微服务-连接到单个旧数据库时的连接池

Question

I am working on developing micro services for a monolithic application using spring boot + spring cloud + spring JDBC. Currently, the application is connecting to a single database through tomcat JNDI connection pool.

We have a bottleneck here, not to change the database architecture at this point of time because of various reasons like large number of db objects,tight dependencies with other systems,etc.

So we have isolated the micro services based on application features. My concern is if we develop microservices with each having its own connection pool, then the number of connections to the database can increase exponentially.

Currently, I am thinking of two solutions

1. To calculate the number of connections that is being used currently by each application feature and arriving at max/min connection params per service- which is a very tedious process and we don't have any mechanism to get the connection count per app feature.

2. To develop a data-microservice with a single connection pool which gets the query object from other MS, triggers the query to the database and returns the resultset object to the caller.

Not sure whether the second approach is a best practice in the microservices architechture.

Can you please suggest any other standard approaches that can be helpful in the current situation?

Answer 1

It's all about the tradeoffs.

1. To calculate the number of connections that is being used currently by each application feature and arriving at max/min connection params per service.

Cons : As you said, some profiling and guesswork needed to reach the sweet number of connection per app feature.

Pros : Unlike the second approach, you can avoid performance overhead

2. To develop a data-microservice with a single connection pool which gets the query object from other MS, triggers the query to the database and returns the resultset object to the caller.

Pros : Minimal work upfront

Cons : one more layer, in turn one more failure point. Performance will degrade as you have to deal with serialization -> Http(s) network latency -> deserialization->(jdbc fun stuff which is part of either approach) -> serialization -> Http(s) network latency -> deserialization . (In your case this performance cost may be negligible. But if every millisecond counts in your service, then this is a huge deciding factor)

In my opinion, I wouldn't split the application layer alone until I have analyzed my domains and my datastores.

This is a good read: http://blog.christianposta.com/microservices/the-hardest-part-about-microservices-data/

Answer 2

I am facing a similar dilemma at my work and I can share the conclusions we have reached so far.

There is no silver bullet at the moment, so:

1 - Calculate the number of connections dividing the total desired number of connections for the instances of microservices will work well if you have a situation where your microservices don't need to drastically elastic scale.

2 - Not having a pool at all and let the connections be opened on demand. This is what is being used in functional programming (like Amazon lambdas). It will reduce the total number of open connections but the downside is that you lose performance as per opening connections on the fly is expensive.

You could implement some sort of topic that let your service know that the number of instances changed in a listener and update the total connection number, but it is a complex solution and goes against the microservice principle that you should not change the configurations of the service after it started running.

Conclusion: I would calculate the number if the microservice tend to not grow in scale and without a pool if it does need to grow elastically and exponentially, in this last case make sure that a retry is in place in case it does not get a connection in the first attempt.

There is an interesting grey area here awaiting for a better way of controlling pools of connections in microservices.

In time, and to make the problem even more interesting, I recommend reading the
article About Pool Sizing from HikariCP: https://github.com/brettwooldridge/HikariCP/wiki/About-Pool-Sizing The ideal concurrent connections in a database are actually smaller than most people think.