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.

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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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Here are the technology bonuses for the InterSystems Developer Tools Contest 2025 that will give you extra points in the voting:

  • IRIS Vector Search usage -3
  • Embedded Python usage -3
  • InterSystems Interoperability - 3
  • InterSystems IRIS BI - 3
  • VSCode Plugin - 3
  • FHIR Tools - 3
  • Docker container usage -2
  • ZPM Package Deployment - 2
  • Implement InterSystems Community Idea - 4
  • Find a bug in Embedded Python - 2
  • Article on Developer Community - 2
  • The second article on Developer Community - 1
  • Video on YouTube - 3
  • First Time Contribution - 3

See the details below.<--break->

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In this article I'll show you how to set up in your laptop, very quickly, a cluster of IRIS nodes in sharding. It's not the goal of this article neither to talk about sharding in detail nor define a deployment of a production ready architecture, but to show how to set up quickly, in your own machine, a cluster of IRIS instances configured as shard nodes, with which you'll able to play and test this functionality. If you're insterested in knowing more about sharding in IRIS, take a look at the documentation clicking here.

First and foremost, I want to remark that IRIS sharding will allow us 2 things:

  • Define, load and query shard tables, which data will be distributed transparently between the cluster's nodes
  • Define federated tables, which offer a global and composed view of data belonging to different tables that will be physically stored in different distributed nodes

So, as I said, we let for other article playing with shard or federated tables, and just focus now in the previous step, that is, setting up the cluster of shard nodes.

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