The YellowDog Platform is made up of several, modular microservices: allowing customers flexibility between business areas, use cases and even individual workloads. Customers can communicate with the YellowDog Platform via their preferred platform client.
These microservices perform the core functions related to workload management. They are clusterable, scalable and support multi-tenanted deployments both on-premise and in the cloud.
Our Account Service provides secure Identity and Access Management for the YellowDog Platform. We use best in class, secure Keyrings technology for the storage of cloud credentials.
Using military-grade AES-256 encryption, the user retains full control over sensitive access credentials. During automated operation, our system creates temporary, privilege and time constrained access to only execute the task at hand. Full auditing of accounts, identities and actions ensure traceability and accountability.
Our Object Store Service combines multiple distinct storage providers (e.g. Azure Blob, Amazon S3, Google Cloud Storage) across multiple providers and regions into one coherent data surface. This overcomes many of the data management constraints inherent in hybrid- and multi-cloud deployments.
Our Object Store Service segmentation and distribution of data improves the storage performance beyond that offered by a single Object Store. As our Object Store Service distributes the data across multiple buckets, the impact of any bandwidth limits are dispersed. This means that a cloud Object Store can be fast enough to boot an Operating System, or transfer assets at a speed that would otherwise require a high-end data transfer appliance.
Our Object Store Service also verifies effective data transfer, allowing faster and connectionless data transfer protocols to be used.
Our Image Service is a virtual machine image catalogue for all images across all regions and cloud providers.
This ensures that the right version of the image is matched to the right type of computing instance and Operating System in every region, in every cloud. This is imperative when the YellowDog Platform is automatically choosing the Best Source of Compute and when incompatibilities in the underlying instance type and Operating System would mean that applications and workloads underperform or fail. As a result, the tasks are completed faster and at a lower cost than any other third-party workload manager.
Our Compute Service is a common API to provision, manage and de-provision computing resources across multiple clouds and on-premise infrastructure. When combined with our Client Software Development Kits (SDKs), our Compute Service makes it quick and easy to orchestrate cloud and on-premise computing resources.
Out of the box connectors are available for:
Multiple deployment strategies are supported, including managing “fleets” of AWS Spot Instances and GCP pre-emptive instances.
With our Compute Service, strategies can be deployed to determine and provision the Best Source of Compute for workloads across multiple clouds. This could be the fastest deployment time, the lowest cost, the lowest environmental impact, or delivery to a deadline. It also means that business constraints can be adhered to; constraints such as data sovereignty, security certifications or environmental impact.
For intelligent computing resource management, our Compute Service can combine different strategies within a single Workload Requirement to achieve the ultimate efficiency and performance.
Intelligent placement is made by understanding:
Our Scheduler Service increases utilisation levels by sharing computing resources using fine grained control and prioritisation of tasks.
Scheduling workloads in a hybrid- and multi-cloud environment is significantly more complex than in a data centre based, single-system scheduler location. To provide robust and consistent performance, the scheduler must handle issues such as varying environmental characteristics (e.g. external factors impacting network or vCPU performance), greater asynchronicity of interactions, distributed resource management and ownership, dynamic resource availability, complex network topographies, and failures of both computing resources and network connections.
Our Scheduler Service is built from the ground up to handle these problems and results in efficient, reliable and well utilised computing resources.
Our Scheduler Service is also designed to complement any existing schedulers that may be implemented to enhance and improve their performance for hybrid- and multi-cloud deployments.
Our Scheduler Service is fully integrated with our Object Store Service so data is automatically supplied for tasks exactly when it is needed; and data output is captured, stored or provided as a form of data pipeline between tasks. This ensures that any dependencies between tasks and tasks groups are mapped, tracked and synchronised so that workloads are delivered effectively, regardless of where processing takes place.
Contact our team today to learn more or request a demo.
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