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- 2008 BuiltQ: Where would a scaled relational DB fall in the CAP theorem? If you have scaled SQL server with one DB for writes and multiple DBs for reads. Wouldn't there be a delay for data to be replicated from the write DB to the to other read databases? In which case isn't the data inconsistent? 
So where would a scaled relational DB fall in the CAP theorem? 
Update:
In relational DBs consistency means there wont be partial updates. For example if someone transfers money from one account to another and the whole thing is a part of one transaction, it wont happen that you take money out of one account but doesn't show up in another account.
In CAP theorem consistence means all the components see the same data. That consistency is different from consistency in ACID.
From what I know, relational DBs like SQL server are supposed to be CA (consistent and available). This would make sense if there is just one database. Because everyone would see the same data. But what if the SQL server is scaled with multiple databases? In that case would all databases still see the same data? If not, would it be consistent (in CAP theorem)?
My feeling is a scaled relational DB is AP (Available and partition tolerant) and not CA (Consistent and available). 

A: I've read different definitions of consistency in regards to the CAP theorem.


*

*Some definitions of consistency say that once some data is persisted in a system, all reads will read the most recently written data. In this definition, a replicated database (you call this "scaled" but I wouldn't use that term) has a risk of returning inconsistent data, if the replication is asynchronous. 
To mitigate this risk, some systems make sure replication is synchronous, or as close to synchronous as they can implement. Galera, for example, sends transaction write sets to its replicas synchronously. If you try to read from the replica, and it detects that there are write sets pending but not yet applied, it can block your read until it has caught up with the pending write sets (this behavior is configurable). So you'll never read data that is out of date.
The cost of maintaining perfectly consistent reads over distributed systems in this manner is usually more expensive than users want. It will become a performance bottleneck in a system that has a high rate of updates. So for practical reasons, most projects accept that "replication lag" is a necessary compromise.

*Other definitions of consistency are closer to atomicity, i.e. transactions will not be persisted in a partially-complete state. So all constraints will be satisfied when you read the data, whether you read the data before or after the transaction is applied. In this definition, it's quite easy to imagine the replica database instance remaining consistent, if it applies updates using the same transaction semantics used on the master. If you read data from the replica, you might read data that hasn't yet had the latest updates applied, but it will never be in an inconsistent state with respect to constraints.

A: There is nothing called a scaled RDBMS. We do have "RDBMS Clusters with shared storage": here can keep on adding nodes to achieve high availability of RDBMS.
In other words:
If you meant a "Distributed RDBMS" by mentioning "Scaled RDBMS" - it doesn't exist. You can have RDBMS on only one node. If you add another node, then that will be "another" RDBMS and it would NOT coalesce with the first one giving you a single view(unlike a typical NoSQL Database). Although, you can happily keep on adding storage nodes behind the RDBMS.
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Space is limited and specific instructions with a class linkOne of my regrets for C++ is that it doesn't have interface checking when you instantiate templates. Coupled with the delayed instantiation (the code of a method is not fully type checked until you use it), static type checking of template code has been a hit or miss. Also, when you do get a type error, it is incomprehensible, riddled with the instantiation details that shouldn't be there in the first place. Interface checking means that the compiler can do better type checking before template instantiation. Interface checking has been in development for some time (e.g. Boost Concept Check, ConceptCpp, N2773), but it didn't make into the C++11 standard.
Interface checking in most programming languages follow a fulfillment model where an interface specifies a collection of function method signatures, and if a class implements all the functions (fulfills all signatures), then it is said to implement the interface. This is the case for Java and Go language as well as C++ concept checking in development so far.
However, if I were to develop interface for a new language, I would choose a declarative model where a class has to explicitly declare the interface it intends to implement. The interface is uniquely identifiable in the program's namespace. The motivation is to prevent a class from unintentionally implementing an interface by coincidence.
This is especially important for C++ since many operators are overloaded. For example, a random access iterator looks a lot like an integral type at the interface level (in fact it is a super concept because you can dereference an iterator), but manipulating the iterator like an integral without observing begin() and end() will cause the iterator to go out of bounds.
This semantic gap can be bridged by a more precise type specification using dependent type (not to be confused with C++ dependent type, a class that is complete if and only if a template argument refers to a complete type; complete type here simply means the compiler knows its memory layout so you can do a sizeof(type), for example, to get its size), but we don't yet have an object oriented dependent type system with interface checking. Even if we can bridge the semantic gap, I argue that a declarative interface checking is not less powerful than fulfillment interface checking.
Suppose you have a class Foo that implements all the methods required for interface Xyzzy, but Foo doesn't declare it so. In the fulfillment model, Foo can be used to instantiate any template (generic) that requires interface Xyzzy, but not in the declarative model, which requires Foo to explicitly state that it implements interface Xyzzy. Even if you cannot modify the definition of Foo, all you need to do is to subclass Foo and declare that it implements Xyzzy, and pass it to the template.
Another idea I have (in the context of C++ concept checking at least) is to get rid of the distinction between a class and an interface. Any class can be used as an interface. That's because C++ allows declaration and implementation to be separate. Furthermore, when a class is said to implement another class, it does not mean the class is a subclass of the other class. The compiler will only check that the method signatures are congruent.<issue_start><issue_comment>Title: Add VMI event output
username_0: **What type of PR is this?**
/kind feature

**What this PR does / why we need it**:
Adds the VirtualMachineInstance Events to the CI output when CI fails to schedule a VM

**Does this PR introduce a user-facing change?**:
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