kandi X-RAY | spmia-chapter4 Summary
kandi X-RAY | spmia-chapter4 Summary
Welcome to Spring Microservices in Action, Chapter 4. Chapter 4 builds on the material from Chapter 3 and introduces the concept of service registration and discovery patterns using Spring Cloud and Netflix's Eureka server. Using service discovery, you will be able to add and remove service instances without the clients having to know the physical locations of the service.
Top functions reviewed by kandi - BETA
- Save an organization
- Set the ID of the document
- Saves an organization
- The license allocated for this license
- Sets the number of license allocated for this license
- Update a license
- Updates the license
- The license type
- Set the license type
- List of licenses for an organization
- The maximum allowed for the license
- Sets the maximum license maximum
- The licenseId for the license
- Set the organization ID
- Delete an organization
- Gets the id
- Get information about a license
- Gets a request for a license
- Update an organization
- Main entry point
- The main entry point
- Delete a license
- Get an organization
- Saves licenses
- List of Eureka services
- Set the product name
spmia-chapter4 Key Features
spmia-chapter4 Examples and Code Snippets
Trending Discussions on Microservice
I have a kubernetes cluster that's running datadog and some microservices. Each microservice makes healthchecks every 5 seconds to make sure the service is up and running. I want to exclude these healthcheck logs from being ingested into Datadog.
I think I need to use
log_processing_rules and I've tried that but the healthcheck logs are still making it into the logs section of Datadog. My current Deployment looks like this:
ANSWERAnswered 2022-Jan-12 at 20:28
I think the problem is that you're defining multiple patterns; the docs state,
If you want to match one or more patterns you must define them in a single expression.
Try somtething like this and see what happens:
I have create a simple Serilog sink project that looks like this :...
ANSWERAnswered 2022-Feb-23 at 18:28
If you refer to the Provided Sinks list and examine the source code for some of them, you'll notice that the pattern is usually:
- Construct the sink configuration (usually taking values from
IConfiguration, inline or a combination of both)
- Pass the configuration to the sink registration.
Then the sink implementation instantiates the required services to push logs to.
An alternate approach I could suggest is registering Serilog without any arguments (
UseSerilog()) and then configure the static
Serilog.Log class using the built
I searched a lot how to authenticate/authorize Google's client libraries and it seems no one agrees how to do it.
Some people states that I should create a service account, create a key out from it and give that key to each developer that wants to act as this service account. I hate this solution because it leaks the identity of the service account to multiple person.
Others mentioned that you simply log in with the Cloud SDK and ADC (Application Default Credentials) by doing:...
ANSWERAnswered 2021-Oct-02 at 14:00
You can use a new gcloud feature and impersonate your local credential like that:
I am stuck while calling the graphQL mutation API in spring boot. Let me explain my scenario, I have two microservice one is the AuditConsumeService which consume the message from the activeMQ, and the other is GraphQL layer which simply takes the data from the consume service and put it inside the database. Everything well when i try to push data using graphql playground or postman. How do I push data from AuditConsumeService. In the AuditConsumeService I am trying to send mutation API as a string. the method which is responsible to send that to graphQL layer is...
ANSWERAnswered 2022-Jan-23 at 21:40
You have to send the
query and body as variables in post request like shown here
I'm trying to create a minimal jre for Spring Boot microservices using jdeps and jlink, but I'm getting the following error when I get to the using jdeps part...
ANSWERAnswered 2021-Dec-28 at 14:39
I have been struggling with a similar issue In my gradle spring boot project
I am using the output of the following for adding modules in jlink in my dockerfile with (
We have a bunch of microservices based on Spring Boot 2.5.4 also including
spring-boot-actuator:2.5.4. All the services use Tomcat as servlet container and graceful shutdown enabled. These microservices are containerized using docker.
Due to a misconfiguration, yesterday we faced a problem on one of these containers because it took a port already bound from another one.
ANSWERAnswered 2021-Dec-17 at 08:38
Since you have everything containerized, it's way simpler.
Just set up a small healthcheck endpoint with Spring Web which serves to see if the server is still running, something like:
Ok, I'm totally lost on deadlock issue. I just don't know how to solve this.
I have these three tables (I have removed not important columns):...
ANSWERAnswered 2021-Dec-26 at 12:54
You are better off avoiding serializable isolation level. The way the serializable guarantee is provided is often deadlock prone.
If you can't alter your stored procs to use more targeted locking hints that guarantee the results you require at a lesser isolation level then you can prevent this particular deadlock scenario shown by ensuring that all locks are taken out on
ServiceChange first before any are taken out on
One way of doing this would be to introduce a table variable in
spGetManageServicesRequest and materialize the results of
I have to get the existing microservices run. They are given as docker images. They talk to each other by configured hostnames and ports. I started to use Istio to view and configure the outgoing calls of each microservice. Now I am at the point that I need to rewrite / redirect the host and the port of a request that goes out of one container. How can I do that with Istio?
I will try to give a minimum example. There are two services, service-a and service-b....
ANSWERAnswered 2021-Nov-16 at 10:56
There are two solutions which can be used depending on necessity of using
istio features are planned to use, it can be solved using native kubernetes. In turn, if some
istio feature are intended to use, it can be solved using
istio virtual service. Below are two options:
1. Native kubernetes
Service-x should be pointed to the backend of
service-b deployment. Below is
selector which points to
I am using an API which is sending some data about products, every 1 second. on the other hand I have a list of user-created conditions. And I want to check if any data that comes, matches any of the conditions. and if so, I want to notify the user.
for example , user condition maybe like this :
price < 30000 and productName = 'chairNumber2'
and the data would be something like this :
I am using microservice architecture, and on validating condition I am sending a message on RabbitMQ to my notification service
I have tried the naïve solution (every 1 second, check every condition , and if any data meets the condition then pass on data my other service) but this takes so much RAM and time(time order is in n*m,n being the count of conditions, and m is the count of data), so I am looking for a better scenario...
ANSWERAnswered 2021-Aug-31 at 00:23
It's an interesting problem. I have to confess I don't really know how I would do it - it depends a lot on exactly how fast the processing needs to occur, and a lot of other factors not mentioned - such as what constraints to do you have in terms of the technology stack you have, is it on-premise or in the cloud, must the solution be coded by you/your team or can you buy some $$ tool. For future reference, for architecture questions especially, any context you can provide is really helpful - e.g. constraints.
I did think of Pub-Sub, which may offer patterns you can use, but you really just need a simple implementation that will work within your code base, AND very importantly you only have one consuming client, the RabbitMQ queue - it's not like you have X number of random clients wanting the data. So an off-the-shelf Pub-Sub solution might not be a good fit.
Assuming you want a "home-grown" solution, this is what has come to mind so far:
("flow" connectors show data flow, which could be interpreted as a 'push'; where as the other lines are UML "dependency" lines; e.g. the match engine depends on data held in the batch, but it's agnostic as to how that happens).
- The external data source is where the data is coming from. I had not made any assumptions about how that works or what control you have over it.
- Interface, all this does is take the raw data and put it into batches that can be processed later by the Match Engine. How the interface works depends on how you want to balance (a) the data coming in, and (b) what you know the match engine expects.
- Batches are thrown into a batch queue. It's job is to ensure that no data is lost before its processed, that processing can be managed (order of batch processing, resilience, etc).
- Match engine, works fast on the assumption that the size of each batch is a manageable number of records/changes. It's job is to take changes and ask who's interested in them, and return the results to the RabbitMQ. So its inputs are just the batches and the user & user matching rules (more on that later). How this actually works I'm not sure, worst case it iterates through each rule seeing who has a match - what you're doing now, but...
Key point: the queue would also allow you to scale-out the number of match engine instances - but, I don't know what affect that has downstream on the RabbitMQ and it's downstream consumers (the order in which the updates would arrive, etc).
What's not shown: caching. The match engine needs to know what the matching rules are, and which users those rules relate to. The fastest way to do that look-up is probably in memory, not a database read (unless you can be smart about how that happens), which brings me to this addition:
- Data Source is wherever the user data, and user matching rules, are kept. I have assumed they are external to "Your Solution" but it doesn't matter.
- Cache is something that holds the user matches (rules) & user data. It's sole job is to hold these in a way that is optimized for the Match Engine to work fast. You could logically say it was part of the match engine, or separate. How you approach this might be determined by whether or not you intend to scale-out the match engine.
- Data Provider is simply the component whose job it is to fetch user & rule data and make it available for caching.
So, the Rule engine, cache and data provider could all be separate components, or logically parts of the one component / microservice.
I have a dead simple Golang microservice (no Docker, just simple binary file) which returns simple message on GET-request....
ANSWERAnswered 2021-Jul-14 at 10:26
I've managed to find the answer.
- I'm not that smart if I've decided that Traefik would take /proxy and simply redicrect all request to /api/*. The official docs (https://doc.traefik.io/traefik/routing/routers/) says that (I'm quoting):
Use Path if your service listens on the exact path only. For instance, Path: /products would match /products but not /products/shoes.
Use a Prefix matcher if your service listens on a particular base path but also serves requests on sub-paths. For instance, PathPrefix: /products would match /products but also /products/shoes and /products/shirts. Since the path is forwarded as-is, your service is expected to listen on /products.
- I did not use any middleware for replacing substring of path
Now answer as example.
First at all: code for microservice in main.go file
No vulnerabilities reported
You can use spmia-chapter4 like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the spmia-chapter4 component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .
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