Kubernetes (commonly stylized as k8s) is an open-source container-orchestration system for automating application deployment, scaling, and management. It aims to provide a platform for automating deployment, scaling, and operations of application containers across clusters of hosts. It works with a range of container tools, including Docker.
The InterSystems Kubernetes Operation (IKO) version 3.3 is now available via the WRC download page and the InterSystems Container Registry.
IKO simplifies working with InterSystems IRIS or InterSystems IRIS for Health in Kubernetes by providing an easy-to-use irisCluster resource definition. See the documentation for a full list of features, including easy sharding, mirroring, and configuration of ECP.
IKO 3.3 Highlights:
Support for 2021.2 and 2022.1 editions of InterSystems IRIS & IRIS for Health
Support for Kuberentes 1.21
Deploy common System Alerting and Monitoring (SAM) configurations as part of your irisCluster
InterSystems API Manager (IAM) can now also be deployed and managed as part of the irisCluster
Automatic tagging of mirror pair active side, so a service can always point to the active mirror member.
InterSystems Kubernetes Operator (IKO) 3.6 is now Generally Available. IKO 3.6 adds significant new functionality along with numerous bug fixes. Highlights include:
https://www.youtube.com/embed/Twg7IESeyhQ [This is an embedded link, but you cannot view embedded content directly on the site because you have declined the cookies necessary to access it. To view embedded content, you would need to accept all cookies in your Cookies Settings]
Some of you on the Developer Community have probably interacted with @Luca Ravazzolo if you are interested in cloud and container topics... If so, you'll enjoy Episode 2 of our new podcast — we chatted with Luca about Kubernetes and the InterSystems Kubernetes Operator. He does a great job of explaining the technology and its benefits here!
https://5e18edf067eb59-03854285.castos.com/player/147141 [This is an embedded link, but you cannot view embedded content directly on the site because you have declined the cookies necessary to access it. To view embedded content, you would need to accept all cookies in your Cookies Settings]
In our previous article, we have explored the most common Kubernetes components:
We started with the pods and the services we needed to communicate with each other.
Then, we examined the Ingress component used to Route traffic into the cluster.
We also skimmed through an external configuration using ConfigMaps and Secrets.
Afterward, we analyzed Data persistence with the help of Volumes.
Finally, we took a quick look at pod blueprints with such replicating mechanisms as Deployments and StatefulSets (the latter is employed specifically for such stateful applications as databases).
In this article, we will explore Kubernetes architecture and configuration.
I want to deploy IRIS apps running in containers in Kubernetes with user accounts configured.
I have a %ZSTART routine which looks for an XML file with Users export data and if the %ZSTART routine finds this file, it imports it. This Users export data can be obtained by running a class method.
I have defined a task which can be scheduled or run on demand. This tasks imports user data from an XM file.
In Kubernetes I can provide a ConfigMap to stage the Users data for the %ZSTART routine.
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If you're looking for an introduction to Kubernetes as a technology, and a little teaser about the InterSystems Kubernetes Operator, check out the recently released Kubernetes Overview video. This video will introduce you to the functionality and use cases of Kubernetes, and explain a bit about how the InterSystems Kubernetes Operator makes it beneficial to use Kubernetes with InterSystems IRIS.
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I attended Cloud Native Security Con in Seattle with full intention of crushing OTEL day, then perusing the subject of security applied to Cloud Native workloads the following days leading up to CTF as a professional excercise. This was happily upended by a new understanding of eBPF, which got my screens, career, workloads, and atitude a much needed upgrade with new approaches to solving workload problems.
So I made it to the eBPF party and have been attending clinic after clinic on the subject ever since, here I would like to "unbox" eBPF as a technical solution, mapped directly to what we do in practice (even if its a bit off), and step through eBPF through my experimentation on supporting InterSystems IRIS Workloads, particularly on Kubernetes, but not necessarily void on standalone workloads.
eBee Steps with eBPF and InterSystems IRIS Workloads
The Istio Service Mesh is commonly used to monitor communication between services in applications. The "battle-tested" sidecar mode is its most common implementation. It will add a sidecar container to each pod you have in your namespace that has Istio sidecar injection enabled.
https://www.youtube.com/embed/AjPUDGYyNsU [This is an embedded link, but you cannot view embedded content directly on the site because you have declined the cookies necessary to access it. To view embedded content, you would need to accept all cookies in your Cookies Settings]
Did you catch an Experience Lab at the 2021 Virtual Summit? Head over to the InterSystems Learning siteto access all four of these hands-on exercises, and get up to speed on:
So if you are following from the previous post or dropping in now, let's segway to the world of eBPF applications and take a look at Parca, which builds on our brief investigation of performance bottlenecks using eBPF, but puts a killer app on top of your cluster to monitor all your iris workloads, continually, cluster wide!
Continous Profiling with Parca, IRIS Workloads Cluster Wide
Episode 20 of Data Points features a conversation with Bob Kuszewski about the Kubernetes and the InterSystems Kubernetes Operator (IKO). Take a listen to hear about some of the use cases and features of IKO, plus how it compares to InterSystems Cloud Manager (ICM) within the cloud space.
https://5e18edf067eb59-03854285.castos.com/player/579162 [This is an embedded link, but you cannot view embedded content directly on the site because you have declined the cookies necessary to access it. To view embedded content, you would need to accept all cookies in your Cookies Settings]
IAM - InterSystems API Manager is a great tool for monitoring your traffic. If you are trying to use it in your Kubernetes cluster you may have tried doing a deployment similar to this one:
https://www.youtube.com/embed/8ZQf5m0HA5w [This is an embedded link, but you cannot view embedded content directly on the site because you have declined the cookies necessary to access it. To view embedded content, you would need to accept all cookies in your Cookies Settings]
In today's rapidly evolving threat landscape, organizations deploying mission-critical applications must implement robust security architectures that protect sensitive data while maintaining high availability and performance. This is especially crucial for enterprises utilizing advanced database management systems like InterSystems IRIS, which often powers applications handling highly sensitive healthcare, financial, or personal data.
All pods are assigned a Quality of Service (QoS). These are 3 levels of priority pods are assigned within a node.
The levels are as following:
1) Guaranteed: High Priority
2) Burstable: Medium Priority
3) BestEffort: Low Priority
It is a way of telling the kubelet what your priorities are on a certain node if resources need to be reclaimed. This great GIF below by Anvesh Muppeda explains it.
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This is like my first post in this community. Let's see how this turns out. I have a question about the Intersystems Kubernetes Operator and the deployment of the webgateways.
I am responsible for the hosting and deployment of the apps. For the future we are planning to host our application in a kubernetes cluster. I am using the IKO for this. I am using webgateways, for external access as separate pods. And sidecar containers for internal access, like the management portal.
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