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This chapter is from the book

The Key to Automation? Data Models

In the world of data model–driven management, as the name implies, the essential part is the set of data models. From the data models, you deduce APIs. Figure 2-2 displays a YANG data model (granted, an incomplete one, but sufficient at this point in time) on the left and RESTCONF RPCs (GET, POST, PUT, and DELETE) to manage the respective resources on the right. Paying attention to the color scheme, notice how the RESTCONF operations are built from the YANG module keywords, showing how the APIs are generated from a YANG model.

FIGURE 2.2

Figure 2.2 Data Model–Driven Management Example with RESTCONF

Discussing how data models generate APIs is a good segue to stress one more time the differences between information models and data models. As specified in “On the Difference Between Information Models and Data Models” (RFC 3444), covered in Chapter 1, the main purpose of an information model is to model managed objects at a conceptual level, independent of any specific implementations or protocols used to transport the data. An extra distinction, in light of this YANG module figure, is that data models generate APIs. This is a key message: Automation is driven by APIs (not models that are a means to an end). However, an information model, typically expressed in Unified Modeling Language (UML) do not generate the full APIs, as they lack some of the implementation- and protocol-specific details (for example, rules that explain how to map managed objects onto lower-level protocol constructs). Generating APIs from UML is, however, a field of research and experimentation. In the authors’ view, if the information model would contain all the information to generate complete APIs, then that information model is really a data model.

To get a bit more concrete on the difference between an information model and data model, let’s consider an example. A UML information model might declare that a book object should have title, author, ISBN, language, and price attributes. It might say that the title should be a string, the author should be a reference to an author object, and the price should be a numeric type.

To turn that UML information model into a data model, you would need to add additional information—for example, that ISBNs need to adhere to a very particular format in order to be valid, that the author relation is mandatory while language is not, or that a book isn’t eligible for sale if its price is zero. You would also need to state that there will be a list of books called the catalog and that this list is to be indexed by title. It is only when you add this sort of detailed information that the model becomes usable as an API—that is, as a contract between the client and server where both peers know what to expect and implement for.

YANG and the Operators Requirements

The YANG language addressed many of the issues raised during the “Overview of the 2002 IAB Network Management Workshop” (RFC 3535), as expressed in “An Architecture for Network Management Using NETCONF and YANG” (RFC 6244). Indeed, per RFC 6244, the YANG language was created to address the following requirements:

  • Ease of use: YANG is designed to be human friendly, simple, and readable. Many tricky issues remain due to the complexity of the problem domain, but YANG strives to make them more visible and easier to deal with.

  • Configuration and state data: YANG clearly divides configuration data from other types of data.

  • Generation of deltas: A YANG module gives enough information to generate the delta needed to change between two configuration data sets.

  • Text friendly: YANG modules are very text friendly, as is the data they define.

  • Task oriented: A YANG module can define specific tasks as RPC operations. A client can choose to invoke the RPC operation or to access any underlying data directly.

  • Full coverage: YANG modules can be defined that give full coverage to all the native capabilities of the device. Giving this access avoids the need to resort to the command-line interface (CLI) using tools such as Expect [EXPECT].14

  • Timeliness: YANG modules can be tied to CLI operations, so all native operations and data are immediately available.

  • Implementation difficulty: YANG’s flexibility enables modules that can be more easily implemented. Adding “features” and replacing “third normal form” with a natural data hierarchy should reduce complexity. YANG moves the implementation burden from the client to the server, where SNMP was simple for the server. Transactions are key for client-side simplicity.

  • Simple data modeling language: YANG has sufficient power to be usable in other situations. In particular, on-box APIs and a native CLI can be integrated to simplify the infrastructure.

  • Human-friendly syntax: YANG’s syntax is optimized for the reader, specifically the reviewer, on the basis that this is the most common human interaction.

  • Semantic mismatch: Richer, more descriptive data models will reduce the possibility of semantic mismatch. With the ability to define new primitives, YANG modules will be more specific in content, allowing more enforcement of rules and constraints.

  • Internationalization: YANG uses UTF-8 (RFC 3629) encoded Unicode characters.

Properties of Good Data Models

Although there are many ways to design good management interfaces (or API contracts), there are even more ways to design bad ones. Just like there are certain properties to look for when writing good contracts, there are certain things to look for when designing an interface. In fact, the list of good properties for these two activities is essentially the same, as displayed in the bullet list that follows. To make this point, the following bullet points are taken from the legal website www.ohiobar.org. It’s like designing a domain-specific language (DSL), with verbs, nouns, adjectives, and so on, plus (grammar) rules for how these elements may be combined. The most expressive, and therefore useful, languages generally have relatively few words, but focus on how the words can be combined into a near infinite number of different messages.

  • Accuracy: The most important aspect of a contract is that it is accurate and therefore makes the reaction of the other party predictable. If there are many exceptions (ifs, whens, and buts) beyond what is mentioned in the contract, the contract loses its value. The contract needs to use relevant terminology correctly, be precise, and cover all cases.

  • Clarity: Unless all parties come to the same understanding when reading the contract, interoperability is not going to happen. The language needs to be unambiguous, internally consistent, and use familiar terms. The document must be structured in a way that is easy to consume. Defaults enhance the clarity on what happens when a short message does not mention everything. Consistency constraints clarify how meaningful messages can be constructed.

  • Efficiency: A classic way to make sure a contract is not read is to make it very long. An even more sure way is to start repeating yourself. When the same lengthy wording appears in section after section, the readability and maintainability are lost. Repeating patterns are great, but only if referenced and reused, rather than repeated each time.

  • Simplicity: While it is tempting to use complicated in-group terms and language, it is usually better to write for a wider audience that may not understand the topic the contract is about at the same depth as the authors. Another important simplicity aspect is to write with the principle of least surprise (a.k.a. the principle of least astonishment) in mind. If something breaks an established pattern, either redesign or make it stand out as different.

  • Resonance: Make sure the contract stays on topic. If the topic is wide, several modular contracts in a suite may make it easier to consume. The contract should spell out sensible defaults to allow the parties to be lazy. The contract needs to consider the needs and terminology of both parties (or all if more than two).

Although YANG adheres to these properties, at this point you might be wondering, why YANG and not another schema language—for example, the Common Information Model (CIM), specified in the Distributed Management Task Force (DMTF)? A pragmatic answer is, YANG was defined as the modeling language for the NETCONF protocol, and although it has pros and cons compared to other modeling languages, the designers within the IETF community chose YANG.

The Different Types of YANG Modules

With the success of YANG as a modeling language, the industry is creating many YANG models to ease automation. YANG modules come from three different sources these days:

  • Standards development organizations (SDOs)

  • Consortiums, forums, and open source projects

  • Native/proprietary YANG models

While Chapter 6, “YANG Data Modeling Developments in the Industry,” covers the YANG data modeling developments in the industry in more much detail, in this chapter we just cover and compare the preceding three categories. The goal of this section is to highlight a couple of differences from the YANG models’ point of view.

As the SDO that specified the YANG language, the IETF was the initial SDO specifying the YANG modules—first in the NETMOD working group and then in different working groups with specific expertise. Different SDOs followed the trend, including the IEEE and ITU-T.15

Also, some consortiums, forums, and open source projects contributed to the YANG models development. To name a few, in no particular order, OpenConfig,11 MEF Forum,16 OpenDaylight,11 Broadband Forum,17 and Open ROADM18 all contributed.

The SDO-produced YANG modules receive the most attention (at least for the IETF, in which the book’s authors participate) as they are reviewed by many people. This review process comes at the cost of taking a long time to finalize the specifications. When developing applications around those YANG modules, it is important to understand that they contain a kind of common denominator, as opposed to the full coverage of the different experimental or proprietary features proposed by the different networking vendors. Extensions for those experimental and proprietary features must be developed on top of the standard YANG models.

On the other end, YANG models produced by consortiums, forums, and open source projects are most of the time targeted toward specific use cases, thus proposing complete solutions. When centered on use cases, a few committers maintain the coherence of the different YANG models, thus guaranteeing the consistency of the entire solution. Quick iterations of the YANG modules certainly improve the speed of delivery, based on the experience gained, but can be perceived as a burden for implementers who have to always keep their developments up to date with the latest version. Note that, in the case of open source projects, code is proposed next to the YANG models. Among all the open source projects, OpenConfig is worth mentioning, as it is getting some traction in the industry (more on this in Chapter 4).

The final category is “native YANG models,” also called “proprietary YANG models.” In order to offer some automation right now, with full coverage (for the entire set of supported features), some networking vendors propose YANG models, based on their proprietary implementations. Most of the time those YANG models are generated from internal databases or CLI representations, which implies that automation across vendors proved difficult. In case of generated YANG models, another potential issue is that new software versions can generate non-backward-compatible YANG modules, mapping the internal backward incompatibility. According to the YANG specifications, changes to published modules are not allowed if they have any potential to cause interoperability problems between a client using an original specification and a server using an updated specification. Expressed differently, a new module name is necessary if there are non-backward-compatible changes. However, in practice, that rule is not always followed. Therefore, there are discussions at the IETF to revise the YANG module update procedures (that is, to relax the rules concerning the condition of documenting the non-backward-compatible changes).

The industry has started to centralize all important YANG modules in GitHub [https://github.com/YangModels/yang], with the YANG Catalog [https://yangcatalog.org/]19 as the graphical interface. Those are two excellent starting points if you are not sure where to begin.

Mapping YANG Objects from MIB Modules

Before we begin this section about generating YANG modules as a translation from Management Information Based (MIB) modules, you should note that it refers to a couple of technical concepts introduced in later in this chapter and in the next two chapters. Since there is no other natural place to discuss mapping YANG objects from MIB modules later in the book, you are advised to re-read this section once you have mastered YANG and NETCONF.

When the IETF started its modeling work, there were no YANG modules (although there were plenty of MIB modules) to be used with the SNMP protocol. As already mentioned, many MIB modules were actively used for monitoring in network management. Therefore, it was only natural to invent a method to leverage what was good from SNMP and convert the MIB modules into YANG modules.

“Translation of Structure of Management Information Version 2 (SMIv2) MIB Modules to YANG Modules” (RFC 6643) describes a translation of SMIv2 (RFC 2578, RFC2579, and RFC 2580) MIB modules into YANG modules, enabling read-only access to SMIv2 objects defined in SMIv2 MIB modules via NETCONF. While this translation is of great help to access MIB objects via NETCONF, there is no magic bullet.

First off, the result of the translation of SMIv2 MIB modules into YANG modules, even if SMIv2 objects are read-write or read-create, consists of read-only YANG objects. One reason is that the persistency models of the underlying protocols, SNMP and NETCONF, are quite different. With SNMP, the persistence of a writable object depends either on the object definition itself (that is, the text in the DESCRIPTION clause) or the persistency properties of the conceptual row it is part of, sometimes controlled via a columnar object using the StorageType textual convention. With NETCONF, the persistence of configuration objects is determined by the properties of the underlying datastore. Furthermore, NETCONF, as defined in RFC 6241, does not provide a standard operation to modify operational state. The <edit-config> and <copy-config> operations only manipulate configuration data. You might say that the mapping of read-write or read-create objects is a moot point as there are not many of them in MIB modules. This is correct. Keep in mind that MIB modules do a good job of monitoring but have failed to emerge as a standard for configuring networks.

Second, using the MIB-translated YANG models along with the YANG-defined models still raises a basic problem of data model mapping because the MIB and YANG worlds specify conceptual objects differently. “Translation of Structure of Management Information Version 2 (SMIv2) MIB Modules to YANG Modules” (RFC 6643) might be of some help in creating the YANG module. In practice, new data structures are often created instead of using a mix of hand-edited (in case of MIB data naming misalignment with the YANG data structures or in case of writable objects) and auto-generated YANG modules. As an example, the YANG Interface Management (RFC 7223) followed this approach.

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