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COMPETING VENDORS HAVE AWS CLOUD IN THEIR CROSS-HAIRS
Updated Nov 22, 2019
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1
53
1
Inspirational

For many years Amazon’s cloud platform AWS (Amazon Web Services) has been the champion in the cloud marketplace. Only in the last few years has Microsoft’s Azure platform started to challenge the dominance of AWS in terms of total revenue booked, though AWS still reigns supreme in the IaaS (infrastructure-as-a-service) category of cloud services. But the times they are a-changing’, as the old Bob Dylan song says, and Amazon’s long-time position on the top of the heap has resulted in challenges arising from cloud vendors who until now have been considered underdogs. What seems to be happening now is that some smaller vendors are partnering up to try and challenge AWS and the result has been an increase in the intensity of the Cloud Wars. To gain some insight into what’s currently happening and what may lie ahead, I recently talked with a couple of experts who have a handle on the cloud marketplace.

To get in-depth knowledge on AWS, you can enroll for live Demo Aws online training

AWS cloud: A nice head start

I started by talking with Todd Matters, the chief architect, and co-founder at RackWare, a company that offers a Hybrid Cloud Management Platform that helps enterprises migrate to the cloud & protect their workloads. I asked Todd why is AWS still considered the “big kahuna” in the cloud computing marketplace and what qualities make them the “top dog” that everyone else is gunning for. “AWS was the first vendor in the market by quite a big margin,” Todd said. “It really pushed the envelope in terms of the features, services, and options that were offered. AWS was also very good at providing very attractive entry-level pricing. But by the time enterprises purchase the different services that are necessary, AWS is not necessarily less expensive than the other clouds. AWS looks very attractive to enterprises initially, so they tend to get a lot of attention.”

I mentioned to Todd that one of the reasons that several large enterprises I have contact with decided to go with AWS initially was because they have datacenters all over the world. “Yes, AWS also has many datacenters dispersed very strategically throughout the world,” Todd says, “and by doing this people can take disaster recovery into consideration because there’s always a datacenter someplace that they can take advantage of.” And, of course, disaster recovery, is one of the key things you need to take into consideration when you decide to host your workloads and data in the cloud instead of having it in-house where you have more control.

Playing catch up

Another reason many companies I have familiarity with have chosen to go with AWS is because of the breadth of features available on the platform. Asked whether there are any features that AWS has that competitors are still playing catch up on, Todd replied “AWS’s object storage is still a big advantage. It is a very practical solution that solves a lot of storage needs and is also very cost-effective. But Amazon has impressive feature sets in essentially every area,” emphasizes Todd, “from Kubernetes to containers. It may be a little bit of work, but enterprises can implement disaster recovery and auto-scaling. AWS’s list of services and features is almost astounding. There’s basically something for pretty much everybody.”

The biggest news in recent days concerning the Cloud Wars is, of course, the news that IBM has closed its acquisition of Red Hat for the huge sum of $34 billion. Another expert I talked with, Tim Beerman, CTO at Ensono, a company that offers managed services for mainframe, cloud, and hybrid IT, offered up the following thoughts about the acquisition. “IBM’s acquisition of Red Hat is a big win for the companies and their customers. Red Hat’s technology will help modernize IBM’s software services, IBM’s investment will help Red Hat scale its offerings, and customers will be able to go to market faster. Now that this partnership is finalized, we’ll begin to see more opportunities for hybrid IT, as companies that are hesitant to move their workloads to the public cloud will have the option to add an open-source layer and manage their data across multiple clouds. The added security and flexibility of hybrid IT allows businesses to keep up with evolving cloud computing capabilities, receive more competitive pricing and see results faster.”

Teaming up to take down No. 1

On top of IBM’s deal to acquire Red Hat, however, is the earlier announcement from Microsoft and Oracle that they were going to partner by making their cloud platforms interoperable with each other. When I went back to Todd and asked him what he thought were the underlying strategies behind both Microsoft partnering with Oracle and IBM acquiring RedHat, he suggested that “the cloud providers are playing to their strengths right now. For example, Microsoft has its own software and by partnering with Oracle Cloud Infrastructure, they can be more competitive in the industry without really threatening their core cloud business. In turn, Oracle has an opportunity to increase their revenue by providing services where they are the dominant leader.” So, in other words, these changes in the cloud marketplace aren’t just happening because the vendors involved believe in the idea that bigger is better. Instead, there is more at play here. “Because they can be mutually beneficial,” says Todd, “we are going to see more kinds of those partnerships moving forward.”

So how then is this intense competition happening between top cloud vendors going to impact their enterprise customers? Will it all be good, or will there also likely be some problems? I asked Todd this question and he replied that “competition among the cloud vendors will always be good for customers. It will continue to drive down prices, increase innovation and solve real problems for enterprises.” Let’s cross our fingers and hope that this is the case because the big fish are getting bigger and fewer when it comes to cloud services vendors.

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4 Collaboration Spaces Available

COMPETING VENDORS HAVE AWS CLOUD IN THEIR CROSS-HAIRS

For many years Amazon’s cloud platform AWS (Amazon Web Services) has been the champion in the cloud marketplace. Only in the last few years has Microsoft’s Azure platform started to challenge the dominance of AWS in terms of total revenue booked, though AWS still reigns supreme in the IaaS (infrastructure-as-a-service) category of cloud services. But the times they are a-changing’, as the old Bob Dylan song says, and Amazon’s long-time position on the top of the heap has resulted in challenges arising from cloud vendors who until now have been considered underdogs. What seems to be happening now is that some smaller vendors are partnering up to try and challenge AWS and the result has been an increase in the intensity of the Cloud Wars. To gain some insight into what’s currently happening and what may lie ahead, I recently talked with a couple of experts who have a handle on the cloud marketplace.

To get in-depth knowledge on AWS, you can enroll for live Demo Aws online training

AWS cloud: A nice head start

I started by talking with Todd Matters, the chief architect, and co-founder at RackWare, a company that offers a Hybrid Cloud Management Platform that helps enterprises migrate to the cloud & protect their workloads. I asked Todd why is AWS still considered the “big kahuna” in the cloud computing marketplace and what qualities make them the “top dog” that everyone else is gunning for. “AWS was the first vendor in the market by quite a big margin,” Todd said. “It really pushed the envelope in terms of the features, services, and options that were offered. AWS was also very good at providing very attractive entry-level pricing. But by the time enterprises purchase the different services that are necessary, AWS is not necessarily less expensive than the other clouds. AWS looks very attractive to enterprises initially, so they tend to get a lot of attention.”

I mentioned to Todd that one of the reasons that several large enterprises I have contact with decided to go with AWS initially was because they have datacenters all over the world. “Yes, AWS also has many datacenters dispersed very strategically throughout the world,” Todd says, “and by doing this people can take disaster recovery into consideration because there’s always a datacenter someplace that they can take advantage of.” And, of course, disaster recovery, is one of the key things you need to take into consideration when you decide to host your workloads and data in the cloud instead of having it in-house where you have more control.

Playing catch up

Another reason many companies I have familiarity with have chosen to go with AWS is because of the breadth of features available on the platform. Asked whether there are any features that AWS has that competitors are still playing catch up on, Todd replied “AWS’s object storage is still a big advantage. It is a very practical solution that solves a lot of storage needs and is also very cost-effective. But Amazon has impressive feature sets in essentially every area,” emphasizes Todd, “from Kubernetes to containers. It may be a little bit of work, but enterprises can implement disaster recovery and auto-scaling. AWS’s list of services and features is almost astounding. There’s basically something for pretty much everybody.”

The biggest news in recent days concerning the Cloud Wars is, of course, the news that IBM has closed its acquisition of Red Hat for the huge sum of $34 billion. Another expert I talked with, Tim Beerman, CTO at Ensono, a company that offers managed services for mainframe, cloud, and hybrid IT, offered up the following thoughts about the acquisition. “IBM’s acquisition of Red Hat is a big win for the companies and their customers. Red Hat’s technology will help modernize IBM’s software services, IBM’s investment will help Red Hat scale its offerings, and customers will be able to go to market faster. Now that this partnership is finalized, we’ll begin to see more opportunities for hybrid IT, as companies that are hesitant to move their workloads to the public cloud will have the option to add an open-source layer and manage their data across multiple clouds. The added security and flexibility of hybrid IT allows businesses to keep up with evolving cloud computing capabilities, receive more competitive pricing and see results faster.”

Teaming up to take down No. 1

On top of IBM’s deal to acquire Red Hat, however, is the earlier announcement from Microsoft and Oracle that they were going to partner by making their cloud platforms interoperable with each other. When I went back to Todd and asked him what he thought were the underlying strategies behind both Microsoft partnering with Oracle and IBM acquiring RedHat, he suggested that “the cloud providers are playing to their strengths right now. For example, Microsoft has its own software and by partnering with Oracle Cloud Infrastructure, they can be more competitive in the industry without really threatening their core cloud business. In turn, Oracle has an opportunity to increase their revenue by providing services where they are the dominant leader.” So, in other words, these changes in the cloud marketplace aren’t just happening because the vendors involved believe in the idea that bigger is better. Instead, there is more at play here. “Because they can be mutually beneficial,” says Todd, “we are going to see more kinds of those partnerships moving forward.”

So how then is this intense competition happening between top cloud vendors going to impact their enterprise customers? Will it all be good, or will there also likely be some problems? I asked Todd this question and he replied that “competition among the cloud vendors will always be good for customers. It will continue to drive down prices, increase innovation and solve real problems for enterprises.” Let’s cross our fingers and hope that this is the case because the big fish are getting bigger and fewer when it comes to cloud services vendors.

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5Mins Each
1
ISSUE
What Is AWS Backup and how it works?
Updated Nov 25, 2019
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16
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AWS Backup is a fully managed backup service that makes it easy to centralize and automate the backup of data across AWS services in the cloud and on-premises. Using AWS Backup, you can centrally configure backup policies and monitor backup activity for your AWS resources. AWS Backup automates and consolidates backup tasks that were previously performed service-by-service, removing the need to create custom scripts and manual processes. With just a few clicks on the AWS Backup console, you can create backup policies that automate backup schedules and retention management. Learn AWS Training

AWS Backup provides a fully managed, policy-based backup solution, simplifying your backup management, and enabling you to meet your business and regulatory backup compliance requirements.

AWS Backup Overview

AWS Backup provides the following features and capabilities.

Centralized Backup Management

AWS Backup provides a centralized backup console, a set of backup APIs, and the AWS Command Line Interface (AWS CLI) to manage backups across the AWS services that your applications use. With AWS Backup, you can centrally manage backup policies that meet your backup requirements. You can then apply them to your AWS resources across AWS services, enabling you to back up your application data in a consistent and compliant manner. The AWS Backup centralized backup console offers a consolidated view of your backups and backup activity logs, making it easier to audit your backups and ensure compliance.

Policy-Based Backup Solutions

With AWS Backup, you can create backup policies known as backup plans. Use these backup plans to define your backup requirements and then apply them to the AWS resources that you want to protect across the AWS services that you use. You can create separate backup plans that each meet specific business and regulatory compliance requirements. This helps ensure that each AWS resource is backed up according to your requirements. Backup plans make it easy to enforce your backup strategy across your organization and across your applications in a scalable manner.

Tag-Based Backup Policies

You can use AWS Backup to apply backup plans to your AWS resources by tagging them. Tagging makes it easier to implement your backup strategy across all your applications and to ensure that all your AWS resources are backed up and protected. AWS tags are a great way to organize and classify your AWS resources. Integration with AWS tags enables you to quickly apply a backup plan to a group of AWS resources, so that they are backed up in a consistent and compliant manner.

Backup Activity Monitoring

AWS Backup provides a dashboard that makes it simple to audit backup and restore activity across AWS services. With just a few clicks on the AWS Backup console, you can view the status of recent backup jobs. You can also restore jobs across AWS services to ensure that your AWS resources are properly protected.

AWS Backup integrates with AWS CloudTrail. CloudTrail gives you a consolidated view of backup activity logs that make it quick and easy to audit how your resources are backed up. AWS Backup also integrates with Amazon Simple Notification Service (Amazon SNS), providing you with backup activity notifications, such as when a backup succeeds or a restore has been initiated.

Lifecycle Management Policies

AWS Backup enables you to meet compliance requirements while minimizing backup storage costs by storing backups in a low-cost cold storage tier. You can configure lifecycle policies that automatically transition backups from warm storage to cold storage according to a schedule that you define.

Backup Access Policies

AWS Backup offers resource-based access policies for your backup vaults to define who has access to your backups. You can define access policies for a backup vault that define who has access to the backups within that vault and what actions they can take. This provides a simple and secure way to control access to your backups across AWS services, helping you meet your compliance requirements.

AWS Backup: How It Works

AWS Backup is a fully managed backup service that makes it easy to centralize and automate the backing up of data across AWS services. With AWS Backup, you can create backup policies called backup plans. You can use these plans to define your backup requirements, such as how frequently to back up your data and how long to retain those backups. AWS Backup lets you apply backup plans to your AWS resources by simply tagging them. AWS Backup then automatically backs up your AWS resources according to the backup plan that you defined.

The following sections describe how AWS Backup works, its implementation details, and security considerations.

Topics

How AWS Backup Works with Other AWS Services

Metering Backup Usage

How AWS Backup Works with Other AWS Services

Many AWS services offer backup features that help you protect your data. These features include Amazon Elastic Block Store (Amazon EBS) snapshots, Amazon Relational Database Service (Amazon RDS) snapshots, Amazon DynamoDB backups, and AWS Storage Gateway snapshots.

All per-service backup capabilities continue to be available and work as usual. For example, you can make snapshots of your EBS volumes using the Amazon Elastic Compute Cloud (Amazon EC2) API. AWS Backup provides a common way to manage backups across AWS services both in the AWS Cloud and on-premises. AWS Backup provides a centralized backup console that offers backup scheduling, retention management, and backup monitoring.

AWS Backup uses existing backup capabilities of AWS services to implement its centralized features. For example, when you create a backup plan, AWS Backup uses the EBS snapshot capabilities when creating backups on your behalf according to your backup plan. Learn for more information AWS tutorial

Metering Backup Usage

Backup usage for existing backup capabilities, such as Amazon EBS snapshots, will continue to be metered and billed by their respective service, and the pricing remains unchanged. There is no additional charge to use the AWS Backup centralized backup features beyond the existing backup storage pricing charged by AWS services, such as Amazon EBS snapshot storage fees.

For services that introduce backup capabilities on AWS Backup, such as Amazon EFS, backup usage is metered and billed by AWS Backup.

Blog
Read More
Solo Work

What Is AWS Backup and how it works?

AWS Backup is a fully managed backup service that makes it easy to centralize and automate the backup of data across AWS services in the cloud and on-premises. Using AWS Backup, you can centrally configure backup policies and monitor backup activity for your AWS resources. AWS Backup automates and consolidates backup tasks that were previously performed service-by-service, removing the need to create custom scripts and manual processes. With just a few clicks on the AWS Backup console, you can create backup policies that automate backup schedules and retention management. Learn AWS Training

AWS Backup provides a fully managed, policy-based backup solution, simplifying your backup management, and enabling you to meet your business and regulatory backup compliance requirements.

AWS Backup Overview

AWS Backup provides the following features and capabilities.

Centralized Backup Management

AWS Backup provides a centralized backup console, a set of backup APIs, and the AWS Command Line Interface (AWS CLI) to manage backups across the AWS services that your applications use. With AWS Backup, you can centrally manage backup policies that meet your backup requirements. You can then apply them to your AWS resources across AWS services, enabling you to back up your application data in a consistent and compliant manner. The AWS Backup centralized backup console offers a consolidated view of your backups and backup activity logs, making it easier to audit your backups and ensure compliance.

Policy-Based Backup Solutions

With AWS Backup, you can create backup policies known as backup plans. Use these backup plans to define your backup requirements and then apply them to the AWS resources that you want to protect across the AWS services that you use. You can create separate backup plans that each meet specific business and regulatory compliance requirements. This helps ensure that each AWS resource is backed up according to your requirements. Backup plans make it easy to enforce your backup strategy across your organization and across your applications in a scalable manner.

Tag-Based Backup Policies

You can use AWS Backup to apply backup plans to your AWS resources by tagging them. Tagging makes it easier to implement your backup strategy across all your applications and to ensure that all your AWS resources are backed up and protected. AWS tags are a great way to organize and classify your AWS resources. Integration with AWS tags enables you to quickly apply a backup plan to a group of AWS resources, so that they are backed up in a consistent and compliant manner.

Backup Activity Monitoring

AWS Backup provides a dashboard that makes it simple to audit backup and restore activity across AWS services. With just a few clicks on the AWS Backup console, you can view the status of recent backup jobs. You can also restore jobs across AWS services to ensure that your AWS resources are properly protected.

AWS Backup integrates with AWS CloudTrail. CloudTrail gives you a consolidated view of backup activity logs that make it quick and easy to audit how your resources are backed up. AWS Backup also integrates with Amazon Simple Notification Service (Amazon SNS), providing you with backup activity notifications, such as when a backup succeeds or a restore has been initiated.

Lifecycle Management Policies

AWS Backup enables you to meet compliance requirements while minimizing backup storage costs by storing backups in a low-cost cold storage tier. You can configure lifecycle policies that automatically transition backups from warm storage to cold storage according to a schedule that you define.

Backup Access Policies

AWS Backup offers resource-based access policies for your backup vaults to define who has access to your backups. You can define access policies for a backup vault that define who has access to the backups within that vault and what actions they can take. This provides a simple and secure way to control access to your backups across AWS services, helping you meet your compliance requirements.

AWS Backup: How It Works

AWS Backup is a fully managed backup service that makes it easy to centralize and automate the backing up of data across AWS services. With AWS Backup, you can create backup policies called backup plans. You can use these plans to define your backup requirements, such as how frequently to back up your data and how long to retain those backups. AWS Backup lets you apply backup plans to your AWS resources by simply tagging them. AWS Backup then automatically backs up your AWS resources according to the backup plan that you defined.

The following sections describe how AWS Backup works, its implementation details, and security considerations.

Topics

How AWS Backup Works with Other AWS Services

Metering Backup Usage

How AWS Backup Works with Other AWS Services

Many AWS services offer backup features that help you protect your data. These features include Amazon Elastic Block Store (Amazon EBS) snapshots, Amazon Relational Database Service (Amazon RDS) snapshots, Amazon DynamoDB backups, and AWS Storage Gateway snapshots.

All per-service backup capabilities continue to be available and work as usual. For example, you can make snapshots of your EBS volumes using the Amazon Elastic Compute Cloud (Amazon EC2) API. AWS Backup provides a common way to manage backups across AWS services both in the AWS Cloud and on-premises. AWS Backup provides a centralized backup console that offers backup scheduling, retention management, and backup monitoring.

AWS Backup uses existing backup capabilities of AWS services to implement its centralized features. For example, when you create a backup plan, AWS Backup uses the EBS snapshot capabilities when creating backups on your behalf according to your backup plan. Learn for more information AWS tutorial

Metering Backup Usage

Backup usage for existing backup capabilities, such as Amazon EBS snapshots, will continue to be metered and billed by their respective service, and the pricing remains unchanged. There is no additional charge to use the AWS Backup centralized backup features beyond the existing backup storage pricing charged by AWS services, such as Amazon EBS snapshot storage fees.

For services that introduce backup capabilities on AWS Backup, such as Amazon EFS, backup usage is metered and billed by AWS Backup.

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Tips & tricks for developing a serverless cloud app
Updated Nov 26, 2019
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18
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Inspirational

As organizations search for flexible and scalable data solutions, the pull for going serverless has never been stronger. However, applying emerging technologies to your company’s processes is easier said than done. Luckily, you’re not alone in your pursuit of serverless cloud app development.

With first-hand experience in implementing serverless app development as a software engineer at K15t (an Atlassian Platinum Solution Partner and Marketplace Vendor), I’ll reveal some of my best practices and discuss the roadblocks we were able to overcome while going serverless.To get in-depth knowledge on AWS, you can enroll for live demo AWS Online Training

Getting startedBefore we look into the best practices, we need to set up our development environment. There are two ways you can develop serverless functions: locally or directly in the cloud.

Developing a function locally allows you to execute, test, and debug code on your local machine, while the alternative requires you to upload and execute your code in the cloud. In the instance of local development, you have the choice of using different frameworks, like the Serverless framework, the Serverless Application Model (SAM), or LocalStack. In order to go live with your app, you’ll still need to use one of the cloud providers like AWS, Azure, Google, or similar to upload and execute your code. For this article, we’re going to focus on AWS Lambda.

One key drawback we saw with the cloud execution is that debugging your code can be more challenging. To make a well-informed decision about your development approach, it is important to consider three things:

You must have a test environment that closely resembles your production environment. So don’t only use your local machine, because then you’ll always simplify something, be it services, access policies, or something else.Local code updates are generally faster because you don’t need to update or upload your code into the cloud (although this process can be optimized using small tools or a clever approach).

Debugging your code along the way should always be part of your process. Locally running tests of your business logic will help you easily spot errors in your code, so pay close attention to split infrastructure code and business logic.Another important point is to keep track of all your Lambda functions. The best way to do this is to describe your infrastructure using one of the frameworks above to help keep track of the Lambda functions deployed in your environment. You may also utilize a CI/CD pipeline, which allows you to automate your deployment as much as possible.Best practicesKeep it simple

The first best practice when going serverless is to limit the scope of your functions. For example, if there are different tasks you want to accomplish like receiving a webhook, processing the webhook data, and then sending a notification, you could put them all into one Lambda function.

However, this will reduce your app’s scalability. I suggest keeping your functions simple and separate your concerns. Consider focusing on just one task your function will perform and pour your energy into delivering that functionality very well. This will lead to better scalability and reusability in your app. This also reduces the file size of your Lambda function, so you may also be able to reduce the cold-start time.Every millisecond matters here, because the bigger your artifact, the slower the startup time of your function, so decide carefully on which dependencies you’ll include in your code. This is especially important for Java programmers! Avoid using frameworks like Spring — it just slows down your function.If you want to use your Lambda functions as a REST API, look for services like API Gateway or AWS App Sync to connect with your Lambda functions. However, keep in mind that due to the cold-start problem, the response times of your Lambda functions might have some spikes.

Key in on communicationIf you follow the advice from above to split up your Lambda functions, then communication between your functions becomes very important in order to exchange data and create a flow within your app. Depending on your needs, you can utilize:Synchronous communication: Directly call another Lambda function from within a Lambda functionAsynchronous communication: Upload data to a service and let this service trigger another Lambda functionBoth approaches have their drawbacks: synchronous communication results in a tight coupling of your Lambda functions and might be problematic if you need to exchange big chunks of data, whereas asynchronous communication always involves a different party and can get pricey. However, in order to be more flexible and improve the scalability of your app, asynchronous communication is the preferred choice.

Ensure all aspects are scalableMany services like AWS and Jira have the capacity to automatically scale applications, leading many developers to overlook this step. However, you may find yourself working with numerous services in order to achieve the desired functionality for your serverless application. These services won’t all have the same scalability. Protect your code from malfunctioning by setting up a queue, or buffer requests if necessary, to hedge this issue. One service that proved to be very useful for us was Amazon Kinesis, a streaming service capable of handling lots of data, which we use to buffer all incoming webhooks.

Make sure 15 minutes is enough time to execute your appIn Lambda, your functions have 15 minutes to run before they time out. Given that this limit was recently increased from 5 minutes, this may not seem like a big concern. But depending on your app, instances can quickly add up.You can optimize this a bit with some more parallelization within your Lambda function, but to really circumvent these time limits, consider using other approaches like recursion (calling yourself from within a Lambda function to continue processing) or AWS Step Functions, which manage the execution workflow around the time limit. You may also need to consider the viability of outsourcing this to another service.

Understand data limits

Other important aspects to take into consideration are the limits of a Lambda function. For example, you have up to 3 gigabytes available for your memory allocation, but be aware that memory allocation and CPU power correlate: the more memory you allocate, the more CPU power you have. The same is true for network and I/O throughput which correlate to memory allocation as well.

Furthermore, you only have about 512 megabytes available for temporary local storage. If you’re in the middle of a project (or ideally in the planning stage) and feel as though these limitations will be too challenging to overcome, then serverless may not be the way to go for this particular set of code.Serverless to the rescueIf you’re considering (or in the middle of) creating a serverless app, you can utilize these key takeaways from my team at K15t to create a proper scope and avoid potential snags in the dev launch cycle.

Blog
Inspirational
Read More
Solo Work

Tips & tricks for developing a serverless cloud app

As organizations search for flexible and scalable data solutions, the pull for going serverless has never been stronger. However, applying emerging technologies to your company’s processes is easier said than done. Luckily, you’re not alone in your pursuit of serverless cloud app development.

With first-hand experience in implementing serverless app development as a software engineer at K15t (an Atlassian Platinum Solution Partner and Marketplace Vendor), I’ll reveal some of my best practices and discuss the roadblocks we were able to overcome while going serverless.To get in-depth knowledge on AWS, you can enroll for live demo AWS Online Training

Getting startedBefore we look into the best practices, we need to set up our development environment. There are two ways you can develop serverless functions: locally or directly in the cloud.

Developing a function locally allows you to execute, test, and debug code on your local machine, while the alternative requires you to upload and execute your code in the cloud. In the instance of local development, you have the choice of using different frameworks, like the Serverless framework, the Serverless Application Model (SAM), or LocalStack. In order to go live with your app, you’ll still need to use one of the cloud providers like AWS, Azure, Google, or similar to upload and execute your code. For this article, we’re going to focus on AWS Lambda.

One key drawback we saw with the cloud execution is that debugging your code can be more challenging. To make a well-informed decision about your development approach, it is important to consider three things:

You must have a test environment that closely resembles your production environment. So don’t only use your local machine, because then you’ll always simplify something, be it services, access policies, or something else.Local code updates are generally faster because you don’t need to update or upload your code into the cloud (although this process can be optimized using small tools or a clever approach).

Debugging your code along the way should always be part of your process. Locally running tests of your business logic will help you easily spot errors in your code, so pay close attention to split infrastructure code and business logic.Another important point is to keep track of all your Lambda functions. The best way to do this is to describe your infrastructure using one of the frameworks above to help keep track of the Lambda functions deployed in your environment. You may also utilize a CI/CD pipeline, which allows you to automate your deployment as much as possible.Best practicesKeep it simple

The first best practice when going serverless is to limit the scope of your functions. For example, if there are different tasks you want to accomplish like receiving a webhook, processing the webhook data, and then sending a notification, you could put them all into one Lambda function.

However, this will reduce your app’s scalability. I suggest keeping your functions simple and separate your concerns. Consider focusing on just one task your function will perform and pour your energy into delivering that functionality very well. This will lead to better scalability and reusability in your app. This also reduces the file size of your Lambda function, so you may also be able to reduce the cold-start time.Every millisecond matters here, because the bigger your artifact, the slower the startup time of your function, so decide carefully on which dependencies you’ll include in your code. This is especially important for Java programmers! Avoid using frameworks like Spring — it just slows down your function.If you want to use your Lambda functions as a REST API, look for services like API Gateway or AWS App Sync to connect with your Lambda functions. However, keep in mind that due to the cold-start problem, the response times of your Lambda functions might have some spikes.

Key in on communicationIf you follow the advice from above to split up your Lambda functions, then communication between your functions becomes very important in order to exchange data and create a flow within your app. Depending on your needs, you can utilize:Synchronous communication: Directly call another Lambda function from within a Lambda functionAsynchronous communication: Upload data to a service and let this service trigger another Lambda functionBoth approaches have their drawbacks: synchronous communication results in a tight coupling of your Lambda functions and might be problematic if you need to exchange big chunks of data, whereas asynchronous communication always involves a different party and can get pricey. However, in order to be more flexible and improve the scalability of your app, asynchronous communication is the preferred choice.

Ensure all aspects are scalableMany services like AWS and Jira have the capacity to automatically scale applications, leading many developers to overlook this step. However, you may find yourself working with numerous services in order to achieve the desired functionality for your serverless application. These services won’t all have the same scalability. Protect your code from malfunctioning by setting up a queue, or buffer requests if necessary, to hedge this issue. One service that proved to be very useful for us was Amazon Kinesis, a streaming service capable of handling lots of data, which we use to buffer all incoming webhooks.

Make sure 15 minutes is enough time to execute your appIn Lambda, your functions have 15 minutes to run before they time out. Given that this limit was recently increased from 5 minutes, this may not seem like a big concern. But depending on your app, instances can quickly add up.You can optimize this a bit with some more parallelization within your Lambda function, but to really circumvent these time limits, consider using other approaches like recursion (calling yourself from within a Lambda function to continue processing) or AWS Step Functions, which manage the execution workflow around the time limit. You may also need to consider the viability of outsourcing this to another service.

Understand data limits

Other important aspects to take into consideration are the limits of a Lambda function. For example, you have up to 3 gigabytes available for your memory allocation, but be aware that memory allocation and CPU power correlate: the more memory you allocate, the more CPU power you have. The same is true for network and I/O throughput which correlate to memory allocation as well.

Furthermore, you only have about 512 megabytes available for temporary local storage. If you’re in the middle of a project (or ideally in the planning stage) and feel as though these limitations will be too challenging to overcome, then serverless may not be the way to go for this particular set of code.Serverless to the rescueIf you’re considering (or in the middle of) creating a serverless app, you can utilize these key takeaways from my team at K15t to create a proper scope and avoid potential snags in the dev launch cycle.

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What is AWS lambda?
Updated Nov 28, 2019
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Aws Lambda is a compute service, with this you can run the code without servers. It runs the code when it needed, measures automatically in a few seconds. It charges only when you run the code, when your code is not running it won't charge. You can code on any type of application with Zero administration. It runs your code with computing Infrastructure. It performs each administration of the compute resources that includes server and operating system maintenance and many more. Everything you need is to submit your code, to Lambda this code may be in Java, Node. Js and Python. Lambda was announced in 2014.

In this what is AWS Lambda blog we will discuss the following?

To get in-depth knowledge on AWS, you can enroll for live demo AWS Online Training

What is AWS lambda?

Why AWS Lambda is used?

Which language is best for AWS lambda?

Is AWS Lambda is free?

Design AWS Serverless applications composed of functions that started by Events. Which move them by Aws code build and code pipeline.

Why AWS Lambda is used?

Specifically, a lambda can be used in many use cases. It is easy to start and run at a low price. Unique to fewer traffic applications, company IT services. In the same way, Other uses of Lambda include analyzing data on the projects uploaded to S3. Therefore this will check the availability and health of other projects as soon as possible.

We know that it used for serverless websites. While constant content hosted on S3, and front end web will send requests to lambda functions by an API gateway. Lambda functions have application logic and they use RDS or Dynamo-dB for continuous Data. Consequently, you pay only when it depends on the number of requests that occurred in Lambda, API gateway, and S3. For Dynamo-DB and RDS you have to pay on monthly fixed payments.

Which language is best for aws lambda?

Especially Lambda inbuilt supports, the Ruby code, Python, C#, Node. Js, Powershell, Go, Java and many more. It uses Run-time API, that allows you to implement any additional Programming languages to write your Functions. For more information go through OnlineITGuru IT training Java, python, Ruby blogs.

One of our Programmers has uploaded, Golang Apexin in a lambda to power the apex ping. He has implemented it a year ago. In brief, this works like a better one with 0.5ms on a plain node.

If you want, you can test an application in Lambda. Write the code in a different language. For many things, you will not notice the difference. Most Important, Last year it declared that Node.js.6.10, that available for designing of programming languages that supports lambda. As a matter of fact you can include Java, C, Python to it.

Use AWS Lambdalanguages and layers for Programming in Lambda.

What is a Lambda layer?

A lambda layer is a guide to managing the code centrally to design serverless Applications. It is simple to write code and share that code across the Aws lambda function. That is your custom code, used by a single function or standard set of the library.

Advantages

You can implement separate concerns, in between custom business logic and dependencies. Design your Function code, which is smaller and concentrated, that you need to design

Speed up your Movements, why means less code will be uploaded and packed and Reused equally.

Is AWS Lambda is free?

As we already mentioned, you pay only for what you use. Similarly, You charged depending on the number of functions and the duration of time. In the same fashion, it means the time taken for your coding and execution.

Now we discuss AWS Lambda Pricing

It starts with the count on each request. In other words, it starts processing in reaction to a call or an event alert. Simultaneously You will be charged on all requests of your functions with aws lambda limits.

If you are interested in AWS please go through AWS Online Training Hyderabad

Lambda Free Tier

This free tier includes 1M free requests in a month with 400 GB-seconds of computing time in a month. Not to mention the functioning of your program depends on the memory used by your program. As a result, this free tier option is available more than 12 months after you can see lambda pricing.

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What is AWS lambda?

Aws Lambda is a compute service, with this you can run the code without servers. It runs the code when it needed, measures automatically in a few seconds. It charges only when you run the code, when your code is not running it won't charge. You can code on any type of application with Zero administration. It runs your code with computing Infrastructure. It performs each administration of the compute resources that includes server and operating system maintenance and many more. Everything you need is to submit your code, to Lambda this code may be in Java, Node. Js and Python. Lambda was announced in 2014.

In this what is AWS Lambda blog we will discuss the following?

To get in-depth knowledge on AWS, you can enroll for live demo AWS Online Training

What is AWS lambda?

Why AWS Lambda is used?

Which language is best for AWS lambda?

Is AWS Lambda is free?

Design AWS Serverless applications composed of functions that started by Events. Which move them by Aws code build and code pipeline.

Why AWS Lambda is used?

Specifically, a lambda can be used in many use cases. It is easy to start and run at a low price. Unique to fewer traffic applications, company IT services. In the same way, Other uses of Lambda include analyzing data on the projects uploaded to S3. Therefore this will check the availability and health of other projects as soon as possible.

We know that it used for serverless websites. While constant content hosted on S3, and front end web will send requests to lambda functions by an API gateway. Lambda functions have application logic and they use RDS or Dynamo-dB for continuous Data. Consequently, you pay only when it depends on the number of requests that occurred in Lambda, API gateway, and S3. For Dynamo-DB and RDS you have to pay on monthly fixed payments.

Which language is best for aws lambda?

Especially Lambda inbuilt supports, the Ruby code, Python, C#, Node. Js, Powershell, Go, Java and many more. It uses Run-time API, that allows you to implement any additional Programming languages to write your Functions. For more information go through OnlineITGuru IT training Java, python, Ruby blogs.

One of our Programmers has uploaded, Golang Apexin in a lambda to power the apex ping. He has implemented it a year ago. In brief, this works like a better one with 0.5ms on a plain node.

If you want, you can test an application in Lambda. Write the code in a different language. For many things, you will not notice the difference. Most Important, Last year it declared that Node.js.6.10, that available for designing of programming languages that supports lambda. As a matter of fact you can include Java, C, Python to it.

Use AWS Lambdalanguages and layers for Programming in Lambda.

What is a Lambda layer?

A lambda layer is a guide to managing the code centrally to design serverless Applications. It is simple to write code and share that code across the Aws lambda function. That is your custom code, used by a single function or standard set of the library.

Advantages

You can implement separate concerns, in between custom business logic and dependencies. Design your Function code, which is smaller and concentrated, that you need to design

Speed up your Movements, why means less code will be uploaded and packed and Reused equally.

Is AWS Lambda is free?

As we already mentioned, you pay only for what you use. Similarly, You charged depending on the number of functions and the duration of time. In the same fashion, it means the time taken for your coding and execution.

Now we discuss AWS Lambda Pricing

It starts with the count on each request. In other words, it starts processing in reaction to a call or an event alert. Simultaneously You will be charged on all requests of your functions with aws lambda limits.

If you are interested in AWS please go through AWS Online Training Hyderabad

Lambda Free Tier

This free tier includes 1M free requests in a month with 400 GB-seconds of computing time in a month. Not to mention the functioning of your program depends on the memory used by your program. As a result, this free tier option is available more than 12 months after you can see lambda pricing.

Read More
Solo Work