Added Optimizing compute resources content to 4.0

Author: ahardin-rh

_topic_map.yml

@@ -111,6 +111,8 @@ Topics:
   File: scaling-cluster-monitoring-operator
 - Name: Planning your environment according to object limits
   File: planning-your-environment-according-to-object-limits
+- Name: Optimizing compute resources
+  File: optimizing-compute-resources
 ---
 Name: Operators
 Dir: operators

modules/debugging-issues-with-rhel-tools.adoc

@@ -0,0 +1,30 @@
+// Module included in the following assemblies:
+//
+// scalability_and_performance/optimizing-compute-resources.adoc
+
+[id='how-to-debug-issues-with-rhel-tools-{context}']
+= Debugging scaling or performance issues using the RHEL Tools container image
+
+Red Hat distributes a `rhel-tools` container image, packaging tools that aid in
+debugging scaling or performance problems. This container image:
+
+* Allows users to deploy minimal footprint container hosts by moving packages out
+of the base distribution and into this support container.
+
+* Provides debugging capabilities for Red Hat Enterprise Linux 7 Atomic Host,
+which has an immutable package tree. `rhel-tools` includes utilities such as
+tcpdump, sosreport, git, gdb, perf, and many more common system administration
+utilities.
+
+.Procedure
+
+. to use the rhel-tools` container, run:
++
+----
+# atomic run rhel7/rhel-tools
+----
+
+.Additional resources
+
+* link:https://access.redhat.com/documentation/en/red-hat-enterprise-linux-atomic-host/7/getting-started-with-containers/chapter-11-using-the-atomic-tools-container-image[RHEL
+Tools Container documentation ]

modules/using-a-pre-deployed-image-to-improve-efficiency.adoc

@@ -0,0 +1,38 @@
+// Module included in the following assemblies:
+//
+// scalability_and_performance/optimizing-compute-resources.adoc
+
+[id='using-a-pre-deployed-image-to-improve-efficiency-{context}']
+= Using a pre-deployed image to improve efficiency
+
+You can create a base {product-title} image with a number of tasks built-in to
+improve efficiency, maintain configuration consistency on all node hosts, and
+reduce repetitive tasks. This is known as a pre-deployed image. For example,
+because every node requires the `ose-pod` image in order to run pods, each node
+has to periodically connect to the container image registry in order to pull the
+latest image. This can become problematic when you have 100 nodes attempting
+this at the same time, and can lead to resource contention on the image
+registry, waste of network bandwidth, and increased pod launch times.
+
+.Procedure
+
+To build a pre-deployed image:
+
+. Create an instance of the type and size required.
+
+. Ensure a dedicated storage device is available for CRI-O or local image
+or container storage, separate from any persistent volumes for containers.
+
+. Fully update the system, and ensure CRI-O or Docker is installed.
+
+. Ensure the host has access to all yum repositories.
+
+. Set up thin-provisioned LVM storage.
+
+. Pre-pull your commonly used images (such as the rhel7 base image), as well as
+{product-title} infrastructure container images (`ose-pod`, `ose-deployer`, and
+so on) into your pre-deployed image.
+
+. Ensure that pre-deployed images are configured for any appropriate cluster
+configurations, such as being able to run on Red Hat OpenStack, or Amazon Web
+Services (AWS), as well as any other cluster configurations.

scalability_and_performance/optimizing-compute-resources.adoc

@@ -0,0 +1,23 @@
+[id='optimizing-compute-resources']
+= Optimizing compute resources
+include::modules/common-attributes.adoc[]
+:context:
+
+toc::[]
+
+
+Containers can specify compute resource requests and limits. Requests are used
+for scheduling your container and provide a minimum service guarantee. Limits
+constrain the amount of compute resource that may be consumed on your node.
+
+The scheduler attempts to optimize the compute resource use across all nodes in
+your cluster. It places pods onto specific nodes, taking the pods' compute
+resource requests and nodes' available capacity into consideration.
+
+Requests and limits enable administrators to allow and manage the overcommitment
+of resources on a node, which may be desirable in development environments where
+a tradeoff of guaranteed performance for capacity is acceptable.
+
+include::modules/using-a-pre-deployed-image-to-improve-efficiency.adoc[leveloffset=+1]
+
+include::modules/debugging-issues-with-rhel-tools.adoc[leveloffset=+1]