Operations | Monitoring | ITSM | DevOps | Cloud

I’d like to take a moment to point out some of my favorite things that have come across my Twitter timeline in the last week, if you’d like to see more follow Stackery on twitter!

We’ve been busy over the last week rolling out new product features that make the cloud feel and perform as if it was right there in the building with you - specifically geographic storage and edge caching.

The race is on to turn data into useful information. Company executives across a wide range of departments are increasingly tasked with modernization and digital transformation initiatives. But what is digital transformation in IT? IT pros are racing to keep up with rapid industry changes and must consider efforts such as digitizing assets, restructuring department goals to focus on providing a seamless customer experience, or shifting from on-premises to public cloud.

Join me on my Azure Monitor journey as I learn all there is to know about the platform. Check out my intro note here for a brief series overview and a bit about me (tl;dr former SCOM admin, avid tech blogger, SquaredUp tech evangelist). We’ll start with the basics and dive deeper as we go along. Buckle up, your journey to becoming an Azure Monitor superhero starts here!

Amazon ELB (Elastic Load Balancing) allows you to make your applications highly available by using health checks and intelligently distributing traffic across a number of instances. It distributes incoming application traffic across multiple targets, such as Amazon EC2 instances, containers, IP addresses, and Lambda functions. You might have heard the terms, CLB, ALB, and NLB. All of them are types of load balancers under the ELB umbrella.

“Today, maintaining a high performance and continuous availability of cloud production environments are some of the most significant pain points for technology organizations. Production availability is commonly measured and managed by evaluating some of the following dimension: Does the product or service work fast enough? Does its performance meet the expected metrics? Is it able to deliver the optimal customer experience?

You know what they say: successful deploys are all alike; every unsuccessful deploy is unsuccessful in its own way (ok, no one actually says that, except engineers who have read way too much Russian literature, ahem).

AWS Lambda is a compute service that enables you to build serverless applications without the need to provision or maintain infrastructure resources (e.g., server capacity, network, security patches). AWS Lambda is event driven, meaning it triggers in response to events from other services, such as API calls from Amazon API Gateway or changes to a DynamoDB table.

In Part 1 of this series, we discussed AWS Lambda functions and some key metrics for monitoring them. In this post, we’ll look at using Amazon’s native tooling to query those metrics. We’ll also show you how to collect logs and traces that provide further visibility into your Lambda functions. Amazon provides built-in monitoring functionality through CloudWatch and X-Ray.