Operations | Monitoring | ITSM | DevOps | Cloud

Microsoft Azure is a fantastic platform that allows customers to access many cloud resources that customers can then connect to solve business problems. There is enormous power in the platform, and it’s like having your giant box of Lego bricks, which you can build into any solution. The challenge with a platform in which you can build anything you want is that when your application is built, the platform view makes it difficult to create a way for your non-cloud experts to support the end solution.

Gone are days of large applications having tens of servers to deal with gigabytes of data, when seconds of response time and hours of offline maintenance were acceptable. Modern applications are deployed on everything running thousands of multi-core processors; end-users expect millisecond response times and 100% uptime. Need not mention the applications work with Data in Petabytes.

Welcome once again to another Logic App Best practices, Tips, and Tricks. In my previous blog posts, I talked about some of the most essential best practices you should have while working with the Azure Logic App: And some tips and tricks: Today I’m going to speak about another critical Best practice, Tips, and Tricks that you need to implement while administrating your cloud integration resources: Control your connectors (API connections).

When a startup is in its very early stages, rapid iteration and dynamism are at the top of its priorities. The ability to do so, while maintaining a stable and high-quality product, is a big challenge facing the R&D group. We want to release features as quickly as possible, but this rapid velocity cane cause conflicts when writing in-depth, comprehensive tests.

Losing track of communication between applications or code has become a problem with the tech world growing more into supporting Serverless cloud architectures and allowing the developer to maintain, upgrade and update these services. One might say that services and code are becoming more loosely coupled, allowing code to run and execute in silos. Let's take an AWS Lambda function as an example.

AWS Lambda is a compute service that lets you run code on high-availability infrastructure without any server provisioning. You can perform tasks such as maintenance of servers and operating systems, capacity provisioning, automatic scaling, and code logging and monitoring. When using AWS Lambda, you are just responsible for your code. Lambda manages the resources needed to run your code, like CPU, network infrastructure, and memory.

Welcome once again to another Logic App Best practices, Tips, and Tricks. In my previous blog posts, I talked about some of the most essential best practices you should have while working with the Azure Logic App: And some tips and tricks: Today I’m going to speak about in my opinion one of the most annoying features/tasks and recommend some Best practices, Tips, and Tricks to minimize it: working with expressions.

Recently we had an interesting use case from our customer for which Serverless360 mapped a perfect solution. We resolved the issue with the new Log Analytics and Application Insights capabilities from Serverless360. This blog will help you better understand the feature set with a real-time use case.