Where is the Cloud Computing bus going?

Technological innovation patterns have often repeated themselves in history. So it is with Cloud Computing. Familiar patterns of change seem to emerge today

Here are some of main trends that I see in Cloud Computing

Advent of containers: Containers are the new hot topic in cloud computing. In virtualization guest OS’es run separately. Running separate guest OS over the hypervisor is associated with a lot of overhead for each of the heavy weight OS’es. Containers can be used as an alternative to OS-level virtualization to run multiple isolated systems on a single host. Containers within a single operating system are much more efficient being light weight while being able to provide the same level of isolation. Containers run the same kernel as the host. Here is an interesting article on containers Containers, not virtual machines are the future of the cloud.

In many ways this containers over VM innovation pattern is reminiscent of the advantages of lightweight ‘threads’ over the heavy and slow ‘process’ approach in the OS world. It is inevitable that containers will eventually score over VMs

Open ‘something’ over proprietary’ness: Technology over the decades has always moved into an ‘open’ approach over proprietary solutions. Hence, for example, we have OpenStack for creating instances, provisioning storage, network to do many things that are being done separately by VMWare, Citrix, Hyper-V. The intent is to have a common approach over several disparate approaches. In the networking world there is OpenFlow which tries to have a uniform interface to the many different standards maintained by the Ciscos, Junipers and Brocades of the world. There are also other technologies like OpenCV (Computer Vision processing), Open VPN (VPN protocol) etc. In all these approaches there is either to move to unify or to provide a layer over and above the disparate approaches. I am not sure whether Openstack will prevail, only time will tell. I personally think we will move to a level abstraction that will be even above that of Open Stack.

Software Defined Everything: Cloud Computing started with the need to be able to provision computing resources through a user interface or the Web portal. This was made possible, thanks to virtualization. Users could now define and request computing resources. Soon this led to the need for being able to programmatically request storage. The trick in storage is to do ‘thin-provisioning’ or to provision resources that barely satisfies the needs of the application. The application will be able to request more storage programmatically. Not to be outdone, networking followed suit when Software Defined Networking became a reality when Stanford and University of California came with the Open Flow protocol. We have now entered into the era of Software Defined Datacenter. This is a dominant theme in Cloud Computing.

These are some of the predominant trends that are emerging in the Cloud Computing arena.

I have spent more than 2 decades of my career in telecom, implementing telecom protocols, starting in the mid-1980s. The mid 1980s was the time when digital switches started to emerge. This was followed by a spate of protocols and dizzying innovations like mobile telephony, ISDN, Intelligent Networks, Softswitch, UMTS,3G, HSDPA, LTE etc.

I personally think that Cloud computing, to use a very frayed and hackneyed term, is at a similar ‘inflexion point’. Trends are emerging and we will soon be caught in the maelstrom of rapid change and innovation.

In this post I am going to do a Marty McFly of the ‘Back to Future’ trilogy. I am going to set the clock of the Delorean DMC-12 to 2020 and ‘Whoosh…..’

21 Apr 2020:

It is 21 Apr 2020 and a sunny day. Here is a look at the Cloud Computing landscape

The Organization of Cloud Computing Standards (OCCS) now sets and governs the standards for all Cloud Providers of the world
Common APIs govern provisioning of instances on the cloud regardless of the Cloud Provider. Instances are defined by RPE values, RAM and IOPS, LB, DNS requirements
Networking bandwidth, security and storage are also standards based
Enterprises use a ‘diffuse deployment’ strategy where the organization’s workloads are deployed to multiple cloud providers.
Workloads are Cloud Provider agnostic.
Enterprise applications themselves may span multiple cloud providers for e.g. the e-commerce in Cloud Provider 1, Analytics on HPC instances on Cloud Provider 2 and secure applications on Private Cloud of Cloud Provider 3. Appropriate contracts are maintained between the Cloud Providers for charging for the usage.
Algorithms are used by enterprises to deploy workloads to cloud providers. The algorithms match the SLA and cost requirements of the application with those offered by the cloud provider to minimize the cost while meeting the SLA requirements of the applications.
Compute, storage and networking costs fluctuate and enterprises use algorithms to optimize the deployment of workloads. Workloads are migrated to take advantage of these price changes
Consolidation and acquisitions happen at an alarming pace. Cloud providers, storage, network and HPC providers aslo compete fiercely
Cloud providers are swallowed by others and some lose out. The battle scene is bloody

Time to get back to Delorean. This time the clock on Delorean is set to 2025

18 Sep 2025

Today it is 18 Sep 2025, and it is sunny again, coincidentally.

Cloud Computing is dead, mate. These days technology has moved to ‘Cloud Computing in a box’.
The technology of these times are ‘Haze works’ where the computation happens in the stratosphere over the ether …

So much for looking into the future. It is now time to get back to the reality of VMs

Designing a Scalable Architecture for the Cloud

The promise of the cloud is the unlimited computing power and storage capacities coupled with the pay-per-use policy. This makes the cloud particularly irresistible for hosting web applications and applications whose demand vary periodically. In order to take full advantage of the cloud the application must be designed for optimum performance. Though the cloud provides resources on-demand a badly designed application can hog resources and prove to be extremely expensive in the long run.

One of the first requirements for deploying applications on the cloud is that it should be scalable. Scalability denotes the ability to handle increasing traffic simply by adding more computing resources of the same kind rather than adding resources with greater horse power. This is also referred to scaling horizontally.

Assuming that the application has been sufficiently profiled and tuned for high performance there are certain key considerations that need to be taken into account while deploying on the cloud – public or private. Some of them are being able to scale on demand, providing for high availability, resiliency and having sufficient safeguards against failures.

Given these requirements a scalable design for the Cloud can be viewed as being made up of the following 5 tiers of layers

The DNS tier – In this tier the user domain is hosted on a DNS service like Ultra DNS or Route 53. These DNS services distribute the DNS lookups geographically. This results in connecting to a DNS Server that is geographically closer to the user thus speeding the DNS lookup times. Moreover since the DNS lookups are distributed geographically it also builds geographic resiliency as far as DNS lookups are concerned

Load Balancer-Auto Scaling Tier – This tier is responsible for balancing the incoming traffic among compute instances in the cloud. The load balancing may be made on a simple round-robin technique or may be based on the actual CPU utilization of the individual instances. Typically at this layer we should also have an auto-scaling policy which will add more instances if the traffic to the application increases above a threshold or terminate instances when the traffic falls below a specific threshold.

Compute-Instance Tier – This layer hosts the actual application in individual compute instances on the cloud. It is assumed that the application has been tuned for maximum performance. The choice of small, medium or large CPU should be based on the traffic handling capacity of the instance type versus the cost/hr of the instance.

Cache Tier – This is an important layer in the cloud application where there are multiple instances. The cache tier provides a distributed cache for all the instances. With a distributed caching system like memcached it is possible to share global data between instances. The memcached application uses a consistent-hashing technique to distribute data among a set of participating servers. The consistent hashing method allow for handling of server crashes and new servers joining into the cache layer.

Database Tier – The Database tier is one of the most critical layers of the application. At a minimum the database should be configured in an active-standby mode. Ideally it is always better to have the active and standby in different availability zones to better handle disasters in a particular zone. Another consideration is have separate read replicas that handle reads to database while the primary database handles the write operations

Besides the above considerations it is always good to host the web application in different availability zone thus safeguarding against disasters in a particular region.

The Many Faces of Latency

Nothing is more damaging to a website than poor response times. Latency is probably the most serious issue that website application developers have to contend with. Whether it is retail application or a e-ticketing application poor response times play havoc on user experience. Latency has many faces each contributing in a little way to the overall response times of the application. This article looks at some of the key culprits that contribute to a website latency

Link Latencies: This is one of major contributors. The link speeds from the host computer to the website plays a major role. For those applications that are hosted on the public cloud it makes sense to deploy in multiple availability zones dispersed geographically. This will ensure that people across the globe get to the website from a cloud deployment closest to them. Besides, with the recent Amazon EC2 outage it definitely makes sense to be able to deploy across availability zones promoting geographical resiliency in the application. Dispersing the applications geographically helps in connecting the user with the least number of intervening hops thus reducing the response times.

DNS latencies: This is another area which needs to be focused on. DNS lookup can be fairly expensive. Hence it makes sense to speed DNS lookups by using some DNS services that provide additional name servers across geographical regions. There are many such DNS services that speed DNS lookups by propagating DNS lookup across geographies. Some examples are Amazon’s Route 53, UltraDNS etc.

Load Balancer Latencies: Typical cloud deployments will multiple instances usually be behind a load balancer. Depending on what algorithm the load balancer adopts for balancing the incoming traffic it is definitely going to contribute to the latency. Amazon’s Elastic Load Balancer is usually a set of participating IPs.

Application Latencies: When the load balancer sends the request to the Web application the logic in processing the request is a key contributor. This latency is within the control of the developer so it makes sense to bring this down to the absolute minimum.

Web page Rendering Latencies: A poorly designed web page can also result in large latencies. A webpage that needs to download a lot of items prior to being able to render it will definitely affect the user’s experience. Hence it is necessary to design an efficient web page that renders quickly. A standard technique to deliver content to a website is to use a Content Delivery Network (CDN) to deliver content. CDNs typically distribute content across multiple servers dispersed geographically. The content server selected for content delivery is based on user proximity based on the fewest number of hops. Major players in CDNS are Akamai, Edgecast andAmazon’s Cloudfront.

These are the many aspects that contribute to overall latencies. Focus should being trying to optimize in all areas while deploying a web application either in a hosted network or the public cloud.

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