NETCONF Data Modeling Language Working Group (netmod) E. Voit
Internet-Draft A. Clemm
Intended status: Informational S. Bansal
Expires: March 29, 2015 A. Tripathy
P. Yellai
Cisco Systems
September 25, 2014
Requirements for Peer Mounting of YANG subtrees from Remote Datastores
draft-voit-netmod-peer-mount-requirements-00
Abstract
Network integrated applications want simple ways to access YANG
objects and subtrees which might be distributed across network.
Performance requirements may dictate that it is unaffordable for a
subset of these applications to go through existing centralized
management brokers. For such applications, development complexity
must be minimized. Specific aspects of complexity developers want to
ignore include:
o whether authoritative information is actually sourced from remote
datastores (as well as how to get to those datastores),
o whether such information has been locally cached or not,
o whether there are zero, one, or more controllers asserting
ownership of information, and
o whether there are interactions with other applications
concurrently running elsewhere
The solution requirements described in this document detail what is
needed to support application access to authoritative network YANG
objects from controllers (star) or peering network devices (mesh) in
such a way to meet these goals.
Status of This Memo
This Internet-Draft is submitted in full conformance with the
provisions of BCP 78 and BCP 79.
Internet-Drafts are working documents of the Internet Engineering
Task Force (IETF). Note that other groups may also distribute
working documents as Internet-Drafts. The list of current Internet-
Drafts is at http://datatracker.ietf.org/drafts/current/.
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Internet-Drafts are draft documents valid for a maximum of six months
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This Internet-Draft will expire on March 29, 2015.
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Table of Contents
1. Business Problem . . . . . . . . . . . . . . . . . . . . . . 3
2. Terminology . . . . . . . . . . . . . . . . . . . . . . . . . 4
3. Solution Context . . . . . . . . . . . . . . . . . . . . . . 5
3.1. Peer Mount . . . . . . . . . . . . . . . . . . . . . . . 6
3.2. Eventual Consistency and YANG 1.1 . . . . . . . . . . . . 7
4. Example Use Cases . . . . . . . . . . . . . . . . . . . . . . 7
4.1. Cloud Policer . . . . . . . . . . . . . . . . . . . . . . 8
4.2. DDoS Thresholding . . . . . . . . . . . . . . . . . . . . 9
4.3. Service Chain Classification, Load Balancing and Capacity
Management . . . . . . . . . . . . . . . . . . . . . . . 10
5. Requirements . . . . . . . . . . . . . . . . . . . . . . . . 10
5.1. Application Simplification . . . . . . . . . . . . . . . 11
5.2. Caching Considerations . . . . . . . . . . . . . . . . . 12
5.2.1. Caching Overview . . . . . . . . . . . . . . . . . . 12
5.2.2. Pub/Sub of Object Updates . . . . . . . . . . . . . . 13
5.3. Lifecycle of the Mount Topology . . . . . . . . . . . . . 16
5.3.1. Discovery and Creation of Mount Topology . . . . . . 16
5.3.2. Restrictions on the Mount Topology . . . . . . . . . 17
5.4. Mount Filter . . . . . . . . . . . . . . . . . . . . . . 17
5.5. Transport . . . . . . . . . . . . . . . . . . . . . . . . 17
5.6. Security Considerations . . . . . . . . . . . . . . . . . 17
5.7. High Availability . . . . . . . . . . . . . . . . . . . . 18
5.8. Configuration . . . . . . . . . . . . . . . . . . . . . . 19
5.9. Assurance and Monitoring . . . . . . . . . . . . . . . . 19
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6. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 20
7. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . 20
8. References . . . . . . . . . . . . . . . . . . . . . . . . . 21
8.1. Normative References . . . . . . . . . . . . . . . . . . 21
8.2. Informative References . . . . . . . . . . . . . . . . . 21
8.3. URIs . . . . . . . . . . . . . . . . . . . . . . . . . . 21
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 22
1. Business Problem
Instrumenting Physical and Virtual Network Elements purely along
device boundaries is insufficient for today's requirements. Instead,
users, applications, and operators are asking for the ability to
interact with varying subsets of network information at the highest
viable level of abstraction. Likewise applications that run locally
on devices may require access to data that transcends the boundaries
of the device they are deployed. Achieving this can be difficult
since a running network is comprised of a distributed mesh of object
ownership. (I.e., the authoritative device owning a particular
object will vary.) Solutions require the transparent assembly of
different objects from across a network in order to provide
consolidated, time synchronized, and consistent views required for
that abstraction.
Recent approaches have focused on a Network Controller as the arbiter
of new network-wide abstractions. Controller based solutions are
supportable by requirements outlined in this document. However this
is not the only deployment model covered by this document. Equally
valid are deployment models where Network Elements exchange
information in a way which allows one or more of those Elements to
provide the desired network level abstraction. This is not a new
idea. Examples of Network Element based protocols which already do
network level abstractions include VRRP [RFC3768], mLACP/ICCP[ICCP],
and Anycast-RP [RFC4610] . As network elements increase their compute
power and support Linux based compute virtualization, we should
expect additional local applications to emerge as well (such as
Distributed Analytics [1]).
Ultimately network application programming must be simplified. To do
this:
o we must provide APIs to both controller and network element based
applications in a way which allows access to network objects as if
they were coming from a cloud,
o we must enable these local applications to interact with network
level abstractions,
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o we must hide the mesh of interdependencies and consistency
enforcement mechanisms between devices which will underpin a
particular abstraction,
o we must enable flexible deployment models, in which applications
are able to run not only on controller and OSS frameworks but also
on network devices without requiring heavy middleware with large
footprints, and
o we need to maintain clear authoritative ownership of individual
data items while not burdening applications with the need to
reconcile and synchronize information replicated in different
systems, nor needing to maintain redundant data models that
operate on the same underlying data.
These steps will eliminate much unnecessary overhead currently
required of today's network programmer.
2. Terminology
The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
"SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this
document are to be interpreted as described in RFC 2119 [RFC2119].
Authoritative Datastore - A datastore containing the authoritative
copy of an object, i.e. the source and the "owner" of the object.
Client Datastore - a datastore containing an object whose source and
"owner" is a remote datastore.
Data Node - An instance of management information in a YANG
datastore.
Datastore - A conceptual store of instantiated information, with
individual data items represented by data nodes which are arranged in
hierarchical manner.
Data Subtree - An instantiated data node and the data nodes that are
hierarchically contained within it.
Mount Client - The system at which the mount point resides, into
which on or more remote subtrees may be mounted.
Mount Binding - An instance of mounting from a specific Mount Point
to a remote datastore. Types include:
o On-demand: Mount Client only pulls information when application
requests
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o Periodic: Mount Server pushes current state at a pre-defined
interval
o Unsolicited: Mount Server maintains active bindings and sends to
client cache upon change
Mount Point - Point in the local data store which may reference a
single remote subtree
Mount Server - The server with which the Mount Client communicates
and which provides the Mount Client with access to the mounted
information. Can be used synonymously with Mount Target.
Peer Mount - The act of representing remote objects in the local
datastore
Target Data Node - Data Node on Mount Server against which a Mount
Binding is established
3. Solution Context
YANG modeling has emerged as a preferred way to offer network
abstractions. The requirements in this document can be enabled by
expanding of the syntax of YANG capabilities embodied within RFC 6020
[RFC6020] and YANG 1.1 [rfc6020bis]. A companion draft to this one
which details a potential set of YANG technology extensions which can
support key requirements within this document are contained in .
[draft-clemm-mount].A "-02" release of this draft which includes
specifications to support many additional concepts will be posted in
the coming days.
To date systems built upon YANG models have been missing two
capabilities:
1. Peer Datastore Mount: Datastores have not been able to proxy
objects located elsewhere. This puts additional burden upon
applications which then need to find and access multiple
(potentially remote) systems.
2. Eventual Consistency: YANG Datastore implementations have
typically assumed ACID [2] transaction models. There is nothing
inherent in YANG itself which demands ACID transactional
guarantees. YANG models can also expose information which might
be in the process of undergoing convergence. Since IP networking
has been designed with convergence in mind, this is a useful
capability since some types of applications must participate
where there is dynamically changing state.
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3.1. Peer Mount
First this document will dive deeper into Peer Datastore Mount
(a.k.a., "Peer Mount"). Contrary to existing YANG datastores, where
hierarchical datatree(s) are local in scope and only includes data
that is "owned" by the local system, we need an agent or interface on
one system which is able refer to managed resources that reside on
another system. This allows applications on the same system as the
YANG datastore server, as well as remote clients that access the
datastore through a management protocol such as NETCONF, to access
all data as if it were local to that same server. This must be done
in a manner that is transparent to users and applications. This must
be done in a way which does not require a user or application to be
aware of the fact that some data resides in a different location and
have them directly access that other system. In this way, the user
is projected an image of one virtual consolidated datastore.
The value in such a datastore comes from its under-the-covers
federation. The datastore transparently exposes information from
multiple systems across the network. The user does not need to be
aware of the precise distribution and ownership of data themselves,
nor is there a need for the application to discover those data
sources, maintain separate associations with them, and partition its
operations to fit along remote system boundaries. The effect is that
a network device can broaden and customize the information available
for local access. Life for the application is easier.
Any Object type can be included in such a datastore. This can
include configuration data that is either persistent or ephemeral,
and which is valid within only a single device or across a domain of
devices. This can include operational data that represents state
across a single device or across a multiple devices.
Another useful aspect of "Peer Mount" is its ability to embed
information from external YANG models which haven't necessarily been
normalized. Normalization is a good thing. But the massive human
efforts invested in uber-data-models have never gained industry
traction due to the resulting models' brittle nature and complexity.
By mounting remote trees/objects into local datastores it is possible
to expose remote objects under a locally optimized hierarchy without
having to transpose remote objects into a separate local model. Once
this exists, object translation and normalization become optional
capabilities which may also be hidden.
Another useful aspect of "Peer Mount" is its ability to mount remote
trees where the local datastore does not know the full subtree being
installed. In fact, the remote datastore might be dynamically
changing the mounted tree. These dynamic changes can be reflected as
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needed under the "attachment points" within the namespace hierarchy
where the data subtrees from remote systems have been mounted. In
this case, the precise details of what these subtrees exactly contain
does not need to be understood by the system implementing the
attachment point, it simply acts as a single point of entry and
"proxy" for the attached data.
3.2. Eventual Consistency and YANG 1.1
The CAP theorem [3] states that it is impossible for a distributed
computer system to simultaneously provide Consistency, Availability,
and Partition tolerance. (I.e., distributed network state management
is hard.) Mostly for this reason YANG implementations have shied
away from distributed datastore implementations where ACID
transactional guarantees cannot be given. This of course limits the
universe of applicability for YANG technology.
Leveraging YANG concepts, syntax, and models for objects which might
be happening to undergo network convergence is valuable. Such reuse
greatly expands the universe of information visible to networking
applications. The good news is that there is nothing in YANG 1.1
syntax that prohibits its reapplication for distributed datastores.
Extensions are needed however.
Requirements described within this document can be used to define
technology extensions to YANG 1.1 for remote datastore mounting.
Because of the CAP theorem, it must be recognized that systems built
upon these extensions MAY choose to support eventual consistency
rather than ACID guarantees. Some applications do not demand ACID
guarantees (examples are contained in this document's Use Case
section). Therefore for certain classes of applications, eventual
consistency [4] should be viewed as a cornerstone feature capability
rather than a bug.
4. Example Use Cases
Many types of applications can benefit from the simple and quick
availability of objects from peer network devices. Because network
management and orchestration systems have been fulfilling a subset of
the requirements for decades, it is important to focus on what has
changed. Changes include:
o SDN applications wish to interact with local datastore(s) as if
they represent the real-time state of the distributed network.
o Independent sets of applications and SDN controllers might care
about the same authoritative data node or subtree.
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o Changes in the real-time state of objects can announce themselves
to subscribing applications.
o The union of an ever increasing number of abstractions provided
from different layers of the network are assumed to be consistent
with each other (at least once a reasonable convergence time has
been factored in).
o CPU and VM improvements makes running Linux based applications on
network elements viable.
Such changes can enable a new class of applications. These
applications are built upon fast-feedback-loops which dynamically
tune the network based on iterative interactions upon a distributed
datastore.
4.1. Cloud Policer
A Cloud Policer enables a single aggregated data rate to tenants/
users of a data center cloud that applies across their VMs; a rate
independent of where specific VMs are physically hosted. This works
by having edge router based traffic counters available to a
centralized application, which can then maintain an aggregate across
those counters. Based on the sum of the counters across the set of
edge routers, new values for each device based Policer can be
recalculated and installed. Effectively policing rates are
continuously rebalanced based on the most recent traffic offered to
the aggregate set of edge devices.
The cloud policer provides a very simple cloud QoS model. Many other
QoS models could also be implemented. Example extensions include:
o CIR/PIR guarantees for a tenant,
o hierarchical QoS treatment,
o providing traffic delivery guarantees for specific enterprise
branch offices, and
o adjusting the prioritization of one application based on the
activity of another application which perhaps is in a completely
different location.
It is possible to implement such a cloud policer application with
maximum application developer simplicity using peer mount. To do
this the application accesses a local datastore which in turn does a
peer mount from edge routers the objects which house current traffic
counter statistics. These counters are accessed as if they were part
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of the local datastore structures, without concern for the fact that
the actual authoritative copies reside on remote systems.
Beyond this centralized counter collection peer mount, it is also
possible to have distributed edge routers mount information in the
reverse direction. In this case local edge routers can peer mount
centrally calculated policer rates for the device, and access these
objects as if they were locally configured.
For both directions of mounting, the authoritative copy resides in a
single system and is mounted by peers. Therefore issues with regards
to inconsistent configuration of the same redundant data across the
network are avoided. Also as can be seen in this use case, the same
system can act as a mount client of some objects while acting as
server for other objects.
4.2. DDoS Thresholding
Another extension of the "Cloud Policer" application is the creation
of additional action thresholds at bandwidth rates far greater than
might be expected. If these higher thresholds are hit, it is
possible to connect in DDoS scrubbers to ingress traffic. This can
be done in seconds after a bandwidth spike. This can also be done if
non-bandwidth counters are available. For example, if TCP flag
counts are available it is possible to look for changes in SYN/ACK
ratios which might signal a different type of attack. In all cases,
when network counters indicate a return to normal traffic profiles
the DDoS Scrubbers can be automatically disconnected.
Benefits of only connecting a DDoS scrubber in the rare event an
attack might be underway include:
o marking down traffic for an out-of-profile tenant so that an
potential attack doesn't adversely impact others,
o applying DDoS Scrubbing across many devices when an attack is
detected in one,
o reducing DDoS scrubber CPU, power, and licensing requirements
(during the vast majority of time, spikes are not occurring), and
o dynamic management and allocation of scarce platform resources
(such as optimizing span port usage, or limiting IP-FIX reporting
to levels where devices can do full flow detail exporting).
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4.3. Service Chain Classification, Load Balancing and Capacity
Management
Service Chains will dynamically change ingress classification
filters, allocate paths from many ingress devices across shared
resources. This information needs to be updated in real time as
available capacity is allocated or failures are discovered. It is
possible to simplify service chain configuration and dynamic topology
maintenance by transparently updating remote cached topologies when
an authoritative object is changed within a central repository. For
example if the CPU in one VM spikes, you might want to recalculate
and adjust many chained paths to relieve the pressure. Or perhaps
after the recalculation you want to spin up a new VM, and then adjust
chains when that capacity is on-line.
A key value here is central calculation and transparent auto-
distribution. In other words, a change only need be updated by an
application in a single location, and the infrastructure will
automatically synchronize changes across any number of subscribing
devices without application involvement. In fact, the application
need not even know many devices are monitoring the object which has
been changed.
Beyond 1:n policy distribution, applications can step back from
aspects of failure recovery. What happens if a device is rebooting
or simply misses a distribution of new information? With peer mount
there is no doubt as to where the authoritative information resides
if things get out of synch.
While this ability is certainly useful for dynamic service chain
filtering classification and next hop mapping, this use case has more
general applicability. With a distributed datastore, diverse
applications and hosts can locally access a single device's current
VM CPU and Bandwidth values. They can do it without needing to
explicitly query that remote machine. Updates from a device would
come from a periodic push of stats to a transparent cache to
subscribed, or via an unsolicited update which is only sent when
these value exceed established norms.
5. Requirements
To achieve the objectives described above, the network needs to
support a number of requirements
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5.1. Application Simplification
A major obstacle to network programmability are any requirements
which force applications to use abstractions more complicated than
the developer cares to touch. To simplify applications development
and reduce unnecessary code, the following needs must be met.
Applications MUST be able to access a local datastore which includes
objects whose authoritative source is located in a remote datastore
hosted on a different server.
Local datastores MUST be able to provide a hierarchical view of
objects assembled from objects whose authoritative source may
originate from potentially different and overlapping namespaces.
Applications MUST be able to access all objects of a datastore
without concern where the actual object is located, i.e. whether the
authoritative copy of the object is hosted on the same system as the
local datastore or whether it is hosted in a remote datastore.
With two exceptions, a datastore's application facing interfaces MUST
make no differentiation whether individual objects exposed are
authoritatively owned by the datastore or mounted from remote. This
includes Netconf and Restconf as well as other, possibly proprietary
interfaces (such as, CLI generated from corresponding YANG data
models). The two exceptions are that it is acceptable to make a
distinction between an object authoritatively owned by the data store
and a remote object as follows:
o Object updates / editing, creation and deletion. E.g. via edit-
config conditions and constraints are assessed at the
authoritative datastore when the update/create/delete is
conducted. Any conditions or constraints at remote client
datastores are NOT assessed.
o Locks obtained at a client datastore: It is conceivable for the
interface to distinguish between two lock modes: locking the
entire subtree including remote data (in which case the
datastore's mount client needs to explicitly obtain and release
locks from mounted authoritative datastores), or locking only
authoritatively owned data, excluding remote data from the lock.
These exceptions should not be very problematic as non-authoritative
copies will typically be marked as read-only. This will not violate
any considerations of "no differentiation" of local or remote.
When a change is made to an object, that change will be reflected in
any datastore in which the object is included. This means that a
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change made to the object through a remote datastore will affect the
object in the authoritative datastore. Likewise, changes to an
object in the authoritative datastore will be reflected at any client
datastores.
The distributed datastore MUST be able to include objects from
multiple remote datastores. The same object may be included in
multiple remote datastores; in other words, an object's authoritative
datastore MUST support multiple clients.
The distributed datastore infrastructure MUST enable to access to
some subset of the same objects on different devices. (This includes
multiple controllers as well as multiple physical and virtual peer
devices.)
Applications SHOULD be able to extract a time synchronized set of
operational data from the datastore. (In other words, the
application asks for a subset of network state at time-stamp or time-
range "X". The datastore would then deliver time synchronized
snapshots of the network state per the request. The datastore may
work with NTP and operational counter to optimize the synchronization
results of such a query. It is understood that some types of data
might be undergoing convergence conditions.)
Authoritative datastore retain full ownership of "their" objects.
This means that while remote datastores may access the data, any
modifications to objects that are initiated at those remote
datastores need to be authorized by the authoritative owner of the
data. Likewise, the authoritative owner of the data may make changes
to objects, including modifications, additions, and deletions,
without needing to first ask for permission from remote clients.
Applications MUST be designed to deal with incomplete data if remote
objects are not accessible, e.g. due to temporal connectivity issues
preventing access to the authoritative source. (This will be true
for many protocols and programming languages. Mount is unlikely to
add anything new here unless applications have extra error handling
routines to deal with when there is no response from a remote
system.).
5.2. Caching Considerations
5.2.1. Caching Overview
Remote objects in a datastore can be accessed "on demand", when the
application interacting with the datastore demands it. In that case,
a request made to the local datastore is forwarded to the remote
system. The response from the remote system, e.g. the retrieved
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data, is subsequently merged and collated with the other data to
return a consolidated response to the invoking application.
A downside of a datastore which is distributed across devices can be
the latency induced when remote object acquisition is necessary.
There are plenty of applications which have requirements which simply
cannot be served when latency is introduced. The good news is that
the concept of caching lends itself well to distributed datastores.
It is possible to transparently store some types of objects locally
even when the authoritative copy is remote. Instead of fetching data
on demand when an application demands it, the application is simply
provided with the local copy. It is then up to the datastore
infrastructure to keep selected replicated info in synch, e.g. by
prefetching information, or by having the remote system publish
updates which are then locally stored.
This is not a new idea. Caching and Content Delivery Networks (CDN)
have sped read access for objects within the Internet for years.
This has enabled greater performance and scale for certain content.
Just as important, these technologies have been employed without end
user applications being explicitly aware of their involvement. Such
concepts are applicable for scaling the performance of a distributed
datastore.
Where caching occurs, it MUST be possible for the Mount Client to
store object copies of a remote data node or subtree in such a way
that applications are unaware that any caching is occurring.
However, the interface to a datastore MAY provide applications with a
special mode/flag to allow them to force a read-through and perhaps
even a write-through.
Where caching occurs, system administration facilities SHOULD allow
facilities to flush either the entire cache, or information
associated with select Mount Points.
5.2.2. Pub/Sub of Object Updates
When caching occurs, data can go stale. Pub/Sub provides a mechanism
where changes in an authoritative data node or subtree can be
monitored. If changes occur, these changes can be delivered to any
subscribing datastores. In this way remote caches can be kept up-to-
date. In this way, directly monitoring remote applications can
quickly receive notifications without continuous polling.
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5.2.2.1. General Pub/Sub Update Requirements
A Mount Client SHOULD be able to take advantage of pub/sub
capabilities offered by a mount server. However, not every Mount
Server offers according capabilities.
A Mount Client SHOULD be able to revert back to retrieve objects "On
Demand" and/or to pre-fetch objects by request.
A Mount Server MAY support a pub/sub capability in which one or more
remote clients subscribe to updates of a target data node / subtree,
which are then automatically published by the Mount Server.
One or more of the following pub/sub policies MUST be supported:
o On Demand (i.e. no pub/sub) - default
o Periodic (with a specified time interval)
o On change, immediate as the change occurs.
o On change, at the end of fixed intervals if a change has occurred
Further modifications are possible: e.g. on change, whether to only
publish only the object that has changed or the entire subtree that
had been subscribed to. (Effectively this is aggregate replication
at tree level, not at the object level.)
Pub/sub is applicable to other applications as well, not limited to
peer mounting. For example, a pub/sub capability can greatly
facilitate monitoring, as applications no longer have to "poll" for
data but can simply choose to subscribe to a stream of the most
current data. Accordingly, servers that offer pub/sub capabilities
for its YANG datastore SHOULD NOT limit subscribers to Mount Clients,
but allow other applications to subscribe as well.
It MUST be possible for Applications to subscribe to Data Node /
Subtrees so that upon Mount Client receipt of subscribed information,
it is immediately passed to the application.
It MUST be possible for the Mount Client to subscribe to Data Node /
Subtrees so that upon Mount Client receipt of subscribed information,
it is cached and therefore awaiting local application requests.
If there are no applications subscribing to a Data Node / Subtree, a
server SHOULD cease to publish the corresponding data.
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It MUST be possible for a Subscription to include a timestamp when
the Subscription will expire.
It MUST be possible to identify a specific time when a Mount Binding
will return the current value(s) of a mounted Data Node / Subtree.
(Such timeframes can be in the very near future in order to support a
snapshot of network state or counters across many devices.)
A publisher is not responsible to monitor if the subscribers are
still active. It MAY do so, but is not obliged to do so.
Subscriptions upon a Target Data Node do not remain active forever
but MUST be periodically re-subscribed . The reason for this is to
avoid "waste", for example in cases when subscribers "die". If a
subscriber restarts, it is the subscribers responsibility to check
whether its subscriptions are still intact or to resubscribe if
needed.
It MUST be possible for a Target Data Node to support 1:1 Mount
Bindings to a single subscribed Mount Point.
It MUST be possible for a Target Data Node to support 1:n Mount
Bindings to many subscribed Mount Points.
5.2.2.2. Periodic Pub/Sub Updates
Especially with network based Counters or Operational data, there
need be no recurring request to send the next instance of data which
is released on schedule to subscribers.
It MUST be possible to for a Periodic Mount Point to identify a
specific time when a Mount Target will return the current value(s) of
a mounted Data Node / Subtree. This will allow for synchronization
of calculation for objects delivered from many Mount Bindings to
local applications.
It MUST be possible to for a Periodic Mount Point to identify the
desired start and stop timestamps for any replicated objects
associated with duration. This will allow for time period
synchronization of source data for objects delivered from many Mount
Bindings to local applications.
5.2.2.3. Change-trigger Pub/Sub Updates
For an Unsolicited Mount Point, if a data node or subtree changes,
the Mount Target MUST provide updated objects to the Mount Client.
For an Unsolicited Mount Point, if a data node or subtree changes,
the Mount Target SHOULD be able to provide just the updated objects
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to the Mount Client. Note: If there is a Mount Filter in place, then
only the updated objects based on the filter will be delivered. It
is possible that a Filter will result in no update needing to be
sent.
It SHOULD be possible to provide criteria per Mount Binding on the
characteristics of changes to a Target Data Node's monitored objects
on before an update is sent to the subscribing system. (Effectively
this becomes a "threshold trigger" for change notification to remote
caches.)
5.3. Lifecycle of the Mount Topology
Mount can drive a dynamic and richly interconnected mesh of peer-to-
peer of object relationships. Each of these Mounts will be
independently established by a Mount Client.
It MUST be possible to bootstrap the Mount Client by providing the
YANG paths to resources on the Mount Server.
There SHOULD be the ability to add Mount Client bindings during run-
time.
A Mount Client MUST be able to be able to create, delete, and timeout
Mount Bindings.
A Mount Server maintaining a periodic or unsolicited Mount Binding
MUST be able to inform the Mount Client of an intentional graceful
disconnection of that binding.
A Mount Client must be able to verify the existence of a periodic or
unsolicited Mount Binding which has successfully been established on
a Mount Server, and re-establish if it has disappeared.
5.3.1. Discovery and Creation of Mount Topology
Application visibility into an ever-changing set of network objects
is not trivial. While some applications can be easily configured to
know the Devices and available Mount Points of interest, other
applications will have to balance many aspects of dynamic device
availability, capabilities, and interconnectedness. For the most
part, maintenance of these dynamic elements can be done on the YANG
objects themselves without anything needed new for Peer Mount.
Technologies such as need reference are covered in other standards
initiatives. Therefore this draft does delve deeply into the needs
for Auto-discovery of YANG objects which may be advertised.
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However it will likely become interesting for a network element to
limit the Data Subtrees which might be subscribed for Unsolicited and
Periodic Update.
It SHOULD be possible for a Mount Server to advertise potential
Target Data Nodes which can support unsolicited and periodic binding
types.
5.3.2. Restrictions on the Mount Topology
Mount Clients MUST NOT create recursive Mount bindings (i.e., the
Mount Client should not load any object or subtree which it has
already delivered to another in the role of a Mount Server.) Note:
Objects mounted from a controller as part of orchestration are *not*
considered the same objects as those which might be mounted back from
a network device showing the actual running config.
5.4. Mount Filter
The Mount Server default MUST be to deliver the same Data Node /
Subtree that would have been delivered via direct YANG access.
It SHOULD be possible for a Mount Client to request something less
that the full subtree or a target node. This will be valuable when
the number or size of objects under a Target Data Node is large.
5.5. Transport
Many secured transports are viable assuming transport, data security,
scale, and performance objectives are met. Netconf is recommended
for starting. Other transports may be proposed over time.
Additional study is needed to assess how aspects of locking will
supported in parallel with eventual consistency for different object
writes.
It MUST be possible to support Netconf Transport of subscribed Nodes
and Subtrees.
RESTconf [RESTconf] must be examined as well, especially as section
1.2 studies a possible mix of locking.
5.6. Security Considerations
Many security mechanisms exist to protect read/write access for CLI
and API on network devices. To the degree possible these mechanisms
should transparently protect data read and write when performing a
Peer Mount. The text below starts with a subset of those
requirements . Additional ones should be added.
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The same mechanisms used to determine whether a remote host has
access to a particular YANG Data Node or Subtree MUST be invoked to
determine whether a Mount Client has access to that information.
The same traditional transport level security mechanism security used
for YANG over a particular transport MUST be used for the delivery of
objects from a Mount Server to a Mount Client.
A Mount Server implementation MUST NOT change any credentials passed
by the Mount Client system for any Mount Binding request.
The Mount Server MUST deliver no more objects from a Data Node or
Subtree than allowable based on the security credentials provided by
the Mount Client.
To ensure the ensuring maximum scale limits, it MUST be possible to
for a Mount Server to limit the number of bindings and transactional
limits
It SHOULD be possible to prioritize which Mount Binding instances
should be serviced first if there is CPU, bandwidth, or other
capacity constraints.
5.7. High Availability
A key intent for Peer Mount is to allow access to an authoritative
copy of an object for a particular domain. Of course system and
software failures or scheduled upgrades might mean that the primary
copy is not consistently accessible from a single device. In
addition, system failovers might mean that the authoritative copy
might be housed on a different device than the one where the binding
was originally established. Peer Mount architectures must be built
to enable Mount Clients to transparently provide access to objects
where the authoritative copy moves due to dynamic network
reconfigurations .
For selected objects, Mount Bindings SHOULD be allowed to Anycast or
ECMP (Equal Cost Multiple Path) addresses so that a Distributed Mount
Server implementation can transparently provide (a) availability
during failure events to Mount Clients, and (b) load balancing on
behalf of Mount Clients.
Where anycast unsolicited or periodic bindings are allowed to Anycast
addresses, the real time state of Mount Server bindings MUST be
coordinated across the set of Anycast addressed devices. In this
way, the state of periodic and unsolicited Mount Bindings will not be
lost during a failover.
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The Mount Client and Mount Server MUST either have heart-beat
mechanism OR use a connection oriented transport to detect each
other's failures.
When a Mount Server detects disappearance of a Mount Client, the
Mount Server SHOULD purge all the mount bindings from the failed
Mount Client.
When a failover occurs on the Mount Client side, the new instance of
the Mount Client SHOULD re-establish the mount bindings with the
Mount Server(s).
When a failover occurs on the Mount Server side, the new owner of an
unsolicited mount binding SHOULD send out the current state of the
object to subscribed Mount Clients.
5.8. Configuration
At the Mount Client, it MUST be possible for all Mount bindings to
configure the following such that the application needs no knowledge.
This will includea diverse list of elements such at the YANG URI path
to the remote subtree.
5.9. Assurance and Monitoring
API usage for YANG should be tracked via existing mechanisms. There
is no intent to require additional transaction tracking than would
have been provided normally. However there are additional
requirements which should allow the state of existing and historical
bindings to be provided.
A Mount Client MUST be able to poll a Mount Server for the state of
unsolicited and periodic Mount Binding maintained between the two
devices.
A Mount Server MUST be able to publish the set of unsolicited and
periodic Mount Bindings which are currently established on or below
any identified data node.
A Mount Server MUST be able to publish the set of unsolicited and
periodic Mount Bindings which are going to a specific Mount Client.
A Mount Server MUST be able to publish the set fulfilled Mount
Bindings which are going to a specific Mount Client.
A Mount Server MUST be able to publish a list of the Mount Bindings
transactions successfully completed.
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A Mount Server MUST be able to publish a list of the Mount Bindings
which failed, along with reasons that they failed. These reasons
might include:
o Improper security credentials provided for the Mount Client to
access the target node
o Target node referenced does not exist
o Binding type requested not available for the target node
o Mount Server out of resources or resources not available
o Connection from client lost before binding complete
A Mount Client MUST be able to publish a list of the Mount Bindings
transactions successfully completed.
A Mount Client MUST be able to publish a list of the Mount Bindings
which failed, along with reasons that they failed. These reasons
might include:
o No response from Mount Client
o Connection could not be established with Mount Client
o Security credentials provided to Mount Server rejected
o Target node referenced does not exist
o Binding type requested not available for the target node
o Mount Server out of resources or resources not available
o Connection from client lost before binding complete
6. IANA Considerations
This document makes no request of IANA.
Note to RFC Editor: this section may be removed on publication as an
RFC.
7. Acknowledgements
We wish to acknowledge the helpful contributions, comments, and
suggestions that were received from Dinkar Kunjikrishnan, Harish
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Gumaste, Rohit M., Shruthi V. , Sudarshan Ganapathi, and Swaroop
Shastri.
8. References
8.1. Normative References
[RFC2119] Bradner, S., "Key words for use in RFCs to Indicate
Requirement Levels", BCP 14, RFC 2119, March 1997.
[RFC3768] Hinden, R., "Virtual Router Redundancy Protocol (VRRP)",
RFC 3768, April 2004.
[RFC4610] Farinacci, D. and Y. Cai, "Anycast-RP Using Protocol
Independent Multicast (PIM)", RFC 4610, August 2006.
[RFC6020] Bjorklund, M., "YANG - A Data Modeling Language for the
Network Configuration Protocol (NETCONF)", RFC 6020,
October 2010.
8.2. Informative References
[ICCP] Martini, L., Ed., "Inter-Chassis Communication Protocol
for L2VPN PE Redundancy", March 2014,
<https://tools.ietf.org/html/draft-ietf-pwe3-iccp-16>.
[RESTconf]
Bierman, A., Ed., "RESTCONF Protocol", July 2014,
<https://tools.ietf.org/html/draft-ietf-netconf-restconf-
01>.
[draft-clemm-mount]
Clemm, A., Ed., "Mounting YANG-Defined Information from
Remote Datastores", September 2013,
<http://tools.ietf.org/id/
draft-clemm-netmod-mount-01.txt>.
[rfc6020bis]
Bjorklund, M., "YANG - A Data Modeling Language for the
Network Configuration Protocol (NETCONF)", July 2014,
<https://datatracker.ietf.org/doc/draft-ietf-netmod-
rfc6020bis/>.
8.3. URIs
[1] http://thomaswdinsmore.com/2014/05/01/distributed-analytics-
primer/
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[2] http://en.wikipedia.org/wiki/ACID
[3] http://robertgreiner.com/2014/08/cap-theorem-revisited/
[4] http://guide.couchdb.org/draft/consistency.html
Authors' Addresses
Eric Voit
Cisco Systems
Email: evoit@cisco.com
Alex Clemm
Cisco Systems
Email: alex@cisco.com
Shashi Kumar Bansal
Cisco Systems
Email: shabansa@cisco.com
Ambika Tripathy
Cisco Systems
Email: ambtripa@cisco.com
Prabhakara Yellai
Cisco Systems
Email: pyellai@cisco.com
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