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Preference-driven systems: a practical bridge to intent-driven systems

Intent-driven orchestration has emerged as a effective model for managing increasingly complex, distributed systems. Rather than prescribing how infrastructure should behave, intent allows users to...

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Power efficiency: throttling for Sustainability

The rise of AI applications has brought us soaring power demands and strains on the environment. Google reported a 13% emission increase thanks to AI, their footprint is huge, some power grids are...

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System Effectiveness

In the world of distributed systems, performance has traditionally been the primary measure of success. Engineers have focused on optimizing for latency, throughput, reliability and scalability,...

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Your personal AI LLM based agent

Trevor Noah made an interesting comment in one of hit recent podcast: You know, the new workforce becomes one where your GPT is almost your resume. Your GPT is almost more valuable than you are in a...

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Intent Driven Orchestration

So let’s start with a bolt statement: the introduction of Microservices/functions and Serverless deployment styles for cloud-native applications has triggered a need to shift the orchestration...

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Write your functions in Rust – with Azure & Rocket

Rust is certainly one of the hot programming languages right now. Besides the cool feature set the language offers, companies – like Microsoft, Intel, Google, AWS, Facebook, etc. – embrace it:...

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AI planning algorithms in Rust

Artificial Intelligence (AI) is a hot topic, although it seams that the focus is on Neural Networks & Deep Learning on the software/algorithmic side, while GPUs/TPUs are the #1 topic for hardware....

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AI reasoning & planning

With the rise of faster compute hardware and acceleration technologies that drove Deep Learning, it is arguable that the AI winters are over. However Artificial Intelligence (AI) is not all about...

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Dancing links, algorithm X and the n-queens puzzle

Donald Knuth’s 24th annual Christmas lecture inspired me to implement algorithm X using dancing links myself. To demonstrate how this algorithms works, I choose the n-queens puzzle. This problem has...

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Tracing your functions

Note: this is mostly just for proof of concept – not necessarily something you want to do in a production system, but might be useful in a staging/test environment. Functions in a Serverless...

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Agent based bidding for merging graphs

There are multiple ways to merge two stitch two graphs together. Next to calculating all possible solutions or use evolutionarty algorithms bidding is a possible way. The nodes in the container, just...

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Q-Learning in python

There is a nice tutorial that explains how Q-Learning works here. The following python code implements the basic principals of Q-Learning: Let’s assume we have a state matrix defining how we can...

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Controlling a Mesos Framework

Note: This is purely for fun, and only representing early results. It is possible to combine more traditional scheduling and resource managers like OpenLava with DCOS like Mesos [1]. The basic...

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Distributed systems: which cluster do I obey?

The topic of cluster formation in itself is not new. There are plenty of methods around to form cluster on the fly [1]. They mostly follow methods which make use of gossip protocols. Implementation can...

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Example 2: Intelligent Orchestration & Scheduling with OpenLava

This is the second post in a series (the first post can be found here) about how to insert smarts into a resource manager. So let’s look how a job scheduler or distributed resource management system...

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Example 1: Intelligent Orchestration & Scheduling with Kubernetes

In the last blog I suggested that analytical capabilities need to move to the core of resource managers. This is very much needed for autonomous controlled large scale systems which figure out the...

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Insight driven resource management & scheduling

Future data center resource and workload managers – and their [distributed]schedulers – will require a new key integrate capability: analytics. Reason for this is the the pure scale and the complexity...

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A data center resource and service landscape

Telemetry and Monitoring system give a great visibility into what is going on with the resources and services in a data center. Applying machine learning and statistical analysis to this massive data...

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Autopiloting the data center

Orchestration and Scheduling are not the newest topics, in fact they have been used in distributed systems forever (as in a couple of decades :-)). Systems like Mesos and Kubernetes (or offerings like...

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Graph stitching

Graph stitching describes a way to merge two graphs by adding relationships/edges between them. To determine which edges to add, a notion of node types is used (based on node naming would be easy :-))....

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