Partner – DBSchema – NPI EA – (tag = SQL)
DbSchema is a super-flexible database designer, which can take you from designing the DB with your team all the way to safely deploying the schema.
The way it does all of that is by using a design model, a database-independent image of the schema, which can be shared in a team using GIT and compared or deployed on to any database.
And, of course, it can be heavily visual, allowing you to interact with the database using diagrams, visually compose queries, explore the data, generate random data, import data or build HTML5 database reports.
>> Take a look at DBSchema
Partner – CAST AI – NPI EA (tag = kubernetes)
The Kubernetes ecosystem is huge and quite complex, so it’s easy to forget about costs when trying out all of the exciting tools.
To avoid overspending on your Kubernetes cluster, definitely have a look at the free K8s cost monitoring tool from the automation platform CAST AI. You can view your costs in real time, allocate them, calculate burn rates for projects, spot anomalies or spikes, and get insightful reports you can share with your team.
Connect your cluster and start monitoring your K8s costs right away:
>> FREE Kubernetes cost monitoring
Partner – MongoDB – NPI EA (tag = MongoDB) Partner – Thundra – NPI EA (tag = Jenkins)
You can get some real insight into your CI pipelines, and into your tests by using Foresight.
This includes not just the basics but some actual, actionable data like Change Impact Analysis, where we can see the changes in a PR and correlate them to test runs and test coverage to show how they affect our builds:
>> Try out Foresight in a project
1. Spring and Java
The reactive support in Spring Data looks very interesting and actually idiomatic. It may also be a nice, high level way to get intro the new programming model.
An opinionated piece from Lukas about the misuse of @NotNull annotations in standard Java code.
Logging can no longer be just an afterthought. As we break our systems apart into multiple deployable units, if we don't dial in logging, we simply won't be able to know what's going on.
This writeup covers some interesting aspects of working with Spring Cloud Sleuth and the ELK stack.
A closer look at the core dependency that's going to power the Spring 5 reactive implementation? Cool beans.
Looking at hundreds of thousands of repositories always produces very interesting data.
And logging data is no exception – some very interesting numbers here, such as the fact that 80% of projects are using SLF4J.
Creating and managing your projects DB structure is never straightforward.
This writeup discusses the available approaches, especially at the beginning of the project, and the advantages of each.
Also worth reading:
Webinars and presentations:
Time to upgrade:
An interesting new diagram style that's able to replace (or maybe upgrade) the venerable sequence diagram.
Like testing, logging is a deceptively difficult thing to master. The technical aspects are dead simple, but HOW to log isn't really the point, but what to log.
This writeup is a good oportunity to revisit assumptions and think about what you're logging in your own system.
Building blocks to process voice and language? What's not to like?
Also worth reading:
12K visitors on the site? It takes a special kind of system to be able to quickly scale up to handle that kind of load.
Developing a curriculum and delivering that training in an engaging way that's actually able to move students forward is not an easy nut to crack.
And of course, training is a topic that I'm particularly interested in (given my own training material here on Baeldung), so this piece was particularly interesting to me.
Also worth reading:
And my favorite Dilberts of the week:
5. Pick of the Week
One of my favorite podcasts out there (non-technical, but well worth listening to):
res – REST with Spring (eBook) (everywhere)