From 15730a89974e10fb19e689c0379a7e761fba0c14 Mon Sep 17 00:00:00 2001
From: Dante Niewenhuis <d.niewenhuis@hotmail.com>
Date: Tue, 5 Nov 2024 18:41:50 +0100
Subject: Hiding all tutorials that are currently not working to reduce
 confusion (#263)

* Hidden all tutorials that are currently not working to reduce confusion

* removed advanced guides from docusaurus

* removed advanced guides from whats-next

* removed advanced guides from support page
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----
-sidebar_position: 1
-title: Cloud Capacity Planning
-hide_title: true
-sidebar_label: Cloud Capacity Planning
-description: Cloud Capacity Planning
----
-
-# Cloud Capacity Planning Tutorial
-
-Using OpenDC to plan and design cloud datacenters.
-
-:::info Learning goal
-
-By doing this assignment, you will learn more about the basic concepts of datacenters and cloud computing systems, as
-well as how such systems are planned and designed.
-:::
-
-## Preamble
-
-Datacenter infrastructure is important in today’s digital society. Stakeholders across industry, government, and
-academia employ a vast and diverse array of cloud services hosted by datacenter infrastructure, and expect services to
-be reliable, high speed, and low cost. In turn, datacenter operators must maintain efficient operation at unprecedented
-scale.
-
-To keep up with growing demand and increasing complexity, architects of datacenters must address complex challenges in
-distributed systems, software engineering and performance engineering. One of these challenges is efficient utilization
-of resources in datacenters, which is only 6-12% industry-wide despite the fact that it is inconvenient for datacenter
-operators to keep much of their infrastructure idle, due to resulting high energy consumption and thus unnecessary
-costs.
-
-It is often quite difficult to implement optimizations or other changes in datacenters. Datacenter operators tend to be
-conservative in adopting such changes in fear of failure or misbehaving systems. Furthermore, testing changes at the
-scale of modern datacenter infrastructure in a real-world setting is prohibitively expensive and hard to reproduce,
-notwithstanding environmental concerns.
-
-A more viable alternative is the use of datacenter simulators such as OpenDC or CloudSim. These tools model datacenter
-infrastructure at a good accuracy and allow us to test changes in a controllable and repeatable environment.
-
-In this tutorial, we will use the OpenDC datacenter simulator to experiment with datacenters and demonstrate the
-process of designing and optimizing datacenters using simulation.
-
-## What is OpenDC
-
-OpenDC is an open source platform for datacenter simulation developed by AtLarge Research. The purpose of OpenDC is
-twofold: we aim to both enable cloud computing education and support research into datacenters.
-An example of the former is this tutorial, and examples of the latter include the numerous BSc and MSc research projects
-that are using OpenDC to run experiments and perform research.
-
-:::caution
-
-OpenDC is still an experimental tool. Your data may get lost, overwritten, or otherwise become unavailable. Sorry for
-the inconvenience.
-
-:::
-
-If you are not familiar with the OpenDC web interface, please follow the [Getting Started](/docs/category/getting-started)
-guide to get an understanding of the main concepts of OpenDC and how to design a datacenter.
-
-:::note Action
-
-Set up a project on the OpenDC website.
-
-:::
-
-
-## Assignment
-
-Acme Inc. is a small datacenter operator in the Netherlands. They are currently in the process of acquiring a new client
-and closing a deal where Acme will migrate all of the client’s business-critical workloads from internal machines to
-Acme’s datacenters. With this deal, the client aims to outsource the maintenance of their digital infrastructure, but in
-turn expects reliable and efficient operation from Acme.
-
-To demonstrate that Acme is capable of this task, it has started a pilot project with the client where Acme will migrate
-already a small subset of the client’s workloads. You are an engineer at Acme. and have been tasked with the design and
-procurement of the datacenter infrastructure required for this pilot project.
-
-To guide your design, the client has provided a workload trace of their business-critical workloads, which consist of
-the historical runtime behavior of 50 virtual machines over time. These virtual machines differ in resource
-requirements (e.g. number of vCPUs or memory) and in resource consumption over time. We can use OpenDC to simulate this
-workload trace and validate your datacenter design.
-
-The assignment is divided into four parts:
-1. Analyzing the requirements to estimate what resources are needed.
-2. Building your design in OpenDC
-3. Validating your design in OpenDC
-4. Optimizing your design in OpenDC
-
-Make notes of your thoughts on the following assignments & questions and discuss with your partner(s).
-
-## Analyze the Requirements
-
-The first step of the assignment is to analyze the requirements of the client in order to come up with a reasonable
-estimation of the datacenter infrastructure needed. This estimation will become our initial design which we will build
-and validate in OpenDC.
-
-Since the client has provided a workload trace representative of the workload that will eventually be running in the
-datacenter, we can use it to guide our design. In [Figure 1](#resource-distribution), the requested memory and vCPUs are
-depicted for the virtual machines in the workload trace.
-
-:::note Action
-
-Determine the total amount of vCPUs and memory required in the trace.
-
-:::
-
-<figure className="figure" id="resource-distribution">
-    <img src={require("./img/resource-distribution.png").default} alt="Resource requirements for the workload" />
-    <figcaption>
-        Requested number of vCPUs and memory (in GB) by the
-        virtual machines in the workload. The left figure shows the number of virtual machines that have requested 1, 2, 4 or 8
-        vCPUs. The right figure shows the amount of memory requested compared to the number of vCPUs in the virtual machine.
-    </figcaption>
-</figure>
-
-Based on this information, we could choose to purchase a new machine for every virtual machine in the workload trace.
-Such a design will most certainly be able to handle the workload. At the same time, it is much more expensive and
-probably unnecessary.
-
-In [Figure 2](#cpu-usage), the CPU Usage (in MHz) of the virtual machines in the workload is depicted over time. Observe that the
-median CPU usage of the virtual machines over the whole trace is approximately 100 MHz. This means that a 2-core
-processor with a base clock 3500 MHz would have utilization of only 1.4% (`100 MHz / (3500 MHz x 2)`) for such a median
-workload.
-
-<figure className="figure" id="cpu-usage">
-    <img src={require("./img/cpu-usage.png").default} alt="CPU usage over time for the workload" />
-    <figcaption>CPU Usage of the virtual machines in the workload over time.</figcaption>
-</figure>
-
-Instead, we could try to fit multiple virtual machines onto a single machine. For instance, the 2-core processor
-mentioned before is able to handle 70 virtual machines, each running at 100 MHz (`(3500 MHz x 2) / 100 MHz`), ignoring
-virtualization overhead and memory requirements.
-
-:::note Action
-
-Make a rough estimate of the number of physical cores required to host the vCPUs in the workload trace.
-
-:::
-
-Now that we have an indication of the number of physical cores we need to have, we can start to compose the servers in
-our datacenter. See **Table 1 and 2** for the equipment list you can choose from. Don’t forget to put enough memory in your
-servers, or otherwise you risk that not all virtual machines will fit on the servers in your datacenter.
-
-| Processor                        | Intel® Xeon® E-2224G | Intel® Xeon® E-2244G | Intel® Xeon® E-2246G |
-|----------------------------------|----------------------|----------------------|----------------------|
-| Base clock (in MHz)              | 3500                 | 3800                 | 3600                 |
-| Core count                       | 4                    | 8                    | 12                   |
-| Average power consumption (in W) | 71                   | 71                   | 80                   |
-
-**Table 1:** Processor options for your datacenter
-
-
-| Memory module                    | Crucial MTA9ASF2G72PZ-3G2E | Crucial MTA18ASF4G72PDZ-3G2E1 |
-|----------------------------------|----------------------------|-------------------------------|
-| Size (in GB)                     | 16                         | 32                            |
-| Speed (in MHZ)                   | 3200                       | 3200                          |
-**Table 2:** Memory options for your datacenter
-
-
-:::note Action
-
-Create a plan detailing the servers you want to have in your datacenter and what resources (e.g. processor or memory)
-they should contain. For instance, such a plan could look like:
-
-1. 8x Server (2x Intel® Xeon® E-2244G, 4x Crucial MTA18ASF4G72PDZ-3G2E1)
-
-:::
-
-:::tip Hint
-
-Budget more capacity than your initial estimates to prevent your datacenter from running at a very high
-utilization. Think about how your datacenter would handle a machine failure, will you still have enough capacity left?
-
-:::
-
-## Build the datacenter
-
-Based on the plan we devised in the previous section, we will now construct a (virtual) datacenter in OpenDC. If you
-have not yet used the OpenDC web interface to design a datacenter, please read [Getting Started](/docs/category/getting-started)
-guide to get an understanding of the main concepts of OpenDC and how to design a datacenter.
-
-:::note Action
-
-Implement your plan in the OpenDC web interface.
-
-:::
-
-## Validate your design
-
-We are now at a stage where we can validate whether the datacenter we have just designed and built in OpenDC is suitable
-for the workload of the client. We will use OpenDC to simulate the workload in our datacenter and keep track of several
-metrics to ensure efficient and reliable operation.
-
-One of our concerns is that our datacenter does not have enough computing power to deal with the client’s
-business-critical workload, leading to degraded performance and consequently an unhappy client.
-
-A metric that gives us an insight in performance degradation is the Overcommitted CPU Cycles, which represents the
-number of CPU cycles that a virtual machine wanted to run, but could not due to the host machine not having enough
-computing capacity at that moment. To keep track of this metric during simulation, we create a new portfolio by clicking
-the ‘+’ next to “Portfolio” in the left sidebar and select the metrics of interest.
-
-:::note Action
-
-Add a new portfolio and select at least the following targets:
-1. Overcommitted CPU Cycles
-2. Granted CPU Cycles
-3. Requested CPU Cycles
-4. Maximum Number VMs Finished
-
-:::
-
-We will now try to simulate the client’s workload trace (called _Bitbrains (Sample)_ in OpenDC). By clicking on ‘New
-Scenario’ below your created portfolio, we can create a base scenario which will represent our baseline datacenter
-design which we will compare against future improvements.
-
-:::note Action
-
-Add a base scenario to your new portfolio and select as trace _Bitbrains (Sample)_.
-
-:::
-
-By creating a new scenario, you will schedule a simulation of your datacenter design that will run on one of the OpenDC
-simulation servers. Press the Play button next to your portfolio to see the results of the simulations. If you have
-chosen the _Bitbrains (Sample)_ trace, the results should usually appear within one minute or less depending on the queue
-size. In case they do not appear within a reasonable timeframe, please contact the instructors.
-
-You can now see how your design has performed. Check whether all virtual machines have finished and whether the
-_Overcommitted CPU Cycles_ metric is not too high. Try to aim for anything below 1 bn cycles. In the next section, we’ll
-try to further optimize our design. For now, think of an explanation for the performance of your design.
-
-## Optimize your design
-
-Finally, let’s try to optimize your design so that it meets the requirements of the client and is beneficial for your
-employer as well. In particular, your company is interested in the follow goals:
-
-1. Reducing _Overcommitted CPU Cycles_ to a minimum for reliability.
-2. Reducing _Total Power Consumption_ to a minimum to save energy costs.
-
-:::note Action
-
-Add a new portfolio and select at least the following targets:
-1. Overcommitted CPU Cycles
-2. Granted CPU Cycles
-3. Requested CPU Cycles
-4. Total Power Consumption
-
-Then, add a base scenario to your new portfolio and select as trace _Bitbrains (Sample)_.
-
-:::
-
-Try to think of ways in which you can reduce both _Overcommitted CPU Cycles_ and _Total Power Consumption_. Create a new
-topology based on your initial topology and apply the changes you have come up with. In this way, you can easily compare
-the performance of different topologies in different scenarios. Note that the choice of scheduler might also influence
-your results.
-
-:::tip Hint
-
-The choice of scheduler (and thus the placement of VMs) might also influence your results.
-
-:::
-
-
-:::note Action
-
-1. Create a new topology based on your existing topology.
-2. Add a new scenario to your created portfolio and select your newly created topology.
-3. Compare the results against the base scenario.
-
-:::
-
-Repeat this approach until you are satisfied with your design.
-
-## Epilogue
-
-In this tutorial, you should have learned briefly about what datacenters are, and the process of designing and
-optimizing a datacenter yourself. If you have any feedback (positive or negative) about your experience using OpenDC
-during this tutorial, please let us know!
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