OpenStack Telemetry

OpenStack Telemetry
Name	OpenStack Telemetry
Developer	OpenStack Foundation
Initial release	2012
Programming language	Python
Operating system	Cross-platform
License	Apache License 2.0

OpenStack Telemetry is a cloud telemetry service project that provides metering, monitoring, and alarming for cloud infrastructure. It originated within the OpenStack ecosystem to collect usage data, resource metrics, and events from compute, storage, and networking services to support billing, capacity planning, and operational observability. The project integrates with a broad array of OpenStack projects, third-party monitoring systems, and orchestration tools to enable multi-tenant telemetry in public, private, and hybrid cloud deployments.

Overview

OpenStack Telemetry sits alongside projects such as Nova (software), Neutron (software), Cinder (software), Glance (software), Keystone (OpenStack), Horizon (OpenStack), Swift (software), Heat (software), and Ceilometer (OpenStack) in the OpenStack family, focusing on measurement and event collection. It provides services for metric aggregation, sample storage, alarm evaluation, and notification to external systems like Nagios, Prometheus, Graphite, Elasticsearch, InfluxDB, and Grafana. The project supports use cases including billing integration with vendors such as SAP, Oracle Corporation, IBM, Microsoft, and Amazon Web Services, and orchestration linkages to Kubernetes, Docker, and Mesos deployments.

History and Development

Telemetry capabilities emerged as part of early OpenStack efforts in conjunction with contributors from organizations like Rackspace, NASA, Red Hat, Canonical (company), HP Inc., Intel Corporation, Cisco Systems, Bloomberg L.P., and Mirantis. The initiative paralleled development histories involving events such as OpenStack Summit gatherings, governance decisions by the OpenStack Foundation, and collaborations among vendors such as Dell Technologies, Fujitsu, Huawei, VMware, SUSE, and Alibaba Group. Influential design discussions referenced standards and protocols championed at bodies like the Internet Engineering Task Force and interoperability workshops that included participation from Mozilla Foundation and Google LLC engineers. Over successive release cycles, the project evolved through interaction with research efforts at institutions such as Massachusetts Institute of Technology, Stanford University, Carnegie Mellon University, University of California, Berkeley, and Princeton University.

Architecture and Components

The Telemetry architecture comprises collectors, agents, publishers, storage backends, and alarm evaluators that interface with compute, block, and networking services including KVM, Xen (software), QEMU, Open vSwitch, and DPDK. Key components were designed to interoperate with identity and messaging systems such as RabbitMQ, Apache Kafka, ZeroMQ, and OAuth 2.0 frameworks implemented by Keycloak. The system's modular design echoes architectural patterns from projects like Apache Cassandra, MongoDB, Hadoop, Spark, and Ceph, allowing horizontal scaling and high-availability deployments compatible with orchestration frameworks like Ansible, Puppet (software), Chef (software), and Terraform.

Data Collection and Telemetry Agents

Data collection relies on agents and plugins that run on hypervisors, storage nodes, and bare-metal servers. Agent implementations were influenced by monitoring agents from Collectd, Telegraf, Sensu, Datadog, and New Relic, and integrate with hardware management APIs such as IPMI and Redfish. Plugins collect metrics from Linux kernel subsystems, libvirt, iSCSI, NVMe, and networking stacks, forwarding samples via message buses to processing pipelines. Vendors including Supermicro, HPE, Lenovo, Broadcom, and Marvell Technology provided ecosystem support for telemetry agents in commercial distributions.

Data Storage and Indexing

Telemetry supports pluggable storage backends for time-series and event data, leveraging systems like InfluxDB, Prometheus TSDB, Graphite Carbon, OpenTSDB, Druid (data store), Elasticsearch, Apache HBase, and Cassandra (database). Indexing strategies borrow techniques from search and analytics engines such as Lucene, Solr, and Elasticsearch to enable tag-based queries, aggregation, downsampling, and rollup. Storage configurations are designed to interoperate with distributed filesystem solutions from Ceph (software), GlusterFS, NFS, and cloud object stores including Amazon S3, Google Cloud Storage, and Azure Blob Storage.

APIs, Querying, and Integration

Telemetry exposes RESTful APIs and notification endpoints compatible with API conventions used by OpenStack API, OAuth 2.0, and OpenID Connect, enabling integrations with orchestration platforms like Heat (software), TOSCA tooling, and service management systems including ServiceNow and JIRA (software). Querying and aggregation capabilities are designed to interoperate with analytics stacks such as Apache Spark, Presto (software), Trino (software), Apache Flink, and Apache Beam, enabling complex event processing pipelines. The project supports telemetry export to cloud management and billing systems used by Verizon Communications, Deutsche Telekom, Orange S.A., and BT Group.

Use Cases and Deployments

Common use cases include chargeback and billing, capacity planning, SLA monitoring, autoscaling policies, root cause analysis, and compliance reporting. Deployments span telecommunications carriers like AT&T, T-Mobile, Vodafone, hyperscalers including Google Cloud Platform, Microsoft Azure, and private cloud adopters in finance such as Goldman Sachs, JPMorgan Chase, Morgan Stanley, and media companies like Netflix. Telemetry functionality has been embedded in edge computing scenarios involving 5G, IoT, and content delivery networks managed by providers such as Akamai Technologies and Fastly.

Security and Privacy Considerations

Security practices address multi-tenancy isolation, role-based access control via Keystone (OpenStack), encryption in transit using TLS, and encryption at rest leveraging key management solutions like HashiCorp Vault and AWS Key Management Service. Privacy and compliance efforts intersect with regulatory frameworks such as General Data Protection Regulation, Health Insurance Portability and Accountability Act, and audit regimes common to enterprises like Deloitte, PricewaterhouseCoopers, and KPMG. Operational security integrates logging and incident response workflows compatible with platforms such as Splunk, Elastic Stack, and Snyk.

Category:OpenStack