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In part one I described the AWS EBS snapshot mechanism. In this part I will drill deeper on how to calculate the EBS snapshot cost. I  will show how to be able to do a rough estimation or even to perform an accurate cost analysis using monitoring tools.

Rough estimation

In order to estimate how large your EBS snapshots will be, you need to know how much your volumes are changing. One way would be to guesstimate,we can use a simple thumb rule that is often used in- backup planning: A typical data volume of a production server changes about 3% a day. Let’s try and calculate the cost. Assuming a 1TB EBS volume, that is 70% full at first. We take snapshots and keep them for 30 days. So, the first full will be taking 700GB (70% of 1TB). For the incremental snapshots we can multiply 30 (days) by 30GB (3% of 1TB) and we reach 900GB. Add them together and we reach about 1.6TB of total snapshot storage. AWS compresses the snapshots when they are stored in S3.

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AWS status checks help the user to identify problems that would stop the instance from running an application. The AWS EC2 status check allows the user to monitor the status of system reachability and instance status. The EBS volumes are used for persistent data storage. It is always recommended to store the data to the EBS volume rather than having a transient storage for the persistent storage option. In the rarest of cases, there could be a probability that something could happen to the EBS volume, which could create inconsistency in the volume data. The AWS EBS volume status check helps to detect the impaired volumes. The impaired volume may not be available immediately.

The present guide demonstrates how to check the status of the EBS volume and enable auto enabled IO.

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What does a cloud computing expert need to know? Let’s dig into deploying applications in the cloud, and day to day operations skills. There’s a lot of material here. I recommend picking a few questions out of the bunch and focusing on those questions, rather than trying to cover all of them.

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Pacemaker is an open source, high availability resource manager suitable for both small and large clusters. It supports many deployment scenarios and can dramatically reduce hardware costs by allowing several active/passive clusters to be combined to share a common backup node. It monitors the system for hardware and software failures, using advanced algorithms to automatically recover applications in the event of a failure.

In this article, Yossi Nachum of Emind Systems gives a step-by-step guide to installing Pacemaker in Amazon AMI.

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Considering the current high demand of infrastructure, Amazon Web Services (AWS) upgrade the infrastructure and corresponding EC2 services regularly on a continual basis, with many patches and upgrades being applied to instances transparently. Some updates require a short instance reboot in order to apply the above mentioned updates. AWS EC2 has a functionality called monitor events, which provides visibility into the timing of the planned reboots. With the help of the above mentioned functionality, the user can use the scheduled events to manage reboots on their own before the scheduled update window.

The present guide demonstrates how to view the scheduled event. You can take actions, such as stop / reboot the instance against a planned action. You can also refer the maintenance guide.

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An AWS spot instance helps to reduce the running cost of the EC2 instance.  The user bids for a spot instance request specifying the maximum price that the user is willing to pay per hour per instance. Once the spot instance request is fulfilled, the instance will continue to run until it is manually terminated or the spot price increases above the maximum bid price. The user is not charged as per the max price; instead the user will be charged at the current spot price in that availability zone. To know the charges for spot instances, Amazon EC2 provides access to a data feed, which details the user’s spot instance usage and pricing every hour.

The present guide demonstrates how to subscribe or delete the spot instances price data feed.

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A spot instance helps to reduce the cost of the instance.  To use spot instances, the user bids for a spot instance request specifying the maximum price that the user is willing to pay per hour per instance. If the maximum price of the bid is greater than the current spot price, the user’s request is fulfilled and the user’s instances run until terminated or the spot price increases above the maximum bid price. When the spot instance request is canceled, the spot instances that were launched previously through the canceled request do not automatically get terminated. The only time that the spot instance service terminates a running instance is when the spot price exceeds the max bid price. Note that though spot instances can use Amazon EBS-backed AMIs, the user cannot stop and start spot instances launched from an AMI with an Amazon EBS root device.

The present guide demonstrates how to view running spot instances and cancel the request.

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Leaving an instance running when it isn’t needed isn’t especially cost effective. But is there a better solution when you need to run short jobs on a recurring schedule? A cloud scheduler allows you “talk” to your cloud and pre-define when instances will start-up and be shut down, from development through to production. Essentially, it enables you to pay only for the time you need.

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Puppet is IT automation software that helps systems administrators to provision, configure, and manage their infrastructure.  According to their website, sys admins can use Puppet to easily automate repetitive tasks, quickly deploy critical applications, and proactively manage change, scaling from 10s of servers to 1000s, on-premise or in the cloud.

Following is a step-by-step guide explaining how to install a Puppet Server with the Puppet Dashboard, compliments of Emind Systems.

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A  few days ago, @IAmOnDemand (a.k.a. “Newvem Community Editor”) sent me a short email including this Quora question. This caught my attention, and led me to place a huge background thread (I call it “unconscious thinking”) about it. Two days later, I got a reasonable answer, leading to this article.

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