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Data ingestion and data analysis are the yin and yang of a time series platform. There are many resources to help you ingest data. Typical ingestions are agent-based, imports via CSVs, using client libraries, or via third-party technologies. Once your time series data arrives, analysis completes the circle and often leads to additional data collection, and so on and so forth.

After an exciting Day 1 and Day 2 from Integrate Remote, the floor was all set for the final day of the virtual event. To know the session highlights, key announcements, and other spotlights from day 3, check out the below blogs. Also, we would highly recommend you to take a look at Day 1 and Day 2 blog coverage of the event.

With Day 1 of the event rolled up, the platform was all set for the next day of the event. Day 2 of Integrate 2020 has been one roller-coaster experience for the attendees with some amazing sessions and certainly, loads of updates from the Microsoft Product Team and MVPs. So, for those who missed it out, make use of this blog.

This blog is an extraction of the session “Event-Driven Microservices with Azure Functions, Event Grid and Cosmos DB” presented by Martin Abbott, who is Azure MVP, Regional Director. We need to first have a deep understanding of all the services and components that are used to create the End to End application.

INTEGRATE has become part of our company culture since we started it back in 2013. We created a place for all Microsoft Integration people from across the world to get together and share experiences. This year, considering the Covid situation, we made a big decision to take INTEGRATE 2020 into a virtual conference with a new branding called “INTEGRATE 2020 REMOTE”. If you wish to get redirected to blogs based on each session on day 1 of the event, here is the quick guide to help you out.

As a Serverless computing service, Lambda already saves hundreds of thousands of dollars for many companies out there. While traditional server-based infrastructures usually lead to overprovisioning and waste, the Serverless pay-per-use model enables cost-effective cloud spending. Nevertheless, there are still more cost-saving opportunities that many development teams miss on AWS Lambda. Optimizing Lambda functions can be time-consuming, though.

We recently wrote about whether API Gateway can act as a Load Balancer. The answer is yes and, in many cases, they are substitutes for each other. But how should we choose which one to use? In this article, we will dive into more details on how these two types of HTTP networking services compare, using the AWS services as a base level: API Gateway and Application Load Balancer (ALB). Both are highly-scalable services to a point that scalability should not be a concern for most use cases.

The most common API architecture on Serverless backends is not necessarily the most scalable and resilient option. Many developers take for granted that an AWS Lambda processing external requests will require an API Gateway endpoint connected directly to it. One of the best options to decouple a Lambda function and an API Gateway endpoint is by using an SQS queue. Requests come into API Gateway, which are sent as messages to SQS.

We added out of the box alerts for irregular behaviors. Lumigo Insights will trigger an alert the second it detects an irregularity with your functions ensuring you’ll know the second things start to go sideways.

This blog will brief on how to encrypt a text file using Azure Logic App out of the box. In this blog, we will use keys from the Azure Key Vault to encrypt the file. Consider a scenario in which I receive an e-mail with high importance along with the attachments. When it happens, I wish to back up those attachments carrying sensitive information in Azure Storage blobs in an encrypted format. As mentioned above I will use keys from Azure Key Vault to encrypt the files.