JetStream (Technical Preview)
JetStream is the NATS.io persistence engine that will support streaming as well as traditional message and worker queues for At-Least-Once delivery semantics.
Contents
- Concepts
- Getting Started
- Administration and Usage from the CLI
- Configuration Management
- Model Deep Dive
- NATS API Reference
- Next Steps
- Discussion Items
Concepts
In JetStream the configuration for storing messages is defined separately from how they are consumed. Storage is defined in a Stream and consuming messages is defined by multiple Consumers.
We'll discuss these 2 subjects in the context of this architecture.
While this is an incomplete architecture it does show a number of key points:
- Many related subjects are stored in a Stream
- Consumers can have different modes of operation and receive just subsets of the messages
- Multiple Acknowledgement modes are supported
A new order arrives on ORDERS.received, gets sent to the NEW Consumer who, on success, will create a new message on ORDERS.processed. The ORDERS.processed message again enters the Stream where a DISPATCH Consumer receives it and once processed it will create an ORDERS.completed message which will again enter the Stream. These operations are all pull based meaning they are work queues and can scale horizontally. All require acknowledged delivery ensuring no order is missed.
All messages are delivered to a MONITOR Consumer without any acknowledgement and using Pub/Sub semantics - they are pushed to the monitor.
As messages are acknowledged to the NEW and DISPATCH Consumers, a percentage of them are Sampled and messages indicating redelivery counts, ack delays and more, are delivered to the monitoring system.
Streams
Streams define how messages are stored and retention duration. Streams consume normal NATS subjects, any message found on those subjects will be delivered to the defined storage system. You can do a normal publish to the subject for unacknowledged delivery, else if you send a Request to the subject the JetStream server will reply with an acknowledgement that it was stored.
As of January 2020, in the tech preview we have file and memory based storage systems, we do not yet support clustering.
In the diagram above we show the concept of storing all ORDERS.* in the Stream even though there are many types of order related messages. We'll show how you can selectively consume subsets of messages later. Relatively speaking the Stream is the most resource consuming component so being able to combine related data in this manner is important to consider.
Streams can consume many subjects. Here we have ORDERS.* but we could also consume SHIPPING.state into the same Stream should that make sense (not shown here).
Streams support various retention policies - they can be kept based on limits like max count, size or age but also more novel methods like keeping them as long as any Consumers have them unacknowledged, or work queue like behavior where a message is removed after first ack.
When defining Streams the items below make up the entire configuration of the set.
| Item | Description |
|---|---|
| MaxAge | Maximum age of any message in the stream, expressed in microseconds |
| MaxBytes | How big the Stream may be, when the combined stream size exceeds this old messages are removed |
| MaxMsgSize | The largest message that will be accepted by the Stream |
| MaxMsgs | How many messages may be in a Stream, oldest messages will be removed if the Stream exceeds this size |
| MaxConsumers | How many Consumers can be defined for a given Stream, -1 for unlimited |
| Name | A name for the Stream that may not have spaces, tabs or . |
| NoAck | Disables acknowledging messages that are received by the Stream |
| Replicas | How many replicas to keep for each message (not implemented as of January 2020) |
| Retention | How message retention is considered, LimitsPolicy (default), InterestPolicy or WorkQueuePolicy |
| Discard | When a Stream reached it's limits either, DiscardNew refuses new messages while DiscardOld (default) deletes old messages |
| Storage | The type of storage backend, file and memory as of January 2020 |
| Subjects | A list of subjects to consume, supports wildcards |
Consumers
Each Consumer, or related group of Consumers, of a Stream will need an Consumer defined. It's ok to define thousands of these pointing at the same Stream.
Consumers can either be push based where JetStream will deliver the messages as fast as possible to a subject of your choice or pull based for typical work queue like behavior. The rate of message delivery in both cases is subject to ReplayPolicy. A ReplayInstant Consumer will receive all messages as fast as possible while a ReplayOriginal Consumer will receive messages at the rate they were received, which is great for replaying production traffic in staging.
In the orders example above we have 3 Consumers. The first two select a subset of the messages from the Stream by specifying a specific subject like ORDERS.processed. The Stream consumes ORDERS.* and this allows you to receive just what you need. The final Consumer receives all messages in a push fashion.
Consumers track their progress, they know what messages were delivered, acknowledged, etc., and will redeliver messages they sent that were not acknowledged. When first created, the Consumer has to know what message to send as the first one. You can configure either a specific message in the set (StreamSeq), specific time (StartTime), all (DeliverAll) or last (DeliverLast). This is the starting point and from there, they all behave the same - delivering all of the following messages with optional Acknowledgement.
Acknowledgements default to AckExplicit - the only supported mode for pull-based Consumers - meaning every message requires a distinct acknowledgement. But for push-based Consumers, you can set AckNone that does not require any acknowledgement, or AckAll which quite interestingly allows you to acknowledge a specific message, like message 100, which will also acknowledge messages 1 through 99. The AckAll mode can be a great performance boost.
Some messages may cause your applications to crash and cause a never ending loop forever poisoning your system. The MaxDeliver setting allow you to set a upper bound to how many times a message may be delivered.
To assist with creating monitoring applications, one can set a SampleFrequency which is a percentage of messages for which the system should sample and create events. These events will include delivery counts and ack waits.
When defining Consumers the items below make up the entire configuration of the Consumer:
| Item | Description |
|---|---|
| AckPolicy | How messages should be acknowledged, AckNone, AckAll or AckExplicit |
| AckWait | How long to allow messages to remain un-acknowledged before attempting redelivery |
| DeliverPolicy | The initial starting mode of the consumer, DeliverAll, DeliverLast, DeliverNew, DeliverByStartSequence or DeliverByStartTime |
| DeliverySubject | The subject to deliver observed messages, when not set, a pull-based Consumer is created |
| Durable | The name of the Consumer |
| FilterSubject | When consuming from a Stream with many subjects, or wildcards, select only a specific incoming subjects, supports wildcards |
| MaxDeliver | Maximum amount times a specific message will be delivered. Use this to avoid poison pills crashing all your services forever |
| OptStartSeq | When first consuming messages from the Stream start at this particular message in the set |
| ReplayPolicy | How messages are sent ReplayInstant or ReplayOriginal |
| SampleFrequency | What percentage of acknowledgements should be samples for observability, 0-100 |
| OptStartTime | When first consuming messages from the Stream start with messages on or after this time |
Configuration
The rest of this document introduces the nats utility, but for completeness and reference this is how you'd create the ORDERS scenario. We'll configure a 1 year retention for order related messages:
$ nats str add ORDERS --subjects "ORDERS.*" --ack --max-msgs=-1 --max-bytes=-1 --max-age=1y --storage file --retention limits --max-msg-size=-1 --discard=old
$ nats con add ORDERS NEW --filter ORDERS.received --ack explicit --pull --deliver all --max-deliver=-1 --sample 100
$ nats con add ORDERS DISPATCH --filter ORDERS.processed --ack explicit --pull --deliver all --max-deliver=-1 --sample 100
$ nats con add ORDERS MONITOR --filter '' --ack none --target monitor.ORDERS --deliver last --replay instantGetting Started
This tech preview is limited to a single server and defaults to the global account. JetStream is NATS 2.0 aware and is scoped to accounts from a resource limit perspective. This is not the same as an individual server's resources, but may feel that way starting out. Don't worry, clustering is coming next but we wanted to get input early from the community.
Using Docker
The synadia/jsm:latest docker image contains both the JetStream enabled NATS Server and the nats utility this guide covers.
In one window start JetStream:
$ docker run -ti --name jetstream synadia/jsm:latest server
[1] 2020/01/20 12:44:11.752465 [INF] Starting nats-server version 2.2.0-beta
[1] 2020/01/20 12:44:11.752694 [INF] Git commit [19dc3eb]
[1] 2020/01/20 12:44:11.752875 [INF] Starting JetStream
[1] 2020/01/20 12:44:11.753692 [INF] ----------- JETSTREAM (Beta) -----------
[1] 2020/01/20 12:44:11.753794 [INF] Max Memory: 1.46 GB
[1] 2020/01/20 12:44:11.753822 [INF] Max Storage: 1.00 TB
[1] 2020/01/20 12:44:11.753860 [INF] Store Directory: "/tmp/jetstream"
[1] 2020/01/20 12:44:11.753893 [INF] ----------------------------------------
[1] 2020/01/20 12:44:11.753988 [INF] JetStream state for account "$G" recovered
[1] 2020/01/20 12:44:11.754148 [INF] Listening for client connections on 0.0.0.0:4222
[1] 2020/01/20 12:44:11.754279 [INF] Server id is NDYX5IMGF2YLX6RC4WLZA7T3JGHPZR2RNCCIFUQBT6C4TP27Z6ZIC73V
[1] 2020/01/20 12:44:11.754308 [INF] Server is ready
And in another log into the utilities:
$ docker run -ti --link jetstream synadia/jsm:latest
This shell has the nats utility and all other NATS cli tools used in the rest of this guide.
Now skip to the Administer JetStream section.
Using Docker with NGS
You can join a JetStream instance to your NGS account, first we need a credential for testing JetStream:
$ nsc add user -a YourAccount --name leafnode --expiry 1M
You'll get a credential file somewhere like ~/.nkeys/creds/synadia/YourAccount/leafnode.creds, mount this file into the docker container for JetStream using -v ~/.nkeys/creds/synadia/YourAccount/leafnode.creds:/leafnode.creds.
$ docker run -ti -v ~/.nkeys/creds/synadia/YourAccount/leafnode.creds:/leafnode.creds --name jetstream synadia/jsm:latest server
[1] 2020/01/20 12:44:11.752465 [INF] Starting nats-server version 2.2.0-beta
...
[1] 2020/01/20 12:55:01.849033 [INF] Connected leafnode to "connect.ngs.global"
Your JSM shell will still connect locally, other connections in your NGS account can use JetStream at this point.
Using Source
You will also want to have installed from the nats.go repo the examples/tools such as nats-pub, nats-sub, nats-req and possibly nats-bench. One of the design goals of JetStream was to be native to core NATS, so even though we will most certainly add in syntactic sugar to clients to make them more appealing, for this tech preview we will be using plain old NATS.
You will need a copy of the nats-server source locally and will need to be in the jetstream branch.
$ git clone https://github.com/nats-io/nats-server.git
$ cd nats-server
$ git checkout jetstream
$ go build
$ ls -l nats-server
Starting the server you can use the -js flag. This will setup the server to reasonably use memory and disk. This is a sample run on my machine. JetStream will default to 1TB of disk and 75% of available memory for now.
$ ./nats-server -js
[16928] 2019/12/04 19:16:29.596968 [INF] Starting nats-server version 2.2.0-beta
[16928] 2019/12/04 19:16:29.597056 [INF] Git commit [not set]
[16928] 2019/12/04 19:16:29.597072 [INF] Starting JetStream
[16928] 2019/12/04 19:16:29.597444 [INF] ----------- JETSTREAM (Beta) -----------
[16928] 2019/12/04 19:16:29.597451 [INF] Max Memory: 96.00 GB
[16928] 2019/12/04 19:16:29.597454 [INF] Max Storage: 1.00 TB
[16928] 2019/12/04 19:16:29.597461 [INF] Store Directory: "/var/folders/m0/k03vs55n2b54kdg7jm66g27h0000gn/T/jetstream"
[16928] 2019/12/04 19:16:29.597469 [INF] ----------------------------------------
[16928] 2019/12/04 19:16:29.597732 [INF] Listening for client connections on 0.0.0.0:4222
[16928] 2019/12/04 19:16:29.597738 [INF] Server id is NAJ5GKP5OBVISP5MW3BFAD447LMTIOAHFEWMH2XYWLL5STVGN3MJHTXQ
[16928] 2019/12/04 19:16:29.597742 [INF] Server is ready
You can override the storage directory if you want.
$ ./nats-server -js -sd /tmp/test
[16943] 2019/12/04 19:20:00.874148 [INF] Starting nats-server version 2.2.0-beta
[16943] 2019/12/04 19:20:00.874247 [INF] Git commit [not set]
[16943] 2019/12/04 19:20:00.874273 [INF] Starting JetStream
[16943] 2019/12/04 19:20:00.874605 [INF] ----------- JETSTREAM (Beta) -----------
[16943] 2019/12/04 19:20:00.874613 [INF] Max Memory: 96.00 GB
[16943] 2019/12/04 19:20:00.874615 [INF] Max Storage: 1.00 TB
[16943] 2019/12/04 19:20:00.874620 [INF] Store Directory: "/tmp/test/jetstream"
[16943] 2019/12/04 19:20:00.874625 [INF] ----------------------------------------
[16943] 2019/12/04 19:20:00.874868 [INF] Listening for client connections on 0.0.0.0:4222
[16943] 2019/12/04 19:20:00.874874 [INF] Server id is NCR6KDDGWUU2FXO23WAXFY66VQE6JNWVMA24ALF2MO5GKAYFIMQULKUO
[16943] 2019/12/04 19:20:00.874877 [INF] Server is ready
These options can also be set in your configuration file:
// enables jetstream, an empty block will enable and use defaults
jetstream {
// jetstream data will be in /data/nats-server/jetstream
store_dir: "/data/nats-server"
// 1GB
max_memory_store: 1073741824
// 10GB
max_file_store: 10737418240
}
Administration and Usage from the CLI
Once the server is running it's time to use the management tool. This can be downloaded from the GitHub Release Page or you can use the synadia/jsm:latest docker image.
$ nats --help
usage: nats [<flags>] <command> [<args> ...]
NATS Management Utility
Flags:
--help Show context-sensitive help (also try --help-long and --help-man).
--version Show application version.
-s, --server="localhost:4222" NATS servers
--creds=CREDS User credentials
--tlscert=TLSCERT TLS public certifcate
--tlskey=TLSKEY TLS private key
--tlsca=TLSCA TLS certifcate authority chain
--timeout=2s Time to give JetStream to respond to queries
Commands:
help [<command>...]
Show help.
...
We'll walk through the above scenario and introduce features of the CLI and of JetStream as we recreate the setup above.
Throughout this example, we'll show other commands like nats pub and nats sub to interact with the system. These are normal existing core NATS commands and JetStream is fully usable by only using core NATS.
We'll touch on some additional features but please review the section on the design model to understand all possible permutations.
Account Information
JetStream is multi-tenant so you will need to check that your account is enabled for JetStream and is not limited. You can view your limits as follows:
$ nats account info
Memory: 0 B of 6.4 GB
Storage: 0 B of 1.1 TB
Streams: 1 of Unlimited
Streams
The first step is to set up storage for our ORDERS related messages, these arrive on a wildcard of subjects all flowing into the same Stream and they are kept for 1 year.
Creating
$ nats str add ORDERS
? Subjects to consume ORDERS.*
? Storage backend file
? Retention Policy Limits
? Discard Policy Old
? Message count limit -1
? Message size limit -1
? Maximum message age limit 1y
? Maximum individual message size [? for help] (-1) -1
Stream ORDERS was created
Information for Stream ORDERS
Configuration:
Subjects: ORDERS.*
Acknowledgements: true
Retention: File - Limits
Replicas: 1
Maximum Messages: -1
Maximum Bytes: -1
Maximum Age: 8760h0m0s
Maximum Message Size: -1
Maximum Consumers: -1
Statistics:
Messages: 0
Bytes: 0 B
FirstSeq: 0
LastSeq: 0
Active Consumers: 0
You can get prompted interactively for missing information as above, or do it all on one command. Pressing ? in the CLI will help you map prompts to CLI options:
$ nats str add ORDERS --subjects "ORDERS.*" --ack --max-msgs=-1 --max-bytes=-1 --max-age=1y --storage file --retention limits --max-msg-size=-1 --discard old
Additionally one can store the configuration in a JSON file, the format of this is the same as $ nats str info ORDERS -j | jq .config:
$ nats str add ORDERS --config orders.json
Listing
We can confirm our Stream was created:
$ nats str ls
Streams:
ORDERS
Querying
Information about the configuration of the Stream can be seen, and if you did not specify the Stream like below, it will prompt you based on all known ones:
$ nats str info ORDERS
Information for Stream ORDERS
Configuration:
Subjects: ORDERS.*
No Acknowledgements: false
Retention: File - Limits
Replicas: 1
Maximum Messages: -1
Maximum Bytes: -1
Maximum Age: 8760h0m0s
Maximum Consumers: -1
Statistics:
Messages: 0
Bytes: 0 B
FirstSeq: 0
LastSeq: 0
Active Consumers: 0
Most commands that show data as above support -j to show the results as JSON:
$ nats str info ORDERS -j
{
"config": {
"name": "ORDERS",
"subjects": [
"ORDERS.*"
],
"retention": "limits",
"max_consumers": -1,
"max_msgs": -1,
"max_bytes": -1,
"max_age": 31536000000000000,
"storage": "file",
"num_replicas": 1
},
"stats": {
"messages": 0,
"bytes": 0,
"first_seq": 0,
"last_seq": 0,
"consumer_count": 0
}
}
This is the general pattern for the entire nats utility as it relates to JetStream - prompting for needed information but every action can be run non-interactively making it usable as a cli api. All information output like seen above can be turned into JSON using -j.
Copying
A stream can be copied into another, which also allows the configuration of the new one to be adjusted via CLI flags:
$ nats str cp ORDERS ARCHIVE --subjects "ORDERS_ARCVHIVE.*" --max-age 2y
Stream ORDERS was created
Information for Stream ARCHIVE
Configuration:
Subjects: ORDERS_ARCVHIVE.*
...
Maximum Age: 17520h0m0s
...
Editing
A stream configuration can be edited, which allows the configuration to be adjusted via CLI flags. Here I have a incorrectly created ORDERS stream that I fix:
$ nats str info ORDERS -j | jq .config.subjects
[
"ORDERS.new"
]
$ nats str edit ORDERS --subjects "ORDERS.*"
Stream ORDERS was updated
Information for Stream ORDERS
Configuration:
Subjects: ORDERS.*
....
Additionally one can store the configuration in a JSON file, the format of this is the same as $ nats str info ORDERS -j | jq .config:
$ nats str edit ORDERS --config orders.json
Publishing Into a Stream
Now let's add in some messages to our Stream. You can use nats pub to add messages, pass the --wait flag to see the publish ack being returned.
You can publish without waiting for acknowledgement:
$ nats pub ORDERS.scratch hello
Published [sub1] : 'hello'
But if you want to be sure your messages got to JetStream and were persisted you can make a request:
$ nats req ORDERS.scratch hello
13:45:03 Sending request on [ORDERS.scratch]
13:45:03 Received on [_INBOX.M8drJkd8O5otORAo0sMNkg.scHnSafY]: '+OK'
Keep checking the status of the Stream while doing this and you'll see it's stored messages increase.
$ nats str info ORDERS
Information for Stream ORDERS
...
Statistics:
Messages: 3
Bytes: 147 B
FirstSeq: 1
LastSeq: 3
Active Consumers: 0
After putting some throw away data into the Stream, we can purge all the data out - while keeping the Stream active:
Deleting All Data
To delete all data in a stream use purge:
$ nats str purge ORDERS -f
...
Statistics:
Messages: 0
Bytes: 0 B
FirstSeq: 1,000,001
LastSeq: 1,000,000
Active Consumers: 0
Deleting A Message
A single message can be securely removed from the stream:
$ nats str rmm ORDERS 1 -f
Deleting Sets
Finally for demonstration purposes, you can also delete the whole Stream and recreate it so then we're ready for creating the Consumers:
$ nats str rm ORDERS -f
$ nats str add ORDERS --subjects "ORDERS.*" --ack --max-msgs=-1 --max-bytes=-1 --max-age=1y --storage file --retention limits --max-msg-size=-1
Consumers
Consumers is how messages are read or consumed from the Stream. We support pull and push-based Consumers and the example scenario has both, lets walk through that.
Creating Pull-Based Consumers
The NEW and DISPATCH Consumers are pull-based, meaning the services consuming data from them have to ask the system for the next available message. This means you can easily scale your services up by adding more workers and the messages will get spread across the workers based on their availability.
Pull-based Consumers are created the same as push-based Consumers, just don't specify a delivery target.
$ nats con ls ORDERS
No Consumers defined
We have no Consumers, lets add the NEW one:
I supply the --sample options on the CLI as this is not prompted for at present, everything else is prompted. The help in the CLI explains each:
$ nats con add --sample 100
? Select a Stream ORDERS
? Consumer name NEW
? Delivery target
? Start policy (all, last, 1h, msg sequence) all
? Filter Stream by subject (blank for all) ORDERS.received
? Maximum Allowed Deliveries 20
Information for Consumer ORDERS > NEW
Configuration:
Durable Name: NEW
Pull Mode: true
Subject: ORDERS.received
Deliver All: true
Deliver Last: false
Ack Policy: explicit
Ack Wait: 30s
Replay Policy: instant
Maximum Deliveries: 20
Sampling Rate: 100
State:
Last Delivered Message: Consumer sequence: 1 Stream sequence: 1
Acknowledgment floor: Consumer sequence: 0 Stream sequence: 0
Pending Messages: 0
Redelivered Messages: 0
This is a pull-based Consumer (empty Delivery Target), it gets messages from the first available message and requires specific acknowledgement of each and every message.
It only received messages that originally entered the Stream on ORDERS.received. Remember the Stream subscribes to ORDERS.*, this lets us select a subset of messages from the Stream.
A Maximum Delivery limit of 20 is set, this means if the message is not acknowledged it will be retried but only up to this maximum total deliveries.
Again this can all be done in a single CLI call, lets make the DISPATCH Consumer:
$ nats con add ORDERS DISPATCH --filter ORDERS.processed --ack explicit --pull --deliver all --sample 100 --max-deliver 20
Additionally one can store the configuration in a JSON file, the format of this is the same as $ nats con info ORDERS DISPATCH -j | jq .config:
$ nats con add ORDERS MONITOR --config monitor.json
Creating Push-Based Consumers
Our MONITOR Consumer is push-based, has no ack and will only get new messages and is not sampled:
$ nats con add
? Select a Stream ORDERS
? Consumer name MONITOR
? Delivery target monitor.ORDERS
? Start policy (all, last, 1h, msg sequence) last
? Acknowledgement policy none
? Replay policy instant
? Filter Stream by subject (blank for all)
? Maximum Allowed Deliveries -1
Information for Consumer ORDERS > MONITOR
Configuration:
Durable Name: MONITOR
Delivery Subject: monitor.ORDERS
Deliver All: false
Deliver Last: true
Ack Policy: none
Replay Policy: instant
State:
Last Delivered Message: Consumer sequence: 1 Stream sequence: 3
Acknowledgment floor: Consumer sequence: 0 Stream sequence: 2
Pending Messages: 0
Redelivered Messages: 0
Again you can do this with a single non interactive command:
$ nats con add ORDERS MONITOR --ack none --target monitor.ORDERS --deliver last --replay instant --filter ''
Additionally one can store the configuration in a JSON file, the format of this is the same as $ nats con info ORDERS MONITOR -j | jq .config:
$ nats con add ORDERS --config monitor.json
Listing
You can get a quick list of all the Consumers for a specific Stream:
$ nats con ls ORDERS
Consumers for Stream ORDERS:
DISPATCH
MONITOR
NEW
Querying
All details for an Consumer can be queried, lets first look at a pull-based Consumer:
$ nats con info ORDERS DISPATCH
Information for Consumer ORDERS > DISPATCH
Configuration:
Durable Name: DISPATCH
Pull Mode: true
Subject: ORDERS.processed
Deliver All: true
Deliver Last: false
Ack Policy: explicit
Ack Wait: 30s
Replay Policy: instant
Sampling Rate: 100
State:
Last Delivered Message: Consumer sequence: 1 Stream sequence: 1
Acknowledgment floor: Consumer sequence: 0 Stream sequence: 0
Pending Messages: 0
Redelivered Messages: 0
More details about the State section will be shown later when discussing the ack models in depth.
Consuming Pull-Based Consumers
Pull-based Consumers require you to specifically ask for messages and ack them, typically you would do this with the client library Request() feature, but the jsm utility has a helper:
First we ensure we have a message:
$ nats pub ORDERS.processed "order 1"
$ nats pub ORDERS.processed "order 2"
$ nats pub ORDERS.processed "order 3"
We can now read them using nats:
$ nats con next ORDERS DISPATCH
--- received on ORDERS.processed
order 1
Acknowledged message
$ nats con next ORDERS DISPATCH
--- received on ORDERS.processed
order 2
Acknowledged message
You can prevent ACKs by supplying --no-ack.
To do this from code you'd send a Request() to $JS.NEXT.ORDERS.DISPATCH:
$ nats req '$JS.NEXT.ORDERS.DISPATCH' ''
Published [$JS.NEXT.ORDERS.DISPATCH] : ''
Received [ORDERS.processed] : 'order 3'
Here nats req cannot ack, but in your code you'd respond to the received message with a nil payload as an Ack to JetStream.
Consuming Push-Based Consumers
Push-based Consumers will publish messages to a subject and anyone who subscribes to the subject will get them, they support different Acknowledgement models covered later, but here on the MONITOR Consumer we have no Acknowledgement.
$ nats con info ORDERS MONITOR
...
Delivery Subject: monitor.ORDERS
...
The Consumer is publishing to that subject, so lets listen there:
$ nats sub monitor.ORDERS
Listening on [monitor.ORDERS]
[#3] Received on [ORDERS.processed]: 'order 3'
[#4] Received on [ORDERS.processed]: 'order 4'
Note the subject here of the received message is reported as ORDERS.processed this helps you distinguish what you're seeing in a Stream covering a wildcard, or multiple subject, subject space.
This Consumer needs no ack, so any new message into the ORDERS system will show up here in real time.
Configuration Management
In many cases managing the configuration in your application code is the best model, many teams though wish to pre-create Streams and Consumers. We support Terraform today in addition to the nats CLI, more methods might be added in future, these tools can be called by your CI or other Operations Workflows.
nats CLI
The nats CLI can be used to manage Streams and Consumers easily using it's --config flag, for example:
Add a new Stream
This creates a new Stream based on orders.json. The orders.json file can be extracted from an existing stream using nats stream info ORDERS | jq .config
$ nats str add ORDERS --config orders.json
Edit an existing Stream
This edits an existing stream ensuring it complies with the configuration in orders.json
$ nats str edit ORDERS --config orders.json
Add a New Consumer
This creates a new Consumer based on orders_new.json. The orders_new.json file can be extracted from an existing stream using nats con info ORDERS NEW | jq .config
$ nats con add ORDERS NEW --config orders_new.json
Terraform
Terraform is a Cloud configuration tool from Hashicorp found at terraform.io, we maintain a Provider for Terraform called terraform-provider-jetstream that can maintain JetStream using Terraform.
Setup
Our provider is not hosted by Hashicorp so installation is a bit more complex than typical. Browse to the Release Page and download the release for your platform and extract it into your Terraform plugins directory.
$ unzip -l terraform-provider-jetstream_0.0.2_darwin_amd64.zip
Archive: terraform-provider-jetstream_0.0.2_darwin_amd64.zip
Length Date Time Name
--------- ---------- ----- ----
11357 03-09-2020 10:48 LICENSE
1830 03-09-2020 12:53 README.md
24574336 03-09-2020 12:54 terraform-provider-jetstream_v0.0.2
Place the terraform-provider-jetstream_v0.0.2 file in ~/.terraform.d/plugins/terraform-provider-jetstream_v0.0.2
In your project you can configure the Provider like this:
provider "jetstream" {
servers = "connect.ngs.global"
credentials = "ngs_jetstream_admin.creds"
}And start using it, here's an example that create the ORDERS example. Review the Project README for full details.
resource "jetstream_stream" "ORDERS" {
name = "ORDERS"
subjects = ["ORDERS.*"]
storage = "file"
max_age = 60 * 60 * 24 * 365
}
resource "jetstream_consumer" "ORDERS_NEW" {
stream_id = jetstream_stream.ORDERS.id
durable_name = "NEW"
deliver_all = true
filter_subject = "ORDERS.received"
sample_freq = 100
}
resource "jetstream_consumer" "ORDERS_DISPATCH" {
stream_id = jetstream_stream.ORDERS.id
durable_name = "DISPATCH"
deliver_all = true
filter_subject = "ORDERS.processed"
sample_freq = 100
}
resource "jetstream_consumer" "ORDERS_MONITOR" {
stream_id = jetstream_stream.ORDERS.id
durable_name = "MONITOR"
deliver_last = true
ack_policy = "none"
delivery_subject = "monitor.ORDERS"
}
output "ORDERS_SUBJECTS" {
value = jetstream_stream.ORDERS.subjects
}Model Deep Dive
The Orders example touched on a lot of features, but some like different Ack models and message limits, need a bit more detail. This section will expand on the above and fill in some blanks.
Stream Limits, Retention Modes and Discard Policy
Streams store data on disk, but we cannot store all data forever so we need ways to control their size automatically.
There are 3 features that come into play when Streams decide how long they store data.
The Retention Policy describes based on what criteria a set will evict messages from its storage:
| Retention Policy | Description |
|---|---|
LimitsPolicy |
Limits are set for how many messages, how big the storage and how old messages may be |
WorkQueuePolicy |
Messages are kept until they were consumed by any one single observer and then removed |
InterestPolicy |
Messages are kept as long as there are Consumers active for them |
In all Retention Policies the basic limits apply as upper bounds, these are MaxMsgs for how many messages are kept in total, MaxBytes for how big the set can be in total and MaxAge for what is the oldest message that will be kept. These are the only limits in play with LimitsPolicy retention.
One can then define additional ways a message may be removed from the Stream earlier than these limits. In WorkQueuePolicy the messages will be removed as soon as any Consumer received an Acknowledgement. In InterestPolicy messages will be removed as soon as there are no more Consumers.
In both WorkQueuePolicy and InterestPolicy the age, size and count limits will still apply as upper bounds.
A final control is the Maximum Size any single message may have. NATS have it's own limit for maximum size (1 MiB by default), but you can say a Stream will only accept messages up to 1024 bytes using MaxMsgSize.
The Discard Policy sets how messages are discard when limits set by LimitsPolicy are reached. The DiscardOld option removes old messages making space for new, while DiscardNew refuses any new messages.
Acknowledgement Models
Streams support acknowledging receiving a message, if you send a Request() to a subject covered by the configuration of the Stream the service will reply to you once it stored the message. If you just publish, it will not. A Stream can be set to disable Acknowledgements by setting NoAck to true in it's configuration.
Consumers have 3 acknowledgement modes:
| Mode | Description |
|---|---|
AckExplicit |
This requires every message to be specifically acknowledged, it's the only supported option for pull-based Consumers |
AckAll |
In this mode if you acknowledge message 100 it will also acknowledge message 1-99, this is good for processing batches and to reduce ack overhead |
AckNone |
No acknowledgements are supported |
To understand how Consumers track messages we will start with a clean ORDERS Stream and DISPATCH Consumer.
$ nats str info ORDERS
...
Statistics:
Messages: 0
Bytes: 0 B
FirstSeq: 0
LastSeq: 0
Active Consumers: 1
The Set is entirely empty
$ nats con info ORDERS DISPATCH
...
State:
Last Delivered Message: Consumer sequence: 1 Stream sequence: 1
Acknowledgment floor: Consumer sequence: 0 Stream sequence: 0
Pending Messages: 0
Redelivered Messages: 0
The Consumer has no messages oustanding and has never had any (Consumer sequence is 1).
We publish one message to the Stream and see that the Stream received it:
$ nats pub ORDERS.processed "order 4"
Published 7 bytes to ORDERS.processed
$ nats str info ORDERS
...
Statistics:
Messages: 1
Bytes: 53 B
FirstSeq: 1
LastSeq: 1
Active Consumers: 1
As the Consumer is pull-based, we can fetch the message, ack it, and check the Consumer state:
$ nats con next ORDERS DISPATCH
--- received on ORDERS.processed
order 4
Acknowledged message
$ nats con info ORDERS DISPATCH
...
State:
Last Delivered Message: Consumer sequence: 2 Stream sequence: 2
Acknowledgment floor: Consumer sequence: 1 Stream sequence: 1
Pending Messages: 0
Redelivered Messages: 0
The message got delivered and acknowledged - Acknowledgement floor is 1 and 1, the sequence of the Consumer is 2 which means its had only the one message through and got acked. Since it was acked, nothing is pending or redelivering.
We'll publish another message, fetch it but not Ack it this time and see the status:
$ nats pub ORDERS.processed "order 5"
Published 7 bytes to ORDERS.processed
$ nats con next ORDERS DISPATCH --no-ack
--- received on ORDERS.processed
order 5
$ nats con info ORDERS DISPATCH
State:
Last Delivered Message: Consumer sequence: 3 Stream sequence: 3
Acknowledgment floor: Consumer sequence: 1 Stream sequence: 1
Pending Messages: 1
Redelivered Messages: 0
Now we can see the Consumer have processed 2 messages (obs sequence is 3, next message will be 3) but the Ack floor is still 1 - thus 1 message is pending acknowledgement. Indeed this is confirmed in the Pending messages.
If I fetch it again and again do not ack it:
$ nats con next ORDERS DISPATCH --no-ack
--- received on ORDERS.processed
order 5
$ nats con info ORDERS DISPATCH
State:
Last Delivered Message: Consumer sequence: 4 Stream sequence: 3
Acknowledgment floor: Consumer sequence: 1 Stream sequence: 1
Pending Messages: 1
Redelivered Messages: 1
The Consumer sequence increases - each delivery attempt increase the sequence - and our redelivered count also goes up.
Finally if I then fetch it again and ack it this time:
$ nats con next ORDERS DISPATCH
--- received on ORDERS.processed
order 5
Acknowledged message
$ nats con info ORDERS DISPATCH
State:
Last Delivered Message: Consumer sequence: 5 Stream sequence: 3
Acknowledgment floor: Consumer sequence: 1 Stream sequence: 1
Pending Messages: 0
Redelivered Messages: 0
Having now Acked the message there are no more pending.
Additionally there are a few types of acknowledgements:
| Type | Bytes | Description |
|---|---|---|
AckAck |
nil, +ACK |
Acknowledges a message was completely handled |
AckNak |
-NAK |
Signals that the message will not be processed now and processing can move onto the next message, NAK'd message will be retried |
AckProgress |
+WPI |
When sent before the AckWait period indicates that work is ongoing and the period should be extended by another equal to AckWait |
AckNext |
+NXT |
Acknowledges the message was handled and requests delivery of the next message to the reply subject. Only applies to Pull-mode. |
So far all the examples was the AckAck type of acknowledgement, by replying to the Ack with the body as indicated in Bytes you can pick what mode of acknowledgement you want.
Consumer Starting Position
When setting up an Consumer you can decide where to start, the system supports the following for the DeliverPolicy:
| Policy | Description |
|---|---|
all |
Delivers all messages that are available |
last |
Delivers the latest message, like a tail -n 1 -f |
new |
Delivers only new messages that arrive after subscribe time |
by_start_time |
Delivers from a specific time onward. Requires OptStartTime to be set |
by_start_sequence |
Delivers from a specific stream sequence. Requires OptStartSeq to be set |
Regardless of what mode you set, this is only the starting point. Once started it will always give you what you have not seen or acknowledged. So this is merely how it picks the very first message.
Lets look at each of these, first we make a new Stream ORDERS and add 100 messages to it.
Now create a DeliverAll pull-based Consumer:
$ nats con add ORDERS ALL --pull --filter ORDERS.processed --ack none --replay instant --deliver all
$ nats con next ORDERS ALL
--- received on ORDERS.processed
order 1
Acknowledged message
Now create a DeliverLast pull-based Consumer:
$ nats con add ORDERS LAST --pull --filter ORDERS.processed --ack none --replay instant --deliver last
$ nats con next ORDERS LAST
--- received on ORDERS.processed
order 100
Acknowledged message
Now create a MsgSetSeq pull-based Consumer:
$ nats con add ORDERS TEN --pull --filter ORDERS.processed --ack none --replay instant --deliver 10
$ nats con next ORDERS TEN
--- received on ORDERS.processed
order 10
Acknowledged message
And finally a time-based Consumer. Let's add some messages a minute apart:
$ nats str purge ORDERS
$ for i in 1 2 3
do
nats pub ORDERS.processed "order ${i}"
sleep 60
done
Then create an Consumer that starts 2 minutes ago:
$ nats con add ORDERS 2MIN --pull --filter ORDERS.processed --ack none --replay instant --deliver 2m
$ nats con next ORDERS 2MIN
--- received on ORDERS.processed
order 2
Acknowledged message
Ephemeral Consumers
So far, all the Consumers you have seen were Durable, meaning they exist even after you disconnect from JetStream. In our Orders scenario, though the MONITOR Consumer could very well be a short-lived thing there just while an operator is debugging the system, there is no need to remember the last seen position if all you are doing is wanting to observe the real-time state.
In this case, we can make an Ephemeral Consumer by first subscribing to the delivery subject, then creating a durable and giving it no durable name. An Ephemeral Consumer exists as long as any subscription is active on its delivery subject. It is automatically be removed, after a short grace period to handle restarts, when there are no subscribers.
Ephemeral Consumers can only be push-based.
Terminal 1:
$ nats sub my.monitor
Terminal 2:
$ nats con add ORDERS --filter '' --ack none --target 'my.monitor' --deliver last --replay instant --ephemeral
The --ephemeral switch tells the system to make an Ephemeral Consumer.
Consumer Message Rates
Typically what you want is if a new Consumer is made the selected messages are delivered to you as quickly as possible. You might want to replay messages at the rate they arrived though, meaning if messages first arrived 1 minute apart and you make a new Consumer it will get the messages a minute apart.
This is useful in load testing scenarios etc. This is called the ReplayPolicy and have values of ReplayInstant and ReplayOriginal.
You can only set ReplayPolicy on push-based Consumers.
$ nats con add ORDERS REPLAY --target out.original --filter ORDERS.processed --ack none --deliver all --sample 100 --replay original
...
Replay Policy: original
...
Now lets publish messages into the Set 10 seconds apart:
$ for i in 1 2 3 <15:15:35
do
nats pub ORDERS.processed "order ${i}"
sleep 10
done
Published [ORDERS.processed] : 'order 1'
Published [ORDERS.processed] : 'order 2'
Published [ORDERS.processed] : 'order 3'
And when we consume them they will come to us 10 seconds apart:
$ nats sub -t out.original
Listening on [out.original]
2020/01/03 15:17:26 [#1] Received on [ORDERS.processed]: 'order 1'
2020/01/03 15:17:36 [#2] Received on [ORDERS.processed]: 'order 2'
2020/01/03 15:17:46 [#3] Received on [ORDERS.processed]: 'order 3'
^C
Stream Templates
When you have many similar streams it can be helpful to auto create them, lets say you have a service by client and they are on subjects CLIENT.*, you can construct a template that will auto generate streams for any matching traffic.
$ nats str template add CLIENTS --subjects "CLIENT.*" --ack --max-msgs=-1 --max-bytes=-1 --max-age=1y --storage file --retention limits --max-msg-size 2048 --max-streams 1024 --discard old
Stream Template CLIENTS was created
Information for Stream Template CLIENTS
Configuration:
Subjects: CLIENT.*
Acknowledgements: true
Retention: File - Limits
Replicas: 1
Maximum Messages: -1
Maximum Bytes: -1
Maximum Age: 8760h0m0s
Maximum Message Size: 2048
Maximum Consumers: -1
Maximum Streams: 1024
Managed Streams:
No Streams have been defined by this template
You can see now streams exist now for it, let's publish some data:
$ nats pub CLIENT.acme hello
And we'll have 1 new Stream:
$ nats str ls
Streams:
CLIENTS_acme
When the template is deleted all the streams it created will be deleted too.
Ack Sampling
In the earlier sections we saw that samples are being sent to a monitoring system. Let's look at that in depth; how the monitoring system works and what it contains.
As messages pass through an Consumer you'd be interested in knowing how many are being redelivered and how many times but also how long it takes for messages to be acknowledged.
Consumers can sample Ack'ed messages for you and publish samples so your monitoring system can observe the health of an Consumer. We will add support for this to NATS Surveyor.
Configuration
You can configure an Consumer for sampling by passing the --sample 80 option to nats consumer add, this tells the system to sample 80% of Acknowledgements.
When viewing info of an Consumer you can tell if it's sampled or not:
$ nats con info ORDERS NEW
...
Sampling Rate: 100
...
Consuming
Samples are published to $JS.EVENT.METRIC.CONSUMER_ACK.<stream>.<consumer> in JSON format containing api.ConsumerAckMetric. Use the nats con events command to view samples:
$ nats con events ORDERS NEW
Listening for Advisories on $JS.EVENT.ADVISORY.*.ORDERS.NEW
Listening for Metrics on $JS.EVENT.METRIC.*.ORDERS.NEW
15:08:31] [Ph0fsiOKRg1TS0c2k0mMz2] Acknowledgement Sample
Consumer: ORDERS > NEW
Stream Sequence: 40
Consumer Sequence: 161
Deliveries: 1
Delay: 1.009ms
$ nats con events ORDERS NEW --json
{
"stream": "ORDERS",
"consumer": "NEW",
"consumer_seq": 155,
"stream_seq": 143,
"ack_time": 5387000,
"delivered": 1
}
{
"stream": "ORDERS",
"consumer": "NEW",
"consumer_seq": 156,
"stream_seq": 144,
"ack_time": 5807800,
"delivered": 1
}
NATS API Reference
Thus far we saw a lot of CLI interactions. The CLI works by sending and receiving specially crafted messages over core NATS to configure the JetStream system. In time we will look to add file based configuration but for now the only method is the NATS API.
Reference
All of these subjects are found as constants in the NATS Server source, so for example the $JS.API.STREAM.LIST is a constant in the nats-server source api.JetStreamListStreams tables below will reference these constants and likewise data structures in the server for payloads.
Error Handling
The APIs used for administrative tools all respond with standardised JSON and these include errors.
$ nats req '$JS.API.STREAM.INFO.nonexisting' ''
Published 11 bytes to $JS.API.STREAM.INFO.nonexisting
Received [_INBOX.lcWgjX2WgJLxqepU0K9pNf.mpBW9tHK] : {
"type": "io.nats.jetstream.api.v1.stream_info_response",
"error": {
"code": 404,
"description": "stream not found"
}
}
$ nats req '$JS.STREAM.INFO.ORDERS' ''
Published 6 bytes to $JS.STREAM.INFO.ORDERS
Received [_INBOX.fwqdpoWtG8XFXHKfqhQDVA.vBecyWmF] : '{
"type": "io.nats.jetstream.api.v1.stream_info_response",
"config": {
"name": "ORDERS",
...
}
Here the responses include a type which can be used to find the JSON Schema for each response.
Non admin APIs - like those for adding a message to the stream will respond with -ERR or +OK with an optional reason after.
Admin API
All the admin actions the nats CLI can do falls in the sections below. The API structure are kept in the api package in the jsm.go repository.
Subjects that and in T like api.JSApiConsumerCreateT are formats and would need to have the Stream Name and in some cases also the Consumer name interpolated into them. In this case t := fmt.Sprintf(api.JSApiConsumerCreateT, streamName) to get the final subject.
The command nats events will show you an audit log of all API access events which includes the full content of each admin request, use this to view the structure of messages the nats command sends.
The API uses JSON for inputs and outputs, all the responses are typed using a type field which indicates their Schema. A JSON Schema repository can be found in nats-io/jetstream/schemas.
General Info
| Subject | Constant | Description | Request Payload | Response Payload |
|---|---|---|---|---|
$JS.API.INFO |
api.JSApiAccountInfo |
Retrieves stats and limits about your account | empty payload | api.JetStreamAccountStats |
Streams
| Subject | Constant | Description | Request Payload | Response Payload |
|---|---|---|---|---|
$JS.API.STREAM.LIST |
api.JSApiStreamList |
Paged list known Stream including all their current information | api.JSApiStreamListRequest |
api.JSApiStreamListResponse |
$JS.API.STREAM.CREATE.* |
api.JSApiStreamCreateT |
Creates a new Stream | api.StreamConfig |
api.JSApiStreamCreateResponse |
$JS.API.STREAM.UPDATE.* |
api.JSApiStreamUpdateT |
Updates an existing Stream with new config | api.StreamConfig |
api.JSApiStreamUpdateResponse |
$JS.API.STREAM.INFO.* |
api.JSApiStreamInfoT |
Information about config and state of a Stream | empty payload, Stream name in subject | api.JSApiStreamInfoResponse |
$JS.API.STREAM.DELETE.* |
api.JSApiStreamDeleteT |
Deletes a Stream and all its data | empty payload, Stream name in subject | api.JSApiStreamDeleteResponse |
$JS.API.STREAM.PURGE.* |
api.JSApiStreamPurgeT |
Purges all of the data in a Stream, leaves the Stream | empty payload, Stream name in subject | api.JSApiStreamPurgeResponse |
$JS.API.STREAM.MSG.DELETE.* |
api.JSApiMsgDeleteT |
Deletes a specific message in the Stream by sequence, useful for GDPR compliance | api.JSApiMsgDeleteRequest |
api.JSApiMsgDeleteResponse |
$JS.API.STREAM.MSG.GET.* |
api.JSApiMsgGetT |
Retrieves a specific message from the stream | api.JSApiMsgGetRequest |
api.JSApiMsgGetResponse |
Stream Templates
| Subject | Constant | Description | Request Payload | Response Payload |
|---|---|---|---|---|
$JS.API.STREAM.TEMPLATE.CREATE.* |
api.JSApiTemplateCreateT |
Creates a Stream Template | api.StreamTemplateConfig |
api.JSApiStreamTemplateCreateResponse |
$JS.API.STREAM.TEMPLATE.NAMES |
api.JSApiTemplateNames |
Paged list all known templates | api.JSApiStreamTemplateNamesRequest |
api.JSApiStreamTemplateNamesResponse |
$JS.API.STREAM.TEMPLATE.INFO.* |
api.JSApiTemplateInfoT |
Information about the config and state of a Stream Template | empty payload, Template name in subject | api.JSApiStreamTemplateInfoResponse |
$JS.API.STREAM.TEMPLATE.DELETE.* |
api.JSApiTemplateDeleteT |
Delete a specific Stream Template and all streams created by this template | empty payload, Template name in subject | api.JSApiStreamTemplateDeleteResponse |
Consumers
| Subject | Constant | Description | Request Payload | Response Payload |
|---|---|---|---|---|
$JS.API.CONSUMER.CREATE.* |
api.JSApiConsumerCreateT |
Create an ephemeral Consumer | api.ConsumerConfig, Stream name in subject |
api.JSApiConsumerCreateResponse |
$JS.API.CONSUMER.DURABLE.CREATE.* |
api.JSApiDurableCreateT |
Create an Consumer | api.ConsumerConfig, Stream name in subject |
api.JSApiConsumerCreateResponse |
$JS.API.CONSUMER.LIST.* |
api.JSApiConsumerListT |
Paged list of known Consumers including their current info | api.JSApiConsumerListRequest |
api.JSApiConsumerListResponse |
$JS.API.CONSUMER.NAMES.* |
api.JSApiConsumerNamesT |
Paged list of known Consumer names | api.JSApiConsumerNamesRequest |
api.JSApiConsumerNamesResponse |
$JS.API.CONSUMER.INFO.*.* |
api.JSApiConsumerInfoT |
Information about an Consumer | empty payload, Stream and Consumer names in subject | api.JSApiConsumerInfoResponse |
$JS.API.CONSUMER.DELETE.*.* |
api.JSApiConsumerDeleteT |
Deletes an Consumer | empty payload, Stream and Consumer names in subject | api.JSApiConsumerDeleteResponse |
ACLs
It's hard to notice here but there is a clear pattern in these subjects, lets look at the various JetStream related subjects:
General information
$JS.API.INFO
Stream and Consumer Admin
$JS.API.STREAM.CREATE.<stream>
$JS.API.STREAM.UPDATE.<stream>
$JS.API.STREAM.DELETE.<stream>
$JS.API.STREAM.INFO.<stream>
$JS.API.STREAM.PURGE.<stream>
$JS.API.STREAM.LIST
$JS.API.STREAM.NAMES
$JS.API.STREAM.MSG.DELETE.<stream>
$JS.API.STREAM.MSG.GET.<stream>
$JS.API.CONSUMER.CREATE.<stream>
$JS.API.CONSUMER.DURABLE.CREATE.<stream>.<consumer>
$JS.API.CONSUMER.DELETE.<stream>.<consumer>
$JS.API.CONSUMER.INFO.<stream>.<consumer>
$JS.API.CONSUMER.LIST.<stream>
$JS.API.CONSUMER.MSG.NEXT.<stream>.%s
$JS.API.CONSUMER.NAMES.<stream>
$JS.API.STREAM.TEMPLATE.CREATE.<stream template>
$JS.API.STREAM.TEMPLATE.DELETE.<stream template>
$JS.API.STREAM.TEMPLATE.INFO.<stream template>
$JS.API.STREAM.TEMPLATE.NAMES
Stream and Consumer Use
$JS.API.CONSUMER.MSG.NEXT.<stream>.<consumer>
$JS.ACK.<stream>.<consumer>.x.x.x
Events and Advisories:
$JS.EVENT.METRIC.CONSUMER_ACK.<stream>.<consumer>
$JS.EVENT.ADVISORY.MAX_DELIVERIES.<stream>.<consumer>
This allow you to easily create ACL rules that limit users to a specific Stream or Consumer and to specific verbs for administration purposes. For ensuring only the receiver of a message can Ack it we have response permissions ensuring you can only Publish to Response subject for messages you received.
Acknowledging Messages
Messages that need acknowledgement will have a Reply subject set, something like $JS.ACK.ORDERS.test.1.2.2, this is the prefix defined in api.JetStreamAckPre followed by <stream>.<consumer>.<delivered count>.<stream sequence>.<stream sequence>.
In all the Synadia maintained API's you can simply do msg.Respond(nil) (or language equivalent) which will send nil to the reply subject.
Fetching The Next Message From a Pull-based Consumer
If you have a pull-based Consumer you can send a standard NATS Request to $JS.API.CONSUMER.MSG.NEXT.<stream>.<consumer>, here the format is defined in api.JetStreamRequestNextT and requires populating using fmt.Sprintf().
$ nats req '$JS.API.CONSUMER.MSG.NEXT.ORDERS.test' '1'
Published 1 bytes to $JS.API.CONSUMER.MSG.NEXT.ORDERS.test
Received [js.1] : 'message 1'
Here we ask for just 1 message - nats req only shows 1 - but you can fetch a batch of messages by varying the argument. This combines well with the AckAll Ack policy.
Fetching From a Stream By Sequence
If you know the Stream sequence of a message you can fetch it directly, this does not support acks. Do a Request() to $JS.API.STREAM.MSG.GET.ORDERS sending it the message sequence as payload. Here the prefix is defined in api.JetStreamMsgBySeqT which also requires populating using fmt.Sprintf().
$ nats req '$JS.API.STREAM.MSG.GET.ORDERS' '{"seq": 1}'
Published 1 bytes to $JS.STREAM.ORDERS.MSG.BYSEQ
Received [_INBOX.cJrbzPJfZrq8NrFm1DsZuH.k91Gb4xM] : '{
"type": "io.nats.jetstream.api.v1.stream_msg_get_response",
"message": {
"subject": "x",
"seq": 1,
"data": "aGVsbG8=",
"time": "2020-05-06T13:18:58.115424+02:00"
}
}'
The Subject shows where the message was received, Data is base64 encoded and Time is when it was received.
Consumer Samples
Samples are published to a specific subject per Consumer, something like $JS.EVENT.METRIC.CONSUMER_ACK.<stream>.<consumer> you can just subscribe to that and get api.ConsumerAckMetric messages in JSON format. The prefix is defined in api.JetStreamMetricConsumerAckPre.
Next Steps
There is plenty more to discuss and features to describe. We will continue to add information to this document and feel free to post any questions on the JetStream Slack channel. For the brave, take a look at nats-server/test/jetstream_test.go for all that JetStream can do. And please file any issues or communicate on Slack or by email [email protected].
Next up is a deep dive into the clustering implementation which will be completed before an official beta. The design has been ongoing since the beginning of coding but I wanted to get this out to the community to gather feedback and additional input.
Discussion Items
There a few items we are still considering/thinking about and would love the community's input. In no particular order.
DLQ (Dead Letter Queue)
Do we need or desire these? JetStream separates Streams (producing, retaining and ordering) from the Consumers (consumption). We do indicate the amount of times a message has been delivered and at least it may make sense when creating an Consumer to set a maximum for number of delivery attempts. Once that is reached however it is not clear what to do with the message. If the Stream is limit-based retention, the message will still be there for an admin to create an Consumer and take a look.
Purge or Truncate (not everything)
We offer purge but that deletes all messages from a Stream. Wondering of you may want to truncate. This is if no message or byte limits were set.
NAK w/ Duration Before Redelivery
Should we allow a time duration to be optionally sent with a NAK to say "do not attempt a redelivery for delta time"
MsgSet Immutable?
Streams are always hashed and each message is hashed with sequence number and timestamp. However we do allow the ability to securely delete messages. Should we also allow the creator of a Stream to specify the set is strictly immutable? I had this programmed before where each message hash included the hash from the previous message, making the whole set tamper proof.
DR/Mirror
We will add the ability to mirror a Stream from one cluster to the next. Just need to think this through.
Account Template to Auto-create msgSets.
As we start to directly instrument accounts with JetStream limits etc., should we also allow a subject space that is not directly assigned to a Stream but creates a template for the system to auto-create Streams. Question is, should we auto-delete them as well, like STAN does?
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