

My organization has reduced noise by approximately 20% because of the de-duplication feature in PagerDuty Operations Cloud and the report feature. The report feature sends us a weekly report showing how many similar alerts occurred that week, and we work on reducing those alerts. By following this policy for three months, we reduced noise by 20%, which is a huge achievement for us.

PagerDuty Operations Cloud has improved our response time and mean time to resolution in my organization. We have integrated many monitoring tools through PagerDuty Operations Cloud, and the integration feature is excellent. It integrates very well with other monitoring tools via API and through email. I recommend other organizations use this integration feature.

The platform generates weekly reports showing how many alerts we received and the response time for each service and alert. I now pull daily reports via API. Since my company operates from 7:30 AM to 4:30 PM, with on-calls after hours, I need to know how many alerts occur outside business hours. Using a report scheduled through PagerDuty Operations Cloud API, the system sends me the alerts. I then analyze how many alerts came that night and work with the application team to reduce noise and resolve incidents. I value the report feature completely.

As a technical engineer, I observe that noise is being reduced and platform stability is increasing. My company is product-based with many products, and they are becoming more stable because we receive alert notifications faster. PagerDuty Operations Cloud is helping my organization tremendously.

Overall, I have positive feedback about PagerDuty Operations Cloud, but as an enhancement, I would suggest the reporting feature could be improved. I generate reports based on the service, but it has a limitation where it cannot send all alerts. The limitation is that it can only send 1,000 incidents using the API. If that capacity could be enhanced to send 2,000 alerts in one report, that would be beneficial.

Currently, we have not applied any automation through PagerDuty Operations Cloud. However, it does help with automation in that when we receive more alerts for a similar issue or for only one server, we know that server's health is not good. We then find the root cause and apply automation directly on the server, not through PagerDuty Operations Cloud. The feature would be useful, but my company does not have the automation feature enabled. It shows as a request trial, so I think we need to try that.

I have been using PagerDuty Operations Cloud for one year and two months.

We do not experience downtime. However, I have observed one issue: we integrated with LogicMonitor, which is a monitoring tool, and alerts come from there to PagerDuty Operations Cloud. When alerts are resolved in LogicMonitor, they should also resolve in PagerDuty Operations Cloud, but sometimes they do not resolve. This should happen, and I think this is an API issue that needs to be addressed. I am not certain whether other customers of PagerDuty Operations Cloud are experiencing the same issue.

I have no complaints about customer service because PagerDuty Operations Cloud is an incident management tool and it performs that function very well.

We preferred PagerDuty Operations Cloud over ServiceNow, which we used previously for the same purpose. When an alert came, we would call engineers, and ServiceNow has that feature as well. However, PagerDuty Operations Cloud is much more advanced in terms of notifying users and reducing the time to respond. We are satisfied with it and are not planning to move to other tools currently.

I joined this organization one year and two months ago, and the initial setup was already done. I only enhanced that setup and created new integrations and new event orchestrations. I cannot comment on the initial setup itself, but I am confident it would have been easy.

Overall, I can say PagerDuty Operations Cloud is a critical part of our incident management process. Reliability and alert delivery are strong compared to other tools such as ServiceNow. The area where we see the biggest opportunity is AI-driven event correlation, richer alert context, and improved analytics. I do not think any other tool is near that level. We tried ServiceNow because we have it as well, but it does not match PagerDuty Operations Cloud. The overall feedback is positive.

I would recommend that organizations with high alert noise, whether similar to my company or larger companies, should try PagerDuty Operations Cloud. They should use its event and alert de-duplication features and integration with other tools, which are excellent. The calling notification feature is also very good. Overall, it is a strong solution. I rate PagerDuty Operations Cloud as nine out of ten because I do not see any gaps in what I use on a daily basis.

I started as a user working in an operations team where we handled the AWS infrastructure deployed for a particular company. Whenever any issue occurred, we received pages using PagerDuty Operations Cloud. I gradually learned about PagerDuty Operations Cloud and started integrating it into different workflows. I began integrating it to make Slack bots, and right now I am using PagerDuty Operations Cloud API endpoints to make AI agents as well. I can think of myself as an integration engineer who works extensively with integrating different services, one of which is PagerDuty Operations Cloud.

I also use xMatters alongside PagerDuty Operations Cloud. Speaking from an integrations engineer's perspective, I have not integrated xMatters heavily, but I have been a user of xMatters more lately. The major difference I observed was the workflow management. xMatters has better workflow management than PagerDuty Operations Cloud. Let me explain what I mean by workflow management. If you have a company with ten teams working on a particular product, every member of those teams may or may not receive a page. Every member should have an orchestrator where they can define custom rules such as a service should be paged directly to X team, or if a page comes from ABC issue, it should directly go to Y team without having me to manually put the team name or team details regarding where to page. This capability is lacking in PagerDuty Operations Cloud while in xMatters, it is flawlessly integrated where you can add custom rules and custom rule sets. In PagerDuty Operations Cloud, we have to create separate pages for that functionality. However, when I talk about integration, the xMatters API toolkit is confusing and disorganized. The tree structure is not present in xMatters, but I appreciate that about PagerDuty Operations Cloud. Integration-wise, PagerDuty Operations Cloud is flawless. I love PagerDuty Operations Cloud from an integration perspective, but it makes my life difficult if someone wants me to integrate xMatters.

I appreciate the overall API toolkit very much. It is one of the simplest API toolkits I have seen that lets me do literally anything via API calls, which I can essentially do via the browser. I do not even need to log into my browser to do anything if I have a CLI or any tools integrated with it.

I have built an AI agent which detects if any page comes into PagerDuty Operations Cloud. PagerDuty Operations Cloud has webhooks, which is great. If anything comes into PagerDuty Operations Cloud, I basically poll every detail of that page, perform some incident resolution, and do something on the infrastructure according to whatever page I receive. I add comments in the pages via PagerDuty Operations Cloud API and then do the whole incident life cycle using all the APIs. There is also a very good Python library called PDPYRAS, which I use extensively, which uses PagerDuty Operations Cloud APIs to build SDK. I have developed my own CLI toolkit using PagerDuty Operations Cloud APIs itself, which is on my GitHub.

The UI is good and looks good, but sometimes when pages come very frequently, such as receiving ten to fifteen pages per five to ten seconds, it works flawlessly. However, when you tie your PagerDuty Operations Cloud instance to very large-scale infrastructure where you have millions of instances and get at least five to ten pages per second, the UI starts to hang. The API works flawlessly even then, but if someone does not know how to use all the integrations that PagerDuty Operations Cloud provides, they have only one choice but to log into the UI and check for the pages. Then they will have to face the lag in the UI.

Integration is very easy. I have completed entire integrations, deployments, and testing within six hours. It is just so easy.

One person can do everything end to end on their own. I have done it multiple times, and I have seen other people doing it multiple times as well. Everything is very seamless. I should also appreciate the official documentation that you have. Usually official documentation is not that good, but yours feels like someone has taken time to write those documents. The commands which you have written for back-end integration are straightforward. I literally have to just copy and paste after setting environment variables.

I believe you really need to work on your UI. The UI is good and looks good, but when pages come very frequently, such as receiving ten to fifteen pages per five to ten seconds, it works flawlessly. However, when you tie your PagerDuty Operations Cloud instance to very large-scale infrastructure where you have millions of instances and get at least five to ten pages per second, the UI starts to hang. The API works flawlessly even then, but if someone does not know how to use all the integrations that PagerDuty Operations Cloud provides, they have only one choice but to log into the UI and check for the pages. Then they will have to face the lag in the UI. This is the area where I feel improvements are needed.

PagerDuty Operations Cloud does require a fair amount of maintenance. Many incidents go into triage and need to be regularly cleaned up. If an incident comes for which we have not set rules to auto acknowledge and close, it basically stays in the triage and we have to manually clean it up. I think an auto-detection mechanism can be implemented out of the box. Because it is not there currently, we have to develop modules around that. An alternative would be webhooks that you can come up with which we can utilize to implement this out of the box.

The only lag I have experienced is the UI lag that I have already described.

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

PagerDuty Operations Cloud is scalable. I have not faced any issues with scalability. It is pretty good when it comes to scalability.

I have contacted support multiple times.

There are ticket levels which we can create. I have not called the support team on the phone, but I have mailed and raised tickets with them. There have been instances where I had to integrate a very old server, AIX server framework to PagerDuty Operations Cloud for which the modules were not present in PagerDuty Operations Cloud. I am not blaming them for this; I am blaming the company who are using AIX servers. However, they did not have the module, so I had to raise a ticket. It was around Severity 3. The response was not super fast, which is expected. However, as soon as it escalated to Severity 2, I received an immediate email from PagerDuty Operations Cloud team. I think the support is fine. I have faced just one time some inconvenience. I do not know what was the reason, but there was one time where I did not receive any response for two days. Thank goodness it was not a Severity 1 incident for us, but two days was unacceptable at that point. Hence we started looking at other products including xMatters. There has been just one instance, but the company which I work with, even one instance sometimes causes a lot of friction. People start looking at other options. However, there has been just once.

Integration is very easy. I have completed entire integrations, deployments, and testing within six hours. It is just so easy.

One person can do everything end to end on their own. I have done it multiple times, and I have seen other people doing it multiple times as well. Everything is very seamless. I should also appreciate the official documentation that you have. Usually official documentation is not that good, but yours feels like someone has taken time to write those documents. The commands which you have written for back-end integration are straightforward. I literally have to just copy and paste after setting environment variables. Everything is very easy.

I use xMatters alongside PagerDuty Operations Cloud. Speaking from an integrations engineer's perspective, I have not integrated xMatters heavily, but I have been a user of xMatters more lately. The major difference I observed was the workflow management. The workflow management in xMatters is better than PagerDuty Operations Cloud. Let me explain what I mean by workflow management. If you have a company with ten teams working on a particular product, every member of those teams may or may not receive a page. Every member should have an orchestrator where they can define custom rules such as a service should be paged directly to X team, or if a page comes from ABC issue, it should directly go to Y team without having me to manually put the team name or team details regarding where to page. This capability is lacking in PagerDuty Operations Cloud while in xMatters, it is flawlessly integrated where you can add custom rules and custom rule sets. In PagerDuty Operations Cloud, we have to create separate pages for that functionality. However, when I talk about integration, the xMatters API toolkit is confusing and disorganized. The tree structure is not present in xMatters, but I appreciate that about PagerDuty Operations Cloud. Integration-wise, PagerDuty Operations Cloud is flawless. I love PagerDuty Operations Cloud from an integration perspective, but it makes my life difficult if someone wants me to integrate xMatters.

Regarding pricing, I do not remember the current prices, but I used the first tier about two years back for one of the startup failures which I was working on. That startup did not work out, but I integrated PagerDuty Operations Cloud with a lot of things there.

For the enterprise and for large-scale enterprises, the pricing is good. I will not even say it is fine; it is good for large-scale enterprises. However, for small-scale startups and small businesses, because they already are in a very nascent stage, the pricing is a little on the higher side. There is no custom module which I can just add to my cart which gets me custom pricing. It is just one bucket. For small-scale operations, I think the pricing is a bit pricey.

I do not use PagerDuty Operations Cloud's AI assistant, but I integrate the back-end to create agents. I do not use their default ones. I have never used it, and I do not know how good or bad that is. I am integrating PagerDuty Operations Cloud modules, APIs, and SDKs to develop AI agents, not using anything which comes out of the box.

My overall review rating for PagerDuty Operations Cloud is eight out of ten.

I primarily use PagerDuty Operations Cloud for alert management and incident call rotations. In my earlier firm, we managed rotation shifts across three time zones: EMEA, APAC, and New York time. All rotation and shift management was handled through PagerDuty Operations Cloud schedules. Application monitoring was also updated through PagerDuty Operations Cloud. According to the schedule, we updated people's contact information so that in case of any issues, the contact would be transferred to the respective shift member. We also managed escalations with five layers of escalation. If a first team member missed an alert, it would go to the second team member after 10 minutes, then to the next person after five minutes, continuing according to the priority of the service.

The most valuable features I found were the integration capabilities and notification system. We used the open-source tool Alertmanager, which triggers health metrics from Prometheus and Splunk. PagerDuty Operations Cloud allowed us to integrate alerting seamlessly and notify users effectively, which helped the business significantly. Early detection of issues leads to better service provision. PagerDuty Operations Cloud provides multiple notification channels including SMS, phone calls, and email, which I found to be the best part of the platform.

Regarding the autonomous AI agents, I have not explored them because the AI trend started recently and I have been out of touch for the last seven or eight months. However, I have read about how AI integrates with the scheduling part. Previously, we had to manually update schedules every week, but with AI integration, we can write a prompt and build MCPs. Some firms I read about integrated an MCP they built in-house, and with the MCP, they can provide an Excel sheet or image, and PagerDuty Operations Cloud API can update everything without needing to manually access the platform.

We implemented automation through PagerDuty Operations Cloud for incident response. Previously, we had to manually update service level details, SLAs, notification mechanisms, and API keys. Now we can submit an Excel sheet or CSV file and make an API call using Python, which updates everything automatically. PagerDuty Operations Cloud also helps with analytics by showing how many alerts were triggered, how many were resolved, and which person handled which alert. This visualization helps us demonstrate to clients that we managed a certain number of alerts and reduced the alert count.

PagerDuty Operations Cloud has been excellent so far. Over the last six months, generative AI could help further. Some organizations are using their own MSP engines, but if PagerDuty Operations Cloud provides in-house MCP tools integrated with GenAI, it would be better for end-users. Integrating with in-house tools and something already provided by PagerDuty Operations Cloud would make a difference. I am not certain if this has been explored in the last six months, but this is an area PagerDuty Operations Cloud could improve.

I used PagerDuty Operations Cloud for approximately 3.5 to four years.

PagerDuty Operations Cloud provided notifications early when issues occurred. We used PagerDuty Operations Cloud's status page as our first source of truth to check for existing or ongoing issues. If no issues were listed there, we reached out to a dedicated account manager who would connect us with the concerned team. We rarely encountered any operational issues with PagerDuty Operations Cloud because it was always working. We experienced only one or two latency issues, which were due to underlying cloud infrastructure issues rather than PagerDuty Operations Cloud itself.

PagerDuty Operations Cloud maintained good scalability levels. We started with a beta phase with approximately 50 to 60 members, then moved to a development stage where we increased to 150 people. The platform remained stable as we expanded. We ran some instances on-premises, which required high security, and others on cloud premises for client-facing deployments. We experienced no issues with scalability on either on-premises or cloud deployments, and integration was seamless in both cases.

When making on-premises installations, we connected with PagerDuty Operations Cloud's technical support. They guided us on setup and what to take care of during installation. We had two or three calls with them, and they were very helpful throughout the process.

Before PagerDuty Operations Cloud, we used Alertmanager, which triggered only email notifications and not calls or SMS. PagerDuty Operations Cloud introduced the calling mechanism and SMS capability, which was innovative compared to what we had seen with open-source tools.

The initial setup process involved starting with PagerDuty Operations Cloud's cloud offering. We purchased a plan and set up our account. During actual deployment, we purchased a license with our own DNS, meaning instead of using pagerduty.com, we mapped our own subdomain to our environment. We then created licenses for individual users, starting with approximately 150 members from our technical support team and L1 engineers. We gradually increased our user count rather than immediately granting licenses to thousands of people because they would have received spam calls. We started with 50 to 60 members for a trial to understand how the system should behave and how we could optimize it.

We handled the initial setup and installation of PagerDuty Operations Cloud ourselves, although we received support. When we signed up, the PagerDuty Operations Cloud team called to offer assistance. They set up a demo for our team, but we proceeded with the installation ourselves since we had prior knowledge before starting.

We evaluated other options before choosing PagerDuty Operations Cloud. We attempted to build our own solution using an existing open-source tool, but the latency issues made it not time and cost-optimized. Since a stable product like PagerDuty Operations Cloud already existed, investing two to three years in building our own solution did not make sense. We also explored building a Python solution using Alertmanager before deciding on PagerDuty Operations Cloud.

I have not explored the generative AI capabilities of PagerDuty Operations Cloud. PagerDuty Operations Cloud delivers very high performance when notifying users, especially in high-frequency trading environments where even a second of delay can result in billion or trillion dollar transaction losses. The notification service and seamless integration across different team layers provide significant value. Although open-source tools are available, they are not as effective as PagerDuty Operations Cloud.

Regarding alert fatigue and incident costs, when onboarding new clients in my previous project, I demonstrated our capabilities using incident management charts to showcase our skills. We showed clients how many alerts triggered daily, weekly, or monthly before PagerDuty Operations Cloud, and how we reduced them to monthly or bi-weekly intervals based on specific conditions. This data helped us acquire deals.

PagerDuty Operations Cloud improved my team's ability to focus on core tasks rather than routine issues. Initially, my team was exploring multiple notification and monitoring options and building their own tools. With PagerDuty Operations Cloud as an organization-level mandate, instead of managing different tools across ten teams, we now use one standard tool. This has allowed the team to focus on other important tasks since this major challenge has been resolved.

Regarding preventing costly incidents, I would emphasize business trust more than direct cost savings. We earned significant client trust by detecting issues early and informing clients promptly, allowing them to manage their side of any issues. On multiple occasions, we caught issues before business hours and clients were appreciative of our proactive approach.

I am not aware of the specific pricing and licensing details of PagerDuty Operations Cloud as that is managed by our management. From what I have heard, the business plan is not very expensive. I have not explored individual pricing since our organization was large with dedicated departments handling such decisions. My review rating for PagerDuty Operations Cloud is eight out of ten.

My main use case for PagerDuty Operations Cloud involves working in the AIOps team, which is an operations team. We have a monitoring tool called Checkmk, and we have integrated it with PagerDuty for incident management. We monitor many servers across different teams, including the Linux team, network team, Windows teams, and database team. All of these servers are monitored in Checkmk, tracking live CPU, memory, and file systems. Upon reaching certain thresholds, Checkmk generates events, which we integrate into PagerDuty Operations Cloud console. There, we set conditions so that if an event is critical or a warning, it converts into an incident. We then route the incidents to respective teams, who handle the details.

A specific example of an incident where PagerDuty Operations Cloud played a key role involves automations we created within PagerDuty. Rundeck is a job workflow tool where we can implement scripts or schedule jobs. If a server meets its threshold, it triggers PagerDuty Operations Cloud. We create scripts in Rundeck to handle issues, such as clearing a full file system. We utilize a feature called Automation Actions in PagerDuty Operations Cloud, and whenever an incident comes that matches specific conditions, that job will automatically run in Rundeck. This incident management cycle is effectively managed in PagerDuty Operations Cloud, allowing jobs to run and resolve incidents automatically, ensuring the server is healthy again.

The best features PagerDuty Operations Cloud offers include Incident Workflows, which we use frequently to ease our team's work. These workflows trigger jobs in Rundeck based on certain conditions when incidents occur. We can create flows in Incident Workflow features and utilize Automation Actions, which allow us to run individual jobs in Rundeck. Additionally, Event Orchestration enables us to integrate various tools using integration keys with multiple applications. These features significantly simplify our daily operations within the team.

Integrations with other tools have been beneficial for our team as we receive requests from different teams to integrate their tools with PagerDuty Operations Cloud, enabling them to manage incidents. We have integrated AWS CloudWatch and Azure for monitoring, as well as CyberArk and Guardicore. If teams have specific requirements for integrating their tools, they approach us to create the necessary flows.

PagerDuty Operations Cloud has positively impacted our organization significantly. The response time has improved, and the team responds more quickly now. The PagerDuty Operations Cloud mobile application allows team members to acknowledge incidents via their mobile devices, where they can also receive calls when incidents trigger. The response time has become very quick.

I do not have precise numbers regarding the improvement in response time since using PagerDuty Operations Cloud, but I can share a story about a major incident with Checkmk. After we upgraded our Checkmk console, everything crashed, causing random events to be sent to PagerDuty Operations Cloud. We fixed the event flow from Checkmk using PagerDuty Operations Cloud's features. Furthermore, we have automated the restart of systems through PagerDuty Operations Cloud. If any server requires a restart, we trigger that job with just one click using Ansible, completing the task efficiently.

I do not see immediate improvements for PagerDuty Operations Cloud because there are numerous features we have yet to explore. As a product, it is continually upgrading its features, so we are focusing on how we can incorporate those into our use case.

Concerning PagerDuty Operations Cloud's AI capabilities, I am not certain as we currently do not use advanced AI-related features since our package offers limited access in that area. However, regarding governance and security, it appears very secure.

I have been using PagerDuty Operations Cloud for three months.

PagerDuty Operations Cloud appears to be quite stable. I have not encountered any downtime or reliability issues, and it has consistently operated successfully.

Regarding scalability, I think there is demand for PagerDuty Operations Cloud as we have been striving to mitigate manual tasks within our organization. We conduct demonstrations to illustrate how we can reduce manual work through our automations.

The customer support for PagerDuty Operations Cloud is excellent. They have been very responsive. We have standing weekly calls to discuss any doubts, and there is a dedicated team, including an engineer and a PagerDuty Relations Manager, assigned to support us. They have been excellent in following up on the features we need to use.

I believe a return on investment is occurring because we are promoting PagerDuty Operations Cloud within our organization, aiming to involve more people and teams in using it. We continuously explore new features to facilitate ease of use among many people.

There are many new features introduced in PagerDuty Operations Cloud. AI has been included, and specific features including Incident Workflows and Event Orchestrations have been implemented. One recent implementation in Incident Workflows is SLA tagging for incidents. We created a workflow to notify managers if an SLA has been breached beyond a certain time. This planning has helped us manage incidents more effectively.

I have not utilized PagerDuty Operations Cloud's AI agents to address routine issues. However, for team productivity, we leverage escalation policies in PagerDuty Operations Cloud, assigning individual service directories to teams. Consequently, team members receive calls and messages based on their escalation hierarchy.

We have not utilized PagerDuty Operations Cloud's generative AI for decision-making, but the event analytics and operations console provide valuable insights. I can observe real-time data on incidents and alerts, which helps us address the inflow of events from integration keys. This information allows us to refine our planning and reduce event volumes from Checkmk.

I would highly recommend PagerDuty Operations Cloud as a reliable product. I do not have any negative experiences using PagerDuty Operations Cloud, and I believe it adds significant value to our environment if used properly.

When it comes to the accuracy and reliability of PagerDuty Operations Cloud's output, I find it quite reliable. It presents us with extensive data and analytics. The event flow we get from Checkmk provides much useful information, and we rely heavily on PagerDuty Operations Cloud for this analytics format.

I do not believe we have a business relationship with PagerDuty Operations Cloud beyond being a customer. We purchase memberships based on their plans and use them within our organization. I think we are not partners; rather, we simply resell their services internally.

My overall rating for PagerDuty Operations Cloud is seven out of ten.