Embodiments for scaling services in a distributed network by registering bucket names for the services with a Domain Name Service (DNS) server. Buckets hold resources and distribution of buckets to servers is maintained using a Consistent Hashing Ring. Upon determining that services servers need to be added or deleted based on changes load conditions, leave/join events are managed by a Kubernetes event service and updates are propagated to all of the services by the membership service component. A service scaling process updates the mapping of buckets to the host name of the new service server. A resource request from a client is sent to the mapped bucket name, and a DNS resolver process sends it to the changed service server so that the client is completely unaware of this change in bucket ownership.

Systems, apparatuses, and methods are described for adjusting capacity in a networking environment. A networking system comprising clients, servers, load balancers, and/or other devices may expand and contract network capacity as needed. When expanding network capacity, load balancers may instruct client devices to connect to servers that are part of the expanded network. When network capacity is reduced, a server and/or a load balancer my instruct client devices to close a connection with a first server and establish a connection with a second server. Client devices may seamlessly begin using the connection with a second server without having to wait for a connection timeout with the first server.

The disclosure herein describes using a monitoring tool and a management tool from a cloud native system to monitor and manage an application executing on a legacy system. Network addresses of services running in the application on the legacy systems are discovered. Based on the discovered addresses, a probe is configured for execution on the legacy system by a monitoring tool deployed on the legacy system to obtain metrics data associated with the services running on the legacy system, the metrics data representing execution loads of the application. A management tool deployed on the cloud native system receives the obtained metrics data. The management tool compares the metrics data to one or more performance thresholds associated with the application. Based on the comparison, the management tool adjusts a quantity of instances of the application running on the cloud native system, enabling the cloud native system to share the execution loads.

Provided are a server for controlling data transmission through a data pipeline, and an operation method thereof. A pipeline control server is configured to create and dispose a data broker including a message queue, between a data source and a data sink according to a registration event of the data sink, and to provision an infra of the data pipeline, and an operation method thereof. A pipeline control server is configured to schedule an operation time point of a data dispersal pipeline that transmits data to a data sink based on an operation event of a data ingestion pipeline that transmits data from a data source to a data broker, and an operation method thereof.

Provided are a server for controlling data transmission through a data pipeline, and an operation method thereof. A pipeline control server is configured to create and dispose a data broker including a message queue, between a data source and a data sink according to a registration event of the data sink, and to provision an infra of the data pipeline, and an operation method thereof. A pipeline control server is configured to schedule an operation time point of a data dispersal pipeline that transmits data to a data sink based on an operation event of a data ingestion pipeline that transmits data from a data source to a data broker, and an operation method thereof.

A computer-implemented method for adapting connections between nodes of a layered network. The layered network comprises a plurality of nodes arranged in an ordered set of layers. The ordered set of layers comprises, in order, a core layer comprising a set of core nodes, a second layer comprising a set of second nodes, and one or more outer layers each comprising a respective set of outer nodes. Each core node is connected to at least one other core node. The method is performed by an adapting node, the adapting node being a node of the layered network that is connected to one or more second nodes and multiple core nodes. The method comprises, based on one or more network properties of the layered network, disabling a respective connection between the adapting node and at least one but not all of the multiple core nodes.

Techniques for implementing an infrastructure orchestration service are described. In some examples, a declarative provisioner of the infrastructure orchestration service receives instructions for deployment of a resource. The declarative provisioner identifies that the deployment of the resource is a long-running task stores state information corresponding to the deployment of the resource. In certain embodiments, upon identifying that the deployment of the resource is a long-running task, the declarative provisioner pauses its execution of the long-running task. Responsive to a trigger received from the infrastructure orchestration service, the declarative provisioner resumes execution of the deployment of the resource using the state information and transmits deployment information corresponding to the deployment of the resource to the infrastructure orchestration service.

Techniques for implementing an infrastructure orchestration service are described. In some examples, a declarative provisioner of the infrastructure orchestration service receives instructions for deployment of a resource. The declarative provisioner identifies that the deployment of the resource is a long-running task stores state information corresponding to the deployment of the resource. In certain embodiments, upon identifying that the deployment of the resource is a long-running task, the declarative provisioner pauses its execution of the long-running task. Responsive to a trigger received from the infrastructure orchestration service, the declarative provisioner resumes execution of the deployment of the resource using the state information and transmits deployment information corresponding to the deployment of the resource to the infrastructure orchestration service.

Techniques are disclosed for deploying a computing resource (e.g., a service) in response to user input. A computer-implemented method can include operations of receiving (e.g., by a gateway computer of a cloud-computing environment) a request comprising an identifier for a computing component of the cloud-computing environment. The computing device receiving the request may determine whether the identifier exists in a routing table that is accessible to the computing device. If so, the request may be forwarded to the computing component. If not, the device may transmit an error code (e.g., to the user device that initiated the request) indicating the computing component is unavailable and a bootstrap request to a deployment orchestrator that is configured to deploy the requested computing component. Once deployed, the computing component may be added to a routing table such that subsequent requests can be properly routed to and processed by the computing component.

Techniques are disclosed for deploying a computing resource (e.g., a service) in response to user input. A computer-implemented method can include operations of receiving (e.g., by a gateway computer of a cloud-computing environment) a request comprising an identifier for a computing component of the cloud-computing environment. The computing device receiving the request may determine whether the identifier exists in a routing table that is accessible to the computing device. If so, the request may be forwarded to the computing component. If not, the device may transmit an error code (e.g., to the user device that initiated the request) indicating the computing component is unavailable and a bootstrap request to a deployment orchestrator that is configured to deploy the requested computing component. Once deployed, the computing component may be added to a routing table such that subsequent requests can be properly routed to and processed by the computing component.