Glossary

Communication protocol that enables AI agents to discover, coordinate with, and delegate tasks to other agents in a distributed system.

The A2A protocol allows agents to work together by sharing capabilities, coordinating workflows, and distributing complex tasks across multiple specialized agents. It provides standardized messaging, capability discovery, and task delegation mechanisms for multi-agent systems.

Infrastructure layer that enables AI agents to discover, connect to, and interact with data sources and tools through standardized protocols.

The Agentic Data Plane provides the underlying infrastructure for AI agents to access streaming data, invoke tools, and coordinate operations across distributed systems using protocols like MCP and A2A.

An autonomous program that uses AI models to interpret requests, make decisions, and interact with tools and data sources.

AI agents can understand natural language instructions, reason about tasks, invoke tools through MCP servers, and coordinate multiple operations to accomplish complex workflows.

A credential used specifically for authenticating AI agents and authorizing their access to resources in agentic systems.

AI tokens are specialized authentication credentials for AI agents, distinct from bearer tokens used in traditional API authentication. They enable agents to authenticate with MCP servers and access data plane resources while maintaining audit trails of agent operations.

The maximum amount of text (measured in tokens) that an LLM can process in a single request.

The context window determines how much information an agent can consider at once, including the system prompt, conversation history, tool outputs, and retrieved documents. Larger context windows enable more sophisticated reasoning but may increase latency and cost. Common sizes range from 8K to 200K+ tokens.

The most advanced and capable AI models available, representing the current state-of-the-art in language understanding and reasoning.

Frontier models are cutting-edge large language models with exceptional reasoning, planning, and problem-solving capabilities. Examples include GPT-4, Claude 3, and Gemini Ultra. These models are commonly used to power sophisticated AI agents that require advanced decision-making and tool orchestration.

An AI model trained on vast amounts of text data that can understand and generate human-like text, reason about tasks, and follow instructions.

Large language models power AI agents by providing natural language understanding, reasoning capabilities, and the ability to plan and execute complex tasks. LLMs interpret user requests, decide which tools to invoke, and synthesize responses based on retrieved data.

An AI application or agent that connects to MCP servers to discover and invoke tools.

MCP clients use the Model Context Protocol to communicate with MCP servers, discovering available tools, understanding their capabilities, and invoking them with appropriate parameters. The client handles authentication, request formatting, and response processing.

A service that exposes tools and resources using the Model Context Protocol, allowing AI agents to discover and invoke them.

MCP servers act as bridges between AI agents and external systems, providing standardized interfaces for tool discovery, invocation, and resource access.

A standardized protocol that enables AI agents to connect with external data sources and tools in Redpanda.

MCP provides a consistent interface for AI applications to discover and interact with data sources, services, and computational tools through Redpanda infrastructure.

The ability to understand a system’s internal state by examining its external outputs, such as traces, metrics, and logs.

In Redpanda’s agentic systems, observability enables debugging agent behavior, monitoring performance, analyzing execution flow, and identifying bottlenecks through transcripts captured in the redpanda.otel_traces topic.

Open-source observability framework that provides standardized APIs, libraries, and tools for capturing and exporting telemetry data.

OpenTelemetry provides standardized APIs for capturing traces, metrics, and logs from applications. Redpanda agents and MCP servers automatically emit OpenTelemetry traces to the redpanda.otel_traces topic to provide complete observability into agentic system operations.

Standard protocol for encoding and transmitting telemetry data defined by the OpenTelemetry project.

OTLP is the OpenTelemetry Protocol specification for encoding and transmitting telemetry data. Redpanda stores spans in the redpanda.otel_traces topic using a Protobuf schema that closely follows the OTLP specification.

Natural language instructions or context provided to an LLM to guide its behavior and responses.

Prompts are the primary way to communicate with LLMs and AI agents. They can include instructions, examples, context, and questions that guide the model’s reasoning and output. Effective prompt design is critical for agent performance and reliability.

A single unit of work within a trace representing one operation, such as a data processing operation or an external API call.

Spans are organized in the Redpanda UI as parent-child relationships that show how operations flow through the system. Each span captures details about a specific operation, including timing, status, and metadata.

A specialized AI agent that handles specific tasks or domains as part of a larger multi-agent system.

Subagents are autonomous components within a multi-agent architecture that have focused expertise in particular domains or operations. They communicate with a parent agent or other subagents to accomplish complex workflows that require coordination across multiple specializations.

Initial instructions that define an agent’s role, capabilities, and behavioral guidelines.

The system prompt is provided at the start of an agent session and establishes the agent’s identity, available tools, operating constraints, and response style. It remains active throughout the conversation and shapes all subsequent agent behavior and decision-making.

The process of an AI agent executing an MCP tool to perform a specific operation.

Tool invocation occurs when an agent determines that it needs to use a tool, formats the request with appropriate parameters, sends it to the MCP server, and processes the response. Each invocation is captured in transcripts as spans for observability and debugging.

The complete lifecycle of a request captured as a collection of spans, showing how operations relate to each other.

A trace represents the complete lifecycle of a request (for example, a tool invocation from start to finish). A trace contains one or more spans organized hierarchically, showing how operations relate to each other.

Complete observability record of agent or MCP server operations captured as OpenTelemetry traces and stored in the redpanda.otel_traces topic.

Transcripts capture tool invocations, agent reasoning steps, data processing operations, external API calls, error conditions, and performance metrics. They provide a complete record of how agentic systems operate, enabling debugging, auditing, and performance analysis.

Features in beta are available for testing and feedback. They are not supported by Redpanda and should not be used in production environments.

Bring Your Own Cloud (BYOC) is a fully-managed Redpanda Cloud deployment where clusters run in your private cloud, so all data is contained in your own environment. Redpanda handles provisioning, operations, and maintenance.

A Bring Your Own Virtual Network (BYOVNet) cluster allows you to deploy the Redpanda data plane into your existing Azure VNet to fully manage the networking lifecycle. Compared to standard BYOC, BYOVNet provides more security, but the configuration is more complex.

A Bring Your Own Virtual Private Cloud (BYOVPC) cluster allows you to deploy the Redpanda data plane into your existing VPC on AWS or GCP to fully manage the networking lifecycle. Compared to standard BYOC, BYOVPC provides more security, but the configuration is more complex.

Enables Redpanda to integrate with external systems, such as databases.

This part of Redpanda Cloud enforces rules in the data plane, including cluster management, operations, and maintenance.

This part of Redpanda Cloud contains Redpanda clusters and other components, such as Redpanda Console, Redpanda Operator, and rpk. It is managed by an agent that receives cluster specifications from the control plane. Sometimes used interchangeably with clusters.

Containing all your data in your environment.

With BYOC, Redpanda handles provisioning, monitoring, and upgrades, but you manage your streaming data without Redpanda’s control plane ever seeing it. Additionally, with BYOVPC, the Redpanda Cloud agent doesn’t create any new resources or alter any settings in your account.

A fully-managed Redpanda Cloud deployment option where you host your data in Redpanda’s VPC, and Redpanda handles provisioning, operations, and maintenance. Dedicated clusters are single-tenant deployments that support private networking (for example, VPC peering to talk over private IPs) for better data isolation.

Features in limited availability (LA) are production-ready and are covered by Redpanda Support for early adopters.

A single configuration file running in Redpanda Connect with an input connector, an output connector, and optional processors in between. A pipeline typically streams data into Redpanda from an operational source (like PostgreSQL) or streams data out of Redpanda into an analytical system (like Snowflake).

A fully-managed data streaming service deployed with Redpanda Console. It includes automated upgrades and patching, backup and recovery, data and partition balancing, and built-in connectors. Redpanda Cloud is available in Serverless, Dedicated, and Bring Your Own Cloud (BYOC) deployment options to suit different data sovereignty and infrastructure requirements.

The web-based UI for managing and monitoring Redpanda clusters and streaming workloads. You can also set up and manage connectors in Redpanda Console. Redpanda Console is an integral part of Redpanda Cloud, but it also can be used as a standalone program as part of a Redpanda Self-Managed deployment.

An MCP server hosted in your Redpanda Cloud cluster. It exposes custom tools that AI assistants can call to access your data and workflows.

For more information, see redpanda-cloud:ai-agents:mcp/remote/overview.adoc.

A container for Redpanda Cloud resources, including clusters and networks. You can rename your default resource group, and you can create more resource groups. For example, you may want different resource groups for production and testing.

Serverless is the fastest and easiest way to start data streaming. You host your data in Redpanda’s VPC, and Redpanda handles automatic scaling, provisioning, operations, and maintenance.

Exports data from a Redpanda cluster into a target system.

Imports data from a source system into a Redpanda cluster.

A function that an AI assistant can call to perform a specific task, such as fetching data from an API, querying a database, or processing streaming data. Each tool is defined using Redpanda Connect components and annotated with MCP metadata.

A Redpanda Connect component that transforms data, validates inputs, or calls external APIs within a processing pipeline.

Processors are stateless components in Redpanda Connect that operate on individual messages or batches. When used as MCP tools, processors handle data transformations, validate parameters, and invoke external services. Each processor executes independently per request with no state maintained between invocations.

A process that exposes Redpanda Connect components to MCP clients. You write each tool’s logic using Redpanda Connect configurations and annotate them with MCP metadata so clients can discover and invoke them.

For more information, see redpanda-connect:ai-agents:mcp-server/overview.adoc.

A framework for building data streaming applications using declarative YAML configurations. Redpanda Connect provides components such as inputs, processors, outputs, and caches to define data flows and transformations.

For more information, see redpanda-connect:ROOT:about.adoc.

One or more data centers served by high-bandwidth links with low latency, typically within a close distance of one another.

An instance of Redpanda that stores and manages event streams. Multiple brokers join together to form a Redpanda cluster.

Sometimes used interchangeably with node, but a node is typically a physical or virtual server.

See also: node

A producer application that writes events to Redpanda, or a consumer application that reads events from Redpanda.

This could also be a client library, like librdkafka or franz-go.

One or more brokers that work together to manage real-time data streaming, processing, and storage.

A set of consumers that cooperate to read data for better scalability. As group members arrive and leave, partitions are re-assigned so each member receives a proportional share.

The position of a consumer in a specific topic partition, to track which records they have read. A consumer offset of 3 means it has read messages 0-2 and will next read message 3.

A client application that subscribes to Redpanda topics to asynchronously read events.

A broker that manages operational metadata for a Redpanda cluster and ensures replicas are distributed among brokers. At any given time, one active controller exists in a cluster. If the controller fails, another broker is automatically elected as the controller.

A continuous flow of events in real time that are produced and consumed by client applications. Redpanda is a data streaming platform. Also known as event stream.

A record of something changing state at a specific time. Events can be generated by various sources, including sensors, applications, and devices. Producers write events to Redpanda, and consumers read events from Redpanda.

Producers and consumers interact with Redpanda using the Kafka API. It uses the default port 9092.

A broker that is a follower in a Raft group but is not part of quorum.

In a Raft group, a broker can be in learner status. Learners are followers that cannot vote and so do not count towards quorum (the majority). They cannot be elected to leader nor can they trigger leader elections. Brokers can be promoted or demoted between learner and voter. New Raft group members start as learners.

For more information, see Raft Group Reconfiguration.

Configuration on a broker that defines how it should accept client or inter-broker connections. Each listener is associated with a specific protocol, hostname, and port combination. The listener defines where the broker should listen for incoming connections.

For more information, see Configure Listeners.

One or more records representing individual events being transmitted. Redpanda transfers messages between producers and consumers.

Sometimes used interchangeably with record.

A machine, which could be a server, a virtual machine (instance), or a Docker container. Every node has its own disk. Partitions are stored locally on nodes. In Kubernetes, a Node is the machine that Redpanda runs on. Outside the context of Kubernetes, this term may be used interchangeably with broker, such as node_id.

See also: broker

An acknowledgement that the event has been read.

A unique integer assigned to each record to show its location in the partition.

Original name for the subsystem of Redpanda that allows access to your data through a REST API. This name still appears in the HTTP Proxy API and the Schema Registry API.

Every Redpanda partition forms a Raft group with a single elected leader. This leader handles all writes, and it replicates data to followers to ensure that a majority of brokers store the data.

A subset of events in a topic, like a log file. It is an ordered, immutable sequence of records. Partitions allow you to distribute a stream, which lets producers write messages in parallel and consumers read messages in parallel. Partitions are made up of segment files on disk.

A client application that writes events to Redpanda. Redpanda stores these events in sequence and organizes them into topics.

For more information, see Configure Producers.

A failure zone that has one or more Redpanda brokers assigned to it.

The consensus algorithm Redpanda uses to coordinate writing data to log files and replicating that data across brokers.

For more details, see https://raft.github.io/

A self-contained data entity with a defined structure, representing a single event.

Sometimes used interchangeably with message.

Copies of partitions that are distributed across different brokers, so if one broker goes down, there is a copy of the data.

The mechanism for determining how long Redpanda stores data on local disk or in object storage before purging it.

For more information, see Manage Disk Space.

The number of partition copies in a cluster. This is set to 3 in Redpanda Cloud deployments and 1 (no replication) in Self-Managed deployments. A replication factor of at least 3 ensures that each partition has a copy of its data on at least one other broker. One replica acts as the leader, and the other replicas are followers.

An external mechanism to describe the structure of data and its encoding. Schemas validate the structure and ensure that producers and consumers can connect with data in the same format.

An open-source thread-per-core C++ framework, which binds all work to physical cores. Redpanda is built on Seastar.

For more details, see https://seastar.io/

The initial set of brokers that a Redpanda broker contacts to join the cluster. Seed servers play a crucial role in cluster formation and recovery, acting as a point of reference for new or restarting brokers to understand the current topology of the cluster.

Discrete part of a partition, used to break down a continuous stream into manageable chunks. You can set the maximum duration (segment.ms) or size (segment.bytes) for a segment to be open for writes.

The process of converting a record into a format that can be stored. Deserialization is the process of converting a record back to the original state. Redpanda Schema Registry supports Avro and Protobuf serialization formats.

A CPU core.

A logical grouping or category for schemas. When data formats are updated, a new version of the schema can be registered under the same subject, allowing for backward and forward compatibility.

Programming model that allows Redpanda to pin each of its application threads to a CPU core to avoid context switching and blocking.

A topic may be partitioned through multiple brokers. A "topic partition" represents this logical separation in Redpanda, which is managed natively by Raft.

A logical stream of related events that are written to the same log. It can be divided into multiple partitions. A topic can have various clients writing events to it and reading events from it.

A REST API used to manage and monitor Redpanda Self-Managed clusters. It uses the default port 9644.

For more information about using this API with Self-Managed Redpanda, see /api/doc/admin.

Note: The Redpanda Admin API is different from the Kafka Admin API.

Feature that retains the latest value for each key within a partition while discarding older values.

For more information, see Compaction Settings.

Snapshot of the current cluster metadata state saved to disk, so broker startup is fast.

Framework to manipulate or enrich data written to Redpanda topics. You can develop custom data functions, which run asynchronously using a WebAssembly (Wasm) engine inside a Redpanda broker.

For more information, see Data Transforms.

Redpanda HTTP Proxy (pandaproxy) allows access to your data through a REST API. It is built into the Redpanda binary and uses the default port 8082.

A state where a Redpanda broker temporarily doesn’t take any partition leaderships. It continues to store data as a follower. This is usually done for system maintenance or a rolling upgrade.

For more information, see Maintenance Mode.

Feature that lets you distribute replicas of the same partition across different racks to minimize data loss and improve fault tolerance in the event of a rack failure.

For more information, see Enable Rack Awareness.

Process of moving partition replicas and transferring partition leadership for improved performance.

Redpanda provides various topic-aware tools to balance clusters for best performance.

For more information, see Cluster Balancing.

The process of upgrading each broker in a Redpanda cluster, one at a time, to minimize disruption and ensure continuous availability.

For more information, see Upgrade Redpanda.

Redpanda’s command-line interface tool for managing Redpanda clusters.

A read-only topic that mirrors a topic on a different cluster, using data from Tiered Storage.

Redpanda Schema Registry (pandaproxy) is the interface for storing and managing event schemas. Producers and consumers register and retrieve schemas they use from the registry. It is built into the Redpanda binary and uses the default port 8081.

For more information, see Schema Registry.

Feature that lets you offload log segments to object storage in near real-time, providing long-term data retention and topic recovery.

For more information, see Use Tiered Storage.

A Kubernetes controller that simplifies the process of obtaining, renewing, and using certificates.

For more details, see https://cert-manager.io/docs/

Generates and applies all the manifest files you need for deploying Redpanda in Kubernetes.

For more information, see Redpanda in Kubernetes.

Extends Kubernetes with custom resource definitions (CRDs), which allow Redpanda clusters to be treated as native Kubernetes resources.

For more information, see Redpanda in Kubernetes.

Redpanda software that is available under the Redpanda Business Source License (BSL). These core features are free and source-available.

Redpanda software that is available under the Redpanda Community License (RCL). It includes the free features licensed with the Redpanda Community Edition, as well enterprise features, such as Tiered Storage, Remote Read Replicas, and Continuous Data Balancing.

Redpanda Self-Managed refers to the product offering that includes both the Enterprise Edition and the Community Edition of Redpanda.

Sometimes used interchangeably with self-hosted.

A security feature used to define and enforce granular permissions to resources, ensuring only authorized users or applications can perform specific operations. ACLs act on principals.

For more information, see Configure Authorization.

The address a Redpanda broker broadcasts to producers, consumers, and other brokers. It specifies the hostname and port for connections to different listeners. Clients and other brokers use advertised listeners to connect to services such as the Admin API, Kafka API, and HTTP Proxy API. The advertised address might differ from the listener address in scenarios where brokers are behind a NAT, in a Docker container, or in Kubernetes. Advertised addresses ensure clients can reach the Redpanda brokers even in complex network setups.

The process of verifying the identity of a principal, user, or service account. Also known as AuthN.

For more information, see Configure Authentication.

The process of specifying access rights to resources. Access rights are enforced through roles or access control lists (ACLs). Also known as AuthZ.

For more information, see Configure Authorization.

An access token used for authentication and authorization in web applications and APIs. It holds user credentials, usually in the form of random strings of characters.

For more information, see Configure Authentication.

A service that creates, maintains, and manages identity information while providing authentication services to applications.

Identity providers authenticate users and issue tokens that applications can use to verify identity and access permissions. Common IdPs include Okta, Auth0, Azure AD, and Google Identity Platform.

Authentication layer built on OAuth 2.0 that allows clients to verify user identity and obtain basic profile information.

OpenID Connect provides a standardized way for applications to authenticate users through identity providers. In Redpanda’s agentic systems, OIDC enables secure authentication for AI agents and MCP servers accessing cloud resources.

An entity (such as a user account or a service account) that accesses resources. Principals can be authenticated and granted permissions based on roles to perform operations.

Role-based access control lets you assign users access to specific resources.

An identity independent of the user who created it that can be used to authenticate and perform operations. This is especially useful for authentication of machines.