Until recently, monitoring was exclusive to the IT operations department who was responsible for maintaining the hardware and networking equipment to run a companies’ entire suite of software. But nowadays, changes in deployment frequency, architecture, and cloud hosting have shifted that responsibility. Monitoring is no longer just for ops teams.
In many projects, things that seem very small come to be decisive factors to continue on the current path or find a better one. Starting from simple text editors to tools used for a long period of time, we all have different flavors for each tool in hand. Merging these ideas sometimes comes to be a to-do, and while this happens for any kind of work done in a group, there are also some other factors that shape the path to it. This time, we came across an issue which let us think about how to proceed. Our project is being developed as an integration
What Is Regression Testing? Regression testing, also known as repeated testing, is the process of ensuring all the old functionalities still correctly work with new changes. In other words, regression testing tests an already tested application to find defects resulting from changes. This is a common step in any software development process and is done by testing specialists. Testers do regression testing by re-executing tests against a modified application to evaluate whether the revised code breaks anything which was working earlier. The only reason regression testing might not work is that changing or adding new code to a program can easily introduce errors into code
Since making the jump to developing all of our new production mobile/web apps with Bullet Train for feature flags, one of the latest benefits I’ve come to realise is being able to toggle your app to simulate tedious and complicated scenarios. The Problem: Wasting Time Replicating App Scenarios I know myself a developer have often spent hours replicating issues or developing a new feature that requires the app to be in a certain state. For example, improving onboarding that would require me to signup to my site with around a million Mailinator emails.
By: Alexandr Moroz, Sr. Product Manager, Amazon Route 53; Madhuri Peri, Sr. IoT Architect, AWS Professional Services; Aaron Molitor, Sr. Infrastructure Architect, AWS Professional Services; and Sarma Palli, Sr. DevOps Architect, AWS Professional Services AWS Cloud Map enables you to map your cloud. You can define friendly names for any resource, such as Amazon S3 buckets, Amazon DynamoDB tables, Amazon SQS queues, or custom cloud services built on Amazon EC2, Amazon ECS, Amazon EKS, or AWS Lambda. Your applications can then discover resource location and metadata by friendly name using the AWS SDK and authenticated API queries. Resources can be further filtered and discovered by
We are pleased to announce support for blue/green deployments for services hosted using AWS Fargate and Amazon Elastic Container Service (Amazon ECS). In AWS CodeDeploy, blue/green deployments help you minimize downtime during application updates. They allow you to launch a new version of your application alongside the old version and test the new version before you reroute traffic to it. You can also monitor the deployment process and, if there is an issue, quickly roll back. With this new capability, you can create a new service in AWS Fargate or Amazon ECS that uses CodeDeploy to manage the deployments, testing, and traffic cutover for you.
Today, we are launching support for Amazon Elastic Container Registry (Amazon ECR) as a source provider in AWS CodePipeline. You can now initiate an AWS CodePipeline pipeline update by uploading a new image to Amazon ECR. This makes it easier to set up a continuous delivery pipeline and use the AWS Developer Tools for CI/CD. You can use Amazon ECR as a source if you’re implementing a blue/green deployment with AWS CodeDeploy from the AWS CodePipeline console. For more information about using the Amazon Elastic Container Service (Amazon ECS) console to implement a blue/green deployment without CodePipeline, see Implement Blue/Green Deployments for AWS Fargate and
For a long time, development and operations were isolated modules. Developers wrote code; the system administrators were responsible for its deployment and integration. As there was limited communication between these two silos, specialists worked mostly separately within a project. That was fine when Waterfall development dominated. But since Agile and continuous workflow have taken over the world of software development, this model is out of the game. Short sprints and frequent releases occurring every two weeks or even every day require a new approach and new team roles. Today, DevOps is one of the most discussed software development approaches. It is applied in Facebook, Netflix,
If you’re a developer, containers can feel kind of like magic—they’re portable, efficient, and make it a breeze to spin up new applications. But while containers are great for simple applications, you need extra support as you build them out into larger applications and services. When containers arrived on the scene a few years ago, IT organizations were really struggling to manage them. Deploying containers to their allotted infrastructure was a relatively manual task, with little support for auto-scaling that infrastructure up and down quickly and efficiently. By 2014, we’d been running Borg, our internal container resource manager, for ten years, and thought that putting
Antora is a documentation pipeline that enables docs, product, and engineering teams to create, manage, remix, and publish documentation sites composed in AsciiDoc and sourced from multiple versioned content repositories. You can see several examples out there from Couchbase documentation to Fedora documentation. And of course, Antora documentation is used to generate Antora documentation. You can see it here.