When Squadcast was founded back in 2018, we had a concise yet clear goal—we wanted to make it as easy as possible for companies to manage their IT incident and reliability needs. In the spirit of continuing that mission, today I’m excited to announce our $6M fundraise led by DNX Ventures and backed by Wipro Ventures, Nexus Ventures, and Chiratae Ventures. We’re also pleased to announce the addition of DNX and Q Motiwala to our Board of Directors.

Together with the release of Spot by NetApp’s Elastigroup support for multiple metrics, we are pleased to share that Elastigroup now also support step scaling, a new functionality that allows Elastigroup customers to configure multiple actions under a single, simple scaling policy. In Elastigroup, each simple scaling policy contains two parts. The first is the AWS metric, which is the metric the data is collected from.

Scalability is one of the main reasons why cloud computing has become so popular. Cloud customers can rapidly react to changes in market needs and demands by automatically launching or terminating resources. This way only the exact number of resources required to serve all incoming requests are running (and being paid for) at any given moment.

Amazon Elastic File System (EFS) provides shared, persistent, and elastic storage in the AWS cloud. Like Amazon S3, EFS is a highly available managed service that scales with your storage needs, and it also enables you to mount a file system to an EC2 instance, similar to Amazon Elastic Block Store (EBS).

In Part 1 of this series, we looked at EFS metrics from several different categories—storage, latency, I/O, throughput, and client connections. In this post, we’ll show you how you can collect those metrics—as well as EFS logs—using built-in and external tools.

In Part 1 of this series, we looked at the key EFS metrics you should monitor, and in Part 2 we showed you how you can use tools from AWS and Linux to collect and alert on EFS metrics and logs. Monitoring EFS in isolation, however, can lead to visibility gaps as you try to understand the full context of your application’s health and performance.

Spot by NetApp serves hundreds of customers across industries, with different systems, environments, processes and tools. With this in mind, Spot aims to develop our products with flexibility so that whatever the use case, companies can get the full benefits of the cloud. Spot easily plugs into many tools that DevOps teams are already using, from CI/CD to infrastructure as code, including Terraform.

Spot Ocean offers best-in-class container-driven autoscaling that continuously monitors your environment, reacting to and remedying any infrastructure gap between the desired and actual running containers. The way this typically plays out is that when there are more containers than underlying cloud infrastructure, Ocean immediately starts provisioning additional nodes to the cluster so the container’s infrastructure requirements will be satisfied.

A look at outages and disruptions to the IT systems that power the Olympics, from 1996 to today.

As the adoption to cloud expand, subscribing and provisioning resources increases day by day. Enterprises have multiple strategies to implement their cloud deployments: single cloud, private cloud, multi-cloud, or hybrid cloud. There is a need to analyse and assess on regular basis to keep a watch on the usage to ensure expenditure on the cloud resources are efficient and there is no wastage. There are various possibilities but will need some level of technical competence and regular maintenance.