When you have been using cubes for business intelligence in a namespace for some time, you may find that there are many cubes in the namespace, only some of which are actively being used. However, it can be difficult to tell which cubes users are or are not querying, and maintaining unused cubes can be costly both in terms of storage and of computation to keep them up to date. This article provides some suggestions and examples for monitoring which cubes are in active use, and for removing cubes that you determine are no longer necessary.
System Alerting and Monitoring (SAM) in InterSystems IRIS data platform helps you efficiently monitor and manage your systems. This video shows some solutions it offers for specific challenges faced by developers and operators:
The current version of SAM creates Prometheus metric endpoints which appear to be handled correctly by the current prometheus scraper, however the metrics do not confirm to the current prometheus standard. The standard states:
I installed a community version of Intersystems IRIS in a Large AWS EC2 instance to do some testing. I installed SAM and when I try to "Add a new cluster" I receive the following: "ERROR #5005: Cannot open file '/config/prometheus/isc_tmp_yml_file.yml'"
Previously, I shared with you all a handy operational analytics dashboard you can build to visualize key message processing metrics, such as number of inbound/outbound messages, average processing times, etc.
Whenever the Windows SNMP Service restarts, the snmpdbg log says the following.
13:08:59 :Attempting initial TCP connection(s) with 1 Cache instances ... 13:08:59 :Get connection with ENSEMBLE on port 1972 13:08:59 :Connection refused on port 1972, check if Cache instance ENSEMBLE is started. 13:08:59 :Cache iscsnmp.dll initialized for 1 configs
Ensemble and all productions are running. I've set up Caché SNMP agent on many other servers in our company and those are working fine. However this one server won't budge.
Does anyone know if I can create an API integration, from Ensemble to Salesforce? What I would like to do is trigger a Salesforce case to be opened when for example a Queue reaches a predefined threshold or an interface connection goes from green to non-green.
As part of our continuous efforts to expand and improve the InterSystems IRIS Data Platform, we’ve set up a brief survey around SQL monitoring. Your feedback will help us in designing and developing the right tools for the job and improve the platform’s overall ease-of-use. Please use the link below to access the survey, which should only take around 5 minutes to complete.
GA releases are now available for the first version (v1.0) of InterSystems System Alerting and Monitoring (InterSystems SAM for short)
InterSystems SAM v1.0 provides a modern monitoring solution for InterSystems IRIS based products. It allows high-level views of clusters and single-node drilled down metrics-visualization together with alerts notifications. This first version provides visualization for more than one hundred InterSystems IRIS kernel metrics, and users can extend the default-supplied Grafana template to their liking.
With this article, I would like to show you how easily and dynamically System Alerting and Monitoring(or SAM for short) can be configured. The use case could be that of a fast and agile CI/CD provisioning pipeline where you want to run your unit-tests but also stress-tests and you would want to quickly be able to see if those tests are successful or how they are stressing the systems and your application (the InterSystems IRIS backend SAM API is extendable for your APM implementation).
In this InterSystems IRIS 2020.1 Tech Talk, we focus on DevOps. We'll talk about InterSystems System Alerting and Monitoring, which offers unified cluster monitoring in a single pane for all your InterSystems IRIS instances. It is built on Prometheus and Grafana, two of the most respected open source offerings available.
Next, we'll dive into the InterSystems Kubernetes Operator, a special controller for Kubernetes that streamlines InterSystems IRIS deployments and management. It's the easiest way to deploy an InterSystems IRIS cluster on-prem or in the Cloud, and we'll show how you can configure mirroring, ECP, sharding and compute nodes, and automate it all.
Finally, we'll discuss how to speed test InterSystems IRIS using the open source Ingestion Speed Test. This tool is available on InterSystems Open Exchange for your own testing and benchmarking.
Preview releases are now available for the first version (v1.0) of InterSystems System Alerting and Monitoring (InterSystems SAM for short).
InterSystems SAM v1.0 provides a modern monitoring solution for InterSystems IRIS-based products. It allows high-level views of clusters and single-node drilled down metrics-visualization together with alerts notifications. This first version provides visualization for more than one hundred InterSystems IRIS kernel metrics, and users can extend the default-supplied Grafana template to their liking.
V1.0 is meant to be a simple and intuitive baseline. Please help us make it great by trying it and sending us feedback!
SAM can display information from InterSystems-based instance starting with version 2019.4
SAM is only available in container format. You will need the SAM Manager container plus a small set of additional open-source components (Prometheus and Grafana) that are added automatically by the composition file.
SAM components and the SAM Manager Community Edition are available from
Note (Sept 2018): There have been big changes since this post first appeared, I suggest using the Docker Container version, the project and details for running as a container are still in the same place published on GitHub so you can download, run - and modify if you need to.
One of the topics that comes up often when managing Ensemble productions is disk space:
The database (the CACHE.DAT file) grows in a rate that was unexpected; or the Journal files build up at a fast pace; or the database grows continuously though the system has a scheduled purge of the Ensemble runtime data.
It would have been better if these kind of phenomena would have been observed and accounted for yet at the development and testing stage rather than on a live system.
For this purpose I created a basic framework that could aid in this task.