Operations | Monitoring | ITSM | DevOps | Cloud

Hello, Bitbucket fans It’s Dave from the Bitbucket Cloud product team. We’re happy to introduce another enhancement to help your team better collaborate around code reviews, saving you valuable time – the ability to propose specific code suggestions within a pull request. Code authors can view and apply the proposed code changes without switching contexts, helping teams get pull requests completed even more efficiently. This feature is available today to all teams using Bitbucket Cloud.

Security breaches rarely begin with a hidden zero-day exploit or a complex web of escalated hacks. They often start in very simple ways – an internal team member is breached, a permission is misconfigured, an overly permissive API endpoint is overlooked, or a JWT simply doesn’t expire. An API, or application programming interface, is a set of protocols and tools that enable different software systems to communicate and exchange data, making them essential in modern software development.

Containers and serverless computing are two of the most popular methods for deploying applications. With the rise of microservices and modern DevOps, teams need faster, leaner ways to build and release software. However, selecting the wrong architecture can slow down delivery, increase cloud costs, or lock you into tools that don’t scale with your business. Both methods have their advantages and disadvantages.

Clean, consistent SQL code isn’t just a preference. It’s a pathway to healthier applications, faster debugging, and happier teams. Whether you’re onboarding new developers or optimizing legacy systems, having a clear set of standards can make all the difference. Flyway’s code analysis is a powerful ally in keeping your database code tidy and secure, and making sure best practices are being followed.

ClickHouse is built for high-performance OLAP workloads, capable of scanning billions of rows in seconds. If your analytical queries are bottlenecked on PostgreSQL or MySQL, or you're burning too much on Elasticsearch infrastructure, ClickHouse offers a faster and more cost-efficient alternative. This blog walks through setting up ClickHouse locally with Docker Compose and scaling toward a production-grade cluster with monitoring in place.

It’s 2:47 AM and your Lambda functions are timing out. API response times are spiking. You’re flipping between the CloudWatch console, your APM tool, and your logs, trying to figure out what’s going wrong. CloudWatch has the metrics you need: CPU usage, memory pressure, and request rates — but connecting that data to what your app is doing takes time. The delay in stitching it all together slows down your incident response.