modify some misspellings in notes
Change-Id: I65a8e85ed7d6c642311a0327e58bc9c79535e551
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@ -38,7 +38,7 @@ Alternatives
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We already have two bonding methods in use, the Linux bonding kernel module,
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and Open vSwitch. However, adapter teaming is becoming a best practice, and
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this change will open up that possiblity.
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this change will open up that possibility.
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Security Impact
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---------------
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@ -181,8 +181,8 @@ configuration.
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Documentation Impact
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====================
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The deployment documentaiton will need to be updated to cover the use of
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teaming. The os-net-config sample configurations will demostrate the use
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The deployment documentation will need to be updated to cover the use of
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teaming. The os-net-config sample configurations will demonstrate the use
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in os-net-config. TripleO Heat template examples should also help with
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deployments using teaming.
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@ -21,7 +21,7 @@ The pacemaker architecture deployed currently via
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`puppet/manifests/overcloud_controller_pacemaker.pp` manages most
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service on the controllers via pacemaker. This approach, while having the
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advantage of having a single entity managing and monitoring all services, does
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bring a certain complexity to it and assumes that the operaters are quite
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bring a certain complexity to it and assumes that the operators are quite
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familiar with pacemaker and its management of resources. The aim is to
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propose a new architecture, replacing the existing one, where pacemaker
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controls the following resources:
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@ -130,7 +130,7 @@ The operators working with a cloud are impacted in the following ways:
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https://github.com/ClusterLabs/pacemaker/blob/master/lib/services/systemd.c#L547
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With the new architecture, restarting a native openstack service across
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all controllers will require restaring it via `systemctl` on each node (as opposed
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all controllers will require restarting it via `systemctl` on each node (as opposed
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to a single `pcs` command as it is done today)
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* All services will be configured to retry indefinitely to connect to
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@ -177,7 +177,7 @@ Work Items
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* Prepare the roles that deploy the next generation architecture. Initially,
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keep it as close as possible to the existing HA template and make it simpler
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in a second iteration (remove unnecesary steps, etc.) Template currently
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in a second iteration (remove unnecessary steps, etc.) Template currently
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lives here and deploys successfully:
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https://review.openstack.org/#/c/314208/
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@ -41,7 +41,7 @@ Overview
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The scope of this document for Pike is limited to recommendations for
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developers of containerized services, bearing in mind use cases for hybrid
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environments. It addresses only intermediate implementaion steps for Pike and
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environments. It addresses only intermediate implementation steps for Pike and
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smooth UX with upgrades from Ocata to Pike, and with future upgrades from Pike
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as well.
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@ -61,7 +61,7 @@ The scope for future releases, starting from Queens, shall include best
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practices for collecting (shipping), storing (persisting), processing (parsing)
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and accessing (filtering) logs of hybrid TripleO deployments with advanced
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techniques like EFK (Elasticsearch, Fluentd, Kibana) or the like. Hereafter
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those are refered as "future steps".
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those are referred as "future steps".
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Note, this is limited to OpenStack and Linux HA stack (Pacemaker and Corosync).
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We can do nothing to the rest of the supporting and legacy apps like
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@ -275,7 +275,7 @@ Queens parts:
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* Verify if the namespaced `/var/log/` for containers works and fits the case
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(no assignee).
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* Address the current state of OpenStack infrastructure apps as they are, and
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gently move them towards these guidelines refered as "future steps" (no
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gently move them towards these guidelines referred as "future steps" (no
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assignee).
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Dependencies
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@ -37,7 +37,7 @@ If the size exceeds a predetermined size (e.g. 10MB), Mistral will rename it to
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``tripleo-ui-log-<timestamp>``, and create a new file in its place. The file
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will then receive the messages from Zaqar, one per line. Once we reach, let's
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say, a hundred archives (about 1GB) we can start removing dropping data in order
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to prevent unnecessary data accoumulation.
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to prevent unnecessary data accumulation.
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To view the logging data, we can ask Swift for 10 latest messages with a prefix
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of ``tripleo-ui-log``. These files can be presented in the GUI for download.
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@ -109,7 +109,7 @@ Documentation Impact
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====================
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We should document the new settings introduced by the wizard. The documentation
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should be transferrable between the heat template project, and TripleO UI.
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should be transferable between the heat template project, and TripleO UI.
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References
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==========
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@ -23,7 +23,7 @@ are not being verified whether is failing or passing.
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Even if there is someone responsible to verify these runs, still is a manual
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job go to logs web site, check what's the latest job, go to the logs, verify
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if tempest ran, list the number of failures, check against a list if these
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failures are known failures or new ones, and only afther all these steps,
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failures are known failures or new ones, and only after all these steps,
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start to work to identify the root cause of the problem.
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Proposed Change
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@ -72,7 +72,7 @@ with node introspection for this workflow to be successful.
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During the first iterations, all the roles in a deployment will be
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analyzed to find a service associated with the role, which requires
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parameter derivation. Various options of using this and the final
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choice for the current iteration is discsused in below section
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choice for the current iteration is discussed in below section
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`Workflow Association with Services`_.
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This workflow assumes that all the nodes in a role have a homegenous
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@ -80,7 +80,7 @@ hardware specification and introspection data of the first node will
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be used for processing the parameters for the entire role. This will
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be reexamined in later iterations, based on the need for node specific
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derivations. The workflow will consider the flavor-profile association
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and nova placement scheduler to indentify the nodes associated with a
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and nova placement scheduler to identify the nodes associated with a
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role.
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Role-specific parameters are an important requirement for this workflow.
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@ -121,7 +121,7 @@ take advantage of this optional feature by enabling it via ``plan-
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environment.yaml``. A new section ``workflow_parameters`` will be added to
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the ``plan-environments.yaml`` file to accomodate the additional parameters
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required for executing workflows. With this additional section, we can ensure
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that the workflow sepcific parameters are provide only to the workflow,
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that the workflow specific parameters are provide only to the workflow,
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without polluting the heat environments. It will also be possible to provide
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multiple plan environment files which will be merged in the CLI before plan
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creation.
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@ -154,7 +154,7 @@ Usecase 2: Derivation Profiles for HCI
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This usecase uses HCI, running Ceph OSD and Nova Compute on the same node. HCI
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derive parameters workflow works with a default set of configs to categorize
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the type of the workload that the role will host. An option will be provide to
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override the default configs with deployment specfic configs via ``plan-
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override the default configs with deployment specific configs via ``plan-
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environment.yaml``.
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In case of HCI deployment, the additional plan environment used for the
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@ -230,7 +230,7 @@ service.
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Workflow Association with Services
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----------------------------------
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The optimal way to assosciate the derived parameter workflows with
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The optimal way to associate the derived parameter workflows with
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services, is to get the list of the enabled services on a given role,
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by previewing Heat stack. With the current limitations in Heat, it is
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not possible fetch the enabled services list on a role. Thus, a new
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@ -308,7 +308,7 @@ Other End User Impact
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---------------------
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Operators need not manually derive the deployment parameters based on the
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introspection or hardware specficiation data, as it is automatically derived
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introspection or hardware specification data, as it is automatically derived
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with pre-defined formulas.
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Performance Impact
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@ -369,7 +369,7 @@ Work Items
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* Derive Params start workflow to find list of roles
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* Workflow run for each role to fetch the introspection data and trigger
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individual features workflow
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* Workflow to indentify if a service associated with a features workflow is
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* Workflow to identify if a service associated with a features workflow is
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enabled in a role
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* DPDK Workflow: Analysis and concluding the format of the input data (jpalanis)
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* DPDK Workflow: Parameter deriving workflow (jpalanis)
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@ -59,7 +59,7 @@ compute nodes using TripleO.
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* real-time KVM
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* real-time tuned profiles
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* a new real-time compute role that is a variant of the exising compute role
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* a new real-time compute role that is a variant of the existing compute role
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* huge pages shall be enabled on the real-time compute nodes.
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* huge pages shall be reserved for the real-time guests.
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