Replica
A replica is a copy of data or state, or an equivalent running instance of a component, maintained alongside others in a replicated system.
Elasticsearch in Action, Second Edition
A duplicate copy of a primary shard maintained on a different node for redundancy and read availability.
- How it is used
- Provides redundant shard copies and distributes search reads across nodes for availability and throughput.
- How deep it goes
- Defines placement and failover, then demonstrates health diagnosis, live resizing, and memory-sizing trade-offs.
- Examples
- Uses chats and virus_mutations indexes, allocation explanations, node additions, and live replica-setting updates.
- What you can do after
- Operate/configure replica counts, diagnose unassigned copies, and plan nodes for resilient read-heavy indexes.
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Platform Engineering on Kubernetes
A replica is an additional running instance of a service or application component that provides redundancy and capacity.
- How it is used
- Uses replica counts to scale Conference services and keep a frontend pod available during a pod failure.
- How deep it goes
- Works through scaling and deleting pods, then examines replacement, downtime, state sharing and database connections; leaves ReplicaSet internals unexplored.
- Examples
- Shows two Conference frontend pods after scaling, replacement after pod deletion, and Agenda replicas backed by Redis.
- What you can do after
- Operate/configure it with kubectl to change replica counts and check whether a failed pod is replaced without losing all frontend availability.
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Apache Kafka in Action
A Kafka replica is a copy of a partition maintained on a broker for fault tolerance and high availability.
- How it is used
- Keeps partition data available across broker failures by maintaining copies on multiple running brokers.
- How deep it goes
- Explains topic-level replication factors, leader–follower behavior, inspection, failover, and acknowledgment trade-offs without detailing replica-election internals.
- Examples
- Creates and describes a three-partition, three-replica product-prices topic, then contrasts `acks=all`, `acks=1`, and `acks=0`.
- What you can do after
- Operate/configure it by setting a feasible replication factor, inspecting replica assignments, and choosing producer acknowledgments with their reliability trade-offs in mind.
Kubernetes in Action, Second Edition
An application instance is a running replica of an application managed by Kubernetes.
- How it is used
- Represents a running application instance used to scale an application and distribute client traffic.
- How deep it goes
- Traces replica creation, scheduling, execution, reconciliation, and service traffic without detailing controller internals.
- Examples
- Demonstrates three replicas with kubectl scale, deployment and Pod listings, node placement, and repeated requests reaching different Pods.
- What you can do after
- Operate/configure replicas via kubectl by changing a Deployment's desired count and checking resulting Deployments and Pods.
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ScyllaDB in Action
A replica is a copy of database data maintained on another node for availability, resilience, or read serving.
- How it is used
- Uses replicas to provide database availability, fault tolerance, and scalable query handling across cluster nodes.
- How deep it goes
- Explains copies, replication factor, acknowledgement levels, and trade-offs, while deferring hash-ring internals.
- Examples
- Uses replicated rows and a three-replica comparison of ALL, QUORUM, and ONE consistency levels.
- What you can do after
- Evaluate replica acknowledgement settings by comparing consistency requirements, availability, and tolerated node failures.
Learn Docker in a Month of Lunches, Second Edition
A replica is an independently running instance of a workload maintained to provide capacity or redundancy.
- How it is used
- Uses replicas to add application capacity and keep traffic flowing when individual Pods fail.
- How deep it goes
- Explains replica counts, Pod replacement, Service distribution, and health probes, but stops short of controller internals.
- Examples
- Demonstrates scaling `numbers-api` to three Pods, inspecting endpoints, sending requests, and configuring readiness and liveness probes.
- What you can do after
- Operate/configure a Deployment by changing its replica count and verifying Pods and Service endpoints with kubectl.
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Acing the Certified Kubernetes Administrator Exam, Second Edition
A replica is an independently running copy of a pod or application instance that contributes to workload capacity and redundancy.
- How it is used
- Uses Deployment replicas to provide workload redundancy, fault tolerance, capacity, and faster DNS resolution.
- How deep it goes
- Explains kubectl scaling, pod naming, stateless behavior, and DNS failure through operational examples.
- Examples
- Demonstrates Apache replicas, CoreDNS scaling, pod listings, image replacement, Service access, and DNS failure.
- What you can do after
- Operate/configure Deployment replicas with kubectl and verify resulting pods, images, and DNS availability.
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Bootstrapping Microservices, Second Edition: With Docker, Kubernetes, GitHub Actions, and Terraform
A replica is an additional running instance that duplicates the functionality of another service or component.
- How it is used
- Provides redundancy for fault tolerance and distributes workload for horizontal microservice scaling.
- How deep it goes
- Explains load balancing, restart behavior, and Kubernetes configuration, while deferring performance scaling details to a separate treatment.
- Examples
- Demonstrates three gateway instances behind a load balancer and another instance handling messages after a crash.
- What you can do after
- Operate replicas by changing a Kubernetes Deployment field and applying the configuration with kubectl.
Server-Side WebAssembly
A replica is an independently running copy of a component or service deployed to handle workload alongside other copies.
- How it is used
- Scales wasmCloud components to process concurrent requests and distribute workload across hosts.
- How deep it goes
- Explains configuration, benchmarking, load balancing, host placement, and regional weighting, but does not detail replica lifecycle internals.
- Examples
- Demonstrates one versus ten HTTP-component instances, weighted East/West placement, inventory inspection, and host shutdown.
- What you can do after
- Operate/configure replicas with spreadscaler, deploy them through wash, benchmark them with oha, and inspect host placement.
LLMs in Production
A replica is an additional running instance of a service or workload that provides capacity or redundancy.
- How it is used
- Uses load-test latency and throughput to estimate how many service replicas peak traffic requires.
- How deep it goes
- Explains replicas through capacity extrapolation from failure metrics, but stops short of deployment or orchestration mechanics.
- Examples
- Measures a streamed /generate service with Locust while increasing users toward a visible bottleneck.
- What you can do after
- Evaluate replica capacity by load-testing staged services and relating failure-point metrics to peak demand.
Latency
A replica is a server or other system member that maintains a copy of data or state replicated from a primary.
- How it is used
- Uses replicas to provide multiple data copies, local reads, and fault-tolerant primary–backup operation.
- How deep it goes
- Explains primary–replica message flow, snapshots, broadcasts, quorum acknowledgments, and view changes without detailing durable recovery.
- Examples
- Demonstrates Rust servers, Join and Snapshot messages, shell commands, initial synchronization, and propagated key–value updates.
- What you can do after
- Build it from scratch as an in-memory primary–replica key–value service with joins, snapshots, broadcasts, and local reads.
Kafka for Architects
A replica is a copy of a Kafka partition's records maintained on a broker for redundancy and availability.
- How it is used
- Explains how Kafka preserves partition availability and durability across brokers through leader–follower replication.
- How deep it goes
- Defines placement, asynchronous lag, ISR status, and write thresholds, while deferring detailed client reliability strategies.
- Examples
- Uses leader–follower placement, asynchronous follower catch-up, and a resilience profile of replication factor 3 with min.insync.replicas 2.
- What you can do after
- Configure replication factor and min.insync.replicas to balance availability, durability, and write acceptance.
Related concepts
- horizontal scalingused by · Horizontal scaling is adjusting system capacity by adding or removing computing nodes or equivalent instances that share or distribute the workload.
- replicationproduced by · Replication is the creation or maintenance of multiple copies of data, state, or functionality across separate locations or components.
- uptimeproduces · Uptime is the duration or proportion of a specified period during which a system or service is operational and available to provide its intended function.
- primary nodecontrasts with · A primary node is a designated authoritative or coordinating member of a distributed system, typically responsible for accepting operations or coordinating replicated state.
- load balancerused by · A load balancer is a hardware or software component that distributes incoming network traffic or requests among multiple destinations, such as servers or service instances.
- in-sync replicaincludes · An in-sync replica is a Kafka partition replica sufficiently caught up with its leader to remain eligible for failover.
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