acstech / doppler-events Goto Github PK

Process gRPC messages into the format needed for Kafka

Currently no error is thrown if kafka is down, so the user has no idea that his/her data is not making it to kafka. This should be fixed if at all possible.

This should create its own Document struct every time and return it.

Refactor doppler-events to match professional, production level Golang code.

This will make the help speed up the backend process. EventEnsure should determine if a value exists in the array and if it does not, then it should add it.

Show the query required to get unique tag values.

This would include having Kafka and InfluxDB being run inside of Docker.

When I am sending data from testsend and then try to log on, the login box will just sit there and be unresponsive for an extended amount of time.

I have have not yet seen if it will eventually log on.

Possibly because we are sending to couchbase and then trying to read from it??

Not sure if should be in doppler-events or dopple-api

This means that there should be a bucket with documents in it which relate to each clientID or something of the sort.

This would need a table to be available that contains all event types and that would be updated when a new event type is added.

This means that there should be a specified age of data that will either be dropped or put into some sort of storage for later access.

There is an unexpected error when running all of the services together.

This would include the ability to connect to the database, query for information from the database, and get the result of any queries run.

This would include the backend API being able to take input and direct it to the Kafka Queue.

This should pick out specific fields and make them tags as specified by the query.

This will include finding what queries to run to get the tags and if possible what options are there for storing eventID's and clientID's in a table.

This would include a file and functions that would be able to take user input in and print it out either on a page or in a file.

Use gRPC in order to listen for API calls and receive stream of messages from user

This includes looking at how fast a person can send data to kafka via sarama and still not have an error.

Make sure that all errors are returned back to the main function instead panicking in the middle of the service.

This would require a decision on which kafka connector plugin to use for connecting to influxdb.

This includes what options are available and a decided option to use.

This means that any credentials will be set at run time and not in the docker-compose file explicitly.

This means that the appropriate error message and type should be returned to the client.

This includes the configuration of couchbase for the bucket, host, username, and password.

This means that a docker image will be used for running each of the API's.