We usually use BMC AMI Ops to automate tasks as described, and there are a couple of batch files running in the tool itself which we monitor for the health of the servers that are being assigned to the agents in BMC AMI Ops. We can take one example of a job that is being done on BMC AMI Ops, which is a file transfer job. Before file transfer happens, there is one job called file watcher that watches the file at a specific location on the server. Once the file is received at the path, it gives commands to the next job, which is a file FTP job to transfer that file. Once successful transfer is done, it removes the source file and marks the job as completed. The file watcher and file transfer combination is really helpful to accomplish our tasks. As an SME, we do not know when we are going to receive a file from our offshore clients, so we need to have it monitored to a certain window or time accordingly to process the further steps. There is a job feature called Azure jobs that we were not aware of earlier. It supports cloud pipelines jobs directly integrated with BMC AMI Ops. We are under exploration of that and have experimented with the jobs to run Azure pipelines, which is almost on the verge of successful completion. It is a new feature, and there are a couple of areas we have not explored yet, but as of now, Azure pipeline is helpful. There are three different sections in BMC AMI Ops: define mode, monitoring mode, and others. In the monitoring section, there are varieties of things to be monitored on the dashboard itself. You can customize it and get all the information on one panel, which is usually helpful because you can see everything at one glance, reducing the time and allowing you to take action accordingly. If you are going to check all of the monitoring sections individually, it usually takes around five minutes to check one section, so it would take around fifteen minutes total. However, using it on one dashboard and checking all of the monitoring sections at once lets us save up to half an hour, compared to checking ten monitoring tasks manually. We usually use automation in day-to-day executions. For example, we have tasks where files are delivered by offshore teams to us, and we can read the files, check for errors, and execute SQL queries to check for the desired output, confirming whether it is successful. If it is not, it presents the error indicating that it is not the desired output we expect. Automation is used daily and helps streamline our processes significantly. Cost is monitored by the number of job executions, which helps us understand what is really required. Previously, using automation tools, we ran all jobs across all environments, such as dev, test, and production. However, after learning from IR management that we pay for every job execution, we collaborated with SMEs to rectify unnecessary executions and streamline our operations according to necessity.
My main use case for BMC AMI Ops is to monitor the health and performance of our maintenance to keep the system running optimally. It helps us detect issues, monitor system resources, and ensure critical business applications run smoothly. I can provide a specific example of how I have used BMC AMI Ops in my day-to-day work. Recently, we noticed CPU utilization was much higher than normal during peak business hours. Because of BMC AMI Ops, we received an immediate alert and identified that our workload was utilizing maximum CPU. We resolved the issue before any users were impacted. To monitor everything effectively, I need to keep an eye on my CPU and any utilization patterns.
I use BMC AMI Ops to maintain its usability for the main team so that the main team can use the product to install it for various clients. BMC AMI Ops is a product that is given to us by a vendor, and we run a couple of jobs called JCL, which is a language in mainframes. Mainframes are a really old kind of technology. In mainframes, we use all these vendor products to help our clients manage their own system.
I have used BMC AMI Ops, which is a mainframe operation management tool, to work on the mainframe's application. I have used this for a monitoring solution that provides real-time visibility into the system performance, handles workload activity, resource utilization, and operational health. It helps the operations team proactively detect issues, improve availability, and optimize performance across operating systems. In my project, I have used the OpenTelemetry integration for streaming operational data, mainly for observability purposes within our mainframe environment. This integration allows us to incorporate operational metrics with our broader monitoring ecosystem, enhancing cross-team collaboration and simplifying troubleshooting efforts. I used OpenTelemetry for streamlining operational data and incorporating mainframe metrics into our observability platforms, yielding significant business impact.
BMC AMI Ops is an advanced suite designed to streamline and optimize mainframe management, providing users with efficient monitoring and automation capabilities.
BMC AMI Ops offers a comprehensive mainframe management experience, letting users proactively monitor and manage their mainframe environments. Its robust features ensure better performance, leading to a seamless, uninterrupted IT operation. This solution is equipped to tackle real-time challenges, fueling informed decision-making...
We usually use BMC AMI Ops to automate tasks as described, and there are a couple of batch files running in the tool itself which we monitor for the health of the servers that are being assigned to the agents in BMC AMI Ops. We can take one example of a job that is being done on BMC AMI Ops, which is a file transfer job. Before file transfer happens, there is one job called file watcher that watches the file at a specific location on the server. Once the file is received at the path, it gives commands to the next job, which is a file FTP job to transfer that file. Once successful transfer is done, it removes the source file and marks the job as completed. The file watcher and file transfer combination is really helpful to accomplish our tasks. As an SME, we do not know when we are going to receive a file from our offshore clients, so we need to have it monitored to a certain window or time accordingly to process the further steps. There is a job feature called Azure jobs that we were not aware of earlier. It supports cloud pipelines jobs directly integrated with BMC AMI Ops. We are under exploration of that and have experimented with the jobs to run Azure pipelines, which is almost on the verge of successful completion. It is a new feature, and there are a couple of areas we have not explored yet, but as of now, Azure pipeline is helpful. There are three different sections in BMC AMI Ops: define mode, monitoring mode, and others. In the monitoring section, there are varieties of things to be monitored on the dashboard itself. You can customize it and get all the information on one panel, which is usually helpful because you can see everything at one glance, reducing the time and allowing you to take action accordingly. If you are going to check all of the monitoring sections individually, it usually takes around five minutes to check one section, so it would take around fifteen minutes total. However, using it on one dashboard and checking all of the monitoring sections at once lets us save up to half an hour, compared to checking ten monitoring tasks manually. We usually use automation in day-to-day executions. For example, we have tasks where files are delivered by offshore teams to us, and we can read the files, check for errors, and execute SQL queries to check for the desired output, confirming whether it is successful. If it is not, it presents the error indicating that it is not the desired output we expect. Automation is used daily and helps streamline our processes significantly. Cost is monitored by the number of job executions, which helps us understand what is really required. Previously, using automation tools, we ran all jobs across all environments, such as dev, test, and production. However, after learning from IR management that we pay for every job execution, we collaborated with SMEs to rectify unnecessary executions and streamline our operations according to necessity.
My main use case for BMC AMI Ops is to monitor the health and performance of our maintenance to keep the system running optimally. It helps us detect issues, monitor system resources, and ensure critical business applications run smoothly. I can provide a specific example of how I have used BMC AMI Ops in my day-to-day work. Recently, we noticed CPU utilization was much higher than normal during peak business hours. Because of BMC AMI Ops, we received an immediate alert and identified that our workload was utilizing maximum CPU. We resolved the issue before any users were impacted. To monitor everything effectively, I need to keep an eye on my CPU and any utilization patterns.
I use BMC AMI Ops to maintain its usability for the main team so that the main team can use the product to install it for various clients. BMC AMI Ops is a product that is given to us by a vendor, and we run a couple of jobs called JCL, which is a language in mainframes. Mainframes are a really old kind of technology. In mainframes, we use all these vendor products to help our clients manage their own system.
I have used BMC AMI Ops, which is a mainframe operation management tool, to work on the mainframe's application. I have used this for a monitoring solution that provides real-time visibility into the system performance, handles workload activity, resource utilization, and operational health. It helps the operations team proactively detect issues, improve availability, and optimize performance across operating systems. In my project, I have used the OpenTelemetry integration for streaming operational data, mainly for observability purposes within our mainframe environment. This integration allows us to incorporate operational metrics with our broader monitoring ecosystem, enhancing cross-team collaboration and simplifying troubleshooting efforts. I used OpenTelemetry for streamlining operational data and incorporating mainframe metrics into our observability platforms, yielding significant business impact.