RFC 5277 defines notification replay support. Just wondering what customer problems this notification replay can solve? What could be the need to scan through list of past notifications? At any point of time, controllers can always fire "get" RPC and determine current state.
Any inputs on this are appreciated.
Notification replay is mostly required to sync NETCONF clients with servers without the need to do a full RPC.
In some systems, the configuration + operational data becomes quite large, so the notification replay allows for a delta sync.
The main problem with this is that the server will only keep a limited time window of notifications; so if a client asks for a replay of the last week, the server may be only able to provide a subset of that.
RESTCONF has a different solution for this same issue, the last-modified header field(https://www.rfc-editor.org/rfc/rfc8040#section-3.4.1.1), which allows for doing a get of 'data that has changed since timestamp x'.
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Looking to understand whether there is a a bulletproof event from the namagedObject side of c8y where we know the device has just connected.
I have a microservice that listens for events in real time and I want to trigger a process once we know a device has connected to send its payload.
We have used:
"c8y_Connection": {"status":"CONNECTED"}
We have had the microservice log to Slack all events from managedObjects where we saw for three days the "status":"CONNECTED" value in the payload of our demo devices at reporting times.
But after three days, we see no more this "CONNECTED" state (all payloads showing "DISCONNECTED").
What I am trying to achieve from the inventoryObject event is to understand when a device had connected and sent payload to know when data had arrived. I then go get the data and process it externally. This is post registration and as part of the daily data send cycle for my type of device.
What would be the best way to understand when a device has sent payload in a microservice? I want to notify an external application with either “data is arriving for id 35213” or even better, “data has arrived for device 35213, and here’s the $payload”.
Just as a general information ahead:
The c8y_Connection fragment showing connected shows an active MQTT connection or an active long polling connection and it is only evaluated once every minute.
So if the client is just sending data and immediately disconnecting afterwards this might not picked up.
If you want to see the device having send something to Cumulocity maybe the c8y_Availability fragment is a better as it holds the timestamp when the device last send something.
{ "lastMessage": "2022-10-11T14:49:50.201+09:00", "status": "UNAVAILABLE"}
Also here the evaluation (or better the update to database) only happens every minute.
Both c8y_Availability and c8y_Connection however are only generated if the availability monitoring has been activated for the device (by defining a required interval for the device).
So if you have activated the availability monitoring and you see a "lastMessage" you can reliably say that the device has already send something to Cumulocity.
I have a working monolith application (deployed in a container), for which I want to add notifications feature as a separate microservice.
I'm planning for the monolith to emit events to a message bus (RabbitMQ) where they will be received by the new service, which will send the notification to user. In order to compose a notification, it will need other information about the user from the monolit, so it will call monolith's REST API in order to obtain it.
The problem is, that access to the monolith's API requires authentication in form of a token. I was thinking of:
using the secret from the monolith to issue a never-expiring token - I don't think this is a great idea from the security perspective, and also I know that sometimes the keys rotate in which case the token would became invalid eventually anyway
using the message bus to retrieve the information - this does not seem a good idea either as the asynchrony would make it very complicated
providing all the info the notification service needs in the event - this would make them more coupled together, and moreover, I plan to also send notifications based on the state on the monolith not triggered by an event
removing the authentication from the monolith and implementing it differently (not sure how yet)
My question is, what are some of the good ways this kind of problem can be solved, and also, having just started learning about microservices, is what I am trying to do right in the first place?
When dealing with internal security you should always consider the deployment and how the APIs are exposed to the outside world, an API gateway might be used to simply make it impossible to access internal APIs. In that case, a fixed token might be good enough to ensure that the client is authorized.
In general, though, I would suggest looking into OAuth2 or a JWT-based solution as it helps to validate the identities of the calling system as well as their access grants.
As for your architecture doubts, you need to consider the following scenarios when building out the solution:
The remote call can fail, at any time for unknown reasons, as such you shouldn't acknowledge the notification event until you're certain that the notification has been processed successfully.
As you've mentioned RabbitMQ, you should aim to keep the notification queue as small as possible, to that effect, a cache that contains the user details might help speed things along (and help you reduce the chance of failure due to the external system not being available).
If your application sends a lot of notifications to potentially millions of different users, you could consider having a read-only database replica of the users which is accessible to the notification service, and directly read from the database cluster in batches. This reduces the load on the monolith and shift it to the database layer
using stackdriver's url monitoring.
When it goes down, one time will come but the next will not come.
I would like you to repeatedly notify this if the situation does not change in the next 5 minutes, but I do not know the setting.
somebody help!
https://i.stack.imgur.com/eLROH.png
I'm a product manager with Stackdriver. This is a feature request that we have heard before and are aware of.
This is, unfortunately, not supported at this time, though there are some workarounds:
PagerDuty can be used as a notification channel, and PagerDuty supports repeated notifications.
Webhook can be used as a notification channel, which can be used to create a fully custom delivery mechanism (including one that delivers repeatedly).
Sorry that this isn't available more simply. Hope this helps.
Microsoft Exchange introduced Streaming notifications as an alternative to pull/push notifications with Exchange 2010. Basic introduction on streaming can be found on this msdn article and blog
However, I cant figure out the actual advantage of streaming over push notifications.
The only advantage mentioned in the blog is "..and you don’t have to create a listener application as for the push notifications." Apart from that, are there any other advantages and disadvantages?
How do other factors like managing the subscription, re-subscription logic, scalability, max num of subscriptions, etc compare over push? Also, Streaming subscription has a maximum alive time of 30 mins and I would have to re-subscribe every 30 mins? Isnt that a disadvantage for a large number of subscriptions(my application has to manage 20K+ mailboxes)?
Any light on the comparison factors would be helpful.
The main reason for Streaming Notifications (SNs) is Exchange Online. You can't have EOL opening up an HTTP connection to an application potentially behind a firewall. Even within a corporate network there are firewall issues. I've had several cases where my app could not get Push Notifications (PNs) because of the firewall on its own server.
On the surface SNs would also seem to be more efficient because each notification is not opening up its own TCP connection, but rather they flow in on a single pipe. After doing some Wiresharking on this, I'm not really convinced this is so because it seems like under the covers they're doing Long Polling, so each notification coming in will cause a new HTTP call back up to Exchange.
The 30 minute max is no big deal, just reopen the connection in the handler and you're done--you don't have to actually re-subscribe. In fact, I am of the opinion that I want to lower that even more to say 3 minutes. You apparently cannot add new subscriptions or remove old ones except within the disconnect handler. (Try it, and you get errors.)
And yes, you don't have to code an HTTP handler, which is nice I guess.
I understand that, roughly speaking, Trello uses Redis for a transient data store.
Is anyone able to elaborate further on the part it plays in the application?
We use Redis on Trello for ephemeral data that we would be okay with losing. We do not persist the data in Redis to disk, and we use it allkeys-lru, so we only store things there can be kicked out at any time with only very minor inconvenience to users (e.g. momentarily seeing an incorrect user status). That being said, we give it more than 5x the space it needs to store its actual working set and choose from 10 keys for expiry, so we really never see anything get kicked out that we're using.
It's our pubsub server. When a user does something to a board or a card, we want to send a message with that delta to all websocket-connected clients that are subscribed to the object that changed, so all of our Node processes are subscribed to a pubsub channel that propagates those messages, and they propagate that out to the appropriately permissioned and subscribed websockets.
We SORT OF use it to back socket.io, but since we only use the websockets, and since socket.io is too chatty to scale like we need it to at the moment, we have a patch that disables all but the one channel that is necessary to us.
For our users who don't have websockets, we have to keep a list of the actions that have happened on each object channel since the user's last poll request. For that we use a list which we cap at the most recent 100 elements, and an auxilary counter of how many elements have been added to the list since it was created. So when we're answering a poll request from such a browser, we can check the last element it reports that it has seen, and only send down any messages that have been added to the queue since then. So that gets a poll request down to just a permissions check and a single Redis key check in most cases, which is very fast.
We store some ephemeral data about the active status of connected users in Redis, because that data changes frequently and it is not necessary to persist it to disk.
We store short-lived keys to support OAuth logins in Redis.
We love Redis; once you have an instance of it up and running, you want to use it for all kinds of things. The only real trouble we have had with it is with slow-consuming clients eating up the available space.
We use MongoDB for our more traditional database needs.
Trello uses Redis with Socket.IO (RedisStore) for scaling, with the following two features:
key-value store, to set and get values for a connected client
as a pub-sub service
Resources:
Look at the code for RedisStore in Socket.IO here: https://github.com/LearnBoost/socket.io/blob/master/lib/stores/redis.js
Example of Socket.IO with RedisStore: http://www.ranu.com.ar/2011/11/redisstore-and-rooms-with-socketio.html