C++ Actor Framework VS dapr

CAF

I'd like to mention the native actor model implementation CAF, the C++ Actor Framework, and share some experiences. (Disclaimer: I've been developing on CAF in the past and have a good relationship with the creator.) CAF (1) provides native actors without an VM layer, (2) type-safe interfaces so that the compiler yells at you when a receiver cannot handle a message, and (3) transparent copy-on-write messaging so that you can still push stuff through pipelines and induce only copies only when a ref count is greater than one.

In our telemetry engine VAST, we've been using CAF successfully for several years for building a distributed system that always has a saturated write path. CAF provides a credit-based streaming abstraction as well, so that you can have backpressure across a chain of actors, making burst-induced OOM issues a blast from the past. You also get all the other benefits of actors, like linking and monitoring, to achieve well-defined failure semantics: either be up and running or collectively fail, but still allowing for local recovery—except for segfaults, this is where "native" has a disadvantage over VM-based actor models.

With CAF's network transparent runtime, a message ender doesn't need to know where receiver lives; the runtime either passes the message as COW pointer to the receiver or serializes it transparently. Other actor model runtimes support that as well, but I'm mentioning it because our experience showed that this is great value: we can can slice and dice our actors based on the deployment target, e.g., execute the application in one single process (e.g., for a beefy box) or wrap actors into single OS processes (e.g., when deploying on container auto-scalers).

The deep integration with the C++ type system allowed us to define very stable RPC-like interfaces. We're currently designing a pub/sub layer as alternate access path, because users are interested in tapping into streaming feeds selectively. This is not easy, because request-response and pub/sub are two ends of a spectrum, but it turns out we can support nicely with CAF.

Resources:

- CAF: https://github.com/actor-framework/actor-framework

- VAST: https://tenzir.github.io/vast/docs/understand-vast/actor-mod... (sorry for the incompleteness, we're in migration mode from the old docs, but this page is summarizing the benefits of CAF for us best)

- Good general actor model background: http://dist-prog-book.com/chapter/3/message-passing.html#why...

VAST is a flight recorder and security content execution engine. On the one hand, there exists a continuous stream of high-volume data sources (such as network telemetry as NetFlow, Zeek, Suricata, and endpoint telemetry). On the other hand, VAST processes needle-in-haystack queries to provide answers to questions like "has this threat been relevant to us 8 months ago?", and supports threat hunters with an interactive query capability to explore the data. From an engineering perspective, we focus especially on the separation of read and write path, concurrent message passing in an actor model runtime (CAF), and leveraging open standards, like Apache Arrow, to establish a high-bandwidth data plane for sharing data with downstream tooling. A flexible plugin API enables additional security-specific use cases on top, such as realtime matching of threat intelligence or mining of asset data for passive inventorization.

Technologies: Apache Arrow, Flatbuffers, C++ Actor Framework, Linux, Docker, Kubernetes

Dapr provides a set of building blocks that abstract concepts commonly used in distributed systems. This includes secured synchronous and asynchronous communication between services, caching, workflows, resiliency, secret management and much more. Not having to implement these features yourself eliminates boilerplate, reduce complexity and allows you to focus on developing your business features.

Diagrid Catalyst is a Developer API platform providing a brand-new approach to distributed application development. Using the Catalyst APIs, powered by the Dapr open source project, developers can overcome the complexity of rewriting common software patterns and achieve higher productivity by offloading infrastructure concerns from their code to Catalyst.

The following two examples are open-source projects maintained by Fermyon with contributions from companies like Microsoft and SUSE. The first is Spin, which allows us to use WebAssembly to create Serverless applications. The second, SpinKube, combines some of the topics I'm most excited about these days: WebAssembly and Kubernetes Operators :) The official website says, "By running applications in the Wasm abstraction layer, SpinKube offers developers a more powerful, efficient, and scalable way to optimize application delivery on Kubernetes." By the way, this post shows how to integrate SpinKube with Dapr, another technology I'm very interested in, and I should write some posts soon.

Speaking of this has anyone had much experience with Dapr (https://dapr.io/) before?

I always thought this was a particularly interesting approach from Microsoft where they use this pattern to essentially take the complexity of micro services and instead try and keep it as simple as a normal .NET application but (and I think this is the clever part) in both a vendor and language neutral way.

But all of a sudden it means you can start removing all kinds of cruft and random SDKs from your codebase and push almost all of your interactions with the outside world into something like this .

Azure Container Apps hosting of Azure Functions is a way to host Azure Functions directly in Container Apps - additionally to App Service with and without containers. This offering also adds some Container Apps built-in capabilities like the Dapr microservices framework which would allow for mixing microservices workloads on the same environment with Functions.

Having containers is nice but everything (well ... nearly everything 😉) gets better with Dapr as an outstanding tool for app development in the container-based area. Here we go what might be worth a look:

Anyone using or planing to use darp Distributed application platform runtime as a microservices platform? https://dapr.io/

A CNCF project, the Distributed Application Runtime (Dapr) provides APIs that simplify microservice connectivity. Whether your communication pattern is service to service invocation or pub/sub messaging, Dapr helps you write resilient and secured microservices. Essentially, it provides a new way to build microservices by using the reusable blocks implemented as sidecars.

Dapr is a runtime that implements common patterns such as pub/sub, state storage, etc. It runs as a sidecar to your app. Your app then interfaces with it using an sdk or http calls to use said patterns instead of implementing those patterns directly yourself. Seems pretty cool to me, but you can find out more at https://dapr.io/.