Operations | Monitoring | ITSM | DevOps | Cloud

When building systems that need to scale above a certain number of users, we usually can’t stay on one machine. This is where cloud providers like AWS usually come into play. They allow us to rent VMs or containers for small intervals. This way, we can start a few different machines when more traffic hits, and when it goes down later, we can simply turn off our extra capacity and save money. The question is, how does all this traffic get to our new machines? AWS Elastic Load Balancing!

We’ve entered a time when hard drives are becoming less important than data speeds, syncing, and remote storage. More and more end-users are saving their files in the cloud for convenience, safety, and cost savings. That said, some people still have concerns about cloud computing -- namely around security. How safe are files that are stored hundreds or thousands of miles away, on some other organization’s hardware?

Yes. Privacy is (mostly) dead. Not to be all doom and gloom, but the state of online privacy is far from ideal. Many of us can agree that some semblance of privacy is indeed an excellent thing. We all wish for more privacy and more control over where our data ends up, what it's being used for, and who profits from it. While the fight for digital rights still rages, the right to privacy has been completely obliterated over the past decade or so.

The combination of SNS to SQS to Lambda is a common sight in serverless applications on AWS. Perhaps triggered by messages from an API function. This architecture is great for improving UX by offloading slow, asynchronous tasks so the API can stay responsive. It presents an interesting challenge for observability, however. Because observability tools are not able to trace invocations through this combination end-to-end. In X-Ray, for example, the trace would stop at SNS.

Kubernetes may provide an abundance of benefits, but those who are using it may be well aware that it often requires quite a bit (or even a lot!) of effort and skill to run the platform independently. So – rather than having to put up with it on their own, organizations are able to pay for a managed Kubernetes service instead. This is where Google Kubernetes Engine (GKE), Azure Kubernetes Service (AKS), and Amazon Elastic Kubernetes Service (EKS) come in.

AWS is a comprehensive, evolving cloud computing program built to provide IT infrastructure for businesses, and the program has an active user base of roughly 1,000,000 customers. With the massive responsibility of providing services for such a large customer base, it’s important for their services to be reliable and trustworthy.

Open-source software (OSS) relational database management systems (RDBMSes) are becoming incredibly popular in the cloud computing world. In this article, I’ll discuss one of the most popular OSS relational databases, PostgreSQL, and the options you have for this database in the Microsoft Azure cloud. It’s worth noting these products are large with many detailed aspects, so consider this article a cursory, high-level overview of each offering.

Among the 200+ fully features services that Amazon Web Services (AWS) offers, Elastic Compute Cloud (EC2) is the most popular. In the recent eG Innovations and DevOps Institute survey of 900+ IT professionals, cloud instances were the most commonly used cloud service, with 63% usage among respondents.

This is the second tutorial in a two-part series. You can also learn how to automate AWS Lambda function deployments to AWS CDK.