api

Last week, we listed 16 practices to help secure one’s APIs and described how to implement them with Apache APISIX. Authentication 🕵️️ - Verifies the identity of users accessing APIs.Authorization 🚦 - Determines permissions of authenticated users.Data Redaction 🖍️ - Obscures sensitive data for protection.Encryption 🔒 - Encodes data so only authorized parties can decode it.Error Handling ❌ - Manages responses when things go wrong, avoiding revealing sensitive info.

A couple of months ago, I stumbled upon this list of Secure your API with these 16 practices to secure your API: Authentication 🕵️️ - Verifies the identity of users accessing APIs.Authorization 🚦 - Determines permissions of authenticated users.Data Redaction 🖍️ - Obscures sensitive data for protection.Encryption 🔒 - Encodes data so only authorized parties can decode it.Error Handling ❌ - Manages responses when things go wrong, avoiding revealing sensitive info.

A couple of months ago, I stumbled upon this list of 16 practices to secure your API: Authentication 🕵️️ - Verifies the identity of users accessing APIs.Authorization 🚦 - Determines permissions of authenticated users.Data Redaction 🖍️ - Obscures sensitive data for protection.Encryption 🔒 - Encodes data so only authorized parties can decode it.Error Handling ❌ - Manages responses when things go wrong, avoiding revealing sensitive info.

I’m continuing my API journey by reading books, viewing relevant YouTube videos, and reading relevant IETF RFCs. Today is a book review. Facts 21 chapters$38.

I already mentioned how I’m trying to get to speed in the API world: reading books, viewing relevant YouTube videos and reading relevant IETF RFCs. Facts 30 chapters, $35.00The author is a Principal Software Engineer at GoogleHe’s also the author behind https://google.aip.

Creating a full-fledged API requires resources, both time and money. You need to think about the model, the design, the REST principles, etc., without writing a single line of code. Most of the time, you don’t know whether it’s worth it: you’d like to offer a Minimum Viable Product and iterate from there. I want to show how you can achieve it without writing a single line of code. The solution The main requirement of the solution is to use the PostgreSQL database.

Ever since I started to work on the Apache APISIX project, I’ve been trying to improve my knowledge and understanding of REST RESTful HTTP APIs. For this, I’m reading and watching the following sources: Books. At the moment, I’m finishing API Design Patterns. Expect a review soon.YouTube. I’d recommend ErikWilde' channel. While some videos are better than others, they all focus on APIs.IETF RFCs.

Designing an intuitive, user-friendly RESTful API is a tough job. It might already be a massive task if it’s your first attempt. Planning for the lifecycle management of your API is likely to be an afterthought. But it’s possible anyway: in this post, I’d like to propose a no-nonsense approach to evolving your APIs, even if it was not planned. The initial situation Let’s consider a sample application that says 'Hello' when using it. > curl http://org.

December was not a good time for Java developers and even less for Ops. The former had to repackage their apps with a fixed Log4J’s version, and the latter had to redeploy them - several times. Yet, every cloud has a silver lining. In my case, I learned about System.Logger. A good time to start using the new standard System.Logger API introduced in Java 9: https://t.co/SaBUnqEZqF. It works like SLF4J and by default logs using JUL but can use Log4J or any othet logging under the hood.

The need for shorter and shorter Time-To-Market requires to integrate more and more third-party libraries. There’s no time for the NIH syndrom anymore if it ever was. While most of the time, the library’s API is ready to use, it happens that one needs to 'adapt' it to the codebase sometimes. How easy the adaptation is depends a lot on the language. For example, in the JVM, there are a couple of Reactive-Programming libraries: RxJava, Project Reactor, Mutiny, and coroutines.

The JVM ecosystem is mature and offers plenty of libraries, so you don’t need to reinvent the wheel. Basic - and not so basic - functionalities are just a dependency away. Sometimes, however, the dependency and your use-case are slightly misaligned. The correct way to fix this would be to create a Pull Request. But your deadline is tomorrow: you need to make it work now! It’s time to hack the provided API.

Last week, I described a use-case for a custom Stream Collector. I received a intriguing comment on Twitter: There was a 'Not Found' error fetching URL: 'https://twitter.com/Miguucm/status/1389258245886390292' Hats off to you, Miguel! Your comment revealed a method I didn’t know! So I decided to investigate what the teeing() method is about. Returns a Collector that is a composite of two downstream collectors.

Java Stream’s Collectors methods fit most use-cases. They allow returning either a Collection or a scalar. For the former, you use one of the toXXX() method, for the latter, one of the reducing() one. Let’s imagine an e-commerce platform that implements a shopping cart. The cart is modeled as the following: This diagram might translate into the following (abridged) code: Product.

This week, I learned about a nifty 'new' feature of Optional that I want to share in this post. It’s available since Java 9, so its novelty is relative. Let’s start with the following sequence to compute the total price of an order: public BigDecimal getOrderPrice(Long orderId) { List<OrderLine> lines = orderRepository.findByOrderId(orderId); BigDecimal price = BigDecimal.ZERO; (1) for (OrderLine line : lines) { price = price.add(line.

Lately, I succumbed to nostalgia, and agreed to do some consulting for a customer. The job was to audit the internal quality of an application, and finally to make recommandations to improve the code base and reimburse the technical debt. While parsing the source code, I couldn’t help but notice a bug in the implementation of a Comparator. This post is to understand how sorting works in Java, what is a Comparator, and how to prevent fellow developers to fall into the same trap.

If you’ve been working in Java since 'quite some time', you probably are experienced in using Map objects. One very frequent use-case is to check if a Map contains a value: Get the valueIf the value is null, put an initial value.If isn’t, transform the get value and put the new value into the map under the same key Map<String, Integer> map = new HashMap<>(); // ... Integer value = map.get(key); if (value == null) { map.put(key, 1); } else { map.

It might happen that you need to deduplicate a list of items…​ coming from legacy code. The class - let’s call it LegacyObject has already implementations for equals() and hashCode(). It’s not possible to change the implementation, for fear of breaking the running code. And unfortunately, the Java API doesn’t offer a distinctBy() feature.

Some time ago, I described a couple of surprising design choices in the JDK functional interfaces API. Lately, during a lesson, a student of mine proposed to shallow-copy an ArrayList by using the clone() method: I thought this is another API gotcha worth writing about. Cloning an object means a new object is created with the same state as the original one. As per the JavaDoc: Creates and returns a copy of this object. The precise meaning of 'copy' may depend on the class of the object.

I’m a big fan of Baeldung’s blog. One of his latest post is about casting in Java. Unfortunately, I feel it misses one important point: dynamic casting. Since that’s is (very) relatively new, this post will try to fill that gap.

At the root of Kotlin’s Collection API lies the Iterator interface, similar to Java’s. But the similitude stops after that. java.util.ListIterator features are broken down into different contracts.

Kotlin’s extension functions are a great way to add behavior to a type sitting outside one’s control - the JDK or a third-party library. For example, the JDK’s String class offers the toLowerCase() and toUpperCase() methods but nothing to capitalize the string. In Kotlin, this can be helped by adding the desired behavior to the String class through an extension function: fun String.capitalize() = when { length < 2 -> toUpperCase() else -> Character.

A little more than 2 years ago, I wrote a post on how you could create a Die rolling API in Scala. As I’m more and more interested in Kotlin, let’s do that in Kotlin. At the root of the hierarchy lies the Rollable interface

I wanted to create a small project where I could achieve results fairly quickly in technologies I never (or rarely) use. At the Mix-IT conference, I realized the few stuff I learned in Scala had been quickly forgotten. And I wanted wanted to give Gradle a try, despite my regular bitching about it.