AWS EC2 Archives - Botmetric

Not Only EC2, 6 More AWS Services That Can be Reserved

Posted on August 5, 2017 by Rajeev Kumar

Cloud Cost Management through Reserved Instance option

AWS, the pioneer of Cloud Platforms, has created three different pricing models which can suit an organization based on the life cycle stage they are in regard to Cloud usage. The first and most well-known model is the on-demand model under which resources are priced based on actual usage like hourly compute or storage, I/O capacity consumption etc. This pricing model is best suited when a company is not exactly sure of its usage pattern and is getting started on the Cloud Platform. Once the company is accustomed to the Cloud Platform and its benefits, it can upgrade to the next model -“Reserved instance”, to get 30-50% price reduction by committing the resource consumption for a one or three years’ time. The third model, “Spot Instances” is for buying resources to use only in periodic surges in resource demand.

While Reserved Instance Model for AWS EC2 is quite well known, AWS also provides the same pricing model for many other services as well. Let us look in-depth into 6 More AWS Services which can be consumed under Reserved Instance price model.

AWS RDS

After Computing Power, the most used resource is database. Databases are a very significant portion of an enterprise’s resource capacity and as it is often run 24/7. Hence adopting the Reserved Instance pricing model for RDS is a worthwhile investment. Amazon RDS Reserved Instances give you the option to reserve a DB instance for one or three year term and in turn receive a significant discount compared to the On-Demand Instance pricing for the DB instance.

It is important to note that RDS will be charged for every hour during the entire reservation term one selects, regardless of whether the database instance is running or not. There are two different factors that have to be considered while planning out Reserved Instances for RDS.

Commitment Term: AWS provides two types of commitment terms durations.

1-year term which is useful for production databases with predictable workloads

3-year term which is useful for stable production databases for long running applications

Payment Options: Once the commitment term is decided, there are 3 payment options to choose from, based on the percentage of upfront payment one is willing to pay.

No Upfront: In this model, no upfront payment is required at purchase. The discount is however lower when compared to other payment options. This is not applicable if the commitment term is 3 years.

Partial Upfront: In this model, a portion of the cost is paid upfront and the remaining hours in the term are billed at the established discounted hourly rate. This model strikes a right balance between upfront and hourly.

Full Upfront: In this model, the cost of the entire term is paid to get the best effective hourly price

AWS DynamoDB

Amazon DynamoDB is a fully managed NoSQL database service that provides fast and predictable performance with seamless scalability. When using DynamoDB, the pricing is a flat, hourly rate service based on how much capacity is provisioned. Like other services, DynamoDB Reserved Capacity also offers significant savings over the on-demand price of DynamoDB if the capacity is paid for in advance. One has to choose to commit a capacity model comprising of a fixed amount of Write Capacity and Read Capacity units. However, the cost is incurred even if the resource is not utilized.

Amazon CloudFront

Amazon CloudFront is the content delivery web service that helps businesses to distribute content to end users with low latency and high data transfer speeds. AWS CloudFront Reserved Capacity gives you the option to commit to a minimum monthly usage level for a year or longer to receive a significant discount. AWS CloudFront Reserved Capacity pricing metric is based on volume of data transfer. The pricing begins at a minimum of 10 TB of data transfer per month from a single region. If the users commit to higher volume usage, they are eligible for receiving additional discounts.

AWS ElastiCache

ElastiCache helps developers to set up, manage, and scale a distributed in-memory cache environment in the cloud. Developers can choose their cache engine to be either Memcached or Redis protocol-compliant. The key benefit of using AWS ElastiCache is that provides a high-performance, scalable and cost-effective caching solution, without the usual complexity of managing a distributed cache environment manually.

The reserved instance price model is almost same as that of AWS DynamoDB where Reserved nodes are charged an upfront fee that depends upon the node type and the reservation term years. In addition to the upfront charge there is an hourly usage charge

Elastic MapReduce

Amazon Elastic MapReduce is BigData Platform as a Service for large volume data analysis. AWS Elastic MapReduce is based on Apache Hadoop which distributes work across different virtual servers which are in clusters in AWS Cloud.

The Unique Reserved Instance Pricing Policy of AWS Elastic MapReduce are as follows:

An On-Demand Instance should be specified in the cluster configuration that matches the Reserved Instance specification. The cluster should be launched within the same Availability Zone of the instance reservation

Amazon RedShift

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. Amazon Redshift On-Demand pricing has no upfront costs and has an on-demand pricing scheme where users pay an hourly rate based on the type and number of nodes in the cluster. Users can save up to 75% over On-Demand rates by committing to a Reserved Instance for a fixed term ranging from 1 year to 3 years.

Your Cloud Strategy is optimal only when Reserved Instances are leveraged well and wherever applicable. Botmetric can help you manage your Cloud from Cloud Perspective through proactive advices based on Best Practices. Take a Complete demo of Botmetric to benefit from its capabilities.

Demystifying Your Monthly AWS Cloud Usage Costs

Posted on June 22, 2017 by Rajeev Kumar

Over the last few years, AWS has seen some absolutely great adoption across industries. This is definitely not surprising given how well it works. One important aspect of using AWS for your business is to figure out the billing process so that you can estimate the amount that you’ll need to spend on it. Understanding how the AWS billing process works is important in order to optimise costs. The great thing about AWS is that its allows you to pay only for the services that you use. At the same time, you have flexibility and agility to scale up and scale down your computing infrastructure based on your business needs.

Besides, AWS also offer several innovative services at a fraction of what similar on-premises solutions would cost. Amazon RDS for Aurora and Amazon Redshift are great examples of solutions that can help you run enterprise-grade solutions at one tenth of the cost of comparable on-premises solutions.

Most IT managers need to walk the delicate tight rope, balancing both performance and cost. Therefore, a thorough understanding of how AWS costing works can be extremely valuable.

Features of AWS Cost Structure

AWS’ pricing philosophy has remained unchanged despite the deluge of new products that they’ve launched over the years. Basically, you’re billed at the end of every month, and you pay for what you use. Also, there is no are no long-term contracts etc. required. That , which means you can start or stop using a product at any time. The pricing for each service is listed clearly on the AWS Pricing page.

Immense flexibility: Since each service is priced individually, users can choose only the services only the services they need for their businesses and pay only for those.

Optimum Infrastructure: There are no minimum commitments or long-term contracts. This means that businesses have the liberty to choose only get the required services just-in-time. that they need, at the time they need it. You don’t have to pay Not only do you not pay upfront for excess capacity, neither there is penalty for underestimating your needs. Your money is not locked in because you pay a low a lesser variable cost rather than an incurring an upfront capital expense. You pay for compute resources on an hourly basis, counting from the time you launch a resource until the time you terminate it. On the other hand, for data storage and transfer, the cost is determined a on gigabyte used. Similarly, AWS charges underlying infrastructure and services based on the actual consumption.

Volume Advantage: Because pricing is tiered for storage and data transfer, users can accrue the benefit of lower prices per gigabyte as usage grows. The bigger you grow, the more you save. For compute too, you get volume discounts of up to 10% when you reserve greater volumes.

Reserve Option: AWS lets users pay less than ‘on-demand’ prices by investing in reserved capacity to get a significantly discounted hourly rate. In fact, users can save up to 60% as compared to equivalent On-Demand capacity.

AWS grows, you win: As AWS grows, it gains from economies of scale based by on reducing its data center hardware costs, improving operational efficiencies, lowering power consumption, and overall cost of doing business. And these get passed on to the users!

Complimentary offerings: AWS has some amazing services that it offers at no extra cost. Amazon Virtual Private Cloud (Amazon VPC), AWS Elastic Beanstalk, AWS CloudFormation, AWS Identity and Access Management (IAM) and Auto Scaling are some great examples.

AWS Pricing Fundamentals

When it comes to AWS pricing, you essentially pay for three things: compute, storage, and data transfer out; although this may differ slightly depending on the AWS product that you are using, these have the highest impact on your AWS cost.

One interesting characteristic fact is that while AWS charges for data transfer out, inbound data transfer or for data transfer between other Amazon Web Services within the same region is not charged. The outbound data transfer is aggregated across Amazon EC2, Amazon S3, Amazon RDS, Amazon SimpleDB, Amazon SQS, Amazon SNS, and Amazon VPC and then charged at the outbound data transfer rate. It is important to note that this charge appears as AWS Data Transfer Out on the monthly statement. When it comes to Inbound Data Transfer, there is no charge for inbound data transfer across all Amazon Web Services in all regions.

Price Estimation for various AWS services

Amazon Elastic Compute Cloud (Amazon EC2) While Amazon EC2 is obviously great because it provides complete controls of your the entire computing resources. because An added advantage is that AWS charges only for the capacity that you actually use. There are several factors that you need to consider when it comes to estimating the cost of using Amazon EC2. These include clock hours of Server Time; Machine Configuration (Instance pricing varies with the AWS region, OS, number of cores, and memory); Machine Purchase Type; Number of Instances etc. The number of hours the Elastic Load Balancer runs and the amount of data it processes contribute to the monthly cost. Factors such as auto scaling, IP Addresses, Operating Systems and Software Packages also play a role in influencing cost.

The most important component of this is usually the Elastic Cloud Compute (EC2), which contributes to 70 to 75% of the AWS bill for an average AWS user. Because it is used in conjunction with other AWS services, it may appear in the AWS bill in the form of several line items, making it challenging to figure out what exactly is driving usage and costs. Analysing this usage and breaking it up by various dimensions like resource, instance type, services and accounts can help in optimizinge AWS costs. The “EC2 Cost Analysis” available in the ‘All-New’ Botmetric platform as part of it’s ‘Cost Management and Governance’ can help in achievinge this.

Amazon Simple Storage Service (Amazon S3): The great thing about Amazon S3 is that it provides a simple web services’ interface that can be used to store and retrieve any amount of data, at any time, from anywhere on the web. Some of the factors that need to be considered while estimating this project are storage class, number and size of objects stored, number and type of requests and the amount of data transferred out of the Amazon S3 region.

Amazon Elastic Block Store (Amazon EBS): It has three volume types: General Purpose (SSD), Provisioned IOPS (SSD), and Magnetic. Each of these varies in terms of performance characteristics and cost, allowing you to choose the right storage performance and price for the needs of your applications. The factors that matter are volume (amount you provision in GB per month); Input Output Operations per Second (IOPS); whether you have opted for Snapshot backup and the amount of data transferred out of your application.

Amazon Relational Database Service (Amazon RDS): Amazon RDS provides cost-efficient and resizable capacity while managing time-consuming database administration tasks that, you can estimate the cost of Amazon RDS, based on factors including Clock Hours of Server Time; Database Characteristics (database engine, size, and memory class); Database Purchase Type; Number of Database Instances; Provisioned Storage; Additional Storage; number of input and output requests to the database; Deployment Type (number of Availability Zones) and Data Transfer.

Amazon CloudFront: The cost can be estimated by considering factors such as Traffic Distribution, the number and type of requests (HTTP or HTTPS) made and the geographic region in which the requests are made, and finally, the amount of data transferred out of the user’s Amazon CloudFront edge locations.

Being proactive about AWS Cost Management

Some of the most attractive characteristics of AWS are Agility, Flexibility and the Pay-on-Demand features. But to get the most out of your AWS investment, proactive Cost Management is a must. As with most things, maintaining the balance between performance and cost is of utmost importance. Cost/spend tracking and optimization are the most important considerations to actively manage cost. Some of the ways to go about cost management are:

To monitor reports & alerts around set-up, spend, usage, billing etc.
Identify idle resources
Use AWS Trusted Advisor to run multiple configuration checks and recommend savings
Use Amazon Cloudwatch to provides resource utilization information
Match resources and workloads by choosing the right instance types that meet your basic requirements

Additionally, using a cost-management tool can help in several ways. It can help in detecting unused and underused resources that ; helps you in prioritizinge. With some tools such as the Botmetric Intelligent Cloud Platform for AWS Cost Management, you don’t need to stop at just detecting; but you can actually remove unused resources without even going to AWS console. You can not only save cost by automating start/stop of your instances, but you can also drill down on cost to a granular level.

One way to optimize your costs for Amazon EC2 is by purchasing EC2 Reserved Instances or Spot Instances. While on-demand instances work great if you need to run your Amazon EC2 Instances for a couple of hours a day or a few days a week; Reserved Instances work much better when you need to run your Amazon EC2 Instances more often than that. Reserved Instances enable you to reserve capacity and receive a discount on your instance usage. Reliable Reserved Instances provide a capacity reservation so that you can confidently launch instances you have reserved when you need them.

Conclusion

To sum up, the number and types of services offered by AWS may have increased dramatically over the last few years, but the philosophy on pricing has not changed. This means that you still pay as you go, pay for what you use, pay less as you use more, and pay even less when you reserve capacity.

Having said, projecting costing for specific use cases can sometimes get pretty challenging because it typically involves the use of multiple features across multiple AWS products. In turn, this means that there are more factors and purchase options to consider, which means that there is greater complexity. For such instances, it may make sense to examine the fundamental characteristics for each AWS product, and estimate your usage for each of those characteristics. Once you have a better sense of how much each features or characteristic is likely to be used, figuring out the cost is just a matter of looking up prices posted on the AWS website. Additionally, there are tools such as the AWS Simple Monthly Calculator that you can use to estimate your monthly bill. It works well because it allows you to breakdown the cost per service and also get an aggregate monthly estimate.

AWS EC2 Pricing and Best Practices: The Complete Factsheet on Price Reduction and Cost Optimization

Posted on June 15, 2017 by Rajeev Kumar

For the uninitiated, AWS recently announced a price reduction on its compute instances. The most significant part of the announcement is the new three-year no-upfront Standard RI. As an AWS user, you must understand the price reduction completely and learn how to make better use of reduction in AWS EC2 pricing and reap the most of it.

However, before we directly get the price reduction, let’s start with the AWS EC2 pricing with the real fact sheets.

AWS EC2: Four-way Pay and Usage

“Pay-as-you-go” is the fundamental of AWS pricing and this applies very well to the AWS EC2 pricing. You use the computing resources as you want, and pay only for what you use. This unique proposition has been the win-win for both the customer and AWS making it the market leader in cloud computing infrastructure.

There are four ways to pay for AWS EC2 instances: On-Demand, Reserved Instances, Spot Instances, and Dedicated Hosts.

Let’s analyze these offerings in detail before we start price reduction and optimal usage of the various AWS EC2 products.

On-Demand instances

AWS EC2 On-Demand instances enable you to pay for computing capacity by the hour. There are no long-term commitments or upfront payments. You pay only for the specified hourly usage of the instances you have opted for, and can increase or decrease your computing capacity depending on the demands of your applications.

On-Demand instances are highly recommended if:

You prefer the low cost and flexibility of AWS EC2 without any upfront payment or long-term commitment.
You have applications with short-term, spiky, or unpredictable workloads that cannot be interrupted.
Your applications being developed or tested on AWS EC2 for the first time.

On-Demand Pricing

On-Demand instances let you pay for compute capacity by the hour with no long-term commitments.

If you really want to free yourself from the costs and complexities of planning, purchasing, and maintaining hardware, you must go for AWS EC2 On-Demand instances. This offering transforms large fixed costs into much smaller variable costs.

For complete AWS EC2 On-Demand instances pricing, visit the AWS EC2 On-Demand Pricing page.

Spot Instances

AWS EC2 Spot instances allow you to bid on spare AWS EC2 computing capacity for up to 90% of the On-Demand price. You get access to unused AWS EC2 instance capacity at discounts relative to On-Demand instance prices. It’s like a bid where, the Spot instance price fluctuates based on the supply and demand of available unused AWS EC2 capacity.

Spot instances are recommended if:

You have applications that have flexible start and end times.
You have applications that are only feasible at very low compute prices.
You need compute capacity urgently for large amounts of additional capacity.

Spot Pricing

In a Spot instance bid, you specify the maximum Spot price you are willing to pay. Your Spot instance is launched when the Spot price is lower than the price you specified, and will continue to run until you choose to terminate it or the Spot price exceeds the maximum price you specified.

You will never be charged more than the maximum price you specified and while your instance runs, you are charged the Spot price that is in effect for that period. If the Spot price exceeds your specified price, your instance will receive a two-minute notification before it is terminated, and you will not be charged for the partial hour that your instance has run.

For complete AWS EC2 Spot Instance pricing, visit the AWS EC2 Spot Instances Pricing page.

Reserved Instances

AWS EC2 Reserved instances provide you with a significant discount (up to 75%) compared to On-Demand instance pricing. Reserved instances also provide a capacity reservation, if assigned to a specific Availability Zone, thereby ensuring your ability to launch instances when you need them.

AWS EC2 Reserved instances come handier when you have applications that have steady state or predictable usage, and provide significant savings compared to using On-Demand instances.

Reserved Instances are recommended if:

You have applications with steady state usage.
You have applications that may require reserve capacity.
You are a committed customer for a one year or three year term.

Reserved Pricing

There are two types pricing models for AWS EC2 Reserved Instances: Standard Pricing and Convertible Pricing.

The Standard pricing model enables you to purchase reserved instances for a one-year or three-year term and offers significant discounts (up to 75%) compared to On-Demand instances. You have the flexibility to change the Availability Zone, the instance size, and networking type of your Standard Reserved Instances.

The Convertible pricing model suits best if you need additional flexibility, such as the ability to use different instance families, operating systems, or tenancies over the Reserved Instance term. Convertible Reserved Instances provide you with a significant discount (up to 45%) compared to On-Demand and can be purchased for a 3-year term.

Reserved Instance Payment Options

There are three payment options for you to choose when you purchase Standard or Convertible Reserved Instance:

No Upfront—discounted hourly rate for every hour within the term, regardless of usage. No upfront payment is required. For Standard Reserved Instances, this option is only available as a 1-year reservation. For Convertible Reserved Instances, the option is available as a 3-year reservation.
Partial Upfront—pay a portion of the cost upfront and the remaining hours in the term are billed at a discounted hourly rate, regardless of usage.
All Upfront—Full payment is made at the start of the term, with no other costs incurred for the remainder of the term regardless of the number of hours used. This option provides you with the largest discount compared to On-Demand instance pricing.

For complete AWS EC2 Reserved Instance pricing, visit the AWS EC2 Reserved Instances Pricing page.

Dedicated Hosts

A Dedicated Host is a physical AWS EC2 server dedicated for your use. Dedicated Hosts address your compliance requirements and reduce costs by allowing you to use your existing server-bound software licenses.

You can purchase Dedicated Hosts on hourly on-demand basis and as a reservation for up to 70% off the On-Demand price.

Dedicated Hosts are recommended if:

You have to launch AWS EC2 instances on physical servers that are dedicated for your use.
You require additional visibility and control over how instances are placed on a physical server.
You have to consistently deploy your instances to the same physical server over time.
You have existing server-bound software licenses that need to be deployed on physical server and you have to address corporate compliance and regulatory requirements.

Dedicated Hosts Pricing

The price for Dedicated Hosts vary based on the instance family, region, and payment option that you choose. However, you pay only hourly for each active Dedicated Host, regardless of the quantity or the size of instances that you choose to launch on a particular Dedicated Host. You are not billed for the usage of your instances!

You must choose and instance type configuration for the host, when you allocate a Dedicated Host. This selection defines the number of sockets and physical cores per host, the type of instance and the number of instances you can run on each host. A Dedicated Host can support only one instance type at a time.

There are two pricing models for Dedicated Hosts: On-Demand Pricing and Reservation Pricing.

On-Demand Dedicated Hosts Pricing

In the on-demand pricing model for Dedicated Hosts, you pay for each hour that the Dedicated Host is active or allocated in your account. When you release the on-demand Dedicated Host, you also terminate the billing.

On-Demand gives you the flexibility to scale up or down without long-term commitments.

Reservation Dedicated Hosts Pricing

Just like the AWS EC2 Reserved Instances, the AWS EC2 Dedicated Hosts reservations also provide up to a 70% discount compared to the on-demand price.

There are three payment options for you to choose when you purchase Reserved Dedicated Hosts.

All Upfront —you pay for the entire Dedicated Host Reservation with one upfront payment. This option provides you with the largest discount compared to On-Demand pricing.
Partial Upfront —you make a low upfront payment and are then charged a discounted hourly rate for the Dedicated Host for the duration of the reservation.
No Upfront —you do not need to make an upfront payment and you get a discounted hourly rate for the duration of the term.

For complete AWS EC2 Dedicated Hosts pricing, visit the AWS EC2 Dedicated Hosts Pricing page.

Cost Estimation with AWS EC2 Instances

So, you have got an idea of the various AWS EC2 instances and their pricing. What next? How would you estimate the costs for the desired instance type?

As an AWS EC2 user or one who is going to use AWS EC2, you are well aware the fact that AWS EC2 facilitates complete control of your computing resources. “AWS EC2 changes the economics of computing by charging you only for capacity that you actually use” as stated in an Amazon Web Services pricing guide.

According to the latest AWS pricing guide, consider the following points when you estimate the cost of your AWS EC2 requirements:

Clock Hours of Server Time – Resource charges are applied when they are running. For example, from the time AWS EC2 instances are launched until they are terminated.
Machine Configuration – The physical capacity of the Amazon EC2 instance you choose along with the AWS region, OS, number of cores, and memory.
Machine Purchase Type –On-Demand instances, Reserved Instances, Spot Instances, or Dedicated Hosts.
Number of Instances – Based on the number of instances that you want to provision to handle peak loads. You can have multiple instances of your AWS EC2 and Amazon EBS resources.
Load Balancing –Use an Elastic Load Balancer to distribute traffic among AWS EC2 instances. Calculate the number of hours the Elastic Load Balancer runs and the amount of data it processes to the cost.
Detailed Monitoring –Use Amazon CloudWatch to monitor your AWS EC2 instances. The default basic monitoring is enabled and available at no additional cost. You can opt for detailed monitoring for a fixed monthly rate. Partial months are charged on an hourly pro rata basis, at a per instance-hour rate.
Auto Scaling – Use Auto Scaling to automatically adjust the number of AWS EC2 instances in your deployment according to conditions you define. This service is available at no additional charge beyond Amazon CloudWatch fees.
Elastic IP Addresses – You can have one Elastic IP (EIP) address associated with a running instance at no charge.
Operating Systems and Software Packages – Operating System prices are included in the instance prices. These commercial operating systems require are no additional licensing costs:
- Red Hat Enterprise Linux
- SUSE Enterprise Linux
- Windows Server
- Oracle Enterprise Linux

AWS has partnered with Microsoft, IBM, and several other vendors so you can run commercial software packages on your AWS EC2 instances (for example, Microsoft SQL Server on Windows, IBM Software). These costs need to be estimated. Also, for commercial software packages that AWS does not provide, such as nonstandard operating systems, Oracle Applications, Windows Server applications such as Microsoft SharePoint and Microsoft Exchange, you need to obtain a license from the vendors. You can also bring your existing license to the cloud through specific vendor programs such as Microsoft License Mobility through Software Assurance Program.

Make Hay While AWS Drops Prices!

In May 2017, AWS announced significant price reductions on their EC2 instances. “As AWS grows, we continue to find ways to make it an even better value. We work with our suppliers to drive down costs while also finding ways to build hardware and software that is increasingly more efficient and cost-effective”, declares AWS’s chief evangelist in a blog post that announced the 61st price reduction.

AWS reiterates the fact that in addition to reducing the prices, they also give customers options that help them to optimize their use of AWS.

Let’s take a closer look at the May 2017 AWS EC2 price reductions:

New No Upfront Payment Option for 3 Year Standard RIs –No Upfront payment option with a 3 year term for C4, M4, R4, I3, P2, X1, and T2 Standard Reserved Instances.
Lower Prices for No Upfront Reserved Instances – lower by up to 17% prices for No Upfront 1 Year Standard and 3 Year Convertible Reserved Instances for the C4, M4, R4, I3, P2, X1, and T2 instance types, depending on instance type, operating system, and region.

An indicative chart for the estimated average reductions for No Upfront Reserved Instances for Linux in representative regions:

*	US East (Northern Virginia)	US West (Oregon)	EU (Ireland)	Asia Pacific (Tokyo)	Asia Pacific (Singapore)
C4	-11%	-11%	-10%	-10%	-9%
M4	-16%	-16%	-16%	-16%	-17%
R4	-10%	-10%	-10%	-10%	-10%

*Source: EC2 Price Reductions – Reserved Instances & M4 Instances AWS Blog

Lower Prices for Convertible Reserved Instances –lower by up to 21% prices for 3 Year Convertible Reserved Instances for the C4, M4, R4, I3, P2, X1, and T2 instances.

Convertible Reserved Instances allow you to change the instance family and other parameters associated with the RI at any time; this allows you to adjust your RI inventory as your application evolves and your needs change.

An indicative chart for the estimated average reductions for Convertible Reserved Instances for Linux in representative regions:

*	US East (Northern Virginia)	US West (Oregon)	EU (Ireland)	Asia Pacific (Tokyo)	Asia Pacific (Singapore)
C4	-13%	-13%	-5%	-5%	-11%
M4	-19%	-19%	-17%	-15%	-21%
R4	-15%	-15%	-15%	-15%	-15%

*Source: EC2 Price Reductions – Reserved Instances & M4 Instances AWS Blog

Lower Prices for M4 Instances –lower by up to 7% prices for M4 Linux instances.

As an AWS customer, you can use multiple strategies to purchase and manage your Reserved Instances. You may prefer to make an upfront payment and earn a bigger discount; or prefer to pay nothing upfront and get a smaller, but still substantial, discount. Else, make a partial upfront payment and a discount that falls in between the two other options.

All changes in prices and the reductions are already effective. So, why wait? Make the most of it…Now!

How to Further Save Costs?

Coming back to the actual business, the major driving factors of the cost of your AWS EC2 compute infrastructure should be the needs of your applications and how you intend to use the resources for optimal results. You no longer need to but the cutting edge physical hardware to provide computing. Instead, you are now using the flexible of benefit of cloud computing by spinning AWS EC2 instances whenever you need those. Your computing infrastructure sizes to be a physical datacenter!

However, even on the cloud, without proper cost analysis, cost implementation, usage management, and resource optimization, you are running the risk of bottlenecking performance of your infrastructure both in terms of technical oversights and financial mismanagement. All that can happen due to mismatches in technical requirements and AWS EC2 resourcing.

To avoid all possible bottlenecks and to engage your resources properly, you need to understand the following key parameters:

How AWS users use and pay for EC2 instances
The different families and sizes of EC2 instances
How to identify opportunities to optimize EC2 instances

You can optimize your costs for AWS EC2 instances by purchasing EC2 Reserved Instances or Spot Instances. On-Demand instances are a good option if you run your Amazon EC2 Instances a couple of hours a day or a few days per week; however, if you plan to run your Amazon EC2 Instances more than that, Reserved Instances can save you money…etc…etc…

Sounds tough?

Botmetric Helps to Make the Right Directions

Facts are stated. Directions are set. Now, you must take right decisions on your AWS EC2 resources based on the facts, figures, and directions. Just to recap, you have a gamut of AWS EC2 instances to choose from, a set of cost reduction and optimization guidelines to conform to, and a new set of price reduction from AWS as high level guidance. And you have the Botmetric’s analytical tools and expert analysts to help you out.

Ultimate Comparison of AWS EC2 T2.Large Vs. M4.Large for Media Industry

Posted on May 30, 2017August 21, 2017 by Tarun G

AWS presents a series of large EC2 instances that can be used optimally for various computing needs. Of these, the t2.large and m4.large are two blockbuster instance types that a media company’s resource utilization decision makers must think through and compare before they make a decision. Because, if you look at the comparative matrix, both t2.large and m4.large instances look very similar. That makes it a challenge to decide the best resource, in terms of price and performance. Here’s a information break-up of AWS EC2 t2.large vs. m4.large for media companies.

The Backdrop

Typically, media sites handle large number of concurrent visitors at any given time. Visitors spend time on each page, reading, watching videos, or interacting with the content, before they go to another page or leave the site. And when you are running a campaign or a viral content, the site visits manifolds. So, your site needs heavy storage and high bandwidth. A compute instance must satisfy these requirements along with the need to run many applications in one production environment.

As a resource planner, you will tend to look at large AWS EC2 instances. And you are right in doing so. But then, which one to choose amongst the many ‘large’ instances that AWS provides? You have t2.large, m4.large, m3.large, c4.large, c3 large, etc. Which one is better for your media site that optimally provides a balance of compute, memory, and network resources and a platform to run those many applications and utilities? Plus you need to know which is the most optimized and economical instance that caters to all your compute, memory, and network resource needs?

Confused! Do not worry; we have two large instance type champions: t2.large and m4.large, which provide similar capabilities for your requirements. A right-sized and optimized cloud environment is going to give anyone the best savings. So, let’s explore some of the reasons why your engineering team would consider either EC2 instance over the other. Here’s a closer look at both the instances’ specifications:

Now let’s take a closer look at both the instances’ pricing comparison(for US East Region), which is a major differentiating factor to make a decision:

From the above compare matrix, we can see that both t2.large and m4.large instances feature dual-core vCPUs, with the t2 sporting high-frequency Intel Xeon processors with turbo modes up to 3.3GHz. The m4.large features 2.4GHz Intel Xeon Haswell CPU, which AWS markets as being “optimized for EC2.” While the t2.large features burstable compute, the m4.large has a cap of 6.5 units.

Both the instances feature the same amount of memory and both require the provisioning of AWS EBS volumes. As far as cost management goes, users should be ready to also account for the spending on EBS when using either the t2.large or the m4.large. If storage access speed is a big deal, it is very significant to note that the m4.large features EBS optimization.

The Catch

As media sites require heavy storage and high bandwidth, m4.large are a better fit. Because, m4.large has a dedicated EBS bandwidth of 450 Mbps.

In brief, m4.large instances are the latest generation of General Purpose Instances from AWS EC2. They provide a balance of compute, memory, and network resources, and it is a good choice for many applications. Like the AWS EC2 site states, the m4 family is “great for many web server applications and other general uses. Plus, it’s EBS-optimized offering comes by default, at no additional cost.

Here’re some useful scenarios of m4 instances in general and m4.large in particular:

Small and mid-size databases
Data processing tasks that require additional memory
Caching fleets
Running backend servers for SAP, Microsoft SharePoint, cluster computing, and other enterprise applications.

The Bottomline

Now that you have understanding of the capabilities of t2.large and m4.large instances and the price comparison, the next step would be to firm the decision. Botmetric can help you optimize your instance purchase and usage decisions. To know more about how m4.large is a better option for your requirements, get in touch us.

At Botmetric, we provide intelligent analysis of your requirements, suggest ways and means to optimize instances, and get you going with your instances. No more discussions and researches on which instance to choose and how to maximize the potential of your cloud infrastructure! Talk to our experts and leverage our expertise. support@botmetric.com; and very much social: Twitter, Facebook, or LinkedIn.

Cost Allocation for AWS EBS Snapshots Made Easy, Get Deeper AWS Cost Analysis

Posted on May 26, 2017August 21, 2017 by Manav Narang

All AWS EBS snapshots (which allow you to create persistent block storage volumes for your AWS EC2 instances), including the untagged/underused/unused volumes, cost money. AWS has been evolving the custom tagging support for most of the services like EC2, RDS, ELB, BeanStalk etc. And now it has introduced Cost Allocation for EBS snapshots.

This new feature allows you to use Cost Allocation Tags for your EBS snapshots so that you can assign costs to your customers, applications, teams, departments, or billing codes at the level of individual resources. With this new feature you can analyze your EBS snapshot costs as well as usage easily.

Botmetric, quickly acting on this new AWS announcement, incorporated this cost allocation and cost analysis for EBS snapshots. Of course you can use AWS’ console to activate EBS snapshot tagging and get EBS cost analysis (read this detailed post by AWS to know how). However, when you take this approach, you are required to download the cost and and usage report and analyze it using excel sheets. This get’s tedious. But with this feature now available on Botmetric, you need not juggle through complex excel sheets.

Importance of Tagging EBS Snapshots for Cost Allocation and Analysis

Tagging has been an age old practice with AWS enthusiasts. Not every AWS service permits customer-defined tags for every AWS service. Some that do can be tagged only using API command line access. Among several AWS services, EBS snapshot storage too is one of the metrics that AWS accounts are charged for. So, tagging the EBS snapshots is pivotal for proper cost allocation.

More than that, as an AWS user, you can now see exactly how much data changes have been made between each snapshot, thus giving visibility on how much you can save by copying the snapshots to Glacier instead.

This new feature of will be of greatest interest to enterprise customers seeking to track their cost associated with EBS snapshots, which generally add few thousands of dollars to their AWS bill.

Earlier, it was a huge challenge for enterprises to track snapshot cost as they could not tag EBS snapshots for cost allocation. But with the availability of this new feature from AWS complemented with Botmetric’s capability to provide cost analysis for EBS snapshots, they get to drill-drown deeper into cost allocation and get a consolidated cost analysis view too.

Even Jeff Barr recounts this fact in his blog post that this feature will be very useful for enterprises, even for AWS customers of all shapes and sizes. He also adds the fact that managed service providers, some of whom manage AWS footprints that encompass thousands of EBS volumes and many more EBS snapshots, will be able to map snapshot costs back to customer accounts and applications.

Analyzing and Generating Cost Reports of Tagged EBS Snapshots in Botmetric

Botmetric, since long, has been offering cost allocation and cost analysis feature. Right from helping customers with proper tagging policies, tagging resources that have not been properly tagged to providing them an edge to allocate costs for those items for which AWS does not allow, analyzing costs of resources for which tagging was not possible earlier, and much more.

If you have to manage your AWS cloud budget like a pro, your AWS cost allocation & chargeback must be perfect. Thanks to Botmetric Cost & Governance’s Chargeback and Analyze, many AWS customers have been able to define, control, allocate, and understand their AWS cost allocation by different cost centers in their organization, while also having an ability to generate internal chargeback invoices. Now with AWS releasing the capability to tag EBS snapshot, you will have a better visibility into your AWs spend.

Cost Allocation for EBS Snapshots in Botmetric

Using Botmetric Cost & Governance’ Chargeback, you can allocate cloud resources with IDs, including the EBS snapshots. Please refer the image below:

Cost Analysis of EBS Snapshots in Botmetric

Using Botmetric Cost & Governance’ Analyze, you can analyze the total cost incurred by the EBS snapshots for a particular day or the month using the filter ‘EC2-EBS-Snapshot.’

You can even analyze the cost for each resource for a particular time stamp, so that you can get complete visibility into your EBS snapshot.

Report Scheduling and Shareability in Botmetric

With Botmetric, you can even schedule alerts and share the cost reports with a set of recipients, so that other members too have visibility into cost allocation and cost analysis.

With Botmetric, you can even share the cost allocation and analysis reports directly with the intended recipients.

P.S: According to AWS, snapshots are created incrementally and that the first snapshot will look expensive. In regards to a particular EBS volume, deleting the snapshot with the highest cost may simply move some of the costs to a more recent snapshot. Because when you delete a snapshot that contains blocks that are being used by a later snapshot, the space referenced by the blocks will be attributed to the later snapshot.

To Conclude

Since long, Botmetric has the feature to automate taking EBS snapshots based on instance tags, and volume tags, at regular intervals and at any time of day/week/month. With this feature, you can easily perform AWS EC2-EBS cost allocation and analysis.

And to bring cloud cost accounting under control, you need to build a cost reporting strategy for your cloud deployments. Having said that, this can be a daunting task. If you are looking for an easier way to track your cloud spend, the best way forward is to plug-in your AWS to Botmetric Cost & Governance cloud cost management console. Read this post if you want to know how to schedule interval job to capture EBS snapshots based on Instance tags. Until our next blog, stay tuned with us.

5 AWS Tips and Tricks to Solidify your EC2 and RDS RI Planning in 2017

Posted on January 23, 2017August 21, 2017 by Editor

Almost 92% of AWS users fail to manage EC2 and RDS Reserved Instances (RIs) properly, thus failing to optimize their AWS spend. An effective AWS cost optimization excise starts with an integrated RI strategy that combines a well thought out AWS EC2 and RDS planning. To this end, we have collated top 5 tips and tricks to solidify your EC2 and RDS RI planning.

Continuously Manage and Govern Both EC2 and RDS RIs Effectively. Don’t Stop at Reservation

RIs, irrespective of EC2 or RDS, can offer optimal savings only when they are modified, tuned, managed, and governed continuously according to your changing infrastructure environment in AWS cloud. For instance, if you have bought the recent Convertible RIs, then modifying them for the desired class. And, if you have older RIs, then get them to work for you either by breaking them into smaller instances or by combining them for a larger instance as per the requirement.

Take Caution While Exchanging Standard RIs for Convertible RIs

Standard RIs work like a charm, in regards to cost saving and offering plasticity, only when you have a good understanding of your long-term requirements. And if you have no idea of your long-term demand, then Convertible RIs are perfect, because you can have a new instance type, operating system, or tenancy at your disposal in minutes without resetting the term.

However, there is a catch here: AWS claims there’s no fee for making an exchange to Convertible RI. True that. But when you opt for an exchange, be aware that you can acquire new RIs that are of equal or greater value than those you started with. Sometimes, you’ll need to make a true-up payment to balance the books. Essentially, the exchange process is based on the list value of each Convertible RI. And the list value is simply the sum of all payments you’ll make over the remaining term of the original RI.

Don’t Forget to Use the Regional Benefit Scope for Older Standard RIs

The new regional RI benefit broadens the application of your existing RI discounts. It waives the capacity reservation associated with Standard RIs. With Regional scope selected, the RI can be used by your instance in any AZ in the given Region. Plus, you can have your RI discount automatically applied without you worrying about which AZ. If you frequently launching and terminating instances, then this option will reduce the amount of time and effort you spend looking for optimal alignment between your RIs and your instances in different AZs. In cases of new RI purchases, the Scope selects Region by default, however, with older RIs, you need to manually change the current RIs scope from AZ to Region.

Leverage Content Delivery Networks (CDNs) to Reinforce EC2 RI Planning

CDNs reduce the reliance on EC2 for content delivery while providing optimal user experience for your applications by leveraging edge locations. With CDNs, the cost of delivering content is limited to the data transfer costs for the services. In AWS, static content such as images and video files can be stored in S3 buckets. Your application EC2 instances can be configured in the CDN to be used to cache the dynamic content so you can reduce the dependency on the backend instances.

For CDNs that have a minimum monthly usage level of 10TB per month from a single region, AWS provides significant discounts. When the capacity request is higher, the discount also increases. If CDNs are included in the capacity planning for EC2, the usage requirement for EC2 itself can go down for your business thus reducing the need for RIs.

Complement RDS RI Planning by Opting for Non-SQL Database and In-memory Data Stores

Just like CDN, in-memory data stores and data caches can reduce the reliance and utilization of RDS. AWS also provides RI option for AWS ElastiCache (the in-memory data store and cache service) and DynamoDB (the NoSQL database). The technical advantages of these database technologies over relational databases will contribute indirectly to cost optimization of RDS. Leveraging in-memory data stores can also speed up your application performance.

To Wrap-Up

You might have heard this several times: Effective RI planning optimizes AWS cost by 5X. True that. And the fact is there is no universal formula, a magic wand or a one-solution-fits-all that can provide perfect EC2 and RDS RI planning. Be it 2017 or 2020, the secret recipe to solid AWS RI planning lies in understanding your long term usage, application requirements and of course planning reservations for all resources. To know more, read Botmetric’s expert blog, 7 Stepping Stones to Bulletproof Your AWS RI Planning.

And if you find this overwhelming, then you should try Botmetric Cost & Governance that can optimize your cloud spend with smart RI capacity planning, without you managing RIs from your AWS console. And if you think, we have missed any of the key points that can help bolster up EC2 and RDS RI planning, then just drop in a comment below, or on any of our social media pages, Twitter, Facebook or LinkedIn. We are all ears!

Top 11 Hard-Won Lessons We’ve Learned about AWS Auto Scaling

Posted on January 16, 2017August 21, 2017 by Rajeev Kumar

Auto scaling, as we know today, is one of the most powerful tools leveraging the elasticity feature of public cloud – Amazon Web Services (AWS). Its ability to improve the availability of an application or a service, while still keeping cloud infrastructure costs under check, has been applauded by many enterprises across verticals, be it fleet management services or NASA’s research base.

However, at times, AWS Auto Scaling can be a double-edged sword. For the reason that, it introduces higher level complexity in the technology architecture and daily operations management. Without the proper configuration and testing, it might do more harm than good. Even so, all these challenges can be nullified with few precautions. To this end, we’ve collated few lessons we learned over a period – to help you make the most of Auto Scaling capabilities on AWS.

Use Auto Scaling, whether your application is stateful or dynamic

There is a myth among many AWS users that AWS Auto Scaling is hard to use and not so useful with stateful applications. However, the fact is that it is not hard to use. You can get started in minutes, with few precautionary measures like using sticky sessions, keeping provisioning time to minimum, etc. Plus, AWS Auto Scaling helps monitor the instances and heals them if they become unhealthy.

Here’s how: Once the Auto Scaling is activated, it automatically creates an Auto Scaling Group, and provisions the instances accordingly behind the load balancer. This maintains the performance of the application. In addition, Auto Scaling’s Rebalance feature ensures that your capacity is automatically distributed among several availability zone to maximize the resilience of the application. So, whether your application is stateful or dynamic, AWS Auto Scaling helps maintain its performance irrespective of compute capacity demands.

Identify the metrics that impact the performance, during capacity planning

Identify the metrics for the constraining resources, like CPU utilization, memory utilization, of an application. By doing so, it will help track how the resources are impacting the performance of the application. And the result of this analysis will provide the threshold values that will help scale up and scale down the resources perfectly.

Configure AWS CloudWatch to track the identified metrics

The best way forward is to configure Auto Scaling with AWS CloudWatch so that you can fetch these metrics, as and when needed. Using CloudWatch, you can track the metrics in real-time. CloudWatch can be configured to launch the provisioning of an auto scaling group based on the state of a particular metric.

Understand functionality of Auto Scaling Groups while using Dynamic Auto Scaling

The resource configurations have to be specified in Auto Scaling groups feature provided by AWS. Auto scaling groups would also include rules defining circumstances under which the resources will be launched dynamically. AWS allows assigning the of autoscale groups to the Elastic Load Balancers (ELBs) so that the requests coming to the load balancers are routed to the newly deployed resources whenever they are commissioned.

Use Custom Metrics for Complex Auto Scaling Policies

A practical auto-scaling policy must include multiple metrics, instead of just one allowed by CloudWatch. The best approach to circumvent this restriction is to code a custom metric as a Boolean function using Python and the Boto framework. You can use application specific metric as well along with default metrics like memory utilization or CPU, network, etc.

Use Simple Queuing Services

As an alternative to writing complex code for the custom metric, you can also architect your applications to take requests from a Simple Queuing Service and enable CloudWatch to monitor the length of the queues to decide the scale of the computing environment based on the amount of items in the queue at a given time.

Create Custom Amazon Machine Images (AMIs)

To reduce the time taken to provision instances that contain many custom software (not included in the standard AMIs), you can create a custom AMI that contains the software components and libraries required to create the server instance.

Scaling up other AWS services other than EC2, like AWS DynamoDB

Along with AWS EC2, other resources such as AWS DynamoDB, can also be scaled up and scaled down using Auto Scaling. However, the implementation of the policies are different. Since storage is the second most important service other than computing service, efforts to optimize storage will yield good performance as well as cost benefits.

Predictive Analytics for Proactive Management

Setting up thresholds as described above is reactive. Hence, you can leverage time-series prediction analytics to identify patterns within the traffic logs and ensure that the resources are scaled up at pre-defined time, before events take place.

Custom define Auto Scaling policies & provision AZs capacity accordingly

Auto scaling policies must be defined based on the capacity needs as per Availability Zone (AZ) to save on cost spikes. Because pricing of the resources are based on different regions that encompass these AZs. This is critical especially for Auto Scaling groups configured to leverage multiple AZs along with a percent-based scaling policy.

Use Reactive Scaling policies on top of schedule scaling feature

By using Reactive Scaling policies on top of schedule scaling feature will give you the ability to really respond to the dynamic changing conditions in your application.

Conclusion:

Embrace an intelligent cloud management platform.

Here’s why: Despite configuring CloudWatch and other features of Auto Scaling, you cannot always get everything you need. Further automating various Auto Scaling features using key data-driven insights is the way forward. So, sign-up for an intelligent cloud management platform like Botmetric, which throws key insights to manage AWS Auto Scaling, provides detailed predictive analytics and helps you leapfrog your business towards digital disruption.

Also, do listen to Andre Dufour’s recent keynote on AWS Auto Scaling during the recent 2016 re:Invent, where he reveals that Auto Scaling feature will be available to Amazon EMR (Elastic Map Reduce) service as well along with AWS ECS Container service, and Spot Fleet in regards to dynamic scheduling policies.

It is evident. Automation in every field is upon us. There will soon be a time when we will reach the NoOps state. If you have any questions in regards to AWS Auto Scaling or how you can minimize Ops work with scheduled Auto Scaling or anything about cloud management, just comment below or give us a shout out on Twitter, Facebook, or LinkedIn. We’re all ears! Botmetric Cloud Geeks are here to help.

Introducing EC2 Cost Analysis in New Botmetric: A Game Plan to Optimize AWS Spend

Posted on December 19, 2016August 21, 2017 by Editor

Elastic Cloud Compute (EC2) is one of the most popular services of AWS and used by almost every Amazon cloud customer. And, in general, EC2 usage accounts for 70 to 75% of AWS bill for an average AWS user. Moreover, most of the underlying services like EBS, EIP, ELB, NAT, etc. are used in conjunction with EC2 service for deploying applications on AWS cloud.

So, several unique EC2-related line items can show up on your AWS bill, which will further make it even more difficult to comprehend what’s driving all that spending. A high-level view of the spend will not suffice. Because of this, it is critical to analyze EC2 usage and its spend breakdown by various dimensions like resource, instance type, services, accounts, and more while optimizing AWS costs.

To cater to this need and help our customers understand their AWS EC2 spend easily and efficiently, we have introduced the support for “EC2 Cost Analysis” in the ‘All-New’ Botmetric platform as part of its Cost Management and Governance’ Analyze feature.

Here’re the top features that the new Botmetric EC2 Cost Analysis offers:

1. Know your EC2 spend by instance type: You can quickly drill down and understand your total EC2 cost on AWS cloud split across different EC2 instance families. You can filter this further by various AWS accounts.

2. EC2 cost breakdown by sub services: We have brought together the cost of EBS, EIP, ELB, Data Transfer, NAT Gateway under EC2 cost analysis module so you can easily see what is your mix of total spend across various EC2 related services. You can filter this cost further for any AWS account or month so you can drill into specific details. We also encourage you to drill down this analysis for a particular instance family.

3. EC2 cost breakdown across different AWS accounts: You can split the EC2 cost across different AWS accounts in your master payer account so you can categorize them based on your usage.

4. Data export in CSV: We allow you to export different breakdown of EC2 cost into CSV file so you can use it for any internal analysis. The data export option allows you to see the cost breakdown by instance types, AWS accounts, related services, specific EC2 resources, etc.

You can access this feature in Botmetric Cloud Management Platform under Cost & Governance application in the Analyze Module. Please write to us with your feedback on what we can do better and where we can improve it further.

If you want to know some of the AWS EC2 cost saving tips that pro AWS users follow, read this Botmetric blog post. And if you want to know what are the other new features available in the new release of Botmetric, then take an exclusive 14-day trial or read the expert blog post by Botmetric Customer Success Manager, Richa Nath. Until our next blog post, do stay tuned with us on Twitter, Facebook, and LinkedIn for other interesting news from us!

5Ws To Rule The AWS EC2 World

Posted on October 7, 2016August 21, 2017 by Editor

Amazon is the leader in infrastructure cloud computing having a worldwide market share of 31% as of February 2016, according to data from Synergy Research Group. AWS is continuing to grow rapidly and is now Amazon’s most profitable segment, more than its e-commerce site. Thanks to one of its features — the Elastic Compute Cloud, “ or dearly called AWS EC2.” So what is the secret behind its success?

Here’s are some of the deliberations on the 5Ws of AWS EC2 — why, when, what, where and which.

Why AWS EC2?

As the name implies, AWS EC2 provides elastic compute capacity so that enterprises can run their web apps with full flexibility and without downtime. It actually provides what companies are looking for — the ideal Cloud service that helps them build a scalable global infrastructure at the lowest cost, deploy new applications instantly, scale up workload based on demand and remain secure. That’s why AWS EC2!

When to use AWS EC2?

Developers can use AWS EC2 when they need to reduce the time to provision of their IT infrastructure to minutes, instead of months. Designed to make web-scale cloud computing easier, especially for developers, the AWS EC2 provides resizable compute capacity in the cloud. In essence, the AWS EC2 features a simplified and a self-service network model that provides the application developer the option to fit the infrastructure to the app or vice versa.

Where is AWS EC2 useful?

AWS EC2 is most useful when developers need to reduce the time required to obtain and boot new server instances from hours to minutes. It is also useful when they want to quickly scale capacity, both up and down, as the computing requirements change.

Which EC2 plan will help the most?

Every EC2 plan is idiosyncratic in its own way. Developers need to choose which one suits the best for their scenario.

AWS EC2 is available in four different pricing models — on-demand, Spot Instances, Reserved Instances (RIs), and Dedicated Hosts (view the instance type pricing comparison blog here). The on-demand pricing model is ideal for users that prefer the low cost and flexibility of compute capacity without any up-front payment or long-term commitment. The Reserved Instance pricing model is heavily discounted, provided the users commit to a one year to three year period. Unlike on-demand EC2, Spot Instances allow users to bid on spare Amazon EC2 computing capacity for up to 90% off the On-Demand price. Yes! Moreover, Spot Instances are ideal for users with urgent computing needs for large amounts of additional capacity, while the dedicated hosts are ideal for users who are ready to purchase CC as a reservation for up to 70% off the on-demand price.

What are the best practices?

In order to get maximum benefit from AWS EC2 instances, developers need to follow key best practices:

Launch instances into a VPC instead of EC2-Classic
Patch, update, and secure the operating system and applications regularly
Manage IAM users, and IAM roles smartly by establishing credential management policies and procedures
To store temporary data, use the instance store available for the current instance
Track and identify AWS resources using metadata information and custom resource tags
Regularly backup instances using AWS EBS snapshots

To Wrap Up:

AWS has evolved from a pure virtual hosting service provider to a new paradigm in IT infrastructure which provides a cost-effective alternate model to Enterprise IT. AWS enables CIOs to focus on applications and adding business value through technology instead of focusing on the lower levels of IT infrastructure like Server Management. Application developers can design new generation of applications without having to worry about constraints on their existing infrastructure and scaling.

Botmetric Cloud Management Platform, the highest rated app on AWS marketplace, features AWS EC2 Reservation Planner that helps DevOps apply the best practices for their cloud infrastructure without having to worry about the nitty-gritty of the rapidly emerging cloud technologies. Test drive Botmetric today, to see how Cloud Infrastructure costs can be reduced without compromising on performance.

To catch all the latest updates on Botmetric and AWS, follow us on Twitter, Facebook, LinkedIn.

Till then, ‘Keep Calm, and Cloud Easy!’

What’s New in Botmetric ? Enhanced AWS Reserved Instance Planner

Posted on August 17, 2016August 21, 2017 by Tarun G

Reserved Instance Planning on AWS is one of the most important tasks for a AWS cloud IT team with respect to cost optimization and savings. It is also one of the most complex tasks. Botmetric, with its AWS Reserved Instance Planner helps you in resource reservation planning for EC2 and RDS. To further help you in optimizing cost, Botmetric also finds out the unused reservations. It also goes a step ahead and recommends possible modifications within reservations in order to save more efficiently.

We, at Botmetric, understand the importance of reserved instance planning for our customers and constantly work towards enhancing our offering. Botmetric’s AWS reserved instance planner is one of our most used and sought after feature. We received multiple requests from our customers. As always we have listened and acted upon them. We are happy to announce multiple updates to our RI Planner:

EC2 Reserved Instance Portfolio

This was one of the most requested feature. A simple but powerful one. A kind of essential one, so that our customers need not go to AWS console to get the details of the current existing and recently retired reservations while they are planning for their reservations on Botmetric. Also this will eliminate the need to switch across multiple accounts to gather reservation info. What if you have more than 20 Linked accounts! We could feel our customers pain here and acted on it swiftly. Result is brand new EC2 Reserved Instance Portfolio.

We now have a dedicated section for complete EC2 reservations information. You can now do the following with this update:

Get the holistic list of active and retired EC2 reservations across all the Linked accounts under a Payer account. On AWS you need to switch between accounts to get this. And as you may already know, reserved instance planning is something which must be taken up at the payer account level. Hence, the information of all the existing reservations across all Linked accounts at one place becomes very powerful and useful.
Get the list of reservations expiring in near future. You can sort the list as per number of days left for expiring. This can help you in planning your renewals.
Get a list of recently retired reservations and check if any of them is required to be renewed.
You can also look out for old generation AWS instance-types and ensure that you upgrade the corresponding running EC2 instances to a newer generation and renew the reservation accordingly.

RI Planner New Reports

Botmetric’s AWS reserved instance planner now has few more reports added. You can now download three new reports:

EC2 Reservation Recommendation CSV Report
Existing Reservation CSV Report
Expiring RI CSV Report

RI Expiry Email Alert

We have now released Unused RI Email Alert , which updates you with the unused reservations every week. This is an extension of our Unused RI Analyzer. Unused reservations are one of the places where you must definitely optimize. You can modify unused reservations to match existing running instances and save.

There are many updates which you can expect in near future on optimizing unused reservations.

Apart from these updates on our AWS reserved instance planner , we have a few more for you:

You can now analyze cost in Cost Explorer by excluding/including Subscription Cost.
You can now add the emails of multiple Botmetric users in your cloud automation jobs. In case of job failure, all the configured users will get notified. Earlier, only the job creator used to get these email notifications. You asked for it, we heard and delivered!
We have redesigned and improved our summary and alert emails, made them look better.

We believe that with these latest enhancements and additions, our customers AWS cloud management experience on Botmetric will be enriched.

To stay updated on news and views regarding Botmetric, follow us on Twitter.

As always, many of the features and updates in Botmetric are Customer driven. You can share your suggestions or feature requests here.

Are you using AWS for your business and still not using Botmetric?

Don’t wait up. Start optimizing, take control of your cloud infrastructure cost. Try Botmetric for free.

How to Automate AMI Creation for Customized EC2 Instances using Cloud Automation Jobs

Posted on June 27, 2016August 21, 2017 by Rajeev Kumar

AMI (Amazon Machine Image) comes with the advantages of customization of EC2 instances. It also accelerates launching new instances and reduces external dependencies. By creating AMIs, you can launch identical, fully-provisioned copies of your working image into multiple environments. It could be development or production. However, the process of creation of AMIs should be consistent, where the changes between revisions are identifiable and auditable. How to go about it? By automating AMI creation for customized EC2 instances.

The backdrop: Importance of AMIs

An AMI provides the information required to instantiate an EC2 Instance, which is a virtual server in the cloud. You can also specify an AMI when you launch an instance. And you can launch as many instances from the AMI as you need. You can even customize the instance that you launch, from a public AMI. And you can save that configuration as a custom AMI for your own use.

In general, an AMI includes three key components:

A template for the root volume, for the instance. It could be for an operating system, an application server, or for the applications
Launch permissions: Those permissions that help control which AWS accounts can use the AMI – to launch instances
A block device mapping: The one that specifies the volumes to be attached to the instance when it’s launched

Even though AMI comes with the advantages of customization of EC2 instances, it does not help when you need to make additional customization to your AMIs based on the run-time information. Hence, we recommend that the process of creation of AMIs should be consistent with the revisions. And the best way forward to create AMIs consistently is by automating the whole process using the Botmetric Cloud Automation Jobs.

Automate AMI Creation

Using our Botmetric Cloud Automation Jobs, you can automate the task of creating AMI of your customized EC2 Instances. These jobs can be scheduled either at Interval or Cron basis depending on your requirement.

In the dashboard, you can select a single instance or a group of instances for creating AMIs based on the tags.

The Instances with these tags can only be used to create AMIs. These AMIs can be created using “only Root Volume” and “no Reboot” flags that suggest the way to create AMIs.

If only RootVolume is selected in the dashboard: The Botmetric will create AMI that contains only root volume. If RootVolume is deselected, it will create AMI for the instance considering all the attached block devices
If noReboot is selected in the dashboard: The Botmetric will create AMI without restarting the instance. In this case, the Botmetric will first shutdown the instance, create AMI for it, and then start the instance

Additionally, you can also choose the number of AMIs to be retained after creating new AMIs for that instance. It will help in maintaining the latest AMIs available for that instance.

To Conclude

As an AWS expert, we suggest all our customers to look for a hybrid approach. For instance, build static components of your stack into AMIs, and configure dynamic aspects that change regularly (such as application code) at the run time.

Ultimately, you need to build the process of creation of AMIs based on your requirements like frequency of deployments, reduction of external dependencies, requirements to scale quickly, and so forth. To learn how to create AMI for EC2 instances in detail, read our support page here.

This product feature write-up is written by our Software Developer Engineer, Anoop Khandelwal.

Until we come up with the next blog post do keep in touch with us on Facebook, Twitter and LinkedIn.

Making Sense of AWS EC2 Instance Type Pricing: ECU Vs. vCPU

Posted on June 2, 2016August 21, 2017 by Rajeev Kumar

If you are using Amazon Web Services, understanding the nuts and bolts of AWS EC2 instance type pricing is pivotal for you. Why? No two organizations are alike. And every organization has unique computing and storage needs. By knowing the key technicalities, you can only pay for the EC2 Instance Type that fits your business scenarios rather than paying more.

AWS EC2 Instance Type – Unboxed

AWS, long time ago, classified different EC2 instance types (“virtual servers”) by defining an “Amazon EC2 Compute Unit” (ECU). This classification till date helps developers to compare the CPU capacity between different EC2 instance types. AWS used many benchmarks to ensure that ECUs were consistently and predictably measured EC2 CPU capacity, regardless of the underlying hardware. It gave a relative measure of the integer processing power of an AWS EC2 Instance Type.

For new prospective AWS customers, this might be a difficult concept to grasp. Why? For the reason that more traditional deployments, like those on VMWare, were always declared with vCPU (Virtual CPU). The FAQs page on AWS has the complete information on this.

Rather than diving deep into this concept, today, in this blog post, I would like to talk more about ECU and vCPU and how the pricing points differ for both.

As cited on Amazon, EC2 provides a wide selection of instance types optimized to fit different use cases. Instance types comprise varying combinations of CPU, memory, storage, and networking capacity. This type classification gives you the flexibility to choose the appropriate mix of resources for your applications. Each instance type includes one or more instance sizes, allowing you to scale your resources to the requirements of your target workload.

In April 2014, AWS moved towards using vCPU based measure. This compares EC2 Instance sizes as CPU (Clock Speed), the number of CPUs, RAM, Storage, etc. And each vCPU is a hyperthread of an Intel Xeon core for M4, M3, C4, C3, R3, HS1, G2, I2, and D2.

The M3 Instances may also launch as an Intel Xeon E5-2670 (Sandy Bridge) Processor running at 2.6 GHz. While the AVX, AVX2, and enhanced networking are only available on instances launched with HVM AMIs (Amazon Machine Image).

Now, take a look below at AWS EC2 Instance Type Matrix:

Figure: AWS EC2 Instance Type Matrix Using vCPU

There’s a wide variety of EC2 instance types optimized to fit different use cases, combining varying CPU, memory, storage and networking capacities. This classification will help you to choose the right instance type for your particular business needs. Each instance type includes 1+ instance sizes to allow for scalability.

From the above figure and the above classification information, you can get an idea as to how the pricing differs. To know more on this topic read the Amazon documentation.

It might seem daunting when trying to figure out which EC2 instance type you should launch. But that’s where Botmetric comes to your rescue! You will be notified in the “Cloud Insight” view when you should scale down your instance sizes to save money. You also have the EC2 vs. vCPU-based Cost Analytics view in the Cost Analytics Dashboard to monitor your usage and tailor your vCPUs with a fine-tooth comb!

Only pay for the EC2 instance types that fit your business scenario.

Have you faced any challenges with your AWS cloud infrastructure? As a cloud solutions provider, we can help. Just drop us a mail or get in touch with us on Facebook, Twitter, LinkedIn.
This insightful blog article is written by our Chief Evangelist Kim Schmidt.

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