A 12 page paper describing the challenges of diagramming enterprise networks and the benefits of Dynamic Mapping. The paper draws analogies between Dynamic Maps and Google Maps.
The Role of IoT and Sensor Technology in Cargo Cloud Solutions.pptx
[White paper] Maintain-Accurate-Network-Diagrams
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2. WHITEPAPER: APPLYING AUTOMATION TO MAINTAIN ACCURATE NETWORK DIAGRAMS
Table of Contents
1. Executive Summary.............................................................................................................................................................1
2. Why Legacy Diagramming Fails Our Businesses.......................................................................................................1
3. Dynamic Mapping – A Fresh Approach........................................................................................................................2
Data-Driven Mapping.........................................................................................................................................................2
Diagrams On-Demand (Simple Input, Visual Output) .............................................................................................3
Dynamic Network Overview ............................................................................................................................................5
Automatically Updated......................................................................................................................................................6
4. NetBrain: A Fully Dynamic Network Mapping Solution..........................................................................................6
Qmap as a Data-Driven Diagram....................................................................................................................................7
On-Demand Mapping with Qmap .................................................................................................................................7
Qmap Integration with Visio............................................................................................................................................8
Export Qmap Data to a Design Document..................................................................................................................8
3. WHITEPAPER: APPLYING AUTOMATION TO MAINTAIN ACCURATE NETWORK DIAGRAMS 1
1. Executive Summary
Accurate network diagrams are the Holy Grail in enterprise network
management – most network teams know they should be documenting their
networks but haven’t found a universally good way of doing it. Today’s manual
diagramming methods are prohibitively time-consuming and ‘static diagram
generating software’ has not lived up to expectations in easing the burden.
With enterprise networks evolving rapidly, existing ‘static’ diagramming
solutions can’t keep up with the constant changes. A more dynamic mapping
solution is needed. Dynamic mapping is a leap forward in diagramming
technology, replacing gigabytes of static diagrams with the right diagram,
created the moment it’s needed. Dynamic maps are built from live network
data, accessible on-demand, and updated automatically. By implementing
dynamic mapping technology, enterprises are equipped with up-to-date
diagrams that accelerate troubleshooting, drive safe network changes, and
mitigate security risks.
2. Why Legacy Diagramming Fails Our Businesses
Network diagrams are the go-to visual aid engineers turn to when
troubleshooting connectivity problems or considering design changes. Even so,
conflicting priorities prevent network engineers from maintaining their diagram
repository. The static diagrams that result are best described as historical
snapshots – accurate when created, but increasingly untrustworthy as time
goes by. Network engineers are appropriately skeptical of static diagrams, often
choosing to create brand new diagrams instead of referencing old ones.
Accurate network diagrams have become the ‘Holy Grail’ for most network
teams.
Traditional network diagramming is extremely manual, broken down into two
phases: data collection and drawing. There are conflicting schools of thought
regarding how much data is too much, but at a minimum engineers need to
collect hostnames, interface IP address definitions, and routes from devices
before they can begin drawing. With a limited amount of room for stencils and
labels on a single diagram, too much detail clutters the document.
The industry has tried a variety of approaches to improve on purely manual
diagram creation, but with limited success. In the 1990’s, Microsoft added an
SNMP-based discovery function to Visio so that users could automate the
creation of network diagrams, but the sophistication of the tool couldn’t match
the complexity of most networks. Several 2nd generation mapping tools
Without visual aids, the
ability to understand
complex networks begins to
break down.
Accurate network diagrams
have become the ‘Holy
Grail’ for network teams.
2nd generation ‘static
diagram generators’ have
failed due to scalability and
usability problems.
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emerged in the 2000’s in the form of static diagram generators. The main
technology behind these tools – many of which still exist today – hasn’t
changed. Second generation diagramming tools still use SNMP to scan the
network and generate batches of static diagrams. The biggest challenge for
these 2nd generation tools is scalability; these tools just can’t generate usable
diagrams of large networks, as the result is a chaotic mess of lines and icons.
3. Dynamic Mapping – A Fresh Approach
Dynamically changing enterprise networks require a dynamic mapping
solution. But what characterizes a network diagram as ‘dynamic’? The best way
to examine this question is to study a similar problem that was solved by
dynamic mapping technology: the introduction of online mapping services to
solve the problem of outdated road atlases. Google Maps is a good example of
an online mapping service we can use to draw analogies to network
diagramming.
Data-Driven Mapping
Google Maps are ‘data-driven’, which means that Google uses a mathematical
model of Earth’s geography to render the data displayed on each map. That’s
how every landmark and road on a Google map is more than just an icon and
label; each is backed by real data (e.g. street view images, business names, and
phone numbers), guaranteeing accuracy. Similarly, a truly dynamic network
map represents a live rendering of a mathematical model derived from the live
network. The data elements behind each device icon and interface label on the
map are part of that model (e.g. device images, properties, config data, etc.). All
this data needs to be dynamically accessible so that it doesn’t congest the map
with its complexity.
Figure 1: Google Street Map with Landmark Data Elements
Truly dynamic maps are
driven by mathematically
modeled, real-world data.
SNMP discovery is not
enough to build an accurate,
data-driven network model.
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Figure 2: Network Map with Device & Interface Data Elements
In a network environment, SNMP discovery alone is insufficient for collecting
this level of data – other methods need to be in place to dig deeper into the
network’s configuration and design. Further, systems need to be in place to
guarantee the fidelity of the data over time so the diagrams always reflect the
latest network changes.
Diagrams On-Demand (Simple Input, Visual Output)
Most enterprise network diagram repositories have too many diagrams to sort
through. By way of example, let’s say a poorly performing application traverses
the network across three data centers. To troubleshoot the issue, a single
diagram with the relevant devices from the three data centers is required, not
three separate diagrams with all devices in each data center. In other words, the
diagram should adapt to the task at hand.
Google Maps handles this problem by allowing a ‘filtered’ view of the global
map, for example by searching for a landmark and mapping the area around it,
or mapping directions between a starting and destination address. Similarly,
dynamic mapping focuses on creating a tailored diagram containing just the
critical elements related to a specific need – precisely at the moment it’s
needed. The table below describes some scenarios that demonstrate how a
tailored map could address common network tasks.
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Task Input Output (Map)
1. Troubleshoot a
slow application
Input source and
destination addresses to
map the application flow
2. Find and disable
an infected server
Search for the server and
map adjacent LAN
environment to see where it
connects
3. Troubleshoot
multicast video
issues
Map related Downstream
Source Tree
4. Troubleshoot
OSPF routing
issues
Map targeted routing
domain (e.g. OSPF 200)
5. Document a
Data Center
Open Layer-2 Map of Data
Center
Figure 3: Diagramming On-Demand (Simple Input, Visual Output)
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Dynamic Network Overview
Just like zooming into Google Earth to see a particular region or city on the
globe, a dynamic mapping solution should provide a single global view of the
network which a network engineer can drill into site-by-site. By zooming into a
network site, detailed layer-3 topology and design data should be immediately
accessible, and the connections between each site obvious.
Figure 4: Dynamic Global View of Earth
Figure 5: Dynamic Global View of a Network Topology
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Automatically Updated
Google uses a combination of crowdsourcing and manual data collection to
maintain the accuracy of its map data, ensuring map viewers don’t go the
wrong way down a one-way street. With a dynamic network map, this level of
data integrity is equally important. Dynamic maps should rely on a system of
data which is automatically maintained and updated. That way, diagrams can
be created from live data the moment they are needed. In special cases, when
diagrams need to be defined ahead of time, they should be updated
automatically every time they are opened – ideally with the changes
highlighted for you to see.
Figure 6: Visualize Recent Network Changes on a Saved Map
4. NetBrain: A Fully Dynamic Network Mapping
Solution
NetBrain Technologies was founded on the principals of dynamic mapping to
address the challenges of inaccurate network documentation. NetBrain’s
unique ‘Qmaps’ are fully dynamic in nature and serve as the primary network
management interface for documentation, troubleshooting, and change
verification.
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Qmap as a Data-Driven Diagram
NetBrain collects a deeper level of data from the live network than any other
network mapping tool on the market. The unique discovery and benchmark
engine leverages Telnet/SSH in addition to traditional SNMP to login to every
device and extract configuration and design data. This data is compiled into a
mathematical model of the network. Every Qmap represents a rendering of that
mathematical model, making all the data visually accessible.
Figure 7: Live Data Extracted during Discovery/Benchmark
On-Demand Mapping with Qmap
There are several methods of rendering a Qmap within NetBrain, depending on
the requirements of the task-at-hand. Refer to the following table for examples
of real world tasks that can benefit from on-demand mapping.
On-Demand Mapping Applied to Real-World Tasks
1. Troubleshoot Slow Applications
Map out a slow application instantly and diagnose performance issues from the
map
2. Migrate Data Centers
Automatically discover and document a data center before/after migration
3. Assess A Network For VoIP Readiness
Map out potential VoIP paths and measure advanced performance metrics along
the paths
4. Troubleshoot Multicasting Issues
Instantly map a downstream source tree and monitor multicast traffic on the map
5. Meet Compliance Mandates
Automatically create network diagrams of every site to satisfy regulatory
compliance needs
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Qmap Integration with Visio
Network teams don’t need to abandon their existing Visio diagrams altogether,
NetBrain’s dynamic mapping solution can integrate them. Once a Visio diagram
repository is indexed by NetBrain, all of the Visio diagrams become searchable.
Both Qmaps and existing Visio diagrams integrated with NetBrain are listed in
search results.
Qmaps are both forward- and backward- compatible with Visio. Visio diagrams
can be imported and translated into the dynamic Qmap format. Conversely,
Qmaps can be exported to the standard Visio format and maintained
automatically on a set schedule. Even if policy mandates an updated Visio
database, NetBrain users don’t have to worry about manually updating the
diagrams.
Figure 8: Export from Qmap to Visio Format
Export Qmap Data to a Design Document
Diagrams aren’t the only form of documentation that network teams use to
collaborate. Many teams generate MS Word documents for internal design
reviews or for compliance reporting. With NetBrain, engineers can
automatically export data directly from a Qmap to a pre-defined template in MS
Word.
Figure 9: Export from Qmap to MS Word Document
11. About NetBrain Technologies, Inc.
Founded in 2004, NetBrain set out to pursue a new vision: automate time-
consuming tasks associated with network documentation, design, and
troubleshooting. NetBrain’s customers are using map-driven automation to
eliminate manual network documentation, automate troubleshooting tasks,
and mitigate security risks. NetBrain is headquartered in Burlington, MA with
offices in Sacramento, CA, New York, and Beijing, China.
To learn more about NetBrain’s dynamic mapping solution, contact us at
781.221.7199 or download free trial of NetBrain’s Enterprise Suite from
www.netbraintech.com/trial.
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