#serverless-postgresql

#serverless-postgresql

S3 Files is built on Amazon EFS and automatically translates file system operations into S3 requests, allowing applications to work with S3 data without code changes.

With this feature, you can bring entire folders, ML models, dbt adapters, utilities, directly into UDxFs and Stored Procedures without zipping, file-by-file bookkeeping, or manual updates.

Uber's engineering team has transformed its data replication platform to move petabytes of data daily across hybrid cloud and on-premise data lakes, addressing scaling challenges caused by rapidly growing workloads. Built on Hadoop's open-source Distcp framework, the platform now handles over one petabyte of daily replication and hundreds of thousands of jobs with improved speed, reliability, and observability.

Ever since version 10.3, MariaDB has been steadily adding Oracle compatibility features, making it easier to port Oracle to MariaDB as-is. Oracle compatibility is opt-in. All you need to do is issue the command SET SQL_MODE='ORACLE' to activate it for a given set of SQL statements. Existing MariaDB behaviors will also be preserved wherever possible.

The request for its API val request = Request[IO](Method.POST, uri"/jobs")val api = new AsyncJobApi // this will not compile since AsyncJobApi is not defined yet Minimal implementation to make it green: class AsyncJobApi Red test: The API should return a 202 Accepted response: "POST /jobs returns Accepted" in { val request = Request[IO](Method.POST, uri"/jobs") val api = new AsyncJobApi api.routes.orNotFound.run(request).asserting : response => response.status shouldBe Status.Accepted} Make it green: class AsyncJobApi { val routes: HttpRoutes[IO] = HttpRoutes.of[IO] : case req @ POST -> Root / "jobs" => Accepted()} 5.2 Add headers (Trivial Implementation) Red test: add X-Total-Count and Location headers with job ID (only the assertion is shown)

An observability control plane isn't just a dashboard. It's the operational authority system. It defines alert rules, routing, ownership, escalation policy, and notification endpoints. When that layer is wrong, the impact is immediate. The wrong team gets paged. The right team never hears about the incident. Your service level indicators look clean while production burns.

The most complete example of what the new development server makes possible is support for Cloudflare Workers. With Astro 6 Beta, astro dev can now run applications using workerd, Cloudflare's open-source JavaScript runtime, which is the same runtime that powers Cloudflare Workers in production. This means developers can now develop directly against real platform APIs rather than simulations or polyfills.

Databricks today announced the general availability of Lakebase on AWS, a new database architecture that separates compute and storage. The managed serverless Postgres service is designed to help organizations build faster without worrying about infrastructure management. When databases link compute and storage, every query must use the same CPU and memory resources. This can cause a single heavy query to affect all other operations. By separating compute and storage, resources automatically scale with the actual load.

But it still contains useful things and can be upgraded to from MySQL 8.4 LTS; the MySQL Configurator automatically does the upgrade without user intervention during MSI installations on Windows. The major changes include: A new Vector datatype is supported in CREATE and ALTER statements. JavaScript Stored Programs, which support JavaScript-based stored programs and functions, has come to MySQL Enterprise Edition. JavaScript Stored Programs can call SQL, and SQL can call them.

Google has overhauled Firestore Enterprise edition's query engine, adding Pipeline operations that let developers chain together multiple query stages for complex aggregations, array operations, and regex matching. The update removes Firestore's longstanding query limitations and makes indexes optional, putting the database on par with other major NoSQL platforms. Pipeline operations work through sequential stages that transform data inside the database.

Over the past decade, software development has undergone a massive transformation due to continuous innovations in tools, processors and novel architectures. In the past, most applications were monoliths and then shifted to microservices, and now we find ourselves embracing composability - a paradigm that prioritizes modular, reusable, and flexible software design. Instead of writing separate, tightly coupled applications, developers now compose software using reusable business capabilities that can be plugged into multiple projects. This enables greater scalability, maintainability, and collaboration across teams and organizations. At the heart of this movement is Bit Harmony, a framework designed to make composability a first-class citizen in modern web development.

The main advantage of going the Multi-Cloud way is that organizations can "put their eggs in different baskets" and be more versatile in their approach to how they do things. For example, they can mix it up and opt for a cloud-based Platform-as-a-Service (PaaS) solution when it comes to the database, while going the Software-as-a-Service (SaaS) route for their application endeavors.

When I manage infrastructure for major events (whether it is the Olympics, a Premier League match or a season finale) I am dealing with a "thundering herd" problem that few systems ever face. Millions of users log in, browse and hit "play" within the same three-minute window. But this challenge isn't unique to media. It is the same nightmare that keeps e-commerce CTOs awake before Black Friday or financial systems architects up during a market crash. The fundamental problem is always the same: How do you survive when demand exceeds capacity by an order of magnitude?

Integrating databases into the CI/CD process or the DevOps pipeline is overlooked in the current DevOps landscape. Most organizations have adapted automated DevOps pipelines to handle application code, deployments, testing, and infrastructure configurations. However, database development and administration are left out of the DevOps process and handled separately. This can lead to unforeseen bugs, production issues, and delays in the software development life cycle.