Spotlight on Tech

Stateful Edge Computing

Brooke Frischemeier
Head of Product Management, Unified Cloud
Rakuten Symphony
November 1, 2022
minute read

Edge cloud enables operators, enterprises, application developers and content providers to deploy predictable cloud-computing capabilities at the network’s edge, in the immediate proximity of their businesses, as well as mobile networks. As the industry moves into the subsequent phases of 5G rollout and Industry 4.0, “stateful edge” will be a key enabler for enterprises and operators who need to deliver efficiency at the edge, over a number of new services, with lower latency, strict Quality of Service (QoS) and high availability.

Why deploy at the Edge?

  • Provides immediate, lower-latency decision-making without the need for data retrieval or storage over slow WAN links.
  • Enables edge processing efficiencies.
    -   Reduces the amount of active and backup data that needs to be warehoused in a core datacenter.
    -   Reduces WAN utilization and costs associated with remote data storage.
  • Provides data affinity with the region or location the data is being used.
  • Paves the way for low-cost, low-power hyper-converged equipment.

What is “Stateful” Edge?

Before we discuss stateful, let’s first give an example of more simple, stateless applications. “Stateless” applications typically provide a single function, for example, a print server, a basic calculator, or an old-school web search. Furthermore, stateless application transactions do not need to understand or retain any information about a prior transaction to perform the current transaction. In other words, no preexisting conditions or states impact their function. On the other hand, a “stateful” application, such as a bank transaction, does care about preexisting conditions or states. Therefore, it needs to have a “persistent” relationship with its data and users as it scales, migrates, stops, starts and heals.

The list of stateful edge applications is growing as we see innovation in 5G, the Internet of Things (IoT), Industry 4.0, self-driving vehicles, smart cities, video analytics, customized content delivery, security and self-healing networks.

Common Edge Challenges

Stateful edge inherits all of the challenges we associate with orchestrating numerous edge clouds at scale to:

  • Provide lifecycle management of 10,000s (bare-metal servers to NFs, applications and services) of edge nodes and unify them back to the core cloud.
  • Eliminate resource silos with the capability to share resources among multiple cloud technologies.
  • Eliminate operations silos, as a unified operations model is required under the cover, not just a single-pane-of-glass administrative GUI; multiple cloud platforms should not be necessary (e.g., VMs and containers).
  • Effectively monitor the entire solution as a whole and correlate that data to actionable policies.
  • Allow multiple organizations and DevOps to collaborate securely.
  • Support multitenancy with secure user groups and resources.
  • Efficiently use edge resources, low-footprint platforms and data schemes.

While all of these are well known, stateful edge applications provide additional challenges that others cannot support.

Additional challenges found in Stateful Edge

It is no secret that the vast majority of applications are being rolled out on Kubernetes (K8s). But what is not as well known is that vanilla K8s was not designed for stateful applications as they were originally targeted at simple web-scale applications. Stateful applications require more and must provide not only persistent relationships between users and applications but also persistent relationships between applications and the data they use.  

In the past, relationships between data and applications were simple. Prior to K8s, there was a simple direct mapping between data and an application running on bare metal or in a virtual machine. But with K8s innovation comes added complexity. K8s applications are broken up into many micro-services and mapped to different containers, each with a different relationship to the data, as they grow, scale, migrate and heal. This means the data can have a state, but the condition of your K8s containers and micro-services also have a given state that can change the moment they are deployed.  

To complicate the problem, most clouds are running off their legacy storage, where K8s applications and their data are mapped to one another via a “simple” Container Storage Interface (CSI). On one end is the data, for example, a storage array with a CSI, and it sees a generic connection to some downstream node. The array controller does not see or even comprehend the application or the K8s container constructs. On the other end, the application only sees a generic volume and has no notion of what kinds of media make up the storage, where they are located, or how they all fit together in the system.

It is all very generic, as neither side of the generic CSI has the visibility to understand the complexity of the other side. This not only severely limits efficiency and performance but also impacts how one can configure the combined solution for data protection, recovery, quality of service, workload-to-storage affinities and lifecycle automation. Each of these impacts user experience, platform efficiencies, as well as data protection and recovery automation. This disparity is even more exacerbated when one attaches to a volume that spans multiple media types. At the very least, vanilla K8s and a generic CSI hamstring the service designer and the user.

Symworld™ Cloud leads the way forward in Stateful Edge

To sum things up to this point, while cloud-native K8s allows one to scale and enhance performance by leaps and bounds, the relationship between storage and application becomes more complex when it comes to data protection.

  • In cloud-native, the application is no longer a homogenous blob as before.
  • All of its roles are exposed individually.
  • There are multiple containers per role, with their own data needs and connectivity.
  • The containers scale independently and are constantly changing.
  • There is storage, network and compute connectivity to understand.
  • There are application config data, Kubernetes config data, secrets, metadata and Config Maps.

All of these have to relate to storage in their way, and it is constantly changing.

Symworld Cloud Native Storage (CNS)

CNS understands, auto-learns and auto-adapts to all application and data permutations. Backups, snapshots, cloning and DR are all applications, and K8s state aware.

Some other vendors claim K8s-application awareness, but they require manual-intensive tagging and marking over the lifetime of the application. They also need Kubernetes expertise. With CNS, we auto-ingest the application from its Helm chart, YAML file, or operator, then auto-discover it, auto-monitor it and adapt its changes over its entire lifecycle. Fully automated forever and way easier to use, CNS needs no Kubernetes expertise.

CNS provides programmable pre- and post-processing policies that auto-adjust to target environments and can even renumber IP addresses when cloning so there are no network clashes. Furthermore, there is automated storage placement based on easy-to-configure policies and IOPs-based storage QoS.

CNS includes industry-leading, software-defined storage that supports a comprehensive set of application-aware services, including snapshots, clone, backup, encryption and business continuity. All data services are application-aware, tracking not only data storage but metadata and the ever-changing Kubernetes application config, protecting a wide range of datasets for “application-consistent” disaster recovery of complex network- and storage-intensive stateful applications.

Symworld Cloud Native Platform (CNP): A revolutionary cloud platform

Rakuten Symphony’s best-of-breed Kubernetes-based CNP combines one-click application onboarding with declarative, context-aware workload placement, pinning your applications and services to automated policies. Just tell CNP what resources and supporting applications your service needs, and it will auto-discover and configure them for you, as per your policy, over the entire automated lifecycle of the service, providing all of the storage and IP address persistency needed. Add, stop, start, heal and migrate with automated ease.

With CNP, resources are modeled on numerous NUMA-aware options, including memory, CPU cores, Huge Pages, overlay/underlay networks, and redundancy, applying affinity and anti-affinity rules as needed. This also extends into the compute and storage placement and locality, with persistent addressing.

Symworld Orchestrator: Orchestration, automation, and lifecycle management

Orchestrator orchestrates and manages the lifecycle of any workflow, including bare-metal provisioning, cloud platform instantiation, network functions (NF) lifecycle management, network services (NS) lifecycle management, and Methods Of Procedures (MOPs). All of these can be triggered through a policy engine. Orchestrator’s automated workflows support cloud-native network functions (CNF), virtual network functions (VNF), and 3rd party physical network functions (PNF) simultaneously. All of this comes with a full stack observability suite and planning tools.

Orchestrator provides intuitive context-aware lifecycle management for your NFs, services, 3rd party applications and Kubernetes cloud platform. It also integrates those workflows with your physical platforms, like bare-metal servers and third-party appliances.

The Symworld™ Cloud Advantage

Symworld Cloud solves all of the significant stateful edge cloud concerns, unifying edge to the core with the following capabilities:

  • Advanced stateful application and storage with full lifecycle automation capabilities.
  • Automated DR for complex, stateful, and edge applications.
  • Ease of management for 1,000,000s of edge nodes with one-click automation.
    -   Move from test to secure deployment rapidly and easily.
    -   DevOps – CI/CD/CT integration.
  • Full solution observability.
    -   Bare-metal, clusters, applications, services.
    -   Event correlation.
  • Low footprint for:
    -   Edge cloud platform that scales up and down.
    -   Cloud-native, K8s-aware storage services and data.
  • Container and VM support without operations or resource silos – one system, same operations tools and paradigms.
  • Multitenancy and granular role-based access.
  • Policy-driven design – not manual.
    -   Allow the user to easily define policies that eliminate hunting and hardcoding.
    -   Multi-domain policy control – that correlates things we don’t regularly associate with cloud platforms, switches, SDx controllers, transport.
    -   Network slicing for 5G use cases (cloud and transport).
  • Secure operation.
    -   Block access between namespaces.
    -   Isolate resources.
    -   Enforce usage quotas.
    -   Restrict networking access.

For more information on our stateful edge solution advantages and other 5G-related automation and orchestration solutions, check out our Orchestrator page here.

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