We are building a multi tenant application which has restrictions on the regions/countries where the data is persisted.
The application is based on microsoft .Net microservice architecture but we have shared Domains, although we have separate DBs at very lower levels say for each city a separate DB. We cannot persist the data of one country in another country's data center. Hazelcast will be used as the distributed cache. I could not find any direct ways to configure data isolation for ex. like "Memory Regions" in apache ignite. Do we have "Memory Regions" in hazelcast?
I need to write behind the data from cache to respective Database. Can I segregate a part/partition of cache specific to a database instance?
Any help would be greatly appreciated. Thanks in advance.
I am not directly replying to your question. IMHO, from my understanding when you have a data stored across different clusters / nodes, there will still be a network call, despite you having some key formats so that the data is stored within the same Cluster / Node.
Based on my experience, you could easily setup a MemoryCache that comes as part of the System.Runtime.Caching to store the data in every node and then use Redis Pub-Sub or Azure Service bus as the back-bone for the pub-sub.
In that case,
any data that is updated in a cache is notified to all the other instances of the application via a ServiceBus / Redis message which is typically the key.
Upon receipt of the key, each application clears out its internal cache and then gets the data cached back on the next DB access.
This method is more commonly prevalent in Multi-Tenant Applications and also is fail-safe and light weight. The payloads / network transfers are less and each AppDomain has its internal memory used as a cache which does support different regions via different instances of MemoryCache.
Hope this helps if no direct response is available regarding HazelCast
Also, you may refer to this link for some details regarding the Hazelcast
Related
Why?
For educational purposes. I think it would be really nice for my audience to actually "see" it work like that.
Setup
A dockerized Spring boot REST API (serving up customer information)
A dockerized Cassandra cluster consisting of three connected nodes, holding customer data with a replication factor of two.
Suggestions
Showing which IP address or container name served my request
Showing which IP address or container name held the data that was used to show my request.
If I were to run these nodes on three seperate physical machines, maybe which machine held my data?
Something else you have in mind that really shows the distributed capabilities of Cassandra
Can this be achieved in docker logs or something in Spring data Cassandra that I am not aware of?
I don't know about Spring Data, but in normal Java driver you can get execution information from ResultSet via getExecutionInfo, and call function getQueriedHost from it. If you're using default DCAware/TokenAware load balancing policy, then you reach at least one of the nodes that hold your data. The rest of information you can get via Metadata class from which you can get a list of token ranges owned by hosts, generate a token for your partition key, and lookup in the token ranges.
P.S. See Java driver documentation for more details.
We have configured our application servers (two or three), to work as clients with a Hazelcast cluster (one or two members), for session persistence.
At first, we configured it as a two nodes of application servers with the embedded setup of Hazelcast, then we moved on to the client-server scenario.
On the embedded model, the console showed plenty of information related to the cache objects, replicating between nodes and moving from one instance to another when necessary.
On the Client-Server model we see both clients and members registered on the Hazelcast console, and we get basic information (versions, memory consumption, etc). But we cannot see session information (maps) travel and replicate.
We are pretty sure Hazelcast is working, because we have forced some intrincate combinations of client and member shutdowns that ensure that information recovered by next client must come from the surviving member, and data has traveled from cluster member to cluster member before going down to the client.
So, being convinced we are doing something wrong with the configuration, we humbly ask: Did anyone configure this before (sure, because it seems a very common configuration goal), and did you have similar problems? Did you solve them? How?
You need to enable the statistics for caches to monitor them in the Management Center. Use the element or setStatisticsEnabled() method in declarative or programmatic configuration, respectively, to enable the statistics of maps you want to see on Management Center.
I have two servers, where I will be deploying the same application. Basically these two servers will handle work from a common Web API, the work that handed out will be transformed and go through some logic and loaded into DB. I want to cache the data the get loaded/update or deleted in the database, so that when the same data is referenced i can get it from the Cache (Kind of explained the cache mechanism). Now I am using Ncache and it working perfectly fine within one application. I am trying have kind of a shared cache, so that both my application can have access to. How do i go about doing it?
NCache is a distributed cache so you can continue to use that.
There is good general documentation available and very good getting started material that walks you through all the steps required.
In essence you install NCache on both the servers and then reference both servers in your client configuration (%NCHOME%\config\client.ncconf)
In cluster caches, a single logical cache instance is distributed over multiple server nodes and because the cache process is running outside the application address space, multiple applications can share and see the same exact cache data change in terms of addition, removal and update of the cache content.
Local out-proc caches are limited to one server node but as they are outside the application address space, they also support sharing of data between applications.
In fact, besides allowing multiple applications to share data, NCache supports a pub/sub infrastructure to allow for multiple applications to actually communicate with each other. This allows NCache to play a key part in setting up a fast and reliable microservices environment wherein all the participating services send messages to each other through the NCache platform.
See the link below where they have shared information about NCache topologies
http://www.alachisoft.com/resources/docs/ncache/admin-guide/cache-topologies.html
http://www.alachisoft.com/resources/videos/five-steps-getting-started.html
I need to create a food ordering service, using microservices, scalable , cluster, several steps to order. Need to store user data between steps / requests.
What is an approach to keep state and user data? Store it in DB? Cache? Shared memory?
Are there any tutorials for the best practice of it?
(I gonna use spring / springboot and modules)
Anything that you cannot afford to lose (usually the business data) will go in DB and can be parallelly cached in an in-memory DB like Redis that has a cache eviction algorithm inbuilt.
Anything that, if lost, is not a big deal (usually the technical things that are not directly linked with the business data) can go only in an in-memory DB.
Since you are using Spring, you could probably use something like Redis with Spring Data Redis. There are already known Spring solutions (such as this) to fall back on api calls to fetch data from DB if the Redis server goes down. You can also run multiple Redis instances behind Redis Sentinel to provide failover. Redis Cluster provides a way to run a Redis installation where data is automatically sharded across multiple Redis nodes. Also, you can configure Redis to persist the data in file system once daily or so to backup the cache data for disaster recovery.
If you are looking for a fully managed service, AWS provides "Step Functions" to satisfy your stateful requirements: https://stackoverflow.com/questions/tagged/aws-step-functions
I am very much new to redis. I have been investigating on redis for past few days.I read the documentation on cache management(lru cache), commands ,etc. I want to know how to implement caching for multiple microservice(s) data .
I have few questions:
Can all microservices data(cached) be kept under a single instance of redis
server?
Should every microservice have its own cache database in redis?
How to refresh cache data without setting EXPIRE? Since it would consume more memory.
Some more information on best practices on redis with microservices will be helpful.
It's possible to use the same Redis for multiple microservices, just make sure to prefix your redis cache keys to avoid conflict between all microservices.
You can use multi db in the same redis instance (i.e one for each microservice) but it's discouraged because Redis is single threaded.
The best way is to use one Redis for each microservices, then you can easily flush one of them without touching others.
From my personal experience with a redis cache in production (with 2 million keys), there is no problem using EXPIRE. I encourage you to use it.
Please find below the answer to all your questions -
Can all microservices data(cached) be kept under a single instance of redis server? Ans - Yes you can keep all the data under single redis instance, all you need to do is to set that data using different key Name. As redis is basically a Key-Value Database.
Should every microservice have its own cache database in redis? Ans - Not required. Just make different key for each microservice. Also please note that you can use colon (:) to make folders in redis, to identify different microservices easily on Redis Desktop Manager.
Example - Key Name X:Y:Z, here Z is placed in Y folder and Y is in X. SO you will get a folder kind of structure. That would be helpful to differentiate different microservices.
How to refresh cache data without setting EXPIRE? Since it would consume more memory. Ans - You can set data again on the same key if you have any change in Microservice response. That Key value will get over written in that case.
Can all microservices data(cached) be kept under a single instance of redis server?
In microservice architecture it's prefirible "elastic scale SaaS". You can think your Cache service is perse a microservice (that will response on demand) Then you have multiple options here. The recommended practice on data storage is sharding https://azure.microsoft.com/en-us/documentation/articles/best-practices-caching/#partitioning-a-redis-cache .See the diagram below for book Microservices, IoT and Azure
Should every microservice have its own cache database in redis? It's possible to still thinking "vertical partition" but you should consider "horizontal partitions" so again consider sharding; additionally It's not a bad idea to have "local cache" specialy to avoid DoS
"Be careful not to introduce critical dependencies on the availability of a shared cache service into your solutions. An application should be able to continue functioning if the service that provides the shared cache is unavailable. The application should not hang or fail while waiting for the cache service to resume."
How to refresh cache data without setting EXPIRE? Since it would consume more memory.
You can define your synch polices; I think cache is suitable for things that have few changes.
"It might also be appropriate to have a background process that periodically updates reference data in the cache to ensure it is up to date, or that refreshes the cache when reference data changes."
For cahe best practices check
Caching Best Practices