It’s a high-level language made for modeling and validating cloud topologies using reusable and extensible objects. It allows architects to focus on application design and requirements without being bogged down by the ever-changing specificities of cloud platforms, while also allowing engineers to provide rich, up-to-date integrations with those platforms.
TOSCA is so complicated! Help!
I know, right? Now imagine writing a parser for it… Not only is it a complex language, but the specification itself (as of version 1.3) has contradictions, errors, and gaps.
Please join OASIS’s TOSCA community to help improve the language!
Meanwhile, Puccini includes examples of TOSCA’s grammatical features with some running commentary. Treat them as your playground. Also, if you have 4 hours to spare, grab some snacks, get comfortable, and watch the author’s free online course for TOSCA 1.0: part 1, part 2.
(Author’s note: This is my second take at writing a TOSCA parser. The first was AriaTosca, an incubation project under the Apache Software Foundation. I am grateful to Cloudify for funding much of the AriaTosca project. Note, however, that Puccini is a fresh start initiated by myself with no commercial backing. It does not use AriaTosca code and has a radically different architecture as well as very different goals.)
Can Puccini deploy the same TOSCA to either Kubernetes, OpenStack, AWS, Azure, etc.?
If you didn’t plan it that way, then: no. Firstly, Puccini is not an orchestrator. (It’s “BYOO” = “Bring Your Own Orchestrator”). Secondly, creating portable TOSCA may be less useful than expected.
Many orchestrators come with a variety of adapters or plugins to support various cloud platforms coupled with a very specific approach to portability. For example, Ansible’s inventory plugin mechanism can generate a list of host addresses from various cloud sources. You could thus run the same playbook on virtual machines deployed on OpenStack, AWS, baremetal, etc.
But what would portability mean for TOSCA? If your goal is to use TOSCA to generate that inventory, for example with Puccini’s Ansible inventory plugin, then how would you create your TOSCA topology template for it to be portable? What would be the node types?
The best answer would be to use types that are appropriate for your cloud platform, that directly model its compute, networking, storage, etc. resources. So, just like you would use a different Ansible inventory plugin for each cloud platform you are targeting, you would have a different TOSCA service template for each cloud platform.
However, if your desire is to use a single TOSCA service template for all clouds, how would you model it? Your node types would have to match the lowest common set of features for all cloud platforms and nothing more. You could not use any platform-specific feature without breaking portability.
Until TOSCA version 1.3 the specification came with an implicit Simple Profile (as well as a Simple Profile for NFV) that intended to be exactly that: a set of agnostic models for compute, networking, and storage resources that all cloud platforms were presumed to have.
Unfortunately, this approach didn’t work well in practice, for several reasons. Firstly, because cloud platforms are just too different, even in terms of the basics of how they model simple resources. Secondly, because any non-trivial workload would want to leverage platform-specific features. Indeed that is the competitive advantage and indeed a reason to choose one platform over another. Thirdly, because some platform-specific features are non-optional. In such cases the “portable” TOSCA would have to be supplemented with extra artifacts required by each cloud platform, such that though you would have some shared TOSCA you would still need to maintain some platform-specific code, compromising on the goal of true portability.
And so TOSCA 2.0 no longer comes with a normative Simple Profile and does not commit to an expectation for transparent portability. That said, nothing is stopping you from trying anyway. Perhaps you can come up with a better set of portable models than those of the Simple Profile. It’s just not a goal for TOSCA 2.0 and not a goal for Puccini.
The value proposition of TOSCA is not “write-once-run-everywhere” portability but “use the same language and tooling everywhere”, and the value proposition of Puccini is to provide some of that toolchain.
Go is fast becoming the language of choice for cloud-native solutions. It has the advantage of producing very deployable executables that make it easy to containerize and integrate. Go features garbage collection and easy multi-threading (via lightweight goroutines), but unlike Python, Ruby, and Perl it is a strictly typed language, which encourages good programming practices and reduces the chance for bugs.
Our chosen ECMAScript engine is goja, which is 100% Go and does not require any external dependencies.
puccini-tosca compile my-app.yaml | python myprocessor.py
Also check out yq, a great little tool for extracting YAML and even performing simple manipulations. Example:
puccini-tosca compile examples/tosca/requirements-and-capabilities.yaml | yq eval '.vertexes.|select(.properties.name=="light12")' -
Can I use text templates instead of TOSCA functions like
TOSCA’s avoidance of templating is deliberate. Unlike some tools (see Helm), YAML is not treated as plain text to be manipulated by an anemic text templating language, but rather as a representation of a semantic structure.
That said, nothing is stopping you from using templates. You can pipe the TOSCA or Clout to and from the tool of your choice at any point. Just bote the proper escaping of quotation marks to avoid invalid YAML. Also remember that indentation in YAML is significant, so it can be tricky to insert blocks into arbitrary locations. Generally, using text templating to manipulate YAML is not a great idea for these reasons.
Here’s an example using gomplate:
puccini-tosca compile my-app.yaml | gomplate
my-app.yaml can then include template expressions, such as:
If you insist on text templating, a useful convention for your toolchain could be to add a file
extension to mark a file for template processing. For example,
.yaml.j2 could be recognized as
requiring Jinja2 template processing, after which the
.j2 extension would be stripped.
Can I compose a single service from several interrelated Clout files?
TOSCA has a feature called “substitution mapping”, which is useful for modeling service composition. It is, however, a design feature. The implementation is up to your orchestration toolchain. See our examples here and here.
Puccini intentionally does not support service composition. Each Clout file is its own graph universe. If you need to create graph edges between vertexes in one Clout file and vertexes in other Clout files, then it’s up to you and your tools to design and implement that integration. The solution could be very elaborate indeed: the two Clouts might represent services with very different lifecycles, that run in different clouds, that are handled by different orchestrators. And the connection might require complex networking to achieve. There’s simply no one-size-fits-all way Puccini could do it—namespaces? proxies? catalogs? repositories?—so it insists on not having an opinion.
Why is it called “Puccini”?
Giacomo Puccini was the composer of the Tosca opera (based on Victorien Sardou’s play, La Tosca), as well as La bohème, Madama Butterfly, and other famous works. The theme here is orchestration, orchestras, composition, and thus operas. Capiche?
How to pronounce “Puccini”?
For a demonstration of its authentic 19th-century Italian pronunciation see this clip.