Amazon Eventbridge Event Bus
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AutoGineer summary
Written by AutoGineer from the skill’s own files, not by the author
This skill provides comprehensive guidance for building, running, and debugging event-driven applications using the modern EventBridge custom event bus. It covers the lifecycle of event management, including publishing via PutEvents or PutRawEvents, configuring subscribers with filters and transformers, and managing cross-account event routing. The skill emphasizes the distinction between the new custom event bus service and classic EventBridge, providing specific instructions for handling binary payloads, CloudEvents, and complex routing requirements.
What it does
- Guides the creation and management of custom event buses and subscribers.
- Explains the differences between PutEvents and PutRawEvents APIs for payload handling.
- Provides patterns for filtering, transforming, and routing events to various targets.
- Details authorization and security policies for cross-account event sharing.
- Offers troubleshooting steps for delivery failures, observability, and metrics.
- Supports advanced features like event replay, deduplication, and FIFO ordering.
When to use it
- When designing decoupled, asynchronous event-driven architectures.
- When you need to implement fan-out patterns across multiple AWS accounts.
- When you require a managed, serverless alternative to self-hosted event streaming.
- When you need to integrate AWS service events or partner SaaS events into your workflow.
- When you need to perform event transformation or filtering before delivery.
Advantages
- Centrally governed publish/subscribe model for multi-team environments.
- Native support for open standards like CloudEvents, Avro, and Protobuf.
- Built-in durability with configurable event retention and replay capabilities.
- Granular control over subscriber access and per-account throttling.
- End-to-end observability with integrated metrics and delivery logging.
Usage examples
- “Write a filter so this subscriber only gets orders over $500.”
- The agent provides a JSON filter pattern scoped to the event data, ensuring only events matching the specified amount are routed to the target.
- “My producer says PUBLISHED but nothing shows up in the queue. What do I check?”
- The agent guides you through checking subscriber logs, verifying the target role permissions, and confirming the filter logic matches the published payload structure.
- “Should I use PutEvents or PutRawEvents for Protobuf payloads?”
- The agent explains that PutRawEvents is required for binary or non-JSON payloads, and provides instructions on setting the appropriate ContentType.
- “Set up a subscriber that reprocesses everything from the last two days.”
- The agent provides the steps to configure a replay on the event bus, specifying the retention window and the target subscriber.
Install
Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/aws/amazon-eventbridge-event-bus/downloadUnzip it into the cross-client skills folder of your project:
mkdir -p .agents/skills && unzip amazon-eventbridge-event-bus.zip -d .agents/skills
Documentation by AWS
Building with the new EventBridge custom event buses
Overview
The new EventBridge custom event bus routes events and retains them. You publish with one of two APIs, and subscribers filter, optionally transform, and deliver each matching event to one target.
Read chapters 5 and 6 before writing any filter, transformer, or target parameter. The two publish APIs deliver different payload shapes, and an expression written for one silently matches nothing against the other.
Publish metrics are on by default, so you can always tell whether events reached a bus. Subscriber logs are off by default, so turn them on before you debug a delivery rather than after (chapter 18).
Works best with the AWS MCP server, which is recommended for running the CLI calls in this skill: it executes them in a sandboxed environment with audit logging. All guidance also works with standard AWS CLI access.
Conventions
The key words MUST, MUST NOT, SHOULD, and MAY in this skill are to be interpreted as described in RFC 2119. They appear only in decision procedures, where following the wrong course either breaks the configuration or loses events silently. MUST marks an absolute requirement, SHOULD a strong recommendation you may have a specific reason to set aside, and MAY a genuine option.
Everything else is ordinary description. A sentence stating how the service behaves carries no keyword, because it is a fact rather than an instruction to you.
When not to use this skill
This skill is only about the new custom event buses, the service you reach with the eventsv2 CLI
and the eventbridgev2 SDK clients. It does not cover:
Classic EventBridge, meaning the
eventsAPI with rules, targets, archives, and event patterns onAWS::Events::Rule. The two services share theevents:IAM namespace and some vocabulary, which is exactly why they are easy to confuse. If you are writing a rule, you are not on a new bus. Chapter 3 maps the concepts across if you are migrating.EventBridge Pipes, Scheduler, and Schemas (the classic schema registry and its discovery feature). Different APIs.
Configuring the Firehose service itself, such as buffering hints or record transformation. A Firehose delivery stream is a valid subscriber target; chapter 9 covers that side of it.
Trigger examples
"Write a filter so this subscriber only gets orders over $500."
"My producer says PUBLISHED but nothing shows up in the queue. What do I check?"
"Should I use PutEvents or PutRawEvents for Protobuf payloads?"
"Set up a subscriber that reprocesses everything from the last two days."
"Write a JSONata expression that pulls the customer id out of the event into a DynamoDB putItem."
Guardrail — where this skill's own files live (MCP vs local install)
This skill can be loaded two ways, and they resolve the skill's own bundled files from different places. Determine how the skill was loaded before reading a reference:
Loaded through the AWS MCP
retrieve_skilltool: The skill is not installed on the local filesystem. You MUST fetch each reference viaretrieve_skillwith thefileparameter (e.g.file="references/setup-walkthroughs.md"). Do NOTfile_readthese paths locally — they do not exist on disk.Installed locally (e.g.
.kiro/skills/amazon-eventbridge-event-bus/or~/.claude/skills/amazon-eventbridge-event-bus/): Read files from the local skill directory using relative paths.
This distinction applies only to the skill's own packaged files. User data and
session artifacts are always read from and written to the user's working
directory. Never fetch or write customer data through retrieve_skill.
Reference files
The chapters below carry the decisions and the failure modes; the detail lives in these files. Load a file when the task matches its row, and do not load them all by default.
| File | When to load |
|---|---|
| setup-walkthroughs.md | standing up a working bus end to end, in one account or shared across accounts with AWS RAM, including prerequisites and teardown |
| code-samples.md | writing an individual CLI or SDK call (Python, Java, TypeScript): create a bus and subscriber, publish with either API, binary payloads, replay, cross-account grants, waiters, per-entry results, throttling backoff |
| filters-and-expressions.md | writing any filter pattern, JSONata expression, or target parameter that reads the event; both delivered envelopes in full |
| target-configuration.md | configuring any subscriber target, especially a universal target |
| target-contract.md | writing an actual CreateSubscriber call: required fields, a working example per target type, literal versus JSONata, the delivery error taxonomy |
| migrating-from-classic.md | migrating from classic EventBridge, planning the migration sequence, or classic habits producing wrong new-bus config |
| event-sources.md | putting AWS service events or partner events on a bus with an event source, or forwarded events not arriving or not matching a filter |
| provisioning-and-state.md | creating or updating a bus, or a resource stuck in an unexpected state |
| delivery-troubleshooting.md | an event published but never arrived, or building a test rig that counts deliveries correctly |
| authorization.md | writing an IAM policy or bus resource policy, cross-account access checks, or anything that forwards events into a bus |
| replay-and-recovery.md | reading history rather than new events, pausing or resuming, or a replay that looks broken |
| observability.md | setting up metrics, alarms, or the vended-log delivery; reading delivery logs; observing across accounts |
| schema-registries.md | publishing Avro, Protobuf, or anything that is not JSON; the accepted content types; running alongside Kafka |
| cloudevents.md | publishing or consuming CloudEvents, or filtering on CloudEvents attributes |
| security-and-sharing.md | encrypting a bus, sharing it cross-account, or tagging |
| cost-and-quotas.md | billing mechanics, who pays what across accounts, shaping events for cost, or handling throttling |
| infrastructure-as-code.md | writing a CloudFormation template, splitting stacks across accounts, or private connectivity |
1. The three resources
Event bus. The thing you publish to. It routes events and retains them.
Subscriber. A statement of which events you want and where to send them, in one resource. It watches its bus, keeps the events matching its filter, optionally transforms each one, and delivers it to exactly one target. To send one event to several targets, create several subscribers on the same bus.
Event source. A managed feed into a bus, either AWS service events or a partner/SaaS source.
Names and identifiers:
A bus ARN and a subscriber ARN both end in a service-generated id after the name:
arn:aws:events:us-east-1:111122223333:event-busv2/my-bus/exampleid0123456789abcdef. Store the full ARN, not the name, because the name alone does not identify the resource and re-creating a deleted bus with the same name yields a different id.Event source names are unique per account, not per bus.
Three names identify this service and they do not match. The CLI command and the endpoint host are
eventsv2, as inaws eventsv2 create-event-busandeventsv2.{region}.amazonaws.com. The SDK clients areeventbridgev2. IAM actions and ARNs areevents, shared with classic EventBridge, as inevents:PutEventsandarn:aws:events:...:event-busv2/.... See chapter 14.
2. A router with a durable log behind it
The bus routes each event to matching subscribers, and it also retains events for a configured period,
set per bus with StorageConfiguration.RetentionPeriodInDays (1 to 365 days). Retention is what makes
four other features possible: starting positions, pausing and resuming, replay, and a subscriber created
today reading events published yesterday. The retention window is clamped at the bus's creation time, so
on a young bus even a recent past timestamp can fall outside it.
3. Coming from classic EventBridge
A classic rule plus its target becomes one subscriber on the new bus. Four new-bus concepts have no
classic analogue: retention on the bus itself, a subscriber starting position, pause and resume with a
backlog, and two publish APIs with different payload models. That last changes how you write filters, so
a classic event pattern ported unchanged works only for PutEvents. The concept mapping, the habits that
carry over incorrectly, and a step-by-step migration sequence are in
migrating-from-classic.md.
4. AWS service and partner event sources
An event source is a managed feed onto your bus. You create one naming a destination bus and one origin, and the service stands up the forwarding on the classic EventBridge side for you. There is no role and no delivery code: the managed path uses the service's own identity.
Configuration is discriminated and exactly one variant MUST be set:
| Variant | Origin | Required member |
|---|---|---|
AwsServiceEventsConfiguration | one AWS service, as aws.s3 | AwsService |
PartnerEventsConfiguration | a classic partner event source | PartnerEventSourceArn |
Both take an optional Pattern, which narrows what forwards and is evaluated on the classic side against
the classic envelope. Your pattern MUST NOT carry a source key or a top-level account or region,
because the service sets those itself to pin the forward to your account and origin.
A forwarded event arrives as the whole classic envelope. Data holds it, ContentType is
application/eventbridge+json, your content is at $events.Data.detail, and the source and detail-type
are in SystemMetadata as aws:Source and aws:DetailType. So a classic rule's source filter does
not transfer: the equivalent is a SYSTEM_METADATA filter, {"aws:Source":["aws.s3"]}.
Only that SystemMetadata pair proves an AWS service or partner produced the event. No publish call
can write either key. A raw payload can imitate the envelope exactly, so a DATA filter on the payload's
source matches a forgery as readily as the real thing. You SHOULD filter on aws:Source whenever
provenance matters, and MUST match its value rather than its presence, because a direct PutEvents sets
the key too, from its own never-aws.-prefixed Source.
EventBusArn is immutable. Recovery splits by failure: from CREATE_FAILED or UPDATE_FAILED,
UpdateEventSource converges the classic side back to your record, while from DELETE_FAILED the only
recovery is another delete.
A bus owner's control is at create time. CreateEventSource is authorized against the destination bus
with an events:source condition key, and RevokeResource is how an owner stops a feed that already
exists (chapter 22). Prerequisites, encryption, dead-lettering, and what appears in your classic account
are in event-sources.md.
5. Choosing a publish API
The choice fixes the payload shape, and the payload shape determines every filter, transformer, and target parameter you go on to write.
PutEvents | PutRawEvents | |
|---|---|---|
| Payload field | Detail, a JSON string | Data, a base64 blob |
| Payload must be JSON | Yes | No, any format |
| Required per entry | Source, DetailType | Data, SystemMetadata |
ContentType | Not accepted; the service stamps application/eventbridge+json | Required, inside each entry's SystemMetadata |
| Classic-style fields | Resources, Time available | Not present |
| Your own metadata | No | Metadata, up to 100 keys |
| Ordering and dedup inputs | SystemMetadata.EventGroupId, SystemMetadata.DeduplicationId | Same two fields |
Use PutEvents for JSON events where you want the classic-shaped envelope. Use PutRawEvents for binary
or non-JSON payloads, your own metadata keys, or a payload delivered exactly as sent.
Both return one result entry per request entry in the same order, so you correlate by index. Each carries
either a SuccessCode or an ErrorCode and ErrorMessage. SuccessCode is PUBLISHED or DEDUPLICATED,
and DEDUPLICATED is a success, not an error. Code that treats every success as a new event makes
deduplication look like delivery.
Publishing Avro or Protobuf requires a schema registry named on each publish request, not on the bus; a
registry configured in the wrong place leaves your events undecoded. application/octet-stream needs no
registry, because the service does not decode those bytes at all
(schema-registries.md).
6. Addressing: where every field lives
Filters, transformers, and target parameters share one addressing model, and it is not the same for
the two publish APIs. Every event is delivered under three top-level names: Data (the
payload), Metadata (your own keys, PutRawEvents only), and SystemMetadata (service-assigned and
ordering fields). A raw-published payload sits directly in Data; a PutEvents payload sits inside the
classic envelope, one level down under detail. So the same field is $events.Data.m for one API and
$events.Data.detail.m for the other, and the wrong form does not error: it resolves to nothing, the
filter matches nothing, and the transformer emits nothing. If you publish through both APIs onto one bus,
write expressions that work for both, or give each traffic type its own subscribers; no addressing form
spans both. Both envelopes in full, with every SystemMetadata field, are in
filters-and-expressions.md.
7. Filtering
A subscriber's FilterConfiguration holds a list of Filters, and an event must match every filter in
the list to be delivered: the filters are ANDed, not ORed. Each filter has a Pattern and a Scope
(DATA, METADATA, or SYSTEM_METADATA), one filter per scope. A DATA pattern is written against the
chapter 6 shape, so one pattern cannot serve both publish APIs; each is correct for exactly one API and
silently matches nothing for the other. FilterConfiguration is optional on create, and a subscriber
without one receives every event on the bus. A filter that matches nothing is indistinguishable from a
broken subscriber, so confirm a should-match and a should-not-match case by observing the target.
8. Transformation
A subscriber's Transformer has three types: RAW (the default) delivers the payload alone,
WITH_METADATA delivers the three-part envelope, and JSONATA delivers the result of an
expression. A JSONata expression is wrapped in {% %} delimiters and sees the event as $events,
addressed exactly as in chapter 6. Most scalar target parameters also accept an expression in the same
form. Some members refuse one and MUST be literals: an API Gateway header name, a message
attribute's BinaryValue, and InvocationType. An expression is only syntax-checked at create, so its
result is a delivery-time fact. A JSONATA transformer whose expression throws, or evaluates to nothing,
is a customer-fault delivery failure, so you SHOULD test it.
9. Targets and their parameter blocks
InvokeConfiguration carries the TargetArn, the RoleArn, and at most one parameter block, matching
the target. A universal target MUST carry its block; every typed block may be omitted. A classic bus
and a Firehose delivery stream are both valid targets that take no block at all.
The service resolves the target type from the ARN and checks the invariants it owns before storing anything: that the block matches the target, that the ARN's region, partition and account are its own, and that every expression parses. It does not mirror the target API's own parameter grammars, value ranges, identifier limits, or which members that API requires — those stay with the target, so a request the target will reject is accepted at create and fails at delivery.
You MUST supply the parameter block a universal target requires. A typed block may be omitted:
KinesisParameters: {}is stored, and Kinesis reports the missingPartitionKeywhen it is called.You MUST NOT put a constant in a per-message field, because a constant deduplication id makes the target discard everything after the first message. Neither form is checked against the target's range, requiredness or FIFO applicability, so a bad or missing value is a delivery failure.
You SHOULD check the target service's own rules. Existence, reachability, authorization, size after enveloping, and its API's required fields are enforced by the target, at delivery.
You SHOULD confirm at the target, because a
PUBLISHEDresponse is not delivery, and neither is an HTTP 200 from a batch API, which can carry individually failed entries.You MUST attach a dead-letter queue and turn on logs before you test, and MUST grant the delivery role
sqs:SendMessageon that queue, because a failure otherwise leaves no signal anywhere.
Each rule's failure mode, the exact rejection messages, and the per-target blocks are in target-configuration.md. Before writing the call itself, load target-contract.md for the required-field lists, one working example per target type, and the delivery error taxonomy.
10. Universal targets
A universal target invokes any supported AWS API directly, with no intermediate function. The target ARN has a fixed shape:
arn:{partition}:events:::aws-sdk:{service}:{apiAction}Four things to get right, each of which fails at create time with a message that names the problem:
apiAction is camelCase with a lowercase first letter (putItem); service is the SDK service id,
which is not always the obvious word (Step Functions is sfn); UniversalTargetParameters.Input is
required and holds the API request as JSON or a JSONata expression producing it; and
BatchConfiguration is required. The service's validation text abbreviates universal target as "USI
target"; the two mean the same thing.
11. Ordering and deduplication
Ordering is a subscriber property. Type is UNORDERED (no guarantee) or FIFO (ordered within an
event group), and events are grouped by SystemMetadata.EventGroupId at publish time. A FIFO target
enforces its own length and character limits on the group id, and an undeliverable event holds up the
later events in its own group while other groups on the same subscriber keep flowing, so keep group
ids bounded and do not derive them from unbounded input.
Deduplication happens at publish time, two ways. DeduplicationConfiguration.DeduplicationType: CONTENT_BASED on the request hashes the event content, and CONTENT_BASED is the only
DeduplicationType value. To deduplicate on your own key instead, omit DeduplicationConfiguration
and set SystemMetadata.DeduplicationId on each entry. A suppressed duplicate returns
SuccessCode: DEDUPLICATED either way.
Keep the two ideas separate. Bus-level deduplication decides whether an event is accepted. A FIFO target's own deduplication id, set in the target parameter block, decides whether that target accepts the delivery. Different fields at different layers, and the second is a per-message value (chapter 9, rule 2).
12. Retries and dead-lettering
RetryPolicy has three members:
| Member | Range | Default |
|---|---|---|
MaxRetryAttempts | 0-185 | 5 |
MaxEventAgeInSeconds | 60-86400 | 300 |
RetryStrategy | ALL | ALL |
Delivery stops at whichever limit is reached first, and a failing delivery is retried until then. So a
conclusion that "nothing arrived" is only safe after the MaxEventAgeInSeconds window has elapsed.
OnFailureConfiguration.Arn names an SQS queue for dead-lettering, and SQS is the only supported
destination. An event source refuses a FIFO queue there, with the single message
OnFailureConfiguration.Arn must name a standard SQS queue: FIFO queues are not supported as EventSource dead-letter queues;
a subscriber accepts one, so the two
resources differ on this point. Two further limits to plan around: a dead-letter record identifies failed
events by id and timestamp and does not carry the payload, so replaying it needs the event still
inside retention; and the dead-letter queue must be writable by the delivery role, or the failure has
nowhere to go and the events disappear with no signal.
13. Delivery permissions
InvokeConfiguration.RoleArn is the role the service assumes to invoke your target. It MUST belong to
the calling account, its trust policy MUST allow the events.amazonaws.com service principal, and that
policy SHOULD condition on aws:SourceAccount and aws:SourceArn. It MUST carry the action the
target requires (sqs:SendMessage, sns:Publish, lambda:InvokeFunction, kinesis:PutRecords,
states:StartExecution, or whatever your universal target calls), and sqs:SendMessage on your
dead-letter queue, or deliveries fail, no failure record is written, and nothing is observable.
CreateSubscriber also enforces iam:PassRole on that role, so a role you cannot pass fails with
AccessDeniedException before target validation runs. The list understates four: Kinesis delivery calls
PutRecords, Firehose PutRecordBatch, API Gateway needs execute-api:Invoke, an API destination
events:InvokeApiDestination.
The target ARN is checked at create for shape, type, region, partition and account, but not for existence or reachability: a well-formed ARN naming nothing is stored and fails at delivery.
14. Authorization: what your caller needs
Chapter 13 covers the role EventBridge assumes to invoke your target. This chapter covers what your caller needs to reach the API.
Every action name is events:. The CLI command and the endpoint host are eventsv2, and the SDK
clients are named eventbridgev2, but the IAM namespace is events, shared with classic EventBridge. You
MUST NOT write eventbridgev2: or eventsv2: in an IAM policy, because neither names an action that
exists, and both fail closed: the policy is accepted and grants nothing. A policy written from the command
you just ran, granting eventsv2:PutEvents, is the usual way this happens. The name-by-name map is
in authorization.md.
Publishing is authorized against the bus ARN, per entry, with no partial authorization: if one entry fails a condition check the whole request is denied, so a batch is only as authorized as its least authorized entry.
Creating a subscriber or an event source is authorized against the bus, which makes the bus the cross-account grant point: a bus owner decides there whether another account may attach anything.
Forwarding into a bus under a role you supply is authorized at ingestion, per event: a genuine AWS or
partner event needs events:PutEvents, and anything you originated needs events:PutRawEvents. So a
forwarder carrying both kinds MUST be granted both actions, because granting one silently denies half
the stream. The condition keys, the per-create checks, and revocation semantics are in
authorization.md.
15. Provisioning and resource state
Creating a bus is asynchronous: CreateEventBus returns with State: CREATING, and the bus becomes
usable later. Use the waiter rather than a hand-rolled poll, because it fails fast on the failure
states and surfaces StateReason instead of spinning to a timeout:
aws eventsv2 wait event-bus-active --event-bus-arn "$BUS_ARN"A bus has seven states, and the asymmetry that matters is between the two failure states: UPDATE_FAILED
is recoverable in place, and CREATE_FAILED is not. A failed create permits only delete, so that bus
must be deleted and recreated. Delete subscribers and event sources before the bus; a bus that still has
either rejects DeleteEventBus with ResourceInUseException, and the message names which kind is
blocking. Revoked subscribers and event sources do not block the delete.
Creates are idempotent through ClientToken. CreateEventBus, CreateSubscriber, and
CreateEventSource each accept one, and a retry carrying the same token returns the original result
rather than creating a second resource. An SDK generates a fresh token per call when you omit the field,
so a retry your own code issues builds a new request, gets a new token, and creates a second resource.
So you MUST supply your own ClientToken whenever a retry can cross a process, a queue, or a workflow
step. The mismatch error and the naming collision are in
provisioning-and-state.md.
16. Updating safely
One rule governs every update API, and getting it wrong silently discards configuration you did not intend to change:
An omitted top-level member means unchanged. A supplied configuration block replaces that whole block.
So an update that supplies Configuration or FilterConfiguration or LogConfiguration in order to
change one field inside it clears every other field in that block. An event source updated with its
Pattern omitted comes back with no pattern at all, widening its filter to everything, with no warning.
So you MUST read the resource, modify the whole block, write the whole block back, and then read it
back again, because reading it back is the only way to confirm what was stored.
17. Pausing, resuming, and replay
There is no separate replay API. Replay is a subscriber's starting position, evaluated against the bus's retained events, so anything still inside retention can be reread.
StartingPositionat create time isLATEST(only events published after the subscriber exists) orPOINT_IN_TIME(from a point in retained history).Pausing is
State: STOPPEDonUpdateSubscriber. The backlog accrues, bounded by retention, andResumePositiondecides whether the backlog is delivered or skipped on resume.Replayed events are marked.
SystemMetadata."aws:DeliveryType"readsREPLAYinstead ofLIVE, so a consumer can make replay idempotent.A replay has a startup delay, then runs at live speed, so allow for the delay before concluding a replay is broken.
18. Observability: metrics and logs
Two surfaces tell you what the service is doing, and their defaults are opposite.
Publish metrics are on by default, in the AWS/EventsV2 namespace, on the tuple {EventBus} plus
{EventBus, EventSource} for traffic attributed to an event source and {EventBus, PublisherAccount} for
ingress bytes. PublishEventsApproximateCallCount against PublishEventsApproximateSuccessCallCount is
the cheapest check that your producer is reaching the bus at all. The outcome metrics count calls, not
events, so a call that returned a response counts as a success even when every entry in it was rejected;
PublishEventsEntryCount against PublishEventsFailedEntriesCount is what says whether events landed.
The EventBus dimension value is not the bus ARN; querying with the ARN returns no data and looks
identical to no traffic.
Subscriber logs are off by default, and they need two things before they exist: LogConfiguration.Level
raised above OFF, and a CloudWatch Logs vended-log delivery wiring the subscriber to a log group. Set
both up before debugging a delivery, not after. The delivery setup, the metric list, and the
EVENT_DELIVERY_ATTEMPT record fields are in observability.md.
19. Verifying delivery
A publish response tells you the service accepted the event. It says nothing about delivery. To know an event arrived, look at the target.
A healthy delivery reaches the target quickly, so an event that has not arrived promptly is probably failing rather than in flight. But "nothing arrived" is only sound after the retry window elapses, because until then a failing delivery is still being retried.
Two counting mistakes make a working setup look broken. Reading an SQS queue without deleting the messages re-reads them, so raw counts overstate deliveries. And a shared target accumulates messages from earlier runs, so use a fresh target per experiment or a marker unique to the run.
20. When it published but never arrived
Nearly every delivery problem presents identically: the publish succeeded and the target is empty. You SHOULD work the ordered procedure in delivery-troubleshooting.md; it covers eleven causes ordered by how often each is the answer.
Three shortcuts that do not require opening the file:
You SHOULD check
PublishEventsEntryCountfirst (chapter 18). Zero means the problem is upstream of the bus and nothing downstream matters yet.You SHOULD turn on subscriber logs.
INFOwithIncludePayload: FULLshows the per-attempt error and the exacttarget_inputsent, without waiting for retries to exhaust.To see the event as the service sees it, you MAY add a second subscriber with
Transformer: { Type: WITH_METADATA }and no filter, pointed at a queue you own.
21. Errors and client retries
Batch responses are per entry. A publish can return success at the request level with individual entries
failed, so check FailedEntryCount and every entry, not just the HTTP status.
Some malformed input fails the whole request instead of one entry. Anything caught while deserializing the request rejects the entire batch and takes the valid entries with it. Validate per entry client-side, and keep batches small enough that losing one is cheap.
Retryable errors. ConcurrentModificationException and ThrottlingException are retryable with
backoff. InvalidInputException, AccessDeniedException, ResourceNotFoundException, and
IdempotentParameterMismatchException are not; fix the request.
Treat a persistent 500 as a client-side wire-type problem first. The usual cause is a value sent as the wrong JSON type, such as a number where a string is expected or an ISO-8601 string where epoch seconds are. An SDK retries a 500 by contract, and retrying cannot fix a malformed request, so check your types before escalating.
22. Security, encryption, sharing, tagging
Encryption is
EncryptionConfiguration.KmsKeyIdentifieron the bus. Your caller needskms:DescribeKeyon the key at create time, and on a CMK bus every publisher needskms:Decrypton that key too, because a caller who cannot read the bus's events back is not allowed to write them. An unusable key policy on the service's side settles the bus atCREATE_FAILEDwithStateReason: KMS_ACCESS_DENIEDinstead (security-and-sharing.md).To share a bus with another account, use AWS RAM. Resource policies are the fallback for what RAM cannot express, and a hand-written policy is invisible to RAM, so you then own tracking it.
Some operations are restricted to the bus owner, including revoking a shared resource, so a permission grant alone is not always sufficient. Revocation is terminal and scoped to the one resource you name, so stopping an account rather than a resource means also denying it
events:CreateSubscriberandevents:CreateEventSourcein the bus resource policy (authorization.md).
23. Cost, quotas, and platform integration
Four things that change design decisions. Current prices and quota values are on the EventBridge pricing page and in Service Quotas, not here.
Billing rounds up per KB on both ingestion and delivery, so many tiny events cost more than the byte total suggests; batching related facts into one event is cheaper.
"Enriched operations" are billed separately: JSONata evaluation, schema deserialization, and
CONTENT_BASEDdeduplication. So prefer a per-entryDeduplicationId, with noDeduplicationConfiguration, when you already have an idempotency key.Publishing is throttled per account across both publish APIs, so a service splitting traffic between them draws from one budget. Subscriber management has its own per-account limit, so
CreateSubscriberandDeleteSubscribercan be throttled while publishing has headroom. HandleThrottlingExceptionwith backoff (chapter 21).CloudFormation covers the new buses under
AWS::EventsV2::, with three types. Six subscriber properties are create-only and replacement is delete-then-create, so changing a target ARN in a template can silently drop events published during the gap.
Files
- ATTRIBUTION.mdAdded by AutoGineer946 B
- LICENSELicence file added by AutoGineer9.9 KiB
- NOTICELicence file added by AutoGineer67 B
- SKILL.md33.9 KiB
- references/authorization.md17.3 KiB
- references/cloudevents.md3.7 KiB
- references/code-samples.md13.3 KiB
- references/cost-and-quotas.md7.0 KiB
- references/delivery-troubleshooting.md21.8 KiB
- references/event-sources.md18.8 KiB
- references/filters-and-expressions.md10.7 KiB
- references/infrastructure-as-code.md8.1 KiB
- references/migrating-from-classic.md6.3 KiB
- references/observability.md15.9 KiB
- references/provisioning-and-state.md5.0 KiB
- references/replay-and-recovery.md4.6 KiB
- references/schema-registries.md5.5 KiB
- references/security-and-sharing.md6.7 KiB
- references/setup-walkthroughs.md8.9 KiB
- references/target-configuration.md14.8 KiB
- references/target-contract.md44.1 KiB
references/observability.md
Observability: metrics and logs
Load this when setting up monitoring or alarms, or when reading delivery logs to diagnose a failure.
Two surfaces tell you what the service is doing: CloudWatch metrics, which are on by default, and subscriber logs, which are off by default and which you turn on per subscriber.
Publish metrics
Metrics are published to the customer-vended AWS/EventsV2 namespace.
| Metric | Counts | Per |
|---|---|---|
PublishEventsApproximateCallCount | publish calls, whatever their outcome | call |
PublishEventsApproximateSuccessCallCount | calls that returned a response | call |
PublishEventsApproximateFailedCallCount | calls that threw anything other than ThrottlingException | call |
PublishEventsApproximateThrottledCallCount | calls that threw ThrottlingException | call |
PublishEventsEntryCount | entries submitted | entry |
PublishEventsFailedEntriesCount | entries rejected | entry |
PublishEventsIngressBytes | bytes stored | byte |
The three outcome metrics describe the request, not the events in it. Exactly one of them fires per
call. A call that returned a response counts as a success even when every entry inside it was rejected, and
that case reads as PublishEventsFailedEntriesCount equal to PublishEventsEntryCount. So a healthy
PublishEventsApproximateSuccessCallCount does not mean events landed; compare the two entry counts for
that.
A per-entry throttle lands in PublishEventsFailedEntriesCount, because only a whole-request
ThrottlingException counts as a throttled call.
A whole-request failure or throttle still reports every entry. PublishEventsEntryCount carries the
submitted total on all three outcomes, and PublishEventsFailedEntriesCount carries that whole total on a
failure or a throttle, so entry-level ratios stay meaningful through an outage.
PublishEventsIngressBytes
This is the stored size rather than the size you sent. The measurement is taken after the service builds
and encrypts the stored message, so system metadata and framing are inside it, and the two publish APIs
store different shapes: PutEvents stores a composed envelope, and PutRawEvents stores your bytes with
their content type. So a 1 KB event is not 1 KB of ingress.
It trends your ingress bill without equalling it, because billing rounds each entry up to a whole KB before summing while this metric sums the raw stored sizes. Entries of 0.6, 1.5, and 2.2 KB bill as 6 KB and report here as 4.3 KB.
A deduplicated entry stores nothing, so it contributes no bytes while still counting as a successful entry.
So PublishEventsEntryCount does not decompose into bytes plus failures.
It is absent rather than zero when a call stored nothing, so an interval with no datapoint means nothing was
stored rather than data missing. PublishEventsApproximateCallCount is the companion that separates an idle
interval from calls that stored nothing.
Dimensions
Metrics carry dimension tuples rather than independent dimensions:
| Tuple | Carries | Emitted when |
|---|---|---|
{EventBus} | every metric above | always |
{EventBus, EventSource} | the count metrics, and not the bytes | the call is attributed to a registered event source |
{EventBus, PublisherAccount} | PublishEventsIngressBytes alone | in the bus owner's account, when bytes were stored |
Only managed forwarding from classic EventBridge is attributed. That path carries a signed header
naming the classic forwarding rule, which identifies the event source behind it. A do-it-yourself
forwarder, a bus-to-bus forward, and a direct PutEvents or PutRawEvents all emit {EventBus} alone.
The {EventBus, EventSource} tuple is emitted in addition to {EventBus}, not instead of it. So
summing one metric across both tuples counts attributed traffic twice.
Both dimension values are compound, and neither is an ARN:
| Dimension | Value | Example |
|---|---|---|
EventBus | the bus name and the generated id from its ARN, joined by a slash | my-bus/exampleid0123456789abcdef |
EventSource | the discriminator, the name, and the generated id, joined by slashes | aws.service/my-source/exampleid0123456789abcdef |
Querying EventBus with the full bus ARN returns no data and looks identical to no traffic.
Every one of these lands in the bus owner's account, and in the publishing account too when the two
differ. The publisher's copy omits the {EventBus, PublisherAccount} bytes, which stay with the bus
owner. So a bus owner can attribute stored bytes to a publishing account with no cross-account setup, and
a publisher reads its own traffic from its own account.
A call whose event bus cannot be resolved emits no publish metrics at all, and neither does a call that throws before the service records its step.
PublishEventsApproximateCallCount against PublishEventsApproximateSuccessCallCount is the cheapest check
that your producer is reaching the bus at all, and PublishEventsFailedEntriesCount is how you notice
per-entry rejections that a caller ignoring individual entry results would otherwise miss (chapter 21).
There is no delivery-side metric to alarm on. Every metric above is publish-side, so a subscriber that fails every delivery moves none of them. Delivery health has to come from the logs and the dead-letter queue, which is why both are worth configuring before you need them rather than after.
Audit with CloudTrail
You SHOULD enable a CloudTrail trail covering this service before you run a bus in production. Both planes are recorded, and they are recorded differently, so a trail answers questions the metrics above cannot.
Control-plane calls arrive as management events: who created or deleted a bus, who attached or revoked a subscriber, who changed a resource policy, and every KMS operation the service ran against your key under the key policy in security-and-sharing.md. The metrics tell you a subscriber stopped delivering. The trail tells you which principal changed it.
Publishes arrive as data events, recorded per entry rather than per call. One batch publish produces a record for the call and a record for each entry in it. An entry's record carries that entry's own outcome, its assigned event id and success code where it succeeded and its error code where it did not, so a partly failed batch is attributable to the entries that failed. Two fields join the records: a parent request id links an entry record to its call record, and an entry index gives the entry's position in the batch.
That index is the only way to tell which entry a record describes, because no event payload reaches the
trail. A PutEvents entry contributes its Source and DetailType, and its Detail is dropped. A
PutRawEvents entry contributes nothing, because both Data and Metadata are dropped. So the trail
tells you who published what kind of event and with what outcome, and never what the event said.
Entry records exist only where the publish reached the point of having per-entry outcomes. A call rejected before that, an authorization denial for example, leaves the call-level record alone. So no entry records is not evidence that nothing was published, and the call record is what settles it.
EventSource events are audited against the event source rather than as a publish you made: each record describes an event arriving through your event source, and names the event source as the resource it happened to. Forwarding through non-managed rules and targets is recorded as an ordinary publish instead, because that is what it is. Both attribute the record to the producing account.
For the wider control set, see the AWS security best practices guidance at https://docs.aws.amazon.com/wellarchitected/latest/security-pillar/welcome.html
Subscriber logs
Delivery detail comes from per-subscriber logging, set with LogConfiguration:
| Field | Values | Default |
|---|---|---|
Level | OFF, ERROR, INFO | OFF |
IncludePayload | FULL, ON_ERROR_ONLY | ON_ERROR_ONLY |
Level: OFF is the default, so a new subscriber emits no logs until you ask for them. Set ERROR to
record failures only, or INFO to record every delivery attempt including the successes.
IncludePayload: FULL embeds the event payload in every record, which is what you want while debugging and
which you SHOULD reconsider afterwards, both for log volume and because the payload is your own data.
IncludePayload: FULL copies your event bodies out of the bus and into the log group, so the bus's own
encryption stops protecting them there. The log group is encrypted under its own key, and a reader with
logs:GetLogEvents on that group reads every payload. So three things follow. You SHOULD encrypt the
destination log group with a customer managed key (aws logs associate-kms-key). You SHOULD scope read
access to that group as tightly as access to the bus. And you SHOULD set ON_ERROR_ONLY, or
Level: ERROR, once a diagnosis is finished.
A dead-letter queue does not create the same exposure, because a dead-letter record references the failed events instead of containing them; target-contract.md has the record's fields. Scope the queue for the identifiers it does hold, since the event group id and the deduplication id are values you chose and can carry meaning of their own.
You MAY set LogConfiguration at create time or with UpdateSubscriber, and it takes effect without
recreating the subscriber. The Create and Update responses do not echo the field back, so you SHOULD
confirm it with
DescribeSubscriber, which does return it. This is the same read-back discipline chapter 16 asks for.
Setting up the log delivery
Records reach a log group through the CloudWatch Logs vended-log delivery mechanism, and until you
wire it up, no log group appears on its own: turning Level up produces nothing you can read. The
wiring is three CloudWatch Logs calls that pair the subscriber with a destination:
aws logs create-log-group --log-group-name /aws/vendedlogs/my-subscriber-logs
aws logs put-delivery-source --name my-sub-source \
--resource-arn "$SUBSCRIBER_ARN" \
--log-type TRACE_LOGS
aws logs put-delivery-destination --name my-sub-dest \
--delivery-destination-configuration destinationResourceArn=arn:aws:logs:us-east-1:111122223333:log-group:/aws/vendedlogs/my-subscriber-logs
aws logs create-delivery \
--delivery-source-name my-sub-source \
--delivery-destination-arn <the DeliveryDestination ARN returned by put-delivery-destination>Three details that break this when missed:
The log group name MUST start with
/aws/vendedlogs/, because CloudWatch Logs auto-manages the delivery resource policy only for that prefix. A log group elsewhere needs its policy managed by hand.The delivery source's
resource-arnis the subscriber ARN, and thelog-typefor subscriber delivery logs isTRACE_LOGS.One delivery pairs exactly one source with one destination. To send one subscriber's logs to a second destination, you MUST create a second delivery.
Reading a delivery record
Each delivery attempt produces one EVENT_DELIVERY_ATTEMPT record per event in the batch. A record carries
a fixed set of top-level fields, plus a details object holding the delivery state and an error object
present only on failure:
| Field | Contents |
|---|---|
eventId | the event this record is about |
messageType | EVENT_DELIVERY_ATTEMPT |
error | omitted on success. On failure, error_code and error_message |
details.outcome | SUCCESS or FAILURE |
details.attempt_count | which attempt this was, so retries are countable |
details.target_arn | the target invoked |
details.http_status, details.target_request_id | the target's own response, for correlating in the target service |
details.ingestion_to_start_latency_ms, details.ingestion_to_complete_latency_ms | end-to-end latency from ingestion |
details.target_input | what was actually sent to the target, when payloads are included |
details.event_detail, details.event_metadata, details.event_system_metadata | the event as the service held it |
details.target_input is the field to reach for when a transformer or a target parameter is suspected,
because it shows what the target actually received rather than what you intended to send.
Three fields read together tell you where the failure happened, which is faster than reading the message cold:
| Reading | Where it failed |
|---|---|
| no record at all for a published event | the event never reached the subscriber: filter, starting position, or addressing |
outcome: FAILURE, target_request_id empty | before the wire call: the JSONata expression threw or produced nothing, or the resolved request could not be converted or exceeded the target's payload cap |
outcome: FAILURE, http_status 4xx | the target rejected the call. Your request, so retrying will not help — but note it is retried, so attempt_count still climbs |
outcome: FAILURE, http_status 5xx or 429 | the target is unhealthy or throttling. attempt_count climbs |
outcome: SUCCESS but the target is empty | a batch API returned HTTP 200 with individually failed entries. Count at the target, not from the status |
Do not use attempt_count to decide whether a fault is permanent. Every class is retried on the same
budget, so a 4xx and a 5xx look alike in that field. error_code and error_message are what separate
them. target-contract.md §5 has the full class table and what each class does about
retries and dead-lettering.
The error field names differ by surface, and both are correct for their own surface. A log record
carries snake_case fields nested under error: error.error_code and error.error_message. A
dead-letter record carries the same information as top-level camelCase fields: errorCode and
errorMessage. A parser written for one surface reads nothing from the other. The content matches, so
a failure is diagnosable from the log without waiting for retries to exhaust and write the dead-letter
record.
Observability across accounts
Logs are per subscriber, so a topology spanning accounts spreads them across those accounts. Publish metrics already reach more than one account: they land in the bus owner's account, and in the publishing account too when the two differ. Three questions come up.
Aggregating subscriber logs centrally. The vended-log delivery destination can live in a different
account than the subscriber. Each subscriber's delivery source is created in the account that owns the
subscriber, the delivery destination names a log group in the central account, and the central account
MUST allow the delivery with PutDeliveryDestinationPolicy on that destination, naming each source
account. So a platform team can collect every consumer's delivery logs into one log group without
owning the subscribers.
Aggregating metrics centrally. A publish already appears in both the bus owner's account and the
publisher's, and the bus owner additionally gets ingress bytes broken out by PublisherAccount. Nothing
aggregates across buses in different accounts, though. For that, use CloudWatch
cross-account observability: link the bus and subscriber accounts as source accounts to a monitoring
account, and query the AWS/EventsV2 metrics from there. The EventBus dimension still names one bus
per account, so a fleet-wide view is a query across linked accounts rather than a single metric.
Correlating one event across bus hops. There is no service-assigned identifier that follows an
event from one bus to another. aws:EventId identifies the event on the bus that ingested it, a
bus-to-bus forward is a new ingestion at the destination, and the publish request and delivered
envelope define no trace field. So you SHOULD put your own correlation identifier inside the
payload, or in a
Metadata key on PutRawEvents, at the original producer, and have every consumer log it. That
identifier plus the per-hop subscriber logs is the cross-account trace.
Requirements and compatibility
Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta
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Needs: Needs an MCP server
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