Introducing Methodology and System of Cloud Analysis Patterns (CAPS)

We wrote a short post about added complexities of virtualization almost 15 years ago and then about orbifold memory space (named cloud memory space initially) 10 years ago, reflecting cloud internals as a multi-VM/bare metal or multi-process distributed system.

At that time, memory dump analysis patterns were added for several types of memory space, including fiber bundle and manifold memory spaces, and we also held a webinar on cloud memory dump analysis:

In addition to the process/kernel dichotomy, managed space abstracts runtime environments such as .NET CLR.
This picture of complete and cloud spaces is somewhat simplified as it does not reflect the complexities of hypervisor types and some nested spaces, as in Hyperdumps.

Also, at that time, trace and log analysis patterns were being extensively developed and later split into general and special analysis patterns, resulting in the current overall picture:

Memory dump types we can get from VM and traditional OS concepts such as threads and processes that span memory spaces are shown in this picture (spanning means that information about them can be found in all those memory dumps and associated spaces):

If we consider native cloud space as additional abstraction beyond the simple collection of memory spaces, we get the new native cloud memory space with corresponding cloud equivalents for traditional OS concepts:

The advent of container orchestration platforms such as Kubernetes provides a similar hierarchy of concepts with containers corresponding to threads as units of execution, pods to processes as resource containers, kernel to control plane and kubelets, and operators to device drivers:

From the traditional memory perspective, Kubernetes concepts cut across the same spaces since they are implemented as collections of processes:

Our next step here is to adapt memory analysis pattern language to native cloud diagnostics and cloud problem analysis and provide analysis pattern specializations. The other part of software diagnostics, trace analysis pattern language, naturally extends to native cloud analysis, but from container environments, we recently discerned a few new log analysis patterns we plan to publish soon.

For the orchestration abstraction, we may add cluster space for nodes and pods in place of complete space and replace orbifold memory space with the native cloud space:

In the diagram above, nodes, containers, and pods have a different conceptual meaning instead of memory. They are more like spaces of relations between various objects/structures than spaces of objects/structures like memory spaces.

Now, having all these new abstract spaces, the next step is to consider this diagram where we replaced memory analysis patterns altogether with cloud analysis patterns:

Memory analysis patterns are not gone but are at the lower level of abstraction, where individual spaces for cloud analysis patterns may require analysis of specific memory spaces if necessary. It is possible to represent both abstractions as Trace Quilt:

This description is preliminary and may have some modifications in the future. The corresponding analysis pattern language catalog is being developed now.