#cloud-gcp--devops

#cloud-gcp--devops

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.

For years, reliability discussions have focused on uptime and whether a service met its internal SLO. However, as systems become more distributed, reliant on complex internet stacks, and integrated with AI, this binary perspective is no longer sufficient. Reliability now encompasses digital experience, speed, and business impact. For the second year in a row, The SRE Report highlights this shift.

A North American manufacturer spent most of 2024 and early 2025 doing what many innovative enterprises did: aggressively standardizing on the public cloud by using data lakes, analytics, CI/CD, and even a good chunk of ERP integration. The board liked the narrative because it sounded like simplification, and simplification sounded like savings. Then generative AI arrived, not as a lab toy but as a mandate. "Put copilots everywhere," leadership said. "Start with maintenance, then procurement, then the call center, then engineering change orders."

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.

Industry professionals are realizing what's coming next, and it's well captured in a recent LinkedIn thread that says AI is moving on from being just a helper to a full-fledged co-developer - generating code, automating testing, managing whole workflows and even taking charge of every part of the CI/CD pipeline. Put simply, AI is transforming DevOps into a living ecosystem, one driven by close collaboration between human judgment and machine intelligence.

Over the past decade, software development has been shaped by two closely related transformations. One is the rise of devops and continuous integration and continuous delivery (CI/CD), which brought development and operations teams together around automated, incremental software delivery. The other is the shift from monolithic applications to distributed, cloud-native systems built from microservices and containers, typically managed by orchestration platforms such as Kubernetes.

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.

The Harness Resilience Testing platform extends the scope of the tests provided to include application load and disaster recovery (DR) testing tools that will enable DevOps teams to further streamline workflows.

Manual database deployment means longer release times. Database specialists have to spend several working days prior to release writing and testing scripts which in itself leads to prolonged deployment cycles and less time for testing. As a result, applications are not released on time and customers are not receiving the latest updates and bug fixes. Manual work inevitably results in errors, which cause problems and bottlenecks.

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.

Blue/green deployments on Amazon Elastic Container Service (Amazon ECS) have long been a go-to pattern for shipping zero-downtime deployments. Historically, the recommended approach in the AWS Cloud Development Kit (AWS CDK) was to wire ECS to AWS CodeDeploy for traffic shifting, lifecycle hooks, and tight integration with AWS CodePipeline. In July 2025, Amazon ECS launched built-in blue/green deployments. This allows you to operate directly within the ECS service, without requiring the use of Amazon CodeDeploy.