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Doron SamelsonDoron Samelson is co-founder andvice president of DevOps,responsible for customer successand Teridion deployments. Hebrings to the company a deepexperience in so!ware platformmanagement and cloud computingcompanies.
CONTRIBUTED / TECHNOLOGY / TUTORIALS / GLOBAL
Teridion’s Processes and Architecture forMigrating Across Cloud Providers5 MONTHS AGO, BY DORON SAMELSON AND DAVE GINSBURG
With applications, services and now networking moving to the cloud, one key
question is portability — the ability for a company, SaaS or otherwise, to migrate from
one cloud operator to another. In fact, 451 Research reports that a “multi-cloud”
strategy can save up to 74 percent, according to their Cloud Price Index.
Now that companies are comfortable with public and
hybrid clouds, the next logical question is how to deploy
across multiple operators to best leverage their footprints,
capabilities and pricing. The key is to implement processes
and architectures that permit this approach.
One example is Teridion’s Global Cloud Network (GCN),
deployed across upwards of a dozen cloud operators
without having to reinvent the wheel each time. It relies on
a management system, abstraction layer and API that
introduce a common language when spinning up and
breaking down services. For example, if requesting service
“A” in operator “B” and parameters “C,” what is the
equivalent vernacular in operator “D”? Also, what criteria can one use in deciding
which operator to use? A brief review of the Teridion architecture will help before
going into technical details.
Our Teridion GCN is comprised of three primary components:
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Dave GinsburgDave Ginsburg is chief marketingo"icer, bringing to Teridion 25+years of experience spanningcorporate and product marketing,product management, digitalmarketing, and marketingautomation. Previous roles includedPluribus, Extreme, Riverstone,Nortel, and Cisco.
Teridion Measurement Agents (TMAs) run on
virtual machines within cloud operators, and are used
to determine latency across an operator’s backbone
or to other cloud operators. These TMAs are the
collection points for this report.
Teridion Cloud Virtual Routers (TCRs) create
overlay paths across the Internet based on
throughput, latency or geography, to optimize a given
customer’s dynamic content.
The Teridion Management System (TMS) gathers
data from TMAs to paint a live view of Internet
performance, and maintains APIs to cloud operators
to create or destroy TCRs on-demand and based on
customer requirements.
The above diagram depicts the system. The TMS, located in the cloud, spins-up TMAs
in every region of every major cloud operator. These TMAs are constantly gathering
performance data — including throughput via iPerf and latency by establishing TCP
connections — and sending this to the TMS.
Sponsor Note
Teridion’s cloud-optimized routing delivers dynamic content
20x faster. A CDN with no caching, optimized for all IP
applications, and bi-directional.
Any TCRs that already exist do the same via embedded TMAs. The TMS uses all of this
data to build a picture of Internet performance. This same data is used by the TMS to
deploy TCRs, also in cloud operators. Customer tra!ic is sent through these TCRs
following the most optimal paths, and the TCRs are also used to generate link
throughput data. There are two critical operations here:
Determining which cloud operator – when and where – for TCR deployment.
E!iciently interfacing into this cloud operator.
More detailed information on Teridion GCN architecture is here.
Cloud Operator SelectionAs described above, the TMS develops a real-time view of Internet cloud operator
performance. Our customers may select a virtual overlay network based on
throughput, latency, or even to prefer or avoid certain geographies. The TMS,
therefore, uses this along with pricing to select the best cloud operator(s) for a given
customer, and this may di!er by region and by date/time. For example, one of our
customers has over 500 TCRs deployed, on average, across four di!erent operators.
A"er deploying the TCRs, the TMS establishes the overlay path from one to another,
and may also create a standby path for resiliency.
Cloud Operator InterfaceThe TMS is able to accomplish this via an API that contains the necessary hooks for
each of the operators. It needs to be both flexible and capable of very high
performance. One way to look at this abstraction between our control plane — the
TMS — and our data forwarding plane — the TCRs — is to use the analogy of a data
center switch or router. In most cases, a vendor’s network operating system is not
limited to a single silicon family, and implements an abstraction layer. We’ve just
extended this to the cloud, where the TMS is the cloud networking operating system,
and the TCRs — virtual routers within the cloud operators — are the switching
elements.
"targetTMAPort": 80,"tcrBilling": "hourly","networkName": "devopsday-net","customerName": "DevOpsDay","customerId": "a4c064d604364c8e866ff164f3e83267","tcrPackage": "/tcr/TCR-1.0.116-1.x86_64.rpm","regions": [{"regionName": "Japan","geoRegions": ["JP"],"nearDcs": ["SoftLayer-tok02","Amazon-ap-northeast-1"
API Excerpt
High performance is ensured by how we architect the TMS. For a given region and
sub-region, the TMS maintains a list of potential cloud operators. Once it selects a
given operator, it issues a deployment order to spin-up a TCR. Note that the same
process may have occurred in advance of this in creating a TMA. For either, we
implement a Download Server with the TMA/TCR image, and across the Teridion
GCN, di!erent TCRs may run di!erent so"ware releases.
The TMAs and TCRs report back to the TMS queuing/logging engine, based on Kafka.
This is the funnel for all data arriving from the network nodes. From there, data is
shunted in two directions. The TMS builds a real-time view of the GCN via Neo4j, a
graphing database. At the same time, we forward performance data to Elasticsearch
for analytics, Kibana visualization, and ElasticHQ for cluster monitoring and
management. Here is where we determine the Internet state and best paths. Kibana
may be queried in real time for this data.
Teridion Global Cloud Network Architecture
Example Latency Graph from Kibana – UK to UK, USA, and Australia – Di!erentOperators
Example Latency Graph from Kibana – Operator in EMEA to 3 Operators in Singapore
Summary data from our analytics and graph engines is rendered by the user portal,
providing a per-customer view. We also implement a REST API over which a customer
can design their own UI.
Customer REST API Excerpt
ConclusionThe above architecture may serve as a blueprint for an organization wishing to
leverage multiple cloud operators for compute, storage, networking or any
combination of the three. What is critical is not only the documented APIs, but a
backend intelligence that can decide which operator to use, preferably in an
automated way.
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Teridion is a sponsor of The New Stack.
Feature image: “High flyers” by Broo_am (Andy B) is licensed under CC BY-ND 2.0.
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